GUILFORD COUNTY SCHOOL DISTRICT DISPARITY STUDY · GUILFORD COUNTY SCHOOL DISTRICT DISPARITY STUDY 1 | INTRODUCTION GUILFORD COUNTY SCHOOL DISTRICT Final Report | July 20, 2016 PAGE

GUILFORD COUNTY SCHOOL DISTRICT DISPARITY S TUDY

TABLE OF CONTENTS PAGE

GUILFORD COUNTY SCHOOL DISTRICT

Final Report | June 20, 2016 P A G E i

1 INTRODUCTION

1. Introduction .................................................................................................................................................... 1

2. Study Team ..................................................................................................................................................... 1

3. Background ..................................................................................................................................................... 2

4. Overview of Study Approach ................................................................................................................... 2

5. Report Organization .................................................................................................................................... 3

6. Glossary of Terms ......................................................................................................................................... 4

2 LEGAL FRAMEWORK

1. Introduction .................................................................................................................................................... 1

2. Standards of Review for Race-Specific and Gender-Specific Programs ................................. 2

3. To Withstand Strict Scrutiny, an M/WBE Program Must Be Based on Thorough Evidence Showing a Compelling Governmental Interest ........................................ 4

4. Sufficiently Strong Evidence of Significant Statistical Disparities Between Qualified Minorities Available and Minorities Utilized Will Satisfy Strict Scrutiny and Justify a Narrowly Tailored M/WBE Program ......................................................... 6

5. The Governmental Entity or Agency Enacting an M/WBE Program Must Be Shown to Have Actively or Passively Perpetuated the Discrimination .................................... 9

6. Anecdotal Evidence of Discrimination in Disparity Studies ....................................................... 10

7. To Withstand Strict Scrutiny, an M/WBE Program Must Be Narrowly Tailored to Remedy Identified Discrimination .................................................................................................. 11

8. Small Business Procurement Preferences ......................................................................................... 14

9. Conclusions ................................................................................................................................................... 15

3 REVIEW OF POLICIES AND PROGRAMS

1. Introduction .................................................................................................................................................... 1

2. Methodology ................................................................................................................................................. 1

3. M/WBE Goals Program .............................................................................................................................. 2

4. M/WBE Certification .................................................................................................................................... 7

5. Outreach .......................................................................................................................................................... 8

6. Tracking M/WBE Utilization ..................................................................................................................... 9

7. M/WBE Coordinator .................................................................................................................................. 11

8. Prompt Payment ......................................................................................................................................... 11


TABLE OF CONTENTS (continued) PAGE


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9. Loan Programs ............................................................................................................................................ 11

10. Bonding Programs ..................................................................................................................................... 12

11. Management and Technical Assistance ............................................................................................ 12

12. Conclusions ................................................................................................................................................... 13

4 MARKET AREA AND UTILIZATION ANALYSES

1. Chapter Definitions ...................................................................................................................................... 1

2. Data Collection and Management......................................................................................................... 4

3. Market Area Analysis .................................................................................................................................. 5

4. Utilization Analysis ....................................................................................................................................... 8

5. Conclusion ..................................................................................................................................................... 20

5. AVAILABILITY AND DISPARITY ANALYSES

1. Chapter Definitions ...................................................................................................................................... 1

2. Disparity Methodology and Indices ...................................................................................................... 3

3. Guilford County School District Availability and Disparity Summary ...................................... 4

4. Statistical Significance ................................................................................................................................ 9

5. Conclusion ..................................................................................................................................................... 15

6. PRIVATE SECTOR AND NON-GOAL ANALYSES

1. Introduction .................................................................................................................................................... 1

2. Collection and Management of Permits Data................................................................................... 2

3. Private Sector Utilization Analysis, Commercial Construction Permits ................................... 4

4. Nexus Between Commercial and Public Construction .................................................................. 9

5. Private Sector Disparities, U.S. Census Bureau, 2012 Survey of Business Owners Data ................................................................................................................................................. 10

6. Analysis of Race, Ethnicity, and Gender Effects on Self-Employment Rates ....................... 31

7. Conclusion ..................................................................................................................................................... 43

7. ANECDOTAL ANALYSIS

1. Methodology ................................................................................................................................................. 1

2. Demographics ................................................................................................................................................ 5




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3. Barriers to Doing Business with Guilford County School District ............................................ 10

4. Stakeholder Interviews ............................................................................................................................. 11

5. Access to Capital and Bonding ............................................................................................................. 12

6. Disparate Treatment and Discrimination .......................................................................................... 13

7. Suggested Remedies from Anecdotal Participants ...................................................................... 14

8. Conclusion ..................................................................................................................................................... 15

8. FINDINGS AND RECOMMENDATIONS

1. Introduction .................................................................................................................................................... 1

2. Findings ............................................................................................................................................................ 1

3. Commendations and Recommendations ........................................................................................... 6

4. Conclusion ....................................................................................................................................................... 8

APPENDICES

Appendix A: Stakeholder Interview Guide

Appendix B: Custom Census Survey Instrument

Appendix C: Detailed Disparity Analyses

Appendix D: Public Meeting Notices

Appendix E: Survey of Vendors Instrument

Appendix F: Survey of Vendors Results

Appendix G: Regression Analysis

Appendix H: In-Depth Interview Guide

Appendix I-1: Focus Group Guides – Primes

Appendix I-2: Focus Group Guides – Subcontractors

Appendix J: Public Use Microdata Sample (PUMS) Regression Analysis

Appendix K: Detailed Market Area Analysis

TABLES CHAPTER 3

Table 3-1 Documents Reviewed During Policy and Procedure Review ...................................................... 2




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Table 3-2 Guilford County Schools, M/WBE Goals on Randomly Selected Projects, From 2012 ................................................................................................................................................................... 6

Table 3-3 Guilford County Schools, M/WBE Spending on Goods and Services – State Certified, FY 2013-14 ................................................................................................................................. 10

Table 3-3a Guilford County Schools, M/WBE Spending Goods and Services, All Firms (State Certified & Non-State Certified), FY 2013-14 .................................................................... 10

Table 3-3b Guilford County Schools, M/WBE Spending Goods and Services, Shows Money Spent and Not Reported by GCS for Non-State Certified Firms, FY 2013-14 .................................................................................................................................................... 10

CHAPTER 4

Table 4-1 Market Area Analysis, Prime Level, Distribution of Dollars by Business Category ........................................................................................................................................................... 6

Table 4-2 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Construction ............................................................................................... 9

Table 4-3 Utilization of Firms Analysis, Subcontractor Level, Distribution of Dollars by Business Ownership Classification, Construction ............................................................................................. 11

Table 4-4 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Architecture and Engineering ............................................................ 13

Table 4-5 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Professional Services ............................................................................. 15

Table 4-6 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Other Services .......................................................................................... 17

Table 4-7 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Goods and Supplies ............................................................................... 19

CHAPTER 6

Table 6-1 Private Sector Census Disparities, NAICS Code 23, Construction, U.S. Census 2012 Survey of Business Owners, State of North Carolina Marketplace .............................. 12

Table 6-2 Private Sector Census Disparities, NAICS Code 42, Wholesale Trade, U.S. Census 2012 Survey of Business Owners, State of North Carolina Marketplace .............. 14

Table 6-3 Private Sector Census Disparities, NAICS Code 54, Scientific and Technical Services, U.S. Census 2012 Survey of Business Owners, State of North Carolina Marketplace .................................................................................................................................................. 16

Table 6-4 Private Sector Census Disparities, NAICS Code 56, Administrative and Support and Waste Management and Remediation Services, U.S. Census 2012 Survey of Business Owners, State of North Carolina Marketplace ............................................................. 18

Table 6-5 Private Sector Census Disparities, NAICS Code 81, Other Services (Except Public Administration), U.S. Census 2012 Survey of Business Owners, State of North Carolina Marketplace ................................................................................................................... 20




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Table 6-6 Private Sector Census Disparities, NAICS Code 23, Construction, U.S. Census 2012 Survey of Business Owners, Greensboro-High Point, NC Metro Area Marketplace .................................................................................................................................................. 22

Table 6-7 Private Sector Census Disparities, NAICS Code 42, Wholesale Trade, U.S. Census 2012 Survey of Business Owners, Greensboro-High Point, NC Metro Area Marketplace ....................................................................................................................................... 24

Table 6-8 Private Sector Census Disparities, NAICS Code 54, Scientific and Technical Services, U.S. Census 2012 Survey of Business Owners, Greensboro-High Point, NC Metro Area Marketplace ..................................................................................................... 26

Table 6-9 Private Sector Census Disparities, NAICS Code 56, Administrative and Support and Waste Management and Remediation Services, U.S. Census 2012 Survey of Business Owners, Greensboro-High Point, NC Metro Area Marketplace ....................... 28

Table 6-10 Private Sector Census Disparities, NAICS Code 81, Other Services (Except Public Administration), U.S. Census 2012 Survey of Business Owners, Greensboro-High Point, NC Metro Area Marketplace ................................................................ 30

Table 6-11 Percentage of Self-Employed/2014 Earnings, Racial, Ethnic, and Gender Business Ownership Classification ....................................................................................................... 34

Table 6-12 Self-Employment “Odds Ratios” of Minority Groups Relative to Nonminority Males After Controlling for Selected Demographic and Economic Characteristics .............................................................................................................................................. 38

Table 6-13 Earnings Elasticities of Minority Groups Relative to Nonminority Males After Controlling for Selected Demographic and Economic Characteristics ................................. 40

Table 6-14 Observed and Predicted Self-Employment Rates, the Greensboro-High Point, NC CMSA ....................................................................................................................................................... 41

CHAPTER 7

Table 7-1 Guilford County Schools Survey of Vendors Demographics, Number of Respondents ................................................................................................................................................... 5

Table 7-2 Guilford County Schools Survey of Vendors Demographics, Number of Employees ....................................................................................................................................................... 7

Table 7-3 Guilford County Schools Survey of Vendors Demographics, Largest Contract Awarded – Prime .......................................................................................................................................... 8

Table 7-4 Guilford County Schools Survey of Vendors Demographics, Largest Contract Awarded – Subcontractor ......................................................................................................................... 9

Table 7-5 Guilford County School District, Aggregate Bonding Limit ....................................................... 12

Table 7-6 Guilford County School District, Discrimination ............................................................................. 14

CHAPTER 8

Table 8-1 Utilization of Firms Analysis, Sub Level, Distribution of Dollars by Business Ownership Classification, Construction ............................................................................................... 2




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Table 8-2 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Construction, Architecture & Engineering, Professional Services, Other Services, Goods & Supplies ............................................................ 3

Table 8-3 Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, All Procurement Categories Combined ........................................... 4

Table 8-4 Narrowly Tailored M/WBE Program Features ................................................................................... 7

Table 8-5 Proposed MBE and WBE Goals ............................................................................................................... 7

Table 8-6 Portsmouth Public Schools, Proposed M/WBE Aspirational Goals by Procurement Category ............................................................................................................................. 10

Table 8-7 2010 M/W/SBE Aspirational Goals, Charlotte-Mecklenburg Schools ................................... 11

Table 8-8 Revenue Definitions for SBE and MBE, Miami-Dade County Public Schools 2013 ................................................................................................................................................................. 18

EXHIBITS CHAPTER 4

Figure 4-A Examples of Records Excluded ................................................................................................................ 5

Figure 4-B Market Area Analysis, Prime Level, Percentage of Dollars by Business Category ........................................................................................................................................................... 7

Figure 4-C Market Area Analysis, Subcontractor Level, Distribution of Dollars by Business Category ........................................................................................................................................................... 8

Figure 4-D Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Construction ............................................................................................. 10

Figure 4-E Utilization of Firms Analysis, Subcontractor Level, Distribution of Dollars by Business Ownership Classification, Construction ........................................................................... 12

Figure 4-F Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Architecture and Engineering ............................................................ 14

Figure 4-G Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Professional Services ............................................................................. 16

Figure 4-H Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Other Services .......................................................................................... 18

Figure 4-I Utilization of Firms Analysis, Prime Level, Distribution of Dollars by Business Ownership Classification, Goods and Supplies ............................................................................... 20

CHAPTER 5

Figure 5-A Guilford County School District, Construction .................................................................................. 4

Figure 5-B Guilford County School District, Construction, Subcontractor ................................................... 5

Figure 5-C Guilford County School District, Architecture and Engineering ................................................ 6

Figure 5-D Guilford County School District, Professional Services .................................................................. 7

Figure 5-E Guilford County School District, Other Services............................................................................... 8




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Figure 5-F Guilford County School District, Goods and Supplies ................................................................... 9

Figure 5-G T-Test Results for Minority- and Women-Owned Firms, Construction, Prime Level ................................................................................................................................................................. 10

Figure 5-H T-Test Results for Minority- and Women-Owned Firms, Construction, Subcontractor Level ................................................................................................................................... 11

Figure 5-I T-Test Results for Minority- and Women-Owned Firms, Architecture and Engineering, Prime Level ......................................................................................................................... 12

Figure 5-J T-Test Results for Minority- and Women-Owned Firms, Professional Services, Prime Level .................................................................................................................................................... 13

Figure 5-K T-Test Results for Minority- and Women-Owned Firms, Other Services, Prime Level ................................................................................................................................................................. 14

Figure 5-L T-Test Results for Minority- and Women-Owned Firms, Goods and Supplies, Prime Level .................................................................................................................................................... 15

CHAPTER 6

Figure 6-A Utilization Analysis of Permits, Commercial Construction at the Prime Contractor Level ............................................................................................................................................ 5

Figure 6-B Utilization Analysis of Firms, Commercial Construction at the Prime Contractor Level ............................................................................................................................................ 6

Figure 6-C Utilization Analysis of Permits, Commercial Construction at the Subcontractor Level ................................................................................................................................................................... 7

Figure 6-D Utilization Analysis of Firms, Commercial Construction at the Subcontractor Level ................................................................................................................................................................... 8

CHAPTER 7

Figure 7-A Guilford County Schools Survey of Vendors Demographics, Business Industry ................. 6

Figure 7-B Guilford County Schools Survey of Vendors Demographics, Number of Years in Business ....................................................................................................................................................... 7


1 | INTRODUCTION


Final Report | July 20, 2016 P A G E 1

1. INTRODUCTION MGT of America, Inc. (MGT) is pleased to submit the Procurement Disparity Study to the Guilford County School District (District). The MGT team who conducted the District’s Disparity Study is the most experienced in the country and has the most well-rounded experience and in-depth understanding of the legal, social, economic, and political context in which disparity studies are typically conducted. The experience of our team enables us to navigate the challenges, obstacles, and volatility, which can easily derail the most well-planned and executed study. The result is the District’s Disparity Study delivers on our commitment to provide a study which is accurate, valid, reliable, and legally defensible.

2. STUDY TEAM The team of experts who dedicated their time, attention, and expertise to this study include:

MGT PROJECT TEAM MGT is a Tallahassee-based research and management consulting firm. Since 1990, MGT has conducted disparity and disparity-related studies. Our team included the expertise of:

Mr. Reggie Smith, Executive-In-Charge.

Ms. Vernetta Mitchell, Senior Consultant/Project Manager.

Dr. J. Vincent Eagan, JD, Technical Advisor.

Ms. Marilyn Wiley, MS, Consultant/Quantitative Analyst.

MGT SUBCONSULTANTS

BLWall Consulting. Owned by Ms. Bridget Wall-Lennon, is a North Carolina-based consulting firm that managed and co-facilitated the focus group and public meetings, conducted the one-on-one business interviews and the custom census surveys, and developed a master minority- and women-owned business enterprises (M/WBE) database. BLWall Consulting is a certified minority-owned business.

Oppenheim Research. A Tallahassee-based public opinion polling and research firm that conducted the survey of vendors. Ms. Anneliese Oppenheim has provided polling and research services for MGT for over ten years. Oppenheim Research is a woman-owned business (WBE).

C H A P T E R S E C T I O N S

1. Introduction

2. Study Team

3. Background

4. Overview of Study Approach

5. Report Organization

6. Glossary of Terms


1 | INTRODUCTION



3. BACKGROUND In June 2014, the Guilford County School District (District) contracted with MGT to conduct a Disparity Study. This study is the District’s first disparity study. As with first time studies, there are limitations to data, either nonexistent or difficult to analyze. The objectives of this study were:

Determine whether the District, either in the past or currently, engages in discriminatory practices in the solicitation and award of contracts in construction, architecture and engineering consulting, professional service consulting, other services, and goods and supplies to M/WBEs.

Determine if a legally justified need exists for the establishment of an M/WBE program in accordance with the guidelines set forth by the Supreme Court and relevant subsequent cases.

4. OVERVIEW OF STUDY APPROACH MGT followed a carefully designed work plan that allowed study team members to fully analyze availability and utilization with regard to the utilization of M/WBEs in the procurement practices of the District for the study period of fiscal years July 1, 2010 through June 30, 2014. The Disparity Study business categories, defined in Chapter 4, Market Area and Utilization Analyses, are:

Construction.

Architecture and Engineering.

Professional Services.

Other Services.

Goods and Supplies.

The Disparity Study analyzed contracting opportunities in these business categories in order to identify with particularity whether a statistical disparity exists from which the existence of past or present public or private discrimination may be inferred in the relevant market area.

The work plan consisted of, but was not limited to, the following major tasks:

Establish data parameters and finalize the work plan.

Conduct a legal review.

Review policies, procedures, and programs.

These research questions are embedded in relevant chapters throughout this report.

1. Is there factual predicate evidence to support a race- and gender-conscious M/WBE program for the District?

2. How does case law inform the research methodology in a particular region for a particular client?

3. Are there disparities between the availability and utilization of M/WBEs? If there are disparities, what are the most relevant causal factors that contribute directly or indirectly to the disparities between the availability and utilization of M/WBEs?

4. If there is statistical evidence of disparity, what is the cause of the disparity? Is there other evidence that supports and/or explains why there is disparity?

5. Does the District passively engage in practices that result in disparities?

6. Are there statistically significant disparities in the utilization of M/WBEs by prime contractors on projects where there are no M/WBE goals?

7. Is there qualitative/anecdotal evidence of disparate treatment of M/WBE subcontractors by prime contractors?

Research Questions


1 | INTRODUCTION



Conduct market area and utilization analysis.

Determine the availability of qualified firms.

Analyze the utilization and availability data for disparity.

Conduct a survey of business owners.

Collect and analyze anecdotal information.

Prepare and present draft and final reports for the study.

5. REPORT ORGANIZATION In addition to this introductory chapter, this report consists of:

CHAPTER 2 Presents the legal framework and an overview of the controlling legal precedents that impact remedial procurement programs with a particular concentration on the Fourth Circuit.

CHAPTER 3 Provides a review of the District’s policies, procedures, M/WBE programs, and race- and gender-neutral efforts.

CHAPTER 4 Presents the methodology used to determine the District’s relevant market area and statistical analysis of vendor utilization by the District for procurement of contracting, goods, and services activities.

CHAPTER 5 Provides a discussion of the availability of firms and the levels of disparity for vendors as well as a review of the multivariate analysis for the District.

CHAPTER 6 Provides an analysis of the presence of disparity in the private sector and its effect on the ability of firms to win procurement contracts from the District.

CHAPTER 7 Presents an analysis of anecdotal data collected from the survey of business owners, personal interviews, focus group, and public hearings.

CHAPTER 8 A summary of the findings based upon the analyses presented in previous chapters.

APPENDICES Additional analyses, documents used to conduct the study, and back up documentation.

MGT recommends reading the report in its entirety to understand the basis for the findings and conclusions presented in Chapter 8, Findings and Recommendations.


1 | INTRODUCTION



6. GLOSSARY OF TERMS The following terms are used throughout the report.

Anecdotal A personal account of incidents through surveys, interviews, public hearings, and focus groups.

Aspirational Goals A benchmark percentage of spending by an agency with a particular group over a period of time. The aspirational goal is typically an annual goal.

Availability for Anecdotal Activity

A compiled list of firms developed from several different sources including using firms that bid on work, registered vendors as well as various business lists such as Dun and Bradstreet and the Central Contract Registration. Ultimately this compiled list was used as the foundation in developing the pool of available firms to participate in the anecdotal activities.

Centralized Purchasing

One point within an agency where all purchasing transactions are processed.

Compelling Interest

Factual demonstration by a government agency of strong basis in the evidence of past or present racial discrimination sufficient to justify remedial action.

Central Contractor Registration (CCR)

Central Contractor Registration collects, validates, stores, and disseminates data in support of agency acquisition missions, including Federal agency contract and assistance awards. Both current and potential federal government registrants are required to register in CCR in order to be awarded contracts by the federal government. Registrants are required to complete a one-time registration to provide basic information relevant to procurement and financial transactions. Registrants must update or renew their registration at least once per year to maintain an active status.

Custom Census Custom census essentially involves using Dun and Bradstreet as a source of business availability. A short survey is conducted on a random sample of firms supplied by Dun and Bradstreet, asking ethnic and gender status, had they bid or considered bidding on projects by the District, had they bid or considered bidding as a prime contractor, subcontractor, or both, and had they worked as a prime contractor, subcontractor, or both.

Disadvantaged Business Enterprise (DBE)

For-profit small business concerns where socially and economically disadvantaged individuals own at least a 51 percent interest and also control management and daily business operations

Disparity Index The ratio of percentage business utilization and percentage business availability for a particular demographic group.


1 | INTRODUCTION



Good Faith Efforts Documented evidence of what activities occurred to meet established project goals to contract with M/WBE firms.

Historically Underutilized Businesses (HUB)

Per N.C. General Statute 143-128.4, to qualify as a historically underutilized business, a business must be at least 51% owned, controlled and managed, by one or more citizens or lawful permanent residents of the United States who are members of one or more of the following groups: (1) Black, (2) Hispanic, (3) Asian American, (4) American Indian, (5) Female, (6) Disabled and (7) Disadvantaged

Lowest Responsible, Responsive Bidder

An entity that provides a price that is lower than its competition, has responded to the needs of the requestor, and has not violated statutory requirements for vendor eligibility.

M/WBE An ethnic minority or nonminority woman, or group thereof owning at least 51 percent of the general stock and controlling the day-to-day operations of a business.

Master Vendor Database

A database that maintains firms located in the Greensboro metropolitan statistical area (MSA) who have conducted business with the District, registered with the District, or bid on District projects.

MBE An acronym for Minority Business Enterprise. A business owned and operated by a person who is African-American, Asian-American, Hispanic-American, or Native-American.

MSA An acronym for Metropolitan Statistical Area. MSAs are geographic entities defined by the U.S. Office of Management and Budget (OMB) for use by Federal statistical agencies in collecting, tabulating, and publishing Federal statistics. The Greensboro MSA is defined as Greensboro-High Point, NC.

Post-enactment Actions or events that take place after law has been changed.

Pre-enactment Actions or events that take place before or during current law.

Prima Facie Legally sufficient to establish a fact or a case.

Project Goals Goals placed on an individual project or contract, as opposed to aspirational goals placed on overall agency spending.

PUMS Public Use Microdata Sample (PUMS) contains records for a sample of housing units with information on the characteristics of each unit and each person in it. PUMS files are available from the American Community Survey (ACS) and the Decennial Census.

Regression Analysis

Techniques for modeling and analyzing several variables when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one to


1 | INTRODUCTION



understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. For the purposes of this study, a multivariate regression was used to examine the influence of selected company and business characteristics, especially owner race and gender, on gross revenues reported by firms participating in a survey of vendors administered during the study.

Relevant Market The geographical area where the bulk of the firms are located that transact with the City.

Reverse Discrimination

Unfair acts against a majority group.

Set Aside Contracts and purchases that are reserved for an established type of business that competes against like businesses, i.e., small business.

SBE An acronym for Small Business Enterprise.

Sole Source Contracting or purchasing goods or services from one entity.

Statistically Significant

Highly unlikely to be due to random chance alone.

Strict Scrutiny Highest level of federal judicial review to determine whether certain governmental policies are constitutional.

Survey of Vendors Telephone survey administered to firms listed in the master vendor database to solicit responses from business owners and representatives about their firms and their experiences doing business or attempting to do business with the District.

Utilization Examines payments made to firms in the Districts market area for each business category. The measures are presented as dollars, a percentage of dollars as well as the number and percentage of firms utilized by racial, ethnic, and gender classification.

WBE An acronym for Women Business Enterprise. A business owned and operated by a non-minority female.


2 | LEGAL FRAMEWORK



This chapter provides legal background for the study. The focus of the review is on relevant decisions from U.S. Supreme Court and the Fourth Circuit Court of Appeals, which covers the Greensboro area. This chapter is the standard MGT chapter for the Fourth Circuit on this legal material, reviewed for recent cases. The material that follows does not constitute legal advice to Guilford County Schools on minority and women business enterprise (M/WBE) programs, affirmative action, or any other matter. Instead, it provides a context for the statistical and anecdotal analysis that appears in subsequent chapters of this report.

1. INTRODUCTION The Supreme Court decisions in Richmond v. Croson Company (Croson),1 Adarand v. Peña (Adarand),2 and later cases have established and applied the constitutional standards for an affirmative action program. This chapter identifies and discusses those decisions, summarizing how courts evaluate the constitutionality of race-specific and gender-specific programs. Decisions of the Fourth Circuit offer the most directly binding authority; in particular, the recent decision involving the North Carolina Department of Transportation (NCDOT) M/WBE program in H.B. Rowe v. Tippett.3 Where the Fourth Circuit has not directly addressed an issue involving M/WBE programs since the Croson decision, this review considers decisions from other circuits.

By way of a preliminary outline, the courts have determined that an affirmative action program involving governmental procurement of goods or services must meet the following standards:

A remedial race-conscious program is subject to strict judicial scrutiny under the Equal Protection Clause of the Fourteenth Amendment to the United States Constitution.

Strict scrutiny has two basic components: a compelling governmental interest in the program and narrow tailoring of the program.

1 Richmond v. Croson, 488 U.S. 469 (1989). 2 Adarand v. Peña, 515 U.S. 200 (1995). 3 H.B. Rowe v. Tippett, 615 F.3d 233 (4th Cir 2010).


1. Introduction

2. Standards of Review for Race-Specific and Gender-Specific Programs

3. To Withstand Strict Scrutiny, an M/WBE Program Must be Based on Thorough Evidence Showing a Compelling Governmental Interest

4. Sufficiently Strong Evidence of Significant Statistical Disparities Between Qualified Minorities Available and Minorities Utilized Will Satisfy Strict Scrutiny and Justify a Narrowly Tailored M/WBE Program

5. The Governmental Entity or Agency Enacting an M/WBE Program Must be Shown to Have Actively or Passively Perpetuated the Discrimination

6. Anecdotal Evidence of Discrimination in Disparity Studies

7. To Withstand Strict Scrutiny, an M/WBE Program Must be Narrowly Tailored to Remedy Identified Discrimination

8. Small Business Procurement Preferences

9. Conclusions


2 | LEGAL FRAMEWORK



To survive the strict scrutiny standard, a remedial race-conscious program must be based on a compelling governmental interest.

“Compelling interest” means the government must prove past or present racial discrimination requiring remedial attention.

There must be a specific “strong basis in the evidence” for the compelling governmental interest.

Statistical evidence is preferred and possibly necessary as a practical matter; anecdotal evidence is permissible and can offer substantial support, but it probably cannot stand on its own.

Program(s) designed to address the compelling governmental interest must be narrowly tailored to remedy the identified discrimination.

“Narrow tailoring” means the remedy must fit the findings.

The evidence showing compelling interest must guide the tailoring very closely.

Race-neutral alternatives must be considered first.

A lesser standard, intermediate judicial scrutiny, applies to programs that establish gender preferences.

To survive the intermediate scrutiny standard, the remedial gender-conscious program must serve important governmental objectives and be substantially related to the achievement of those objectives.

The evidence does not need to be as strong and the tailoring does not need to be as specific under the lesser standard.

2. STANDARDS OF REVIEW FOR RACE-SPECIFIC AND GENDER-SPECIFIC PROGRAMS

RACE-SPECIFIC PROGRAMS: THE CROSON DECISION

Croson established the framework for testing the validity of programs based on racial discrimination. In 1983, the Richmond City Council (Council) adopted a Minority Business Utilization Plan (the Plan) following a public hearing in which seven citizens testified about historical societal discrimination. In adopting the Plan, the Council also relied on a study indicating, “while the general population of Richmond was 50 percent African American, only 0.67 percent of the city’s prime construction contracts had been awarded to minority businesses in the five-year period from 1978 to 1983.”4

4 Croson. at 479-80.


2 | LEGAL FRAMEWORK



The evidence before the Council also established that a variety of state and local contractor associations had little or no minority business membership. The Council relied on statements by a Council member whose opinion was “the general conduct of the construction industry in this area, the state, and around the nation, is one in which race discrimination and exclusion on the basis of race is widespread.”5 There was, however, no direct evidence of race discrimination on the part of the city in its contracting activities, and no evidence the city’s prime contractors had discriminated against minority-owned subcontractors.6

The Plan required the city’s prime contractors to subcontract at least 30 percent of the dollar amount of each contract to one or more minority-owned business enterprises (MBEs). The Plan did not establish any geographic limits for eligibility. Therefore, an otherwise qualified MBE from anywhere in the United States could benefit from the 30 percent set-aside.

J.A. Croson Company, a non-MBE mechanical plumbing and heating contractor, filed a lawsuit against the city of Richmond alleging the Plan was unconstitutional because it violated the Equal Protection Clause of the Fourteenth Amendment. After a considerable record of litigation and appeals, the Fourth Circuit struck down the Richmond Plan and the Supreme Court affirmed this decision.7 The Supreme Court determined strict scrutiny was the appropriate standard of judicial review for MBE programs, which means a race-conscious program must be based on a compelling governmental interest and be narrowly tailored to achieve its objectives. This standard requires a firm evidentiary basis for concluding the underutilization of minorities is a product of past discrimination.8

GENDER-SPECIFIC PROGRAMS

The Supreme Court has not addressed the specific issue of a gender-based classification in the context of a woman-owned business enterprise (WBE) program. Croson was limited to the review of an MBE program. In evaluating gender-based classifications, the Court has used what some call “intermediate scrutiny,” a less stringent standard of review than the “strict scrutiny” applied to race-based classifications. Intermediate scrutiny requires classifying persons on the basis of sex “must carry the burden of showing an exceedingly persuasive justification for the classification.”9

The Fourth Circuit has ruled the intermediate scrutiny standard is satisfied “by showing at least that the classification serves important governmental objectives and that the discriminatory means employed are

5 Id. at 480. 6 Id. 7 Id. at 511. 8 Id. at 493. 9 Mississippi University for Women v. Hogan, 458 U.S. 718, 724 (1982) (quoting Kirchberg v. Feenstra, 450 U.S. 455, 461 (1981)); see also United States v. Virginia, 518 U. S. 515, 531 (1996), Nguyen v. U.S., 533 U.S. 53, 60 (2001). For an earlier Fourth Circuit application of intermediate scrutiny see Adkins v. Rumsfeld, 464 F.3d 456, 468 (4th cir. 2006).

http://caselaw.lp.findlaw.com/cgi-bin/getcase.pl?navby=case&court=US&vol=450&invol=455&pageno=461

http://caselaw.lp.findlaw.com/cgi-bin/getcase.pl?navby=case&court=US&vol=518&invol=515&pageno=531


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substantially related to the achievement of those objectives.”10 The Fourth Circuit in H.B. Rowe agreed with other federal circuits that intermediate scrutiny “can rest safely on something less than the ‘strong basis in evidence’.”11 This ‘something less’ can mean the state statute in this instance must “present [ ] sufficient probative evidence in support of its stated rationale for enacting a gender preference, i.e., . . . the evidence [must be] sufficient to show that the preference rests on evidence-informed analysis rather than on stereotypical generalizations.”12

3. TO WITHSTAND STRICT SCRUTINY, AN M/WBE PROGRAM MUST BE BASED ON THOROUGH EVIDENCE SHOWING A COMPELLING GOVERNMENTAL INTEREST

For government contracting programs, courts have yet to find a compelling governmental interest for affirmative action other than remedying discrimination in the relevant marketplace. In other arenas, diversity has served as a compelling governmental interest for affirmative action. For example, the Ninth Circuit upheld race-based admission standards at an experimental elementary school in order to provide a more real world education experience.13 More recently, in Petit v. Chicago, the Seventh Circuit relied on Grutter v. Bollinger (Grutter) in stating urban police departments had “an even more compelling need for diversity” than universities and upheld the Chicago program “under the Grutter standards.”14 The recent holding that other compelling interests may support affirmative action does not yet appear to have any application to public contracting.15

Croson identified two necessary factors for establishing racial discrimination sufficiently to demonstrate a compelling governmental interest in establishing an M/WBE program. First, there needs to be identified discrimination in the relevant market.16 Second, “the governmental actor enacting the set-aside program must have somehow perpetuated the discrimination to be remedied by the program,”17 either actively or at least passively with “the infusion of tax dollars into a discriminatory industry.”18

Although the Supreme Court in Croson did not specifically define the methodology that should be used to establish the evidentiary basis required by strict scrutiny, the Court did outline governing principles. Lower

10 Hogan, 458 U.S. at 724 (internal quotation marks omitted). 11 H.B. Rowe, at 10 (citing Engineering Contractors at 909). 12 Id. at 10 (citing Engineering Contractors at 910, Concrete Works at 959). 13 Hunter v. Regents of University of California, 190 F.3d 1061 (9th Cir. 1999). 14 Petit v. Chicago, 352 F.3d 1111 (7th Cir. 2003). 15 Grutter v. Bollinger, 539 U.S. 306 (2003). For an argument that other bases could serve as a compelling interest in public contracting, see Michael K. Fridkin, “The Permissibility of Non-Remedial Justifications for Racial Preferences in Public Contracting,” 24 N. Ill. U. L. Rev. 509 (Summer 2004). 16 Croson, 488 U.S. at 492, 509-10. 17 Coral Construction v. King County, 941 F.2d 910, 918 (9th Cir 1991). 18 Id. at 922.


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courts have expanded the Supreme Court’s Croson guidelines and have applied or distinguished these principles when asked to decide the constitutionality of state, county, and city programs that seek to enhance opportunities for minorities and women.

POST-ENACTMENT EVIDENCE

The Supreme Court in Croson found pre-enactment evidence of discrimination insufficient to justify the program. The defendant in Croson did not seek to defend its program based on post-enactment evidence. However, following Croson, a number of circuits did defend the use of post-enactment evidence to support the establishment of a local public sector affirmative action program.19 Some cases required both pre-enactment and post-enactment evidence.20

The Supreme Court case of Shaw v. Hunt21 (Shaw) raised anew the issue of post-enactment evidence in defending local public sector affirmative action programs. Shaw involved the use of racial factors in drawing voting districts in North Carolina. In Shaw, the Supreme Court rejected the use of reports providing evidence of discrimination in North Carolina because the reports were not developed before the voting districts were designed. Thus, the critical issue was whether the legislative body believed discrimination had existed before the districts were drafted.22 Following the Shaw decision, two district courts rejected the use of post-enactment evidence in the evaluation of the constitutionality of local minority business programs.23 A federal circuit court decision, covering the federal small disadvantaged business enterprise program, stated, “For evidence to be relevant in a strict scrutiny analysis of the constitutionality of a statute, it must be proven to have been before Congress prior to enactment of the racial classification.”24 The issue of post-enactment evidence was not directly addressed in H.B. Rowe, although the NCDOT M/WBE program was upheld based on studies conducted after the program was enacted.

RACIAL CLASSIFICATIONS SUBJECT TO STRICT SCRUTINY

In Scott v. Jackson, the city argued its disadvantaged business program was not a racial classification subject to strict scrutiny because (1) it was based upon disadvantage, not race, and (2) it was a goals program and not a quota. The Fifth Circuit disagreed with the claim the Jackson program was not a racial classification, because the city used the federal Section 8(d), which grants a rebuttable presumption of social and

19 See, e.g., Engineering Contractors v. Dade County, 122 F.3d 895 (11th Cir. 1997); Contractors Association v. Philadelphia, 6 F.3d 990, 1009 n. 18 (3rd Cir. 1993); Concrete Works v. Denver, 36 F.3d 1513 (10th Cir. 1994). 20 See, e.g., Coral Construction, 941 F.2d 910, 920. 21 Shaw v. Hunt, 517 U.S. 899 (1996). 22 Id. at 910. 23 AUC v. Baltimore, 83 F.Supp.2d 613, 620-22 (D.Md. 2000); West Tenn. ABC v. Memphis City Schools, 64 F.Supp.2d 714, 718-21 (W.D. Tenn. 1999). 24 Rothe v. U.S. Dept. of Defense, 413 F.3d 1327, 1328 (Fed Cir 2005).


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economic disadvantage to firms owned by minorities.25 Such a presumption is subject to strict scrutiny. The Fifth Circuit also noted strict scrutiny applied not simply when race-conscious measures were required, but also when such measures were authorized or encouraged.26 While this issue was not directly addressed in H.B. Rowe, the Fourth Circuit did state in an earlier case with regard to a claim that an employment affirmative action program was not a racial quota, “In the end, appellees cannot escape the reality that these preferences will deny some persons the opportunity to be a state trooper or to advance as a state trooper solely because they belong to a certain race.”27

4. SUFFICIENTLY STRONG EVIDENCE OF SIGNIFICANT STATISTICAL DISPARITIES BETWEEN QUALIFIED MINORITIES AVAILABLE AND MINORITIES UTILIZED WILL SATISFY STRICT SCRUTINY AND JUSTIFY A NARROWLY TAILORED M/WBE PROGRAM

The Supreme Court in Croson stated, “where gross statistical disparities can be shown, they alone in a proper case may constitute prima facie proof of a pattern or practice of discrimination.”28 But the statistics must go well beyond comparing the rate of minority presence in the general population to the rate of prime construction contracts awarded to MBEs. The Court in Croson objected to such a comparison, indicating the proper statistical evaluation would compare the percentage of qualified MBEs in the relevant market with the percentage of total municipal construction dollars awarded to them.29

The Supreme Court in Croson recognized statistical measures of disparity that compared the number of qualified and available M/WBEs with the rate of state construction dollars actually awarded to M/WBEs in order to demonstrate discrimination in a local construction industry.30 To meet this more precise requirement, courts, including the Fourth Circuit, have accepted the use of a disparity index.31

DETERMINING AVAILABILITY

To perform proper disparity analysis, the government must determine “availability”—the number of qualified minority contractors willing and able to perform a particular service for the state and local government. In Croson, the Court stated, “Where there is a significant statistical disparity between the

25 Scott v. City of Jackson, 199 F.3d 206, 216-17 (5th 1999). 26 Id.at 215 (quoting Bras v. California Public Utilities Commission, 59 F.3d 869, 875 (9th Cir. 1995)). 27Maryland Troopers Assn v. Evans, 993 F.2d 1072, 1078 (4th Cir 1993). 28 Croson, 488 U.S. at 501, quoting Hazelwood School Division v. United States, 433 U.S. 299, 307-308 (1977). 29 Id. at 501. 30 Croson, 488 U.S. at 503-504. 31 H.B. Rowe, at 244. See also, Engineering Contractors, 122 F.3d at 914; Concrete Works IV, 321 F.3d at 964-69.


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number of qualified minority contractors willing and able to perform a particular service and the number of such contractors actually engaged by the locality or the locality’s prime contractors, an inference of discriminatory exclusion could arise.”32

An accurate determination of availability also permits the government to meet the requirement that it “determine the precise scope of the injury it seeks to remedy” by its program.33 Following Croson’s statements on availability, lower courts have considered how legislative bodies may determine the precise scope of the injury sought to be remedied by an MBE program. Nevertheless, the federal courts have not provided clear guidance on the best data sources or techniques for measuring M/WBE availability.

Different forms of data used to measure availability give rise to particular controversies. In H.B. Rowe, subcontractor availability was estimated using NCDOT-approved subcontractors, subcontractor awardees and prime contractors. The plaintiff’s expert argued in the case that subcontractor bidder data should be employed to estimate subcontractor availability rather than a vendor based approach. The Fourth Circuit in H.B. Rowe noted the available subcontractor bidder data did not change the results of the vendor data.34

RELEVANT MARKET AREA

Another issue in availability analysis is the definition of the relevant market area. Specifically, the question is whether the relevant market area should be defined as the area from which a specific percentage of purchases are made, the area in which a specific percentage of willing and able contractors may be located, or the area determined by a fixed geopolitical boundary.

The Supreme Court has not yet established how the relevant market area should be defined, and the relevant market was not directly addressed in H.B. Rowe. However, the study in H.B. Rowe defined the relevant market as the area in which 75 percent of the dollars was spent by the agency with vendors in a particular procurement category.

FIRM QUALIFICATIONS

Another availability consideration is whether M/WBE firms are qualified to perform the required services. In Croson, the Supreme Court noted although gross statistical disparities may demonstrate prima facie proof of discrimination, “when special qualifications are required to fill particular jobs, comparisons to the general population (rather than to the smaller group of individuals who possess the necessary qualifications) may

32 Croson, 488 U.S. at 509 (emphasis added). 33 Id., 488 U.S. at 498. 34 H.B. Rowe, at 246. In Concrete Works, in the context of plaintiffs’ complaint that the city of Denver had not used such information, the Tenth Circuit noted that bid information also has its limits. Firms that bid may not be qualified or able, and firms that do not bid may be qualified and able, to undertake agency contracts. Concrete Works II, 36 F.3d at 89-90; Concrete Works IV, 321 F.3d at 983-84.


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have little probative value.”35 The Court, however, did not define the test for determining whether a firm is qualified. In H.B. Rowe, the plaintiff’s expert argued that prime contractor assessment of subcontractor qualifications should be used to assess M/WBE subcontractor qualification. But the Fourth Circuit noted there was no data on prime contractor assessment of subcontractor qualifications.36

WILLINGNESS

Croson requires an “available” firm must be not only qualified, but also willing to provide the required services. In this context, it can be difficult to determine whether a business is willing. The decision in H.B. Rowe did not directly address measures of willingness, but implicitly accepted the vendor based measures of availability presented in the NCDOT as a measure of willingness.

ABILITY

Another availability consideration is whether the firms being considered are able to perform a particular service. Those who challenge affirmative action often question whether M/WBE firms have the “capacity” to perform particular services. In H.B. Rowe, the court noted capacity does not have the same force for subcontracts, which are relatively small. NCDOT study provided evidence that more than 90 percent of subcontracts were less than $500,000.37 In addition, the study for NCDOT contained a regression analysis indicating, “African American ownership had a significant negative impact on firm revenue unrelated to firm capacity or experience.”38

DISPARITY INDEX

In the H.B. Rowe decision, the plaintiff noted there was not substantial disparity when the percentage of subcontractors utilized (as opposed to the percent of dollars awarded) was compared to their availability. However, the Fourth Circuit noted, “the State pointed to evidence that prime contractors used minority businesses for low value work in order to comply with the Department’s goals.”39 Along these lines the Fourth Circuit noted the average subcontract awarded to nonminority male subcontractors was more than double the size of subcontracts won by MBE subcontractors.40

35 Croson, 488 U.S. at 501, quoting Hazelwood School District v. United States, 433 U.S. 299, 308, n.13 (1977). 36 H.B. Rowe, at 246. 37 Id. at 247. 38 Id. at 261. 39 Id. at 247. 40 Id. at 245.


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STATISTICAL SIGNIFICANCE IN DISPARITY STUDIES

While courts have indicated anecdotal evidence may suffice without statistical evidence, no case without statistical evidence has been given serious consideration by any circuit court. In practical effect, courts require statistical evidence. Further, the statistical evidence needs to be held to appropriate professional standards.41 In H.B. Rowe, the court noted the NCDOT study focused on disparity ratios lower than 80 percent and conducted t- tests of statistical significance.

NON-GOAL EVIDENCE

Another question that has arisen in the case law is whether evidence of a decline in M/WBE utilization following a change in or termination of an M/WBE program is relevant and persuasive evidence of discrimination. The Fourth Circuit in H.B. Rowe found a 38 percent decline in M/WBE utilization following the suspension of the program, “surely provides a basis for a fact finder to infer that discrimination played some role in prime contractors’ reduced utilization of these groups during the suspension.”42 Similarly, the Eighth Circuit in Sherbrooke Turf Inc. v. Minnesota Department of Transportation and the Tenth Circuit in Concrete Works IV found such a decline in M/WBE utilization was evidence that prime contractors were not willing to use M/WBEs in the absence of legal requirements.43

5. THE GOVERNMENTAL ENTITY OR AGENCY ENACTING AN M/WBE PROGRAM MUST BE SHOWN TO HAVE ACTIVELY OR PASSIVELY PERPETUATED THE DISCRIMINATION

In Croson, the Supreme Court stated, “It is beyond dispute that any public entity, state or federal, has a compelling interest in assuring that public dollars, drawn from the tax contributions of all citizens, do not serve to finance the evil of private prejudice.”44 Croson provided the government “can use its spending powers to remedy private discrimination, if it identifies that discrimination with the particularity required by the Fourteenth Amendment.”45 The government agency’s active or passive participation in discriminatory practices in the marketplace may show the compelling interest. Defining passive participation, Croson stated, “Thus, if the city could show that it had essentially become a “passive participant” in a system of racial exclusion practiced by elements of the local construction industry, we think it clear that the city could take affirmative steps to dismantle such a system.”46

41 Contractors Association, 91 F.3d at 599-601. 42 H.B.Rowe, at 248. 43 Concrete Works at 985; Sherbrooke Turf, 345 F.3d 964, 973 (8th Cir 2003). 44 Coral Construction, 941 F.2d at 922 (citing Croson, 488 U.S. at 492) (emphasis added). 45 See Croson; see generally I. Ayres and F. Vars, “When Does Private Discrimination Justify Public Affirmative Action?” 98 Columbia Law Review 1577 (1998). 46 Croson, 488 U.S. at 492.


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In the H.B. Rowe case, WBEs were over-utilized on NCDOT projects, but evidence was presented of very low M/WBE utilization in private sector commercial construction and econometric evidence of disparities in entry into and earnings from self-employment in construction in the Public Use Micro Sample data. The Fourth Circuit criticized the evidence offered by NCDOT for not having a t-test of statistical significance, for not showing WBEs sought private sector work, and for less anecdotal evidence of private sector discrimination against WBEs than was shown for minorities. The Fourth Circuit contrasted affidavits produced in the Concrete Works case of firms testifying they sought private sector work and could not obtain it. The court also stated NCDOT did not establish the overlap between private sector and public sector work in transportation, although the court acknowledged some of the subcontracting was the same in both sectors. There is negligible private sector highway construction. The econometric evidence of self-employment was not addressed. The Fourth Circuit did acknowledge,

We do not suggest that the proponent of a gender-conscious program must always tie private discrimination to public action…Rather, we simply hold where, as here, there exists substantial probative evidence of overutilization in the relevant public sector, a state must present something more than generalized private-sector data unsupported by compelling anecdotal evidence to justify a gender-conscious program.47

6. ANECDOTAL EVIDENCE OF DISCRIMINATION IN DISPARITY STUDIES

Most disparity studies present anecdotal evidence along with statistical data. The Supreme Court in Croson discussed the relevance of anecdotal evidence and explained, “Evidence of a pattern of individual discriminatory acts can, if supported by appropriate statistical proof, lend support to a local government’s determination that broader remedial relief is justified.”48 Although Croson did not expressly consider the form or level of specificity required for anecdotal evidence, the Fourth Circuit has addressed both issues.

In H.B. Rowe, there was evidence from a telephone survey, interviews, and focus groups. The Fourth Circuit favorably cited survey evidence of a good old boys network excluding MBEs from work, double standards in qualifications, primes viewing MBEs as less qualified, dropping MBEs after contract award, and the firms changing their behavior when not required to use MBEs. This material was affirmed in interviews and focus groups. The Fourth Circuit also seemed to give some weight to the differences in responses between ethnic/gender groups regarding the aforementioned barriers. The Fourth Circuit concluded, “The survey in the 2004 study exposed an informal, racially exclusive network that systematically disadvantaged minority subcontractors.”49

47 H.B. Rowe, at 255. 48 Croson, 488 U.S. at 509. 49 H.B. Rowe, at 251.


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The plaintiff argued this data was not verified. To which the Fourth Circuit responded, “a fact finder could very well conclude that anecdotal evidence need not—and indeed cannot—be verified because it “is nothing more than a witness’ narrative of an incident told from the witness’ perspective and including the witness’ perceptions.”50 The Fourth Circuit also commented favorably on the NCDOT study survey oversampling MBEs as long as the sample was random. The Fourth Circuit did state, citing precedent in Maryland Troopers, it was problematic to infer “discrimination from reports of cronyism absent evidence of racial animus.”51

7. TO WITHSTAND STRICT SCRUTINY, AN M/WBE PROGRAM MUST BE NARROWLY TAILORED TO REMEDY IDENTIFIED DISCRIMINATION

The discussion of compelling interest in the court cases has been extensive, but narrow tailoring may be the more critical issue. Many courts have held that even if a compelling interest for the M/WBE program can be found, the program has not been narrowly tailored.52 The Fourth Circuit has laid out the following factors in determining whether or not a program was narrowly tailored:

(1) the necessity of the policy and the efficacy of alternative race neutral policies; (2) the planned duration of the policy; (3) the relationship between the numerical goal and the percentage of minority group members in the relevant population; (4) the flexibility of the policy, including the provision of waivers if the goal cannot be met; and (5) the burden of the policy on innocent third parties.53

In H.B. Rowe, the Fourth Circuit added to this list “over-inclusiveness,” defined as the “tendency to benefit particular minority groups that have not been shown to have suffered invidious discrimination.”54

RACE-NEUTRAL ALTERNATIVES

Concerning race-neutral alternatives, the Supreme Court in Croson concluded a governmental entity must demonstrate it has evaluated the use of race-neutral means to increase minority business participation in contracting or purchasing activities. In H.B. Rowe, the Fourth Circuit noted NCDOT had a Small Business Enterprise program and had undertaken all the race neutral methods suggested by the DOT DBE program regulations. The Court went on to note the plaintiff had identified “no viable race-neutral alternatives that

50 H.B. Rowe, at 249 (quoting Concrete Works, 321 F.3d at 989). 51 H.B. Rowe at 251 (citing Maryland Troopers). 52 Contractors Association, 91 F.3d at 605; Engineering Contractors, 122 F.3d at 926-929; Verdi v. DeKalb County School District, 135 Fed. Appx 262, 2005 WL 38942 (11th Cir. 2005). 53 H.B. Rowe at 252 (quoting Belk v. Charlotte-Mecklenburg Bd. of Educ., 269 F.3d 305, 344 (4th Cir. 2001)) 54 H.B.Rowe at 252 (quoting Alexander, 95 F.3d at 316).


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North Carolina has failed to consider and adopt”55 (emphasis in the original). The Court further noted disparities persisted in spite of NCDOT employment of these race-neutral initiatives.

DURATION OF THE REMEDY

With respect to program duration, in Adarand v. Peña, the Supreme Court wrote a program should be “appropriately limited such that it will not last longer than the discriminatory effects it is designed to eliminate.”56 In H.B. Rowe, the Fourth Circuit stated, “the district court found two facts particularly compelling in establishing that it was narrowly tailored: the statute’s provisions (1) setting a specific expiration date and (2) requiring a new disparity study every 5 years.”… We agree.”57 Other appellate courts have noted possible mechanisms for limiting program duration: required termination if goals have been met58 and decertification of MBEs who achieve certain levels of success, or mandatory review of MBE certification at regular, relatively brief periods.59

RELATIONSHIP OF GOALS TO AVAILABILITY

Narrow tailoring under the Croson standard requires remedial goals be in line with measured availability. Merely setting percentages without a carefully selected basis in statistical studies, as the city of Richmond did in Croson itself, has played a strong part in decisions finding other programs unconstitutional.60

In H.B. Rowe, the Fourth Circuit found NCDOT participation goals were related to percentage MBE availability. First, the NCDOT goals were set project by project. Second, there was a report detailing the type of work likely to be subcontracted. Third, the NCDOT goal setting committee checks it database for availability. Finally, Fourth Circuit noted 10 percent of the NCDOT projects had a zero M/WBE goal.

FLEXIBILITY

In H.B. Rowe, the Fourth Circuit agreed with the ruling of the federal district court in the case that the NCDOT M/WBE program was flexible, stated,

The Program contemplates a waiver of project-specific goals when prime contractors make good faith efforts to meet those goals...Good faith efforts essentially require only that the prime contractor solicit and consider bids from minorities. The State does not require or expect

55 H.B.Rowe at 252. 56 Adarand, 515 U.S. at 238 (internal quotations and citations omitted). 57 H.B. Rowe, at 253 (quoting H.B. Rowe, Inc., 589 F. Supp. 2d at 597). 58 Sherbrooke, 354 F.3d at 972. 59 Adarand v. Slater, 228 F.3d at 1179, 1180. 60 Contractors Association, 91 F.3d at 607 (“The district court also found … that the … Ordinance offered only one reference point for the percentages selected for the various set-asides -- the percentages of minorities and women in the general population.”). See also Builders Association of Greater Chicago, 256 F.3d at 647.


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the prime contractor to accept any bid from an unqualified bidder, or any bid that is not the lowest bid. Moreover, prime contractors can bank any excess minority participation for use against future goals over the following two years. Given the lenient standard and flexibility of the “good faith” requirement, it comes as little surprise that as of July 2003, only 13 of 878 good faith submissions-including Rowe’s-had failed to demonstrate good faith efforts.

In contrast, the Third Circuit observed in Contractors Association, “As we have explained, the 15 percent participation goal and the system of presumptions, which in practice require non-black contractors to meet the goal on virtually every contract, result in a 15 percent set-aside for black contractors in the subcontracting market.”61

The Fourth Circuit also noted,

The State does not require or expect the prime contractor to accept any bid from an unqualified bidder, or any bid that is not the lowest bid. Moreover, prime contractors can bank any excess minority participation for use against future goals over the following two years.62

It is worth observing these features of the NCDOT program are more narrowly tailored than the federal DBE program for federally funded transportation projects.63

BURDEN ON THIRD PARTIES

Narrow tailoring also requires minimizing the burden of the program on third parties. Waivers and good faith compliance are tools that serve this purpose of reducing the burden on third parties.64 The plaintiff in H.B. Rowe argued the solicitation requirements were burdensome and it was forced to subcontract out work that could be self-performed. The Fourth Circuit noted the solicitation requirements could be met with existing staff and the M/WBE program did not require subcontracting out work that could be self-performed.65

OVER-INCLUSION

Finally, narrow tailoring involves limiting the number and type of beneficiaries of the program. As noted above, there has to be evidence of discrimination to justify a group-based remedy, and over-inclusion of uninjured individuals or groups can endanger the entire program. However, the statute in question limited

61 Contractors Association, 91 F.3d at 606. 62 H.B. Rowe, at 253. 63 Compare federal regulation 49 CFR Part 26 Appendix A(2) with North Carolina regulation 19NCAC 02d.1109(7). 64 49 CFR, Section 26, Part 53. 65 H.B. Rowe, at 254.


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relief to “those racial or ethnicity classifications...that have been subjected to discrimination in the relevant marketplace and that have been adversely affected in their ability to obtain contracts with the Department.”66

8. SMALL BUSINESS PROCUREMENT PREFERENCES Small business procurement preferences have existed since the 1940s. The first small business program had its origins in the Smaller War Plants Corporation (SWPC), established during World War II.67 The SWPC was created to channel war contracts to small business. In 1947, Congress passed the Armed Forces Procurement Act, declaring, “It is the policy of Congress that a fair proportion of the purchases and contracts under this chapter be placed with small business concerns.”68 Continuing this policy, the 1958 Small Business Act requires government agencies award a “fair proportion” of procurement contracts to small business concerns.69 The regulations are designed to implement this general policy.70

Section 8(b)(11) of the Small Business Act authorizes the Small Business Administration (SBA) to set aside contracts for placement with small business concerns. The SBA has the power:

...to make studies and recommendations to the appropriate Federal agencies to insure that a fair proportion of the total purchases and contracts for property and services for the Government be placed with small-business enterprises, to insure that a fair proportion of Government contracts for research and development be placed with small-business concerns, to insure that a fair proportion of the total sales of Government property be made to small-business concerns, and to insure a fair and equitable share of materials, supplies, and equipment to small-business concerns.71

Every acquisition of goods and services anticipated to be between $2,500 and $100,000 is set aside exclusively for small business unless the contracting officer has a reasonable expectation of fewer than two bids by small businesses.72

There has been only one constitutional challenge to the long-standing federal SBE programs. In J.H. Rutter Rex Manufacturing v. United States,73 a federal vendor unsuccessfully challenged the Army’s small business

66 N.C. Gen. Stat. § 136-28.4(c)(2). 67 See, generally, Thomas J. Hasty III, “Minority Business Enterprise Development and the Small Business Administration’s 8(a) Program: Past, Present, and (Is There a) Future?” Military Law Review 145 (Summer 1994): 1-112. 68 10 U.S.C. § 2301 (1976). 69 15 USC 631(a). 70 See 32 C.F.R. §§ 1-701.1 to 1-707.7. 71 15 U.S.C. § 637(b)(11). 72 Federal Acquisition Regulations 19.502-2. 73 706 F.2d 702 (5th Cir. 1983), cert. denied, 464 U.S. 1008 (1983).


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set-aside as in violation of the due process clause of the Fifth Amendment to the U.S. Constitution, as well as the Administrative Procedures Act and the Armed Forces Procurement Act.74 The court held that classifying businesses as small was not a “suspect classification” subject to strict scrutiny. Instead, the court ruled:

Since no fundamental rights are implicated, we need only determine whether the contested socioeconomic legislation rationally relates to a legitimate governmental purpose . . . Our previous discussion adequately demonstrates that the procurement statutes and the regulations promulgated there under are rationally related to the sound legislative purpose of promoting small businesses in order to contribute to the security and economic health of this Nation.75

A large number of state and local governments have maintained small business preference programs for many years.76 No district court cases were found overturning a state and local small business preference program. One reason for the low level of litigation in this area is there has been no significant organizational opposition to SBE programs. There are no reported cases of litigation against local SBE programs. The legal foundations that have typically sued M/WBE programs have actually promoted SBE procurement preference programs as a race-neutral substitute for M/WBE programs.

There has been one state court case in which an SBE program was struck down as unconstitutional. The Cincinnati SBE program called for maximum practical M/WBE participation and required bidders to use good faith effort requirements to contract with M/WBEs up to government-specified M/WBE availability. Failure to satisfy good faith effort requirements triggered an investigation of efforts to provide opportunities for M/WBE subcontractors. In Cleveland Construction v. Cincinnati,77 the state court ruled the Cincinnati SBE program had race and gender preferences and had deprived the plaintiff of constitutionally protected property interest without due process of law. The city acknowledged it had not offered evidence to satisfy strict scrutiny because it felt it had been operating a race-neutral program.

9. CONCLUSIONS As summarized earlier, when governments develop and implement a contracting program that is sensitive to race and gender, they must understand the case law that has developed in the federal courts. These cases establish specific requirements that must be addressed so such programs can withstand judicial review for constitutionality and prove to be just and fair. Given current trends in the application of the law, local governments must engage in specific fact-finding processes to compile a thorough, accurate, and specific

74 Administrative Procedures Act, 5 U.S.C. §§ 552(a)(1)(E) (1976) and the “fair proportion” language of the Armed Forces Procurement Act, 10 U.S.C. § 2301 et seq. (1976), and the Small Business Act, 15 U.S.C. § 631 et seq. (1976). 75 J. H. Rutter Rex Manufacturing, at 706 F.2d at 730 (emphasis added). See also Dandridge v. Williams, 397 U.S. 471 (1970). 76 For example, Florida started a small business preference program in 1985 (FL St Sec. 287); Minnesota, in 1979 (Mn Stat 137.31); New Jersey, in 1993 (N.J.S.A 52:32-17). 77Cleveland Construction v. Cincinnati, Case No. A0402638 (Ct Comm Pleas, Hamilton County, Ohio 2005).


2 | LEGAL FRAMEWORK



evidentiary foundation to determine whether there is, in fact, discrimination sufficient to justify an affirmative action plan. Further, state and local governments must continue to update this information and revise their programs accordingly.

While the Supreme Court has yet to return to this exact area of law to sort out some of the conflicts, the Fourth Circuit has recently provided some guidance on core standards. Ultimately, MBE and WBE programs can withstand challenges if state and local governments comply with the requirements outlined by the courts.


3 | REV IEW OF POL ICIES AND PROGRAMS



1. INTRODUCTION Chapter 3 focuses on policies and procedures used by Guilford County School District (District), to promote inclusion in purchasing. It provides a brief description of the procurement and contracting environment in which minority, and women business enterprises (M/WBEs) operate, as well as background for the data analysis and foundations for the report recommendations. Finally, it provides a brief description of the remedial efforts undertaken by the District with regard to procurement in the categories of construction, architectural and engineering services, services, and goods.

We present our review of remedial efforts in 12 sections. Section 2 describes the methodology used to conduct the review of contracting policies, procedures, and programs. Sections 2 through 12 cover programs to assist M/WBEs.

2. METHODOLOGY This section discusses the steps taken to summarize the District’s policies, procedures, and programs; race- and gender-based programs; and race- and gender-neutral programs. Our review focused on elements of the purchasing process, including remedial programs that might affect M/WBE utilization. The analysis included the following steps:

Collection, review, and summarization of District contracting and purchasing policies currently in use. Discussions with managers about the changes that contracting and purchasing policies underwent during the study period and their effects on the remedial programs.

Development of questionnaires administered to key District contracting and purchasing staff and officials to determine how existing contracting and purchasing policies have been implemented. Interviews were conducted with District management and staff regarding the application of policies, discretionary use of policies, exceptions to written policies and procedures, and impact of policies on key users.

Review of applicable District rules, resolutions, and policies that guide the remedial programs. This included discussing with both District personnel and program participants the operations, policies, and procedures of the remedial programs and any remedial policy changes over time.

Finally, MGT collected and reviewed copies of previous studies of minority business development conducted in the geographic region and performed a review of race- and gender-neutral programs.


1. Introduction

2. Methodology

3. M/WBE Goals Program

4. M/WBE Certification

5. Outreach

6. Tracking M/WBE Utilization

7. M/WBE Coordinator

8. Prompt Payment

9. Loan Programs

10. Bonding Programs

11. Management and Technical Assistance (M&TA)

12. Conclusions





In all, MGT conducted six interviews with current District staff and local agencies during October 2014. For this portion of the study, District documents collected and reviewed are itemized in Table 3-1.

TABLE 3-1 DOCUMENTS REVIEWED DURING POLICY AND PROCEDURE REVIEW

INDEX DESCRIPTION Procurement Related Materials 1. Guilford County Schools, Purchasing Manual, Effective: July 1, 2005 Revised: July 1, 2013 2. 2014-15 Guilford County Schools Budget Book 3. N.C. Gen. Stat. § 44A-26 4. Guilford County Schools, Superintendent’s Recommended Budget, 2014-15 5. 2014-15 Guilford County Schools Organizational Chart M/WBE Materials 6. M/WBE Participation Plan for Selected Projects Update – July 26, 2012 7. Guilford County Schools, Disparity Study of Historically Underutilized Business (HUB), January 2006 8. Guilford County Schools Job Description Job Title: Coordinator – M/WBE, 1994 9. Developing Partnerships with the M/WBE Community - PowerPoint PPT Presentation 10. Guilford County Board of Education Administrative Procedure, Participation By Minority And

Women Owned Businesses (M/WBE), May 26, 2011 11. North Carolina Statutes § 143-128.3. - Minority Business Participation Administration. 12. Guilford County Minority/Women-Owned Business Enterprise (M/WBE) Program Biannual Report

for Fiscal Year 2012-2013 13. Guilford County Schools, 2013-2014_1st_Quarter_HUB_Report_CERTIFIED_firms 14. Guilford County Schools, 2013-2014_2d_Quarter_HUB_Report_CERTIFIED_firms 15. Guilford County Schools, 2013-2014_3rd_Quarter_HUB_Report_CERTIFIED_firms

3. M/WBE GOALS PROGRAM The North Carolina State law encourages the use of good faith efforts by all state universities and public entities to solicit and utilize minority firms to reach a 10 percent participation level on public sector construction projects.78 In keeping with this state statute, the District has had MBE policy for some time.

The District established a 10 percent M/WBE goal in December 1994, which was reaffirmed in 1996. In March 2007, the District adopted a 12.46 percent M/WBE goal for construction, based on a 2003 State of North Carolina Disparity Study79. The GCS goods and services goal remained at 10.0 percent. By way of comparison, the County of Guilford’s Annual M/WBE participation goal is 10 percent.80

The District’s Purchasing Manual also contain general language covering M/WBE utilization, providing that

78 North Carolina Statutes § 143-128.3. - Minority Business Participation Administration. 79 Guilford County Board of Education Administrative Procedure, Participation By Minority And Women Owned Businesses (M/WBE),

Minority Business Subcontractor Goals. March 29, 2007 80 Guilford County Minority/Women-Owned Business Enterprise (M/WBE) Program Biannual Report for Fiscal Year 2012-2013.





The Purchasing Department shall actively seek and identify qualified minority business enterprises (MBE), disabled business enterprises (DBE), and women’s business enterprises (WBE) and offer them the opportunity to bid on items. The Purchasing Department is required by General Statutes to report all purchases made from MBE’s, DBE’s, and WBE’s to the North Carolina Division of Purchase and Contract quarterly, for inclusion in a consolidated report to the General Assembly.81

PROJECT GOALS

The District has the following requirements for M/WBE project goals as one major method of satisfying the overall M/WBE goals,

The bidder must identify on its bid all M/WBE firms that will be utilized on the project with corresponding total dollar value of the bid, an affidavit listing and documenting good faith efforts (Affidavit A), or an affidavit of self-performance of work (Affidavit B), if the bidder will perform work under contract by its own workforce, as required by G.S.143-128.2(c) and G.S.143-128.2(f).

The bidder must complete all Sections of Affidavit A and attach Affidavit A to its bid, with documentation of Good Faith Effort as required, including a description of the portion of work to be executed by M/WBE firms expressed as a percentage of the total contract price, OR

Provide Affidavit B, which includes sufficient information for the District to determine that the bidder does not customarily subcontract work on this type project.

The provisions above allow for flexibility in the District’s M/WBE program insofar as the rules provide for good faith efforts to achieve the M/WBE project goal and allow the prime contractor to self-perform in lieu of satisfying the M/WBE project goal, if the prime has a history of self-performance in a particular work type.

The District Board of Education approved an M/WBE Participation Plan for selected informal projects in July 2012,82 known as Plan B, totaling $3.1 million. The objectives of the District’s M/WBE Participation Plan-B were to:

Increase first tier M/WBE participation on construction projects.

Increase capacity of small and minority contractors within Guilford County.

Increase the overall pool of M/WBE contractors.

Continue to provide successful projects completed on time and within budget.

81 Guilford County Schools, Purchasing Manual, Affirmative Action Procedures for Minority, Disabled and Women's Business Enterprises. 82 Source: M/WBE Participation Plan for Selected Projects Update – July 26, 2012.





Informal projects as defined in Plan-B are those ranging from $30,000 to $500,000. The Plan projected soliciting a minimum of five bidders. The Plan projected the following factors in determining which contractors to solicit:

Local and M/WBE firms

Good performance history with District

Applicable bonding and insurance

Work experience on similar projects

Active license

Results: Although M/WBE participation was good, no first-tier contracts were awarded to solicited M/WBE firms, as none of these vendors submitted a bid.

GOOD FAITH EFFORTS

The State of North Carolina has established good faith efforts requirements which allow for some flexibility in achieving M/WBE project goals. GCS has adopted state requirements; but, some of these requirements are more stringent than those of the State.

Failure to earn at least 50 points from the Good Faith Efforts listed on Affidavit A shall render the bid non-responsive. Achieving the participation goal of 12.46% creates a presumption that the bidder made the required Good Faith Efforts. Regardless of the percentage of participation, however, ALL BIDDERS must complete and submit Affidavit A, and must further provide certain documentation as specified by Affidavit A with their bid in order to receive Good Faith Points items. The District also shall require the apparent lowest, responsible, responsive bidder to provide additional documentation of Good Faith Efforts within 72 hours of notification of being the apparent lowest, responsible, responsive bidder. Failure to submit these documents /information as requested shall be grounds for deduction of Good Faith Points. In the event such a deduction results in a failure to achieve the required number of Good Faith Points, the bid shall be rejected unless the bidder has otherwise demonstrated Good Faith Efforts.83

The District has the following good faith efforts criteria:

1. Contacting at least three M/WBE firms that reasonably could have been expected to submit a quote and that were known to the contractor, or available on approved lists, at least 10 days before the bid date and notified them of the nature and scope of the work to be performed. “Contact” means contact by letter, fax, e-mail or other means to a viable and active address. Contractor must attach evidence of this contact to bid document to Affidavit A and submit with its bid.

83 Guilford County Board of Education Administrative Procedure, Participation By Minority And Women Owned Businesses (M/WBE), Minority Business Subcontractor Goals. March 29, 2007.





2. Making the construction plans, specifications and requirements available for review by prospective M/WBE firms or providing these documents to them at least 10 days before the bids are due.

3. Breaking-down or combining elements of work into economically feasible units to facilitate M/WBE participation.

4. Working with M/WBE trade, community, or contractor organizations identified by the M/WBE Administrator’s Office and included in the bid documents that provide assistance in recruitment of M/WBE firms.

5. Attending pre-bid meetings scheduled by the public owner.

6. Providing assistance in getting required bonding or insurance or providing alternatives to bonding or insurance for subcontractors.

7. Negotiating in good faith with interested M/WBE firms and not rejecting M/WBE firms as unqualified without having a discussion with the firm and providing sound reasons for the rejection based on their capabilities. Any rejection of an M/WBE based on lack of qualification(s) should have the reasons documented in writing and submitted with Affidavit A with the bid.

8. Providing assistance to an otherwise qualified M/WBE in need of equipment, loan capital, lines of credit, or joint pay agreements to secure loans, supplies, or letters of credit, including waiving credit that is ordinarily required. Assisting M/WBE firms in obtaining the same unit pricing with the bidder’s suppliers in order to help M/WBE firms establish their credit.

9. Negotiating joint venture and partnership arrangements with M/WBE participation on this construction or repair project when possible.

10. Providing quick-pay agreements and policies to enable M/WBEs and suppliers to meet cash-flow demands.84

Table 3-2 provides evidence from over $6 million worth of projects that the District M/WBE goals program has not operated as a rigid quota. The table shows that M/WBE project participation has not been identical for every project, but instead reflect relative M/WBE availability for particular projects. Moreover, the District did not meet M/WBE goals on every project. The average MBE participation was 4.62 percent, the average WBE participation was 5.22 percent and the average overall M/WBE participation in this set of projects was 9.84 percent.

84 Guilford County Board of Education Administrative Procedure, Participation By Minority And Women Owned Businesses (M/WBE), Documentation of Good Faith Efforts (Affidavit A, Section III). March 29, 2007.





TABLE 3-2 GUILFORD COUNTY SCHOOLS

M/WBE GOALS ON RANDOMLY SELECTED PROJECTS FROM 2012

PROJECT DESIGNER CONTRACTOR CONTRACT

AWARD AMOUNT

CONSTRUCTION M/WBE

PARTICIPATION HVAC Improvements Sud Associates

(MBE) Lomax

Construction (Majority)

$1,637,900 M/WBE 6.43%

MBE 1.43% WBE 5%

HVAC Improvements Sigma Engineering (MBE)

FABCO Construction

(Majority) $909,000

M/WBE 0% MBE 0% WBE 0%

HVAC Improvements

Sud Associates (MBE)

Lomax Construction

(Majority) $1,019,500

M/WBE 71.01% MBE 71.01%

WBE 0% Track Replacement Hugh Creed

Associates (Majority)

Bar Construction (Majority) $331,500

M/WBE 13.14% MBE 0%

WBE 13.14% Track Replacement Hugh Creed

Associates (Majority)

WC Construction (MBE) $312,700

M/WBE 24.16% MBE 16.98% WBE 7.18%

HVAC Improvements Triad Engineering Consultants (Majority)

H.M. Kern (Majority) $808,500

M/WBE 1.30% MBE 0.54% WBE 0.76%

Chiller & Boiler Replacement

Triad Engineering Consultants (Majority)

Jeff Hargett Mechanical (Majority)

$188,500 M/WBE 8.90%

MBE 4.32% WBE 4.58%

Roof Replacement Rick Nuhn, (Majority)

S&S Building and Development

(Majority) $858,000

M/WBE 14.96% MBE 9.06% WBE 5.90%

Note: these are not Plan B projects.

SUBCONTRACTOR SUBSTITUTION RULES

The District has rules that limit the ability of prime contractors to avoid the M/WBE goals program by substituting subcontractors after contract award.

1. The Director of Construction and the M/WBE Administrator must be notified in writing immediately upon the need to replace any Subcontractor. The notification shall include the following:

a . The basis for the request to terminate;

b . The estimated percentage of completion of the work by the affected Subcontractor;

c . The amount due to the affected Subcontractor, if any, based on work in place/completed;

d. A description of any defective work;

e. The estimated cost of any corrective work; and,





f . Any back charges claimed against the affected Subcontractor.

2. A Contractor shall not replace a mechanical, electrical, or plumbing Subcontractor listed on its bid without the prior written consent of the Director of Construction (following prior notification to the Board) for good cause shown. A Contractor shall not replace an M/WBE listed on its Affidavit A without the prior written consent of the Director of Construction and the M/WBE Administrator (following prior notification to the Board) and for good cause shown.

3. Upon receipt of notification from a Contractor that it seeks to replace a Subcontractor, the Director of Construction shall inform the Superintendent or his/her designee. The Director of Construction also shall immediately provide the affected Subcontractor written notice of the request, and an opportunity of no less than seven (7) days within which to respond.85

4. M/WBE CERTIFICATION The District M/WBE program uses the following definition of “minority”:

A person who is a citizen or lawful permanent resident of the United States and who is:

a . African-American, that is, a person having origins in any of the original racial groups in Africa;

b . Hispanic, that is, a person of Spanish or Portuguese culture with origins in Mexico, South or Central America, or the Caribbean Island, regardless of race;

c . Native-American, that is, a person having origins in any of the original peoples of North America;

d. Asian-American, that is, persons having origin in any of the countries of the Far East, Southeast Asia, or the Indian areas.86

As required, the District recognizes State of North Carolina HUB certification. North Carolina defines a “minority person” as:

“…an individual who is a citizen or lawful permanent resident of the United States and who is Asian American, Black, Female, Hispanic, Native American, Disabled or Socially Disadvantaged.”87

The District uses the following definition of M/WBE:

Minority or Women or Disabled or Disadvantaged Business Enterprises (M/WBE)” – A business enterprise owned and controlled at a minimum of 51% by one or more members of a group defined as a minority or women. A business certified as an M/WBE will show evidence of ownership and

85 Guilford County Board of Education Administrative Procedure, Participation By Minority And Women Owned Businesses (M/WBE), Minority Business Subcontractor Goals. March 29, 2007. 86 Guilford County Board of Education Administrative Procedure, Participation By Minority And Women Owned Businesses (M/WBE), Definitions. March 29, 2007. 87 North Carolina G.S. 143-128.





management interests and the daily business operations are real and continuing not created solely to meet the M/WBE requirements. 88

The State of North Carolina defines "minority businesses" as,

…businesses in which at least fifty-one percent ownership is held by one or more minority persons or by individuals defined as socially and economically disadvantaged.89

The U.S. government defines “socially and economically disadvantaged” individuals under the Small Business Act as follows:

Socially disadvantaged individuals are those who have been subjected to racial or ethnic prejudice or cultural bias because of their identity as a member of a group without regard to their individual qualities.

Economically disadvantaged individuals are those socially disadvantaged individuals whose ability to compete in the free enterprise system has been impaired due to diminished capital and credit opportunities as compared to others in the same business area who are not socially disadvantaged. In determining the degree of diminished credit and capital opportunities the Administration shall consider, but not be limited to, the assets and net worth of such socially disadvantaged individual.90

Note that both the District and the State of North Carolina include the disabled and disadvantaged in the definition of M/WBE.

5. OUTREACH The District’s outreach efforts have included:

Advertising District opportunities

Holding pre-bid conferences.

Posting forthcoming construction projects on the District website

Holding workshops on how to do business with District.

Link to state certified vendors on web site

Holding one-on-one meetings with MBEs.

Attending meetings of the United Minority Contractors

Attending the HUB mixer and state construction conference

88 Guilford County Board of Education Administrative Procedure, Participation By Minority And Women Owned Businesses (M/WBE), Definitions. March 29, 2007. 89 North Carolina General Statutes 143-128. 90 15 USC 637(a)(5),(6).





Attending local M/WBE outreach events

Presenting at HUB academy meetings

Commodity lists generated for users to identify MWBE vendors

Special handling for projects requiring Panduit certification

Joint check agreement

GCS outreach efforts on behalf of the maintenance department have been particularly in the areas that are typically not inclusive which are roofing, HVAC and paving. The outreach consisted of meeting with the contractors encouraging them to increase their participation. In roofing for example, GCS is now able to achieve close to 20 percent participation in many GCS bids, especially in the area of material sales and with sub-contractors in HVAC.

6. TRACKING M/WBE UTILIZATION North Carolina law requires that (A) all-public entities subject to G.S. 143-128.2 are to report to the state on all projects above $30,000. This threshold changed from $5,000 in 2005.

(1) the verifiable percentage goal.

(2) the type and total dollar value of the project, minority business utilization by minority business category, trade, total dollar value of contracts awarded to each minority group for each project, the applicable good faith effort guidelines or rules used to recruit minority business participation, and good faith documentation accepted by the public entity from the successful bidder.

(3) the utilization of minority businesses under the various construction methods under G.S. 143-128(a1).91

Table 3-3 shows the District’s M/WBE utilization submitted to the State HUB Office pursuant to the reporting requirements for the first three quarters of FY 2013-14. The District spent over $3.2 million with M/WBEs, 12.67 percent of total spending reported.

In addition to the requirements of the State, GCS captures and reports data internally on construction projects from $5,000 to $30,000. These projects are managed through a process known as “PRRT,” the Purchase Requisition Review Team. These efforts result in an approximate 50/50 majority/minority participation percentage.

91 North Carolina Statutes § 143-128.3. - Minority Business Participation Administration.






M/WBE SPENDING ON GOODS AND SERVICES - STATE CERTIFIED FY 2013-14

FY 2013-14 MBE WBE M/WBE TOTAL $ % $ % $ %

1st Quarter $421,181 6.53% $678,221 10.51% $1,099,402 17.04% $6,452,549 2d Quarter $185,805 2.28% $201,503 2.48% $387,308 4.76% $8,134,724 3rd Quarter $127,332 1.17% $1,612,795 14.82% $1,740,127 15.99% $10,882,881 Total $734,318 2.88% $2,492,519 9.79% $3,226,837 12.67% $25,470,154

Source: Guilford County Schools.

Table 3-3A below represent M/WBE spending by GCS to self-identified HUB vendors and State Certified vendors (ALL FIRMS) who were paid by GCS. Before the implementation of statewide certification in 2009, firms certified by other governmental entities were included in reportable numbers. We continue to capture the data for these vendors, identifying thru self-validation as an M/WBE because we maintain that it represents a more accurate reflection of our M/WBE participation and GCS total dollars spent.

TABLE 3-3A GUILFORD COUNTY SCHOOLS

M/WBE SPENDING GOODS AND SERVICES ALL FIRMS (STATE CERTIFIED & NON-STATE CERTIFIED)

FY 2013-14 FY 2013-14 MBE WBE M/WBE/DBE Total

$ % $ % $ % 1st Quarter $1,110,959 17.22% $824,582 12.78% $2,065,527 32.01% $6,452,549 2d Quarter $431,240 5.30% $393,929 4.84% $825,170 10.14% $8,134,724 3rd Quarter $244,978 2.25% $2,115,216 19.44% $ 2,360,194 21.69% $10,882,881 Total $1,787,177 7.02% $ 3,333,727 13.09% $ 5,250,891 20.62% $25,470,154

Source: Guilford County Schools. See attachment for calculations in table 3-3A.

Table 3-3B below represent dollars paid to self-identified HUB vendors who are not currently certified by the State. We continue to capture the data for these vendors, because we maintain that it represents a more accurate reflection of our M/WBE participation.

TABLE 3-3B GUILFORD COUNTY SCHOOLS

M/WBE SPENDING GOODS AND SERVICES SHOWS MONEY SPENT AND NOT REPORTED BY GCS FOR NON-STATE

CERTIFIED FIRMS FY 2013-14

FY 2013-14 MBE WBE M/WBE/DBE Total GCS $ % $ % $ % $ not tracked

QUARTERS 1-3 $1,052,859 4.13% $ 841,208 3.30% $2,024,054 7.94% $2,024,054 Source: Guilford County Schools.





7. M/WBE COORDINATOR The District’s M/WBE Coordinator reports directly to the District Chief Information Officer. M/WBE is part of Information Technology, Student Information and Operations. The District M/WBE Coordinator position is currently vacant. The position has existed at least since 1994.92

The District M/WBE Coordinator’s primary responsibility is for outreach and communication with M/WBE contractors who seek to work on construction projects for the school district. In addition to the District’s M/WBE Coordinator, the District has a HUB Advisory Committee which meets periodically.

8. PROMPT PAYMENT It is North Carolina state policy for local government agencies to make prompt payments on public construction contracts.93 Interest of 1 percent per month on the unpaid balance to a prime contractor is to commence 46 days after project completion.94 Subcontractors are to be paid within seven days of payment to the prime contractor. Interest of 1 percent per month on the unpaid balance to a subcontractor commences on the eighth day after the prime has been paid.95 The North Carolina prompt payment statute also regulates the holding of retainage on public construction projects.96

9. LOAN PROGRAMS Like most school districts, Guilford County does not maintain small business lending or business development programs, although there are several such programs in the Greensboro area. The chapter briefly summarizes a selection of these programs below.

The Small Business Administration (SBA) maintains the 504 Loan Program, the 7A Loan Guarantee Program, the SBA’s Community Advantage program and the SBA’s Pre-qualification program. The 504 Program is for the acquisition of fixed assets only, such as real estate and equipment. Small Business Administration 504 loans range from $250,000 to $1,500,000. The 7A Guaranty Program provides lines of credit or term loans for most business purposes. The SBA’s 7A loans range from $50,000 to $2,000,000. As noted above, the Community Advantage Program targets low and moderate-income neighborhoods. The Small Business Development Center PreQual Program assists firms with obtaining SBA loan guarantees. This program is for DBEs, veterans, and rural businesses. The loan funds can be used for working capital, debt payment, equipment and inventory purchases, construction, and real estate purchases.

92 Guilford County Schools Job Description Job Title: Coordinator – M/WBE, 1994. 93 N.C. Gen. Stat. § 143-134-1(a). 94 N.C. Gen. Stat. § 143-134-1(a). 95 N.C. Gen. Stat. § 143-134-1(b). 96 N.C. Gen. Stat. § 143-134-1(b-1).

http://www.sba.gov/financing/index.html

http://www.sba.gov/financing/index.html





10. BONDING PROGRAM The state of North Carolina requires performance bonds on construction contracts to perform public work over $300,000.97 The District does not provide direct bonding assistance to meet these requirements. However, some local programs help firms with bonding.

Under the SBA's Prior Approval Program, the SBA guarantees 90 percent of the losses on contracts up to $100,000 for socially and economically disadvantaged businesses, as well as HUBZone firms, 8(a) firms and veteran owned businesses. The SBA can guarantee bonds up to 80 percent of a $6.5 million bond if a federal contracting officer certifies that the guarantee is necessary. The SBA Preferred Program allows bonds without prior approval. The SBA guarantee for this program is 70 percent. The SBA program does not bond a contractor but guarantees a surety bond. The U.S. DOT STLP, referred to above, has a bonding component.

11. MANAGEMENT AND TECHNICAL ASSISTANCE NUSSBAUM CENTER FOR ENTREPRENEURSHIP

The Nussbaum Center is a nonprofit which operates a small business incubator in Greensboro. The Center’s EASE program assists with business plans, mentoring, marketing, finance, human resources, technical, insurance, and legal assessments.

The Center has graduated 260 firms over a twenty-seven year period. The Nussbaum Center currently has 58 client companies of which 27 percent are African American and 40 percent are women owned.

GUILFORD TECHNICAL COMMUNITY COLLEGE SMALL BUSINESS CENTER

The Small Business Center provides seminars and classes as well as online counseling.

PROCUREMENT TECHNICAL ASSISTANCE CENTER

There are seven branches of the national Procurement Technical Assistance Program (PTAP) in North Carolina, including one in Greensboro at North Carolina A&T. PTAP started in 1985 to assist businesses selling to the U.S. Department of Defense (DOD). PTAP helps with local government procurement in addition to state and federal procurement.

SMALL BUSINESS DEVELOPMENT CENTERS (SBDC)

The North Carolina SBDC Network assists small businesses in the areas of start-up, expansion organizational structure, and management. SBDCs provide free one-on-one consulting by certified consultants. SBDCs

97 N.C. Gen. Stat. § 44A-26.





assist firms in the following areas: accounting, finance, marketing, operations, new venture planning, loan proposals, strategic planning, employee manuals and technical assistance. The SBDC puts on a series on government contracting. The SBDC collaborates with the SBA the University of North Carolina system and the North Carolina Chamber of Commerce. There is a SBDC located in Greensboro at North Carolina A&T.

TRIAD SCORE

The Triad SCORE provides counseling and mentoring and a comprehensive business support website.

12. CONCLUSIONS The District has a long-standing M/WBE policy. There have been stable M/WBE goals. Guilford County Schools has not implemented M/WBE project goals as a rigid quota. They use the State of North Carolina HUB certification; but, identify firms that were previously certified through other state-approved programs, or were self-identified. These numbers are presented in separate reports. The District and the State of North Carolina include the disabled and disadvantaged in the definition of M/WBE. Lastly, the District collaborates with other business development organizations in the Greensboro area.


4 | MARKET AREA AND UTIL IZATION ANALYSES



Chapter 4 presents the market area and utilization analyses results of contracting and procurement expenditures for the Guilford County School District’s (District) prime contracts and subcontracts for the procurement categories of 1) Construction, 2) Architecture and Engineering, 3) Professional Services, 4) Other Services, and 5) Goods and Supplies. The analyses presented in this chapter reflect prime and subcontract expenditures from July 1, 2009, through June 30, 2014.

The following section, Chapter Definitions, presents the definitions to key terms that are used in this chapter.

1. CHAPTER DEFINITIONS Business Ownership Classification. To understand the analyses presented in this study, it is important to define M/WBE firms. The following section provides the study definitions for M/WBE firms.

M/WBE Firms. For the purposes of this study, M/WBE firms are firms owned by minorities or women regardless of certification status. Therefore, M/WBE firms include all identified minorities- and women-owned firms (non-certified and certified). MGT used this approach in analyzing the utilization and availability of firms and to review disparities, if any. Furthermore, courts have accepted disparity studies based on race, ethnicity, and gender of the business owner as opposed to certification status.

M/WBE firms were defined as firms that are at least 51 percent owned or controlled by members of the following groups. These groups were defined according to the United States (U.S.) Census Bureau.

African Americans: U.S. citizens or lawfully admitted permanent residents having an origin in any of the black racial groups of Africa.

Hispanic Americans: U.S. citizens or lawfully admitted permanent residents of Mexican, Puerto Rican, Cuban, Central or South American, or other Spanish or Portuguese cultures or origins regardless of race. This includes all Hispanics (white or nonwhite).

Asian Americans: U.S. citizens or lawfully admitted permanent residents who originate from the Far East, Southeast Asia, the Indian subcontinent, or the Pacific Islands.

Native Americans: U.S. citizens or lawfully admitted permanent residents who originate from any of the original peoples of North America and who maintain cultural identification through tribal affiliation or community recognition.

Nonminority Woman (Female): U.S. citizens or lawfully admitted permanent residents who are non-Hispanic white woman.


1. Chapter Definitions

2. Data Collection and Management

3. Market Area Analysis

4. Utilization Analysis

5. Conclusion





Minority women- and male-owned firms were classified and assigned to their corresponding minority groups. For example, a Hispanic American woman- or Hispanic American male-owned firm was assigned to the Hispanic American-owned firm minority group.

Non-M/WBE Firms. Firms that were identified as nonminority male or majority-owned were classified as non-M/WBE firms. If there was no indication of business ownership, these firms were also classified as non-M/WBE firms.

The M/WBE determinations in this report were based on classifications in the District-provided data (such as vendor data, certified firms, and payment data). In addition, MGT conducted further research to determine the proper business owner classification. If unclear or unknown, the business owner classification was cross referenced with additional sources (custom census, surveys, interviews, and individual research).

Market Area Methodology. In order to establish the appropriate geographic boundaries for the study’s analyses, an overall market area was established. The geographic units (such as counties) are based on the following considerations: 1) the courts have accepted the use of standard geographic units in conducting equal employment opportunity and disparity studies; 2) geographic units are externally determined, so there are no subjective determinations; and 3) U.S. Census and other federal agencies routinely collect data by geographic unit. The following presents the methodology used to determine the overall market area and relevant market area.

Overall Market Area Analyses. To determine the market area and establish the extent, to which District utilized firms on Construction, Architecture and Engineering, Professional Services, Other Services projects, and the purchase of Goods and Supplies MGT staff reviewed the geographic location by using MGT’s Zone Improvement Plan (ZIP) Code Database of each firm conducting business with the District during the study period. Once the firms’ geographic locations were identified the dollars expended with the firms were grouped by the county, state, and business category and referred to as the overall market area. The overall market analyses presents the results based on firms located inside the state of North Carolina and outside the state of North Carolina. The overall market area results by business category are presented in Appendix K, Detailed Market Area Analysis.

Relevant Market Area Analyses. Once the overall market was established, the relevant market area was determined for each business category. The firm’s geographic location that received the most dollars, all of which totaled the majority of the District’s spending98 of the overall market area, were identified. In another relevant case, the court accepted less than 100 percent of data when it was reasonable to assume that the missing data would not significantly change the results

98 MGT uses the “75 percent rule” to determine the relevant market area. This rule is generally accepted in antitrust cases. In another relevant case, James C. Jones v. New York County Human Resources Administration, 528 F.2d 696 (.2d Cir. 1976), the court accepted less than 100 percent of the data when it was reasonable to assume that the missing data would not significantly change the results of the analysis.





of the analysis99. Subsequently, the results were summarized by county according to the location of each firm that provided Construction, Architecture and Engineering, Professional Services, Other Services, and Goods and Supplies to the District. Subsequently, the utilization analyses was based on firms located in the Greensboro-Winston Salem-High Point, NC Combined Statistical Area (CSA)100 plus additional counties in Central North Carolina. For purposes of this study the counties included in the relevant market are called the Guilford County Schools (GCS) Relevant Market Area. The GCS market area consist of the following North Carolina counties:

Alamance Anson Cabarrus Caswell Chatham Davidson Davie, Durham

Forsyth Franklin Granville Guilford Hoke Lee Mecklenburg Montgomery

Moore Orange Person Richmond Rowan Scotland Stanly Randolph

Rockingham Stokes Surry Union Vance Wake Warren Yadkin

Procurement Categories are defined by the District as follows.

CONSTRUCTION

General building contractors engaged primarily in the construction of commercial buildings.

Light maintenance construction services such as carpentry work; electrical work; installation of carpeting; air-conditioning repair, maintenance, and installation; plumbing; and renovation.

Other related services such as water-lining and maintenance, asbestos abatement, drainage, dredging, grading, hauling, landscaping (for large construction projects such as boulevards and highways), paving, roofing, and toxic waste clean-up.

ARCHITECTURE AND ENGINEERING

State-licensed architect.

Professional engineer.

Firm owned by parties with such designations.

PROFESSIONAL SERVICES

Financial services.

Legal services.

99 James C. Jones v. New York County Human Resources Administration, 528 F.2d 696 (.2d Cir. 1976). 100 A business is deemed located in the Relevant Market Area if its headquarters or local office is located within the area.





Medical services.

Educational services.

Other professional services.

OTHER SERVICES

Janitorial and maintenance services.

Uniformed guard services.

Computer services.

Certain job shop services.

Graphics, photographic services.

Landscaping.

Other nontechnical or unlicensed services.

GOODS AND SUPPLIES

Office goods.

Miscellaneous building materials.

Books.

Equipment.

Vehicles.

Computer equipment.

2. DATA COLLECTION AND MANAGEMENT To determine the most appropriate data for our use in this study and to identify data sources, MGT of America, Inc. (MGT) conducted data assessment interviews with key District staff knowledgeable about the District’s contracting and purchasing. Based on the data assessment interviews and follow-up discussions with the District staff, it was agreed that in order to collect the most comprehensive sets of data, data would be collected from various data sources. Electronic encumbrance data and vendor data for primes was extracted from the District’s AS400 and OnDemand Systems and was provided for each year of the study (July 1, 2009, through June 30, 2014). The reported subcontractor payment data was retrieved from the state of North Carolina’s HUBSCO construction tracking and reporting system and provided by the state’s Office of Historically Underutilized Business (HUB) for each year of the study period for Construction only. Bid tabulations, from which the District Construction Management at Risk prequalified vendors was obtained and submitted to MGT by the Districts Facilities Department. Upon receipt of these datasets a Master Encumbrance Database and a Master Vendor Database were developed. The Master Encumbrance Database was the basis for conducting the market area and utilization analyses. The Master Vendor Database was





used as part of the availability analysis discussed in Chapter 5, Availability and Disparity Analyses, and the anecdotal data collection discussed in Chapter 7, Anecdotal Analysis.

Each database was “cleaned” by formatting the data fields in a consistent format, updating missing variables such as address, race/ethnicity/gender, procurement category, and identifying records that should be excluded from the analyses. Figure 4-A gives examples of records excluded. Once excluded records were identified, MGT used various source data and extended research to update missing variables not provided by the District in each database.

FIGURE 4-A EXAMPLES OF RECORDS EXCLUDED

Duplicate records Transactions outside of the study period Transactions associated to nonprofits and

government entities

Salary and fringe benefits, training, travel, or conference fees

Employee Reimbursements Administrative items such as utility payments,

leases for real estate, or insurance

As stated previously, the utilization analysis was disaggregated into the five procurement categories of Construction, Architecture and Engineering, Professional Services, Other Services, and Goods and Supplies. To identify the appropriate ethnic and procurement categories the encumbrance data are grouped in, MGT utilized the MBE codes maintained in the District’s procurement system.

3. MARKET AREA ANALYSIS In order to establish the appropriate geographic boundaries for the statistical analysis, market areas were determined. As described in Section 1, Chapter Definitions, first, the overall market area was determined and then the relevant market area was established. The following analysis presents the results based on the relevant market area, which is the GCS Market Area. The corresponding detailed market area analyses for all business categories are presented in Appendix K, Detailed Market Area Analysis to this report.

The data used to determine the overall and relevant market areas for the District’s business categories were as follows:

Number of individual firms.

Percentage of total firms.

Number of purchase order awarded.

Percentage of total purchase orders awarded.

Payments made.

Percentage of total dollars.





Table 4-1 and Figure 4-B below show that firms located within the relevant market area accounted for 86.38 percent of the dollars paid for services provided at the prime level.

TABLE 4-1 MARKET AREA ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS CATEGORY

LOCATION OF FIRMS DOLLARS PERCENT OF

DOLLARS CUMULATIVE

PERCENT1

ARCHITECTURE & ENGINEERING Inside Market Area $17,697,382 99.85% 99.85% Outside Market Area $26,215 0.15% 100.00% ARCHITECTURE & ENGINEERING, TOTAL $17,723,597 100.00% CONSTRUCTION Inside Market Area $253,170,520 89.19% 89.19% Outside Market Area $30,692,026 10.81% 100.00% CONSTRUCTION, TOTAL $283,862,546 100.00% PROFESSIONAL SERVICES Inside Market Area $23,888,348 88.65% 88.65% Outside Market Area $3,059,032 11.35% 100.00% PROFESSIONAL SERVICES, TOTAL $26,947,380 100.00% OTHER SERVICES Inside Market Area $40,961,718 84.13% 84.13% Outside Market Area $7,726,615 15.87% 100.00% OTHER SERVICES, TOTAL $48,688,333 100.00% GOODS AND SUPPLIES Inside Market Area $167,629,976 81.58% 81.58% Outside Market Area $37,836,900 18.42% 100.00% GOODS AND SUPPLIES $205,466,876 100.00% ALL BUSINESS CATEGORIES Inside Market Area $503,347,944 86.38% 86.38% Outside Market Area $79,340,787 13.62% 100.00% ALL BUSINESS CATEGORIES, TOTAL $582,688,732 100.00%

Source: MGT developed a Master Encumbrance Database based on dollars expended by Guilford County Schools between July 1, 2009, and June 30, 2014. 1 Cumulative percent of total dollars for business category.





FIGURE 4-B MARKET AREA ANALYSIS, PRIME LEVEL

PERCENTAGE OF DOLLARS BY BUSINESS CATEGORY

Source: MGT developed a Master Encumbrance Database based on dollars expended by Guilford County Schools between July 1, 2009, and June 30, 2014.

Figure 4-C below shows that firms located within the relevant market area accounted for 38.6 percent of the dollars paid for services provided at the subcontractor level.

99.85%

89.19%

88.65%

84.13%

81.58%

86.38%

0.15%

10.81%

11.35%

15.87%

18.42%

13.62%

0.00% 20.00% 40.00% 60.00% 80.00% 100.00%

ARCHITECTURE & ENGINEERING

CONSTRUCTION


OTHER SERVICES

GOODS AND SUPPLIES

ALL BUSINESS CATEGORIES

Inside Market Area Outside Market Area





FIGURE 4-C MARKET AREA ANALYSIS, SUBCONTRACTOR LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS CATEGORY

Source: MGT developed a Master Subcontractor Database based on HUBSCO dollars expended by Guilford County Schools between July 1, 2009, and June 30, 2014

4. UTILIZATION ANALYSIS As mentioned in the Section 1, Chapter Definitions, the utilization analyses are based on the relevant market area, which was determined to be the GCS Relevant Market. The subsequent analyses presents MGT’s utilization analyses of firms on Construction, Architecture and Engineering, Professional Services, Other Services, and Goods and Supplies at the prime and Construction subcontractor levels.

Table 4-2 and Figure 4-D below show that the utilization of M/WBE prime firms, as a whole, was 5.96 percent in Construction. In terms of non-M/WBE firms, the utilization was 94.04 percent in Construction contracting. African American-owned firms accounted for 3.00 percent of utilization in Construction, followed by nonminority female-owned firms which accounted for 2.86 percent of utilization in Construction.





TABLE 4-2 UTILIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION CONSTRUCTION

BUSINESS OWNERSHIP CLASSIFICATION

2010 2011 2012 2013 2014 TOTAL

($) ($) ($) ($) ($) ($)

African American Firms $2,021,681 $1,425,041 $1,759,640 $1,415,210 $973,347 $7,594,919

Asian American Firms $0 $0 $117,950 $0 $0 $117,950

Hispanic American Firms $0 $0 $3,469 $98,955 $22,816 $125,240

Native American Firms $0 $0 $0 $0 $0 $0

TOTAL MINORITY FIRMS $2,021,681 $1,425,041 $1,881,059 $1,514,165 $996,163 $7,838,109

Nonminority Female Firms $1,437,353 $1,220,684 $1,575,025 $1,079,277 $1,929,542 $7,241,880 TOTAL M/WBE FIRMS $3,459,033 $2,645,725 $3,456,084 $2,593,442 $2,925,705 $15,079,989

TOTAL NON-M/WBE FIRMS $42,852,028 $17,905,177 $98,989,229 $40,647,235 $37,696,862 $238,090,530

TOTAL FIRMS $46,311,062 $20,550,902 $102,445,313 $43,240,677 $40,622,567 $253,170,520


2010 2011 2012 2013 2014 TOTAL

(%) (%) (%) (%) (%) (%)

African American Firms 4.37% 6.93% 1.72% 3.27% 2.40% 3.00%

Asian American Firms 0.00% 0.00% 0.12% 0.00% 0.00% 0.05%

Hispanic American Firms 0.00% 0.00% 0.00% 0.23% 0.06% 0.05%

Native American Firms 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%

TOTAL MINORITY FIRMS 4.37% 6.93% 1.84% 3.50% 2.45% 3.10%

Nonminority Female Firms 3.10% 5.94% 1.54% 2.50% 4.75% 2.86%

TOTAL M/WBE FIRMS 7.47% 12.87% 3.37% 6.00% 7.20% 5.96%

TOTAL NON-M/WBE FIRMS 92.53% 87.13% 96.63% 94.00% 92.80% 94.04%

TOTAL FIRMS 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% Source: MGT developed a Master Encumbrance Database based on dollars expended by Guilford County Schools between July 1, 2009, and June 30, 2014. Rounding of the percentages causes some total to not equal 100.





FIGURE 4-D UTILIZATION OF FIRMS ANALYSIS, PRIME LEVEL



3.00% 0.05% 0.05% 0.00% 3.10% 2.86% 5.96%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

AfricanAmerican Firms

Asian AmericanFirms

HispanicAmerican Firms

Native AmericanFirms

TOTALMINORITY

FIRMS

NonminorityFemale Firms

TOTAL M/WBEFIRMS





Table 4-3 and Figure 4-E below show that the utilization of M/WBE firms, as a whole, was 59.9 percent in Construction subcontracting. The utilization of non-M/WBE firms, as a whole, was 40.1 percent in Construction subcontracting. Nonminority women-owned firms accounted for 40.5 percent of utilization in Construction subcontracting, followed by African American-owned firms which accounted for 14.7 percent, Hispanic American-owned firms representing 3.3 percent, and Native American-owned firms at 1.5 percent.

TABLE 4-3 UTILIZATION OF FIRMS ANALYSIS, SUBCONTRACTOR LEVEL



2010 2011 2012 2013 2014 TOTAL

($) ($) ($) ($) ($) ($)

African American Firms $2,812,266 $370,520 $792,529 $74,551 $4,730 $4,054,596

Asian American Firms $0 $0 $0 $0 $0 $0

Hispanic American Firms $575,557 $212,910 $144,150 $80,000 $0 $1,012,617

Native American Firms $103,700 $279,120 $69,947 $0 $0 $452,767

TOTAL MINORITY FIRMS $3,491,523 $862,550 $1,006,626 $154,551 $4,730 $5,519,980

Nonminority Female Firms $8,653,974 $1,163,525 $395,162 $2,322,200 $22,383 $12,557,244 TOTAL M/WBE FIRMS $12,145,497 $2,026,075 $1,401,788 $2,476,751 $27,113 $18,077,224

TOTAL NON-M/WBE FIRMS $10,854,751 $1,912,394 $175,150 $124,201 $0 $13,066,496

TOTAL FIRMS $23,000,248 $3,938,469 $1,576,938 $2,600,952 $27,113 $31,143,720


2010 2011 2012 2013 2014 TOTAL

(%) (%) (%) (%) (%) (%)







TOTAL M/WBE FIRMS 52.81% 51.44% 88.89% 95.22% 100.00% 58.04%







FIGURE 4-E UTILIZATION OF FIRMS ANALYSIS, SUBCONTRACTOR LEVEL



Table 4-4 and Figure 4-F below show that the utilization of M/WBE firms, as a whole, was 21.22 percent in Architecture and Engineering services at the prime contractor/ consultant level. In terms of non-M/WBE firms, as a whole, the utilization was 78.78 percent in Architecture and Engineering services.

African American-owned accounted for 11.02 percent of utilization in Architecture and Engineering, followed by Nonminority female-owned firms which accounted for 6.26 percent, and Asian American-owned firms at 3.94 percent.

13.02%

0.00% 3.25% 1.45%

17.72%

40.32%

58.04%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%


Asian AmericanFirms



TOTALMINORITY

FIRMS


TOTAL M/WBEFIRMS






DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION ARCHITECTURE AND ENGINEERING


2010 2011 2012 2013 2014 TOTAL

($) ($) ($) ($) ($) ($)

African American Firms $613,277 $42,876 $874,211 $316,483 $103,867 $1,950,715

Asian American Firms $115,523 $99,960 $272,698 $125,823 $82,914 $696,918

Hispanic American Firms $0 $0 $0 $0 $0 $0


TOTAL MINORITY FIRMS $728,800 $142,836 $1,146,909 $442,306 $186,782 $2,647,633

Nonminority Female Firms $452,227 $164,101 $225,561 $213,913 $52,679 $1,108,479 TOTAL M/WBE FIRMS $1,181,027 $306,937 $1,372,470 $656,219 $239,460 $3,756,112

TOTAL NON-M/WBE FIRMS $5,496,894 $648,154 $4,496,538 $2,080,950 $1,218,735 $13,941,270

TOTAL FIRMS $6,677,921 $955,090 $5,869,008 $2,737,168 $1,458,195 $17,697,382


2010 2011 2012 2013 2014 TOTAL

(%) (%) (%) (%) (%) (%)







TOTAL M/WBE FIRMS 17.69% 32.14% 23.39% 23.97% 16.42% 21.22%







FIGURE 4-F UTILIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION ARCHITECTURE AND ENGINEERING


Table 4-5 and Figure 4-G below show that the utilization of M/WBE firms, as a whole, was 22.05 percent in Professional Services at the prime consultant level. In terms of Non-M/WBE firms, as a whole, the utilization was 77.95 percent in Professional Services. Nonminority female-owned firms accounted for 14.28 percent of utilization in professional services, followed by African American-owned firms which accounted for 7.08 percent, Asian American-owned firms representing .47 percent, and Hispanic American-owned firms at .22 percent.

11.02%3.94%

0.00% 0.00%

14.96%

6.26%

21.22%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%


Asian AmericanFirms



TOTALMINORITY

FIRMS


TOTAL M/WBEFIRMS






DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION PROFESSIONAL SERVICES


2010 2011 2012 2013 2014 TOTAL

($) ($) ($) ($) ($) ($)

African American Firms $452,337 $306,266 $408,857 $418,156 $105,276 $1,690,892

Asian American Firms $39,773 $72,527 $0 $0 $0 $112,300

Hispanic American Firms $0 $0 $5,550 $46,930 $0 $52,480


TOTAL MINORITY FIRMS $492,110 $378,793 $414,407 $465,086 $105,276 $1,855,672

Nonminority Female Firms $607,310 $583,203 $865,760 $494,807 $860,064 $3,411,144 TOTAL M/WBE FIRMS $1,099,420 $961,997 $1,280,167 $959,893 $965,339 $5,266,816


TOTAL FIRMS $7,606,662 $6,141,908 $3,363,506 $3,081,147 $3,695,125 $23,888,348


2010 2011 2012 2013 2014 TOTAL

(%) (%) (%) (%) (%) (%)







TOTAL M/WBE FIRMS 14.45% 15.66% 38.06% 31.15% 26.12% 22.05%







FIGURE 4-G UTILIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION PROFESSIONAL SERVICES


Table 4-6 and Figure 4-H below show that the utilization of M/WBE firms, as a whole, was 19.22 percent in Other Services at the prime vendor level. In terms of non-M/WBE firms, as a whole, the utilization was 80.78 percent in Other Services. African American-owned accounted for 10.93 percent of utilization in Other Services, followed by Nonminority female-owned firms which accounted for 7.46 percent, and Hispanic American-owned firms at .82 percent.

7.08%0.47% 0.22% 0.00%

7.77%14.28%

22.05%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%


Asian AmericanFirms



TOTALMINORITY

FIRMS


TOTAL M/WBEFIRMS






DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION OTHER SERVICES


2010 2011 2012 2013 2014 TOTAL

($) ($) ($) ($) ($) ($)

African American Firms $989,291 $621,195 $1,104,513 $836,378 $926,064 $4,477,439

Asian American Firms $0 $0 $0 $0 $4,750 $4,750

Hispanic American Firms $105,307 $1,000 $118,450 $2,641 $109,728 $337,126


TOTAL MINORITY FIRMS $1,094,597 $622,195 $1,223,112 $839,019 $1,040,542 $4,819,466

Nonminority Female Firms $475,221 $523,383 $532,359 $1,109,693 $414,480 $3,055,135 TOTAL M/WBE FIRMS $1,569,818 $1,145,577 $1,755,471 $1,948,713 $1,455,022 $7,874,601


TOTAL FIRMS $6,242,311 $6,722,230 $9,976,401 $7,654,979 $10,365,797 $40,961,718


2010 2011 2012 2013 2014 TOTAL

(%) (%) (%) (%) (%) (%)







TOTAL M/WBE FIRMS 25.15% 17.04% 17.60% 25.46% 14.04% 19.22%







FIGURE 4-H UTILIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION OTHER SERVICES


Table 4-7 and Figure 4-I below show that the utilization of M/WBE firms, as a whole, was 11.58 percent in Goods and Supplies at the prime vendor level. In terms of non-M/WBE firms, as a whole, the utilization was 88.42 percent in Goods and Supplies. Nonminority female-owned firms accounted for 9.05 percent of utilization in Goods and Supplies, followed by African American-owned firms which accounted for 2.43 percent, Asian American-owned firms representing .11 percent, and Hispanic and Native American-owned firms had no participation.

10.93%

0.01% 0.82% 0.00%

11.77%7.46%

19.22%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%


Asian AmericanFirms



TOTALMINORITY

FIRMS


TOTAL M/WBEFIRMS






DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION GOODS AND SUPPLIES


2010 2011 2012 2013 2014 TOTAL

($) ($) ($) ($) ($) ($)

African American Firms $810,839 $1,205,655 $976,456 $658,140 $418,084 $4,069,175

Asian American Firms $0 $110,129 $67,125 $0 $4,110 $181,364

Hispanic American Firms $490 $0 $0 $1,314 $0 $1,804


TOTAL MINORITY FIRMS $811,329 $1,315,784 $1,043,582 $659,454 $422,194 $4,252,343

Nonminority Female Firms $1,581,538 $2,311,208 $3,797,448 $4,556,765 $2,915,581 $15,162,540 TOTAL M/WBE FIRMS $2,392,867 $3,626,992 $4,841,030 $5,216,219 $3,337,775 $19,414,883


TOTAL FIRMS $32,063,709 $28,786,863 $35,394,879 $36,587,977 $34,796,549 $167,629,976


2010 2011 2012 2013 2014 TOTAL

(%) (%) (%) (%) (%) (%)







TOTAL M/WBE FIRMS 7.46% 12.60% 13.68% 14.26% 9.59% 11.58%







FIGURE 4-I UTILIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION GOODS AND SUPPLIES


5. CONCLUSION Calculating utilization or dollars paid to M/WBE firms between July 1, 2009 and June 30, 2014 is the primary focus of this chapter. The results of the analyses presented illustrates utilization of African American firms at the prime level in all business categories. Overall, M/WBE firms won prime contracts with the District in all business categories except Native American firms in Construction, Hispanic American and Native American firms in Architecture and Engineering, and Native American firms in Professional Services, and Goods and Supplies.

The M/WBE subcontracting utilization was calculated for Construction only and shows that nonminority women-owned firms were paid 40.50 percent of the $31,143,720 in total subcontracting spending according payments recorded in HUBSCO.

2.43% 0.11% 0.00% 0.00% 2.54%9.05% 11.58%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%


Asian AmericanFirms



TOTALMINORITY

FIRMS


TOTAL M/WBEFIRMS


5 | AVAILABIL ITY AND DISP ARITY ANALYSES



This chapter presents the results of MGT of America’s (MGT) analyses on the availability and disparity on the Guilford County School District’ (District) Construction, Architecture and Engineering, Professional Services, Other Services, and Goods and Supplies procurements between July 1, 2009, and June 30, 2014. In this chapter MGT will answer, at least in part, two basic research questions:

1) Are there statistical significant disparities between the availability and utilization of M/WBEs? If there are disparities, what are the most relevant casual factors that contribute directly or indirectly to the disparities between the availability and utilization of M/WBEs?

2) If there is statistical significant evidence of disparity, what is the cause of the disparity? Is there other evidence that supports and/or explains why there is disparity?

To understand the analyses presented in this chapter, it is important to provide definitions to key terms discussed in this chapter. The following section presents these definitions.

1. CHAPTER DEFINITIONS Availability Analysis Methodology. There is no single approach to estimating the availability of firms that has been adopted by the post-Croson case law. As a whole, the case law has emphasized firms being qualified, ready, willing, and able to pursue work with an agency. Therefore, MGT staff analyzed the availability of firms using the following data sources: utilized firms, prequalified bidders, and firms identified in the state of North Carolina Statewide Uniform Certification (SWUC) directory. Using these data sources, the availability estimates were refined to firms providing services and goods typically procured by the District and that were located within the GCS market area.101 Additional measures of availability using the custom census approach are provided in Appendix B, Custom Census Availability.

The following explains how each data source was used to measure the estimates of available firms:

Prime Level Availability Estimates. The measure of availability for the Architecture and Engineering, Professional Services, Other Services and Goods and Supplies procurement categories was based on vendor data from the District. MGT developed a Master Vendor Database that included firms utilized by the District and firms certified as M/WBEs with the State of North Carolina Statewide Uniform Certification (SWUC) Program and located in the GCS Relevant Market Area. There is case law where studies estimating availability based on vendor data have been upheld in federal court.102 For construction prime contractors MGT utilized the list of firms prequalified by the Schools’ Construction Management at Risk program maintained by the District. The

101 Reference Chapter 4, Market Area and Utilization Analyses. 102H.B.Rowe v. North Carolina DOT, 589 FSupp.2d 587 (ED NC 2008).


1. Chapter Definitions

2. Disparity Methodology and Indices

3. Guilford County School District Availability and Disparity Summary

4. Statistical Significance

5. Conclusion





prequalified bidders list contained both M/WBE and non-M/WBE bidders for the District’s construction projects.

Sub Level Availability Estimates. The sub availability estimates were based on firms utilized as subs from HUBSCO reports and SWUC-certified. Availability estimates and thus disparity analyses were not calculated for subs in Architecture and Engineering, Professional Services, Other Services, and Goods and Supplies due to the unavailability of payment data in these categories.

Disparity Analysis Methodology. Disparity, in this context, is the analysis of the differences between the utilization of minority- and woman-owned business enterprises (M/WBEs) and the availability of those firms. Accordingly, we used disparity indices to examine whether M/WBEs received a proportional share of dollars based on the availability of M/WBEs in the Guilford County School District (District) relevant market area. The following explains MGT’s disparity methodology in more detail.

The use of disparity indices for such calculations is supported by several post-Croson cases, most notably Contractors Association of Eastern Pennsylvania v. City of Philadelphia.103 Although a variety of similar indices could be utilized, MGT’s standard for choosing a particular index methodology is that it must yield a value that is easily calculable, understandable in its interpretation, and universally comparable such that a disparity in utilization within minorities- and women-owned firms can be assessed with reference to the utilization of nonminority- and women-owned firms.

Due to the mathematical properties involved in the disparity index calculations, a disparity index value of zero (0.00) indicates absolutely no utilization and, therefore, absolute disparity. A disparity index of 100 indicates that utilization is perfectly proportionate to availability, therefore indicating the absence of disparity (that is, all things being equal). Generally, firms are considered underutilized if the disparity indices are less than 100, and overutilized if the indices are above 100.

Since there is no standardized measurement to evaluate the levels of underutilization or overutilization within a procurement context,

MGT’s methodology to measure disparity, if disparity is found, is based on the Equal Employment Opportunity Commission’s (EEOC) “80 percent rule.”104 In the employment discrimination framework, an employment disparity ratio below 80 indicates a “substantial disparity.” The Supreme Court has accepted the use of the “80 percent rule” in Connecticut v. Teal (Teal), 457 U.S. 440 (1982).105 Therefore, firms are considered substantially underutilized (substantial disparity) if the disparity indices is 80 or less.

Standard Deviation Tests. Standard deviation tests or testing for statistical significance, in this context, is the analysis to determine the significance of the difference between the utilization of

103Contractors Association of Eastern Pennsylvania, Inc. v. City of Philadelphia, 91 F 3d at 603. 104 Equal Employment Opportunity Commission, Uniform Guidelines on Employee Selection Procedures. 105 In Teal and other affirmative action cases, the terms “adverse impact,” “disparate impact,” and “discriminatory impact” are used interchangeably to characterize values of 80 and below.

DISPARITY INDEX FORMULA

Disparity Index =

%Um1p1 ÷ %Am1p1 x 100

Um1p1 = utilization of minorities- and women-owned firms1 for procurement1

Am1p1 = availability of minorities- and women-owned firms1 for procurement1





minorities- and women-owned firms and the availability of those firms. This analysis can determine whether the disparities are substantial or statistically significant, which lends further statistical support to a finding of discrimination. The following explains MGT’s methodology.

Standard deviation measures the probability that a result is a random deviation from a predicted result: greater the number of standard deviations, the lower the probability the result is a random one. The accepted standard used by the Courts is two standard deviations. That is, if there is a result of fewer than two standard deviations, then one can assume that the results are nonsignificant, or that no disparity exists.

In connection with the use of statistical significance in the disparity study context the National Cooperative Highway Research Program Report 644106 report note that:

“. . . for statistical disparities to be taken as legally dispositive in the discrimination context, they should be (a) statistically significant and (b) “substantively” significant. Substantive significance is taken to mean, for example, a DBE utilization measure that is less than or equal to 80% of the corresponding DBE availability measure.” National Cooperative Highway Research Program (NCHRP) Report 644, at 49.

“In discrimination cases, the courts have usually required p-values of 5% or less to establish statistical significance in a two-sided case.” NCHRP Report 644, at 50.

The use of t-test for disparity ratios was approved by the Fourth Circuit in H.B. Rowe v. Tippett, 615 F.3d 233, 243 (4th Cir 2010).

2. DISPARITY METHODOLOGY AND INDICES MGT used the availability and utilization information presented in this report as the basis to determine if M/WBEs received a proportional share of District’s dollars, which is the starting point in our disparity analysis. To determine the proportional share of dollars, MGT calculated the disparity index that analyzes the utilization of firms with the availability of firms in the relevant market area. The disparity index also provides a value that can be given a commonly accepted substantive interpretation.

106 National Academy of Sciences, NCHRP Report 644 Guidelines for Conducting a Disparity and Availability Study for the Federal DBE Program.

STANDARD DEVIATION FORMULA

𝒕𝒕 =𝒖𝒖 − 𝒂𝒂

�𝒂𝒂 ∗ (𝟏𝟏 − 𝒂𝒂) ∗ ∑ 𝒄𝒄𝒊𝒊𝟐𝟐(∑𝒄𝒄𝒊𝒊)𝟐𝟐

t= the t-statistic

u = the ratio of minorities- and women-owned firms dollars to total dollars

a = the ratio of M/W/DBE firms to all firms

ci = the dollar amount.





3. GUILFORD COUNTY SCHOOL DISTRICT AVAILABILITY AND DISPARITY SUMMARY

The following analyses provide the overall availability and disparity indices for Construction, Architecture and Engineering, Professional Services, Other Services, and Goods and Supplies for the District. The analyses are based on the utilization and availability of M/WBEs and non-M/WBES in the GCS relevant market area as discussed in Chapter 4, Market Area and Utilization Analyses. Detailed disparity analyses for each procurement category, for each year of the study period are located in Appendix C, Detailed Disparity Analyses.

CONSTRUCTION PRIME DISPARITY

Construction availability is calculated using the prequalified bidders list. The overall disparity, as shown in Figure 5-A, shows that M/WBEs were significantly underutilized based on the availability of those firms in the relevant market area in the construction business category. Non-M/WBE firms were overutilized during the study period.

FIGURE 5-A GUILFORD COUNTY SCHOOL DISTRICT

CONSTRUCTION

Source: MGT developed a Master Encumbrance Database and Master Vendor Database based on vendor data. Percent of dollars is taken from the utilization analysis presented in Chapter 4, Market Area and Utilization Analyses. Note: Disparity index is the ratio of the percent of dollars to percent of available firms multiplied by 100. Indices below 80 indicate substantial underutilization.

23.04

0.00

2.98

1.58

14.45

151.10

0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00

African American

Native American

Asian American

Hispanic Americans

Nonminority Women

Non-M/WBE Firms

AfricanAmerican

NativeAmerican Asian American Hispanic

AmericansNonminority

WomenNon-M/WBE

FirmsDisparity Index 23.04 0.00 2.98 1.58 14.45 151.10%Availability 13.02% 0.26% 1.56% 3.13% 19.79% 62.24%%Utilization 3.00% 0.00% 0.05% 0.05% 2.86% 94.04%





CONSTRUCTION SUBCONTRACTOR DISPARITY

The District’s construction subcontractor availability is based on vendor data which include firms SWUC-certified. Figure 5-B shows that nonminority women and Native Americans are overutilized as M/WBEs. Non-M/WBE firms were overutilized during the study period.

FIGURE 5-B GUILFORD COUNTY SCHOOL DISTRICT

CONSTRUCTION SUBCONTRACTOR

Source: MGT developed a Master HUBSCO Payments Database and Master Vendor Database based on custom census availability estimates. Percent of dollars is taken from the utilization analysis presented in Chapter 4, Market Area and Utilization Analyses. Note: Disparity index is the ratio of the percent of dollars to percent of available firms multiplied by 100. Indices below 80 indicate substantial underutilization.

60.99

295.12

0.00

86.09

153.47

89.97

0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00

African American

Native American

Asian American

Hispanic Americans

Nonminority Women

Non-M/WBE Firms

African American Native American Asian American HispanicAmericans

NonminorityWomen

Non-M/WBEFirms

Disparity Index 60.99 295.12 0.00 86.09 153.47 89.97%Availability 21.35% 0.49% 1.48% 3.78% 26.27% 46.63%%Utilization 13.02% 1.45% 0.00% 3.25% 40.32% 41.96%





ARCHITECTURE AND ENGINEERING DISPARITY

The overall disparity, as shown in Figure 5-C, shows that all M/WBE firms were substantially underutilized during the study period and non-M/WBE firms were overutilized in the architecture and engineering business category.

FIGURE 5-C GUILFORD COUNTY SCHOOL DISTRICT

ARCHITECTURE AND ENGINEERING

Source: MGT developed a Master Encumbrance Database and Master Vendor Database based on custom census availability estimates. Percent of dollars is taken from the utilization analysis presented in Chapter 4, Market Area and Utilization Analyses. Note: Disparity index is the ratio of the percent of dollars to percent of available firms multiplied by 100. Indices below 80 indicate substantial underutilization.

38.97

0.00

77.97

0.00

17.22

288.84

0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00

African American

Native American

Asian American

Hispanic Americans

Nonminority Women

Non-M/WBE Firms

AfricanAmerican



WomenNon-M/WBE






PROFESSIONAL SERVICES DISPARITY

The disparity for Professional Services also indicated that all M/WBE firms were substantially underutilized compared to availability as shown in Figure 5-D. Non-M/WBE firms were overutilized during the study period.

FIGURE 5-D GUILFORD COUNTY SCHOOL DISTRICT


Source: MGT developed a Master Encumbrance Database and Master Vendor Database based on custom census availability estimates. Percent of dollars is taken from the utilization analysis presented in Chapter 4, Market Area and Utilization Analyses. Note: Disparity index is the ratio of the percent of dollars to percent of available firms multiplied by 100. Indices below 80 indicate substantial underutilization.

31.44

0.00

22.97

40.26

58.15

154.85

0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00

African American

Native American

Asian American

Hispanic Americans

Nonminority Women

Non-M/WBE Firms

AfricanAmerican



WomenNon-M/WBE






OTHER SERVICES DISPARITY

Figure 5-E details the availability of Other Services firms based on vendor data. Non-M/WBE firms are overutilized while M/WBE firms are underutilized during the study period.

FIGURE 5-E GUILFORD COUNTY SCHOOL DISTRICT

OTHER SERVICES

Source: MGT developed a Master Encumbrance Database and Master Vendor Database based on vendor availability. Percent of dollars is taken from the utilization analysis presented in Chapter 4, Market Area and Utilization Analyses. Note: Disparity index is the ratio of the percent of dollars to percent of available firms multiplied by 100. Indices below 80 indicate substantial underutilization.

56.88

0.04

0.00

37.11

41.55

138.33

0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00

African American

Native American

Asian American

Hispanic Americans

Nonminority Women

Non-M/WBE Firms

AfricanAmerican



WomenNon-M/WBE






GOODS AND SUPPLIES DISPARITY

All M/WBE firms were substantially underutilized based on vendor availability of those firms in the relevant market area in the Goods and Supplies procurement category as illustrated in Figure 5-F. Non-M/WBE firms were overutilized during the study period.

FIGURE 5-F GUILFORD COUNTY SCHOOL DISTRICT

GOODS AND SUPPLIES

Source: MGT developed a Master Encumbrance Database and Master Vendor Database based on vendor availability. Percent of dollars is taken from the utilization analysis presented in Chapter 4, Market Area and Utilization Analyses. Note: Disparity index is the ratio of the percent of dollars to percent of available firms multiplied by 100. Indices below 80 indicate substantial underutilization.

4. STATISTICAL SIGNIFICANCE Figure 5-G presents a summary of the t-test results or test for statistical significance for construction at the prime contractor level. The t-test results indicate that the findings of substantial underutilization for minority- and women-owned firms, as a whole, were statistically significant. In each of these cases, the t-tests provide another statistical measure accepted by the courts regarding how far the disparity ratio is from parity.

23.93

0.00

9.19

0.12

62.80

120.66

0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00

African American

Native American

Asian American

Hispanic Americans

Nonminority Women

Non-M/WBE Firms

AfricanAmerican



WomenNon-M/WBE






FIGURE 5-G T-TEST RESULTS FOR MINORITY- AND WOMEN-OWNED FIRMS

CONSTRUCTION PRIME LEVEL


PERCENT OF DOLLARS

AVAILABLE FIRMS

ESTIMATE DISPARITY

INDEX DISPARATE IMPACT OF

UTILIZATION STATISTICAL

SIGNIFICANCE (%)

African American Firms 3.00% 13.02% 23.04 Underutilization * ¥¥ Asian American Firms 0.05% 1.56% 2.98 Underutilization * ¥¥ Hispanic American Firms 0.05% 3.13% 1.58 Underutilization * ¥¥ Native American Firms 0.00% 0.26% 0.00 Underutilization * ¥¥ Total Minority Firms 3.10% 17.97% 17.23 Underutilization * ¥¥ Nonminority Women Firms 2.86% 19.79% 14.45 Underutilization * ¥¥ Total M/WBE Firms 5.96% 37.76% 15.77 Underutilization * ¥¥ Non-M/WBE Firms 94.04% 62.24% 151.10 Overutilization ¥¥

Source: MGT developed a Master Encumbrance Database and Availability Database for the study. Disparity index is the ratio of the percentage of dollars to percentage of available firms multiplied by 100.00. The index is based on the actual percentage value and not the rounded utilization and availability estimates percentage values presented. The disparity indices have been rounded. * indicate a substantial level of disparity, which is a disparity index below 80.00. ¥¥ denotes the ratio of utilization to availability is statistically significant at a 0.05 level. The totals may not equal the sum of components due to rounding.

Figure 5-H presents a summary of the t-test results or test for statistical significance for minority- and nonminority female-owned firms in construction at the subcontractor level. The t-test results indicate that the findings of underutilization for minority-owned firms, as well as the overutilization of nonminority female-owned firms and M/WBE firms, as a whole, were statistically significant.





FIGURE 5-H T-TEST RESULTS FOR MINORITY- AND WOMEN-OWNED FIRMS

CONSTRUCTION SUBCONTRACTOR LEVEL


PERCENT OF DOLLARS

AVAILABLE FIRMS

ESTIMATE DISPARITY INDEX

DISPARATE IMPACT OF UTILIZATION

STATISTICAL SIGNIFICANCE

(%)

African American Firms 13.02% 21.35% 60.99 Underutilization * ¥¥ Asian American Firms 0.00% 1.48% 0.00 Underutilization * Hispanic American Firms 3.25% 3.78% 86.09 Underutilization ¥¥ Native American Firms 1.45% 0.49% 295.12 Overutilization ¥¥ Total Minority Firms 17.72% 27.09% 65.42 Underutilization * ¥¥ Nonminority Women Firms 40.32% 26.27% 153.47 Overutilization ¥¥ Total M/WBE Firms 58.04% 53.37% 108.77 Overutilization ¥¥ Non-M/WBE Firms 41.96% 46.63% 89.97 Underutilization ¥¥


Figure 5-I presents a summary of the t-test results or test for statistical significance for Architecture and Engineering at the prime contractor level. The t-test results indicate that the findings of substantial underutilization for minority-, and nonminority women-owned firms, as a whole, were statistically significant.





FIGURE 5-I T-TEST RESULTS FOR MINORITY- AND WOMEN-OWNED FIRMS

ARCHITECTURE AND ENGINEERING PRIME LEVEL


PERCENT OF DOLLARS

AVAILABLE FIRMS

ESTIMATE DISPARITY



SIGNIFICANCE (%)

African American Firms 11.02% 28.28% 38.97 Underutilization * ¥¥ Asian American Firms 3.94% 5.05% 77.97 Underutilization * ¥¥ Hispanic American Firms 0.00% 3.03% 0.00 Underutilization * ¥¥ Native American Firms 0.00% 0.00% -- N/A NOT APPLICABLE Total Minority Firms 14.96% 36.36% 41.14 Underutilization * ¥¥ Nonminority Women Firms 6.26% 36.36% 17.22 Underutilization * ¥¥ Total M/WBE Firms 21.22% 72.73% 29.18 Underutilization * ¥¥ Non-M/WBE Firms 78.78% 27.27% 288.84 Overutilization ¥¥

Source: MGT developed a Master Encumbrance Database and Availability Database for the study. Disparity index is the ratio of the percentage of dollars to percentage of available firms multiplied by 100.00. The index is based on the actual percentage value and not the rounded utilization and availability estimates percentage values presented. The disparity indices have been rounded. * indicate a substantial level of disparity, which is a disparity index below 80.00. ¥¥ denotes the ratio of utilization to availability is statistically significant at a 0.05 level. N/A and Not Applicable denotes that the analyses cannot be applied in this case due to the mathematical constraint of division by zero. - - indicate where results are based on fewer than five observations. The totals may not equal the sum of components due to rounding.

Figure 5-J presents a summary of the t-test results or test for statistical significance for minority- and nonminority women-owned firms in Professional Services at the prime level. The t-test results indicate that the findings of substantial underutilization for minority- and nonminority women-owned firms, as a whole, were statistically significant.





FIGURE 5-J T-TEST RESULTS FOR MINORITY- AND WOMEN-OWNED FIRMS

PROFESSIONAL SERVICES PRIME LEVEL


PERCENT OF DOLLARS

AVAILABLE FIRMS

ESTIMATE DISPARITY



SIGNIFICANCE (%)

African American Firms 7.08% 22.51% 31.44 Underutilization * ¥¥ Asian American Firms 0.47% 2.05% 22.97 Underutilization * Hispanic American Firms 0.22% 0.55% 40.26 Underutilization * ¥¥ Native American Firms 0.00% 0.00% -- N/A * NOT APPLICABLE Total Minority Firms 7.77% 25.10% 30.95 Underutilization * ¥¥ Nonminority Women Firms 14.28% 24.56% 58.15 Underutilization * ¥¥ Total M/WBE Firms 22.05% 49.66% 44.40 Underutilization * ¥¥ Non-M/WBE Firms 77.95% 50.34% 154.85 Overutilization ¥¥

Source: MGT developed a Master Encumbrance Database and Availability Database for the study. Disparity index is the ratio of the percentage of dollars to percentage of available firms multiplied by 100.00. The index is based on the actual percentage value and not the rounded utilization and availability estimates percentage values presented. The disparity indices have been rounded. * indicate a substantial level of disparity, which is a disparity index below 80.00. ¥¥ denotes the ratio of utilization to availability is statistically significant at a 0.05 level. N/A and Not Applicable denotes the analyses cannot be applied in this case due to the mathematical constraint of division by zero. - - indicate where results are based on fewer than five observations. The totals may not equal the sum of components due to rounding.





Figure 5-K presents a summary of the t-test results or test for statistical significance for minority- and nonminority women-owned firms in Other Services at the prime level. The t-test results indicate that the findings of substantial underutilization for minority- and nonminority women-owned firms, as a whole, were statistically significant.

FIGURE 5-K T-TEST RESULTS FOR MINORITY- AND WOMEN-OWNED FIRMS

OTHER SERVICES PRIME LEVEL


PERCENT OF DOLLARS

AVAILABLE FIRMS

ESTIMATE DISPARITY



SIGNIFICANCE (%)

African American Firms 10.93% 19.22% 56.88 Underutilization * ¥¥ Asian American Firms 0.01% 1.37% 0.84 Underutilization * ¥¥ Hispanic American Firms 0.82% 2.22% 37.11 Underutilization * ¥¥ Native American Firms 0.00% 0.84% 0.04 Underutilization * ¥¥ Total Minority Firms 11.77% 23.65% 49.74 Underutilization * ¥¥ Nonminority Women Firms 7.46% 17.95% 41.55 Underutilization * ¥¥ Total M/WBE Firms 19.22% 41.61% 46.21 Underutilization * ¥¥ Non-M/WBE Firms 80.78% 58.39% 138.33 Overutilization ¥¥


Figure 5-L presents a summary of the t-test results or test for statistical significance for minority- and nonminority women-owned firms in Goods and Supplies at the prime level. The t-test results indicate that the findings of substantial underutilization for M/WBE firms, as a whole, were statistically significant.





FIGURE 5-L T-TEST RESULTS FOR MINORITY- AND WOMEN-OWNED FIRMS

GOODS AND SUPPLIES PRIME LEVEL


PERCENT OF DOLLARS

AVAILABLE FIRMS

ESTIMATE DISPARITY



SIGNIFICANCE (%)

African American Firms 2.43% 10.14% 23.93 Underutilization * ¥¥ Asian American Firms 0.11% 1.18% 9.19 Underutilization * ¥¥ Hispanic American Firms 0.00% 0.91% 0.12 Underutilization * ¥¥ Native American Firms 0.00% 0.09% 0.00 Underutilization * Total Minority Firms 2.54% 12.32% 20.59 Underutilization * ¥¥ Nonminority Women Firms 9.05% 14.40% 62.80 Underutilization * ¥¥ Total M/WBE Firms 11.58% 26.72% 43.34 Underutilization * ¥¥ Non-M/WBE Firms 88.42% 73.28% 120.66 Overutilization ¥¥


5. CONCLUSION The disparity analyses are able to answer, in part, two of our research questions:

1) Are there disparities between the availability and utilization of M/WBEs? If there are disparities, what are the most relevant causal factors that contribute directly or indirectly to the disparities between the availability and utilization of M/WBEs?

Yes, there is disparity between the availability and utilization of M/WBEs in the District’s procurement of goods and services analyzed in the study. As primes, M/WBEs were underutilized in all procurement categories. In Construction subcontracting African American, Asian American, and Hispanic American firms were underutilized. The most relevant causal factor is the low utilization of M/WBE firms.

2) If there is statistical evidence of disparity, what is the cause of the disparity? Is there other evidence that supports and/or explains why there is disparity?

Other evidence that contribute to the disparity are discussed in Chapter 6, Private Sector Analysis, Chapter 7, Anecdotal Analysis, and Chapter 8, Findings and Recommendations.

Chapter 6: Private Sector and Non-Goal Analyses

GUILFORD COUNTY SCHOOL DISTRICT DISPARITY STUDY



1. INTRODUCTION MGT of America, Inc. (MGT) in Chapter 2, Legal Framework detailed the government entity enacting a minority- and women-owned business enterprise (M/WBE) program must have shown to have actively or passively perpetuated discrimination. The questions this chapter attempts to answer are:

1) Does Guilford County School District (District) passively engage in practices which result in disparities?

2) Are there disparities in utilization of M/WBE firms as prime contractors or subcontractors for commercial private sector construction projects relative to their availability?

3) Are there disparities for M/WBE firms in the entry into and earnings from self-employment?

The private sector analysis evaluates the presence or absence of discrimination in the private sector marketplace, and to determine if there is evidence to support anecdotal comments from Chapter 7, Anecdotal Analysis regarding difficulties M/WBE firms have in securing work on private sector projects. The analyses examines M/WBE utilization and availability in the District’s market area107 private commercial construction industry in order to determine disparities in M/WBE utilization at the prime contractor and subcontractor levels. Once the record of private sector utilization was established, we were also able to compare the rates of M/WBE and non-M/WBE utilization in the private sector to their utilization by the District for public sector construction procurement.

METHODOLOGY

Our methodology for the collection of data and the calculation of the District’s market area as the basis for our analysis of private sector utilization of M/WBE firms and non-M/WBE firms and their availability are described in this section.

PRIVATE SECTOR ANALYSIS - RATIONALE In City of Richmond v J.A. Croson (Croson), the Court established a “municipality has a compelling government interest in redressing not only discrimination committed by the municipality itself, but also discrimination committed by private parties within the municipality’s legislative jurisdiction, so long as the

107 Refer to the Market Area Methodology for the District’s market area as defined for the purposes of this study.


1. Introduction

2. Collection and Management of Permits Data

3. Private Sector Utilization Analysis, Commercial Construction Permits

4. Nexus Between Commercial and Public Construction

5. Private Sector Disparities, U.S. Census Bureau, 2012 Survey of Business Owners Data

6. Analysis of Race, Ethnicity, and Gender Effects on Self-Employment Rates

7. Conclusion


6 | PR IVATE SECTOR AND NON-GOAL ANALYSES



municipality in some way participated in the discrimination to be remedied by the program.”108 This argument was reinforced by the Court of Appeals decision in Adarand Construction, Inc. v Rodney Slater, concluding there was a compelling interest for a government Disadvantaged Business Enterprise (DBE) program, based primarily on evidence of private sector discrimination.109 According to this argument, discriminatory practices found in the private sector marketplace may be indicative of government’s passive or, in some cases, active participation in local discrimination. To remedy such discrimination, Croson provided government “can use its spending powers to remedy private discrimination, if it identifies discrimination with the particularity required by the Fourteenth Amendment.”110 Passive discrimination was examined in a disparity analysis of the utilization of M/WBE construction subcontractors by majority prime contractors on projects funded in the District construction market. A comparison of public sector M/WBE utilization with private sector utilization enables an assessment of the extent to which majority prime contractors have tended to hire M/WBE subcontractors only to satisfy public sector requirements. Thus, the following questions are addressed:

Are there disparities in utilization of M/WBE firms as prime contractors for commercial private sector construction projects relative to their availability?

Are there disparities in utilization of M/WBE firms as subcontractors for commercial private sector construction projects relative to their availability?

To what extent are contractors utilized on District projects also utilized on private sector construction projects?

2. COLLECTION AND MANAGEMENT OF PERMITS DATA The source of data for the commercial construction permit data (such as building, electrical, plumbing) was provided by the City of Greensboro’s Development Services department. The data was transmitted electronically in spreadsheets format for construction projects permitted between July 1, 2009, and June 30, 2014. The permits data provided to MGT included the following but not limited data fields:

Permit Type Text Permit # Project Description Scope of Work Provided Owner of Project, Owner Address, City, State, ZIP Code

Contractor Professional Name, Address, City, State, ZIP Code, Phone Number

Job Location Date Issued Dollar Value of Permit Construction Value of Project

108 Croson, 488 U.S. 46, 109 S.Ct. at 720-21, 744-45. 109 Adarand v. Slater, 228 F.3d 1147 (10th Cir. 2000). 110 See Richmond v. Croson, 488 U.S. 492 (1989).





The value in examining permits is it offers up-to-date record of actual construction activity undertaken in the City of Greensboro’s city limits. In order to isolate only commercial construction projects as the focus of analysis, public sector and residential permit records were excluded.

Based on the permit type description (such as building, electrical, plumbing), permits were categorized according to two types of level of work performed: prime contractor and subcontractor. The construction value of the project/permit was not consistently available. Therefore, the utilization of commercial construction permits presented in this chapter examined the utilization of permits and utilization of firms by business ownership classification.

MARKET AREA METHODOLOGY

A United States county is the geographical unit of measure selected for determining market area. Counties are geographical units based on the following considerations: 1) the courts have accepted counties as a standard geographical unit of analysis in conducting equal employment opportunity and disparity analysis; 2) county boundaries are externally determined and thus free from any researcher bias might result from any arbitrary determinations of geographical units of analysis; and 3) the U.S. Census and other federal and state data are routinely collected and reported by county.

The market area for the Study was determined to be the Central North Carolina region which consist of 32 counties within the State of North Carolina, which are as follows: Alamance, Anson, Cabarrus, Caswell, Chatham, Davidson, Davie, Durham, Forsyth, Franklin, Granville, Guilford, Hoke, Lee, Mecklenburg, Montgomery, Moore, Orange, Person, Randolph, Richmond, Rockingham, Rowan, Scotland, Stanly, Stokes, Surry, Union, Vance, Wake, Warren, and Yadkin. Subsequently, our private sector analysis based on commercial permits was based on contractors located within the Central North Carolina region (District market area). The private sector analysis also presents private sector disparities results based on the U.S. Census, 2012 Survey of Business Owners data for the State of North Carolina and Greensboro-High Point North Carolina metro area. The analysis of race, ethnicity, and gender effects on self-employment rates and earnings results was based on Public Use Microdata Samples data derived from the 2014 American Community Survey for the Greensboro–Winston-Salem–High Point, North Carolina Combined Statistical Area.

BUSINESS OWNERSHIP CLASSIFICATION AND PROCUREMENT CATEGORY

In Chapter 4, Market Area and Utilization Analysis, the five M/WBE classifications described—African American, Hispanic American, Asian American, Native American, and nonminority women—were used as the basis of MGT’s analyses for business ownership classification. Since the permits data did not contain the contractor’s race, ethnic, or gender information, MGT assigned business ownership classification using various vendor lists obtained from trade associations and certification agencies in order to conduct a vendor match procedure. This vendor match procedure allowed MGT to assign business ownership classification to firms presented in the permits data. In order to achieve the greatest number of potential match combinations, in addition to linking the various lists to the permits data, a manual match was also





conducted. Firms identified as nonminority male and firms for which there was no business ownership classification were considered to be non-M/WBE firms and counted as non-M/WBE firms in the analyses conducted for this study.

For the procurement category analysis, findings reported in this chapter deal only with private sector construction for two reasons: (1) permit data, by its nature, pertains only to construction activities, which is also the category for which data tends to be most extensive and reliable, and (2) in the courts, historically, construction activity in a given jurisdiction has been scrutinized more than any other procurement category because, in both public and private sector business activity, it tends to be the most financially lucrative in terms of its impact on a local economy. The data was classified according to two categories of construction contractor – prime contractors and subcontractors –based on the permit type data field, or level of work.

3. PRIVATE SECTOR UTILIZATION ANALYSIS, COMMERCIAL CONSTRUCTION PERMITS

PRIME CONTRACTOR LEVEL OF WORK

The following section presents results from the analysis of the utilization of M/WBE and non-M/WBE firms in the private sector commercial construction market. The utilization of M/WBE and non-M/WBE firms for commercial construction permits data based on prime contractor level of work are presented in Figures 6-A through 6-B.

Figure 6-A shows between July 1, 2009, and June 30, 2014, a total of 6,063 commercial construction permits were issued based on prime contractor level of work. M/WBE firms received 189 of the 6,063 commercial construction permits, 3.1 percent of the total. African American firms received 2.1 percent, representing the largest share issued to M/WBE firms.





FIGURE 6-A UTILIZATION ANALYSIS OF PERMITS

COMMERCIAL CONSTRUCTION AT THE PRIME CONTRACTOR LEVEL

Source: MGT developed a Master Commercial Private sector Database based on commercial construction permitting data issued between July 1, 2009, and June 30, 2014.

125 1 9 0 135 54 189

5,874 6,063

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

AfricanAmerican

Firms

AsianAmerican

Firms

HispanicAmerican

Firms

NativeAmerican

Firms

TOTALMINORITY

FIRMS

NonminorityWomen Firms

TOTAL M/WBEFIRMS

TOTAL NON-M/WBE FIRMS

TOTALPERMITS

2.06% 0.02% 0.15% 0.00% 2.23% 0.89% 3.12%

96.88% 100.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

AfricanAmerican

Firms

AsianAmerican

Firms

HispanicAmerican

Firms

NativeAmerican

Firms

TOTALMINORITY

FIRMS


TOTAL M/WBEFIRMS


TOTALPERMITS





Figure 6-B shows 44 individual (unduplicated) M/WBE firms, 7.1 percent of all individual (unduplicated) firms, were issued commercial construction permits based on prime contractor level of work. African American firms represented 3.4 percent and nonminority women firms represented 3.2 of the total individual (unduplicated) firms.

FIGURE 6-B UTILIZATION ANALYSIS OF FIRMS

COMMERCIAL CONSTRUCTION AT THE PRIME CONTRACTOR LEVEL

Source: MGT developed a Master Commercial Private sector Database based on commercial construction permitting data issued between July 1, 2009, and June 30, 2014. The number of firms counts a vendor only once over the entire study period, since a firm could be used in multiple years. Thus the number reflects the unduplicated count.

21

1

2

0

24

20

44

579

623

0 100 200 300 400 500 600 700

African American Firms

Asian American Firms

Hispanic American Firms

Native American Firms

TOTAL MINORITY FIRMS

Nonminority Women Firms

TOTAL M/WBE FIRMS


TOTAL FIRMS

3.37%

0.16%

0.32%

0.00%

3.85%

3.21%

7.06%

92.94%

100.00%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%







TOTAL M/WBE FIRMS


TOTAL FIRMS





SUBCONTRACTOR LEVEL OF WORK

The utilization of M/WBE and non-M/WBE firms for commercial construction permits data based on subcontractor level of work are presented in Figures 6-C through 6-D.

Figure 6-C shows between July 1, 2009 and June 30, 2014, a total of 20,419 commercial construction permits were issued based on subcontractor level of work. M/WBE firms received 941 of the 20,419 commercial construction permits, 4.6 percent of the total. Nonminority women firms received 3.2 percent, representing the largest share issued to M/WBE firms.

FIGURE 6-C UTILIZATION ANALYSIS OF PERMITS

COMMERCIAL CONSTRUCTION AT THE SUBCONTRACTOR LEVEL

Source: MGT developed a Master Commercial Private sector Database based on commercial construction permitting data issued between July 1, 2009, and June 30, 2014.

266 2 9 0 277 664 941

19,478 20,419

0

5,000

10,000

15,000

20,000

25,000

AfricanAmerican

Firms

AsianAmerican

Firms

HispanicAmerican

Firms

NativeAmerican

Firms

TOTALMINORITY

FIRMS


TOTALM/WBEFIRMS

TOTAL NON-M/WBEFIRMS

TOTALPERMITS

1.30% 0.01% 0.04% 0.00% 1.36% 3.25% 4.61%

95.39% 100.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

AfricanAmerican

Firms

AsianAmerican

Firms

HispanicAmerican

Firms

NativeAmerican

Firms

TOTALMINORITY

FIRMS

NonminorityWomen

Firms

TOTALM/WBEFIRMS

TOTAL NON-M/WBEFIRMS

TOTALPERMITS





Figure 6-D shows 67 individual (unduplicated) M/WBE firms, 4.5 percent of all individual (unduplicated) firms, were issued commercial construction permits based on subcontractor level of work. Nonminority women firms represented 2.1 percent and African American firms represented closed to two percent of the total individual (unduplicated) firms.

FIGURE 6-D UTILIZATION ANALYSIS OF FIRMS

COMMERCIAL CONSTRUCTION AT THE SUBCONTRACTOR LEVEL

Source: MGT developed a Master Commercial Private sector Database based on commercial construction permitting data issued between July 1, 2009, and June 30, 2014. The number of firms counts a vendor only once over the entire study period, since a firm could be used in multiple years. Thus the number reflects the unduplicated count.

29

1

6

0

36

31

67

1,418

1,485

0 200 400 600 800 1,000 1,200 1,400 1,600







TOTAL M/WBE FIRMS


TOTAL FIRMS

1.95%

0.07%

0.40%

0.00%

2.42%

2.09%

4.51%

95.49%

100.00%

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%







TOTAL M/WBE FIRMS


TOTAL FIRMS





4. NEXUS BETWEEN COMMERCIAL AND PUBLIC CONSTRUCTION MGT utilized two data sets to compare the utilization of firms. The first data set contained a listing of permits issued to contractors in the Greensboro city limits. The second data set contained firms utilized on District public sector construction projects from July 1, 2009, and June 30, 2014.

The goal of this analysis is to examine public sector and private sector contracting patterns for construction. In doing so, MGT compared the public sector utilization of vendors in District-issued data with private sector utilization of such firms as reflected in the private commercial permit data. The general questions to be answered regarding the permitting analysis included the following:

To what extent do utilized prime contractors which appear in the District data also appear in the permitting data for commercial construction projects?

What is the utilization of subcontractors which are in the District data are also in the permitting data for commercial construction projects?

When prime contractors on the District public construction projects utilized by the District were cross referenced with the commercial construction projects, a total of 31 prime contractors (located in the District’s market rea) were utilized on commercial construction projects to complete prime contractor level of work. Out of these 31 contractors, nine were M/WBE firms. When prime contractors utilized on District public construction projects were cross referenced with the commercial projects, a total of 55 firms were utilized as subcontractors on commercial construction projects. Out of the 55 firms, 17 firms were M/WBE firms.

When subcontractors utilized on District public construction projects were cross referenced with the commercial construction projects, a total of 14 subcontractors (located in the District’s market area) were utilized on commercial construction projects to complete prime contractor level work. Out of these 14 contractors, 12 were M/WBE firms. When subcontractors utilized on District public construction projects were cross referenced with the commercial projects, a total of 30 firms were utilized as subcontractors on commercial construction projects. Out of the 30 firms, 15 firms were M/WBE firms.

The subcontracting data in Chapter 4, Market Area and Utilization Analyses demonstrated clear capacity and availability of M/WBE firms (located within the District market area) to perform close to $20 million of dollars’ worth of construction subcontracting work. It seems unlikely differences in types of subcontracting work on vertical construction between the public sector and private sector can account for the substantial differences in M/WBE subcontractor utilization.





5. PRIVATE SECTOR DISPARITIES, U.S. CENSUS BUREAU, 2012 SURVEY OF BUSINESS OWNERS DATA The following presents measures of private sector disparities based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data by North American Industry Classification System (NAICS) codes at the two-digit level for the State of North Carolina and Greensboro-High Point, North Carolina metro area marketplaces.

The following NAICS codes were analyzed and thus presented in the following section:

NAICS Code 23, Construction

NAICS Code 42, Wholesale Trade

NAICS Code 54, Professional, Scientific, and Technical Services

NAICS Code 56, Administrative and Support and Waste Management and Remediation Services

NAICS Code 81, Other Services (Except Public Administration

The results based on the State of North Carolina are presented first followed by the Greensboro-High Point, North Carolina metro area.

STATE OF NORTH CAROLINA MARKETPLACE

Tables 6-1 through 6-5 shows the measures of private sector disparities based on U.S. Census, 2012 SBO data for the population of available firms in the State of North Carolina by race, ethnicity, and gender for construction; wholesale trade; professional, scientific, and technical services; administrative and support and waste management and remediation services; and other services (except public administration).

Based on the analysis of the U.S. Census, 2012 SBO data, overall there remains a significant gap between the market share of M/WBE firms and their share of the State of North Carolina business population, where data was available.





NAICS CODE 23: CONSTRUCTION, STATE MARKETPLACE

Table 6-1 shows the availability, sales, and disparity results for construction. The results were derived from those firms which provide construction or construction-related services based on the NAICS Code 23.

There was a total of 100,710 construction firms (all firms111) in the State of North Carolina in 2012, of which 7.6 percent was owned by minorities and 14.6 percent by nonminority females.

African American firms (disparity index of 21.96) were substantially underutilized, accounting for 6.2 percent of all firms and 1.4 percent of sales.

Native American firms (disparity index of 5.92) were substantially underutilized, accounting for 0.4 percent of all firms and 0.02 percent of sales.

Asian American firms (disparity index of 43.63) were substantially underutilized, accounting for 0.7 percent of all firms and 0.3 percent of sales.

Hispanic American firms (disparity index of 36.65) were substantially underutilized, accounting for 0.2 percent of all firms and 0.1 percent of sales.

Nonminority female firms (disparity index of 86.35) were underutilized, accounting for 14.6 percent of all firms and 12.6 percent of sales.

There was a total of 21,077 construction employer firms112 in the State of North Carolina in 2012, of which 2.8 percent was owned by minorities and 23.9 percent by nonminority female firms.

African American firms (disparity index of 54.21) were substantially underutilized, accounting for 2.3 percent of employer firms and 1.3 percent of sales.

Asian American firms (disparity index of 98.91) were underutilized, accounting for 0.3 percent of employer firms and 0.3 percent of sales.

Hispanic American firms (disparity index of 30.00) were substantially underutilized, accounting for 0.3 percent of employer firms and 0.1 percent of sales.

Nonminority female firms (disparity index of 52.26) were substantially underutilized, accounting for 23.9 percent of employer firms and 12.5 percent of sales.

Data for Native American employer firms were withheld; therefore, private sector disparities were not conducted.

111 All firms include firms with and without payroll at any time during 2012. 112 Employer firms include firms with payroll at any time during 2012.





TABLE 6-1 PRIVATE SECTOR CENSUS DISPARITIES

NAICS CODE 23, CONSTRUCTION U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, STATE OF NORTH CAROLINA MARKETPLACE


ALL FIRMS (#)

ALL FIRMS, SALES ($1,000)

EMPLOYER FIRMS (#)

EMPLOYER FIRMS SALES ($1,000)

All Firms 100,710 $41,487,760 21,077 $37,293,789 African American Firms 6,286 $568,572 485 $465,195 Native American Firms1 414 $10,103 1 S Asian American Firms2 744 $133,725 53 $92,759 Hispanic American Firms 231 $34,879 51 $27,071 Nonminority Female Firms3 14,651 $5,211,432 5,044 $4,664,042

PERCENTAGE OF MARKETPLACE All Firms 100.00% 100.00% 100.00% 100.00% African American Firms 6.24% 1.37% 2.30% 1.25% Native American Firms1 0.41% 0.02% 0.00% S Asian American Firms2 0.74% 0.32% 0.25% 0.25% Hispanic American Firms 0.23% 0.08% 0.24% 0.07% Nonminority Female Firms3 14.55% 12.56% 23.93% 12.51%

DISPARITY INDEX All Firms 100.00 100.00 African American Firms 21.96 54.21 Native American Firms1 5.92 S Asian American Firms2 43.63 98.91 Hispanic American Firms 36.65 30.00 Nonminority Female Firms3 86.35 52.26

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms. S denotes findings were withheld as the estimates did not meet U.S. Census publication standards.





NAICS CODE 42: WHOLESALE TRADE, STATE LEVEL

Table 6-2 shows the availability, sales, and disparity results for wholesale trade firms. The results was derived from those firms which sell capital or durable goods to other businesses based on NAICS Code 42.

There was a total of 20,408 wholesale trade firms (all firms) in the State of North Carolina in 2012, of which 11 percent was owned by minorities and 27.6 percent by nonminority females.



Asian American firms (disparity index of 44.05) were substantially underutilized, accounting for 2.3 percent of all firms and one percent of sales.


Nonminority female firms (disparity index of 20.18) were substantially underutilized, accounting for 27.6 percent of all firms and 5.6 percent of sales.

There was a total of 9,296 wholesale trade employer firms in the State of North Carolina in 2012, of which 4.5 percent was owned by minorities and 22.5 percent by nonminority female firms.


Native American firms (disparity index of 18.38) were substantially underutilized, accounting for 0.1 percent of employer firms and 0.02 percent of sales.

Asian American firms (disparity index of 39.30) were substantially underutilized, accounting for 2.6 percent of employer firms and one percent of sales.

Hispanic American firms (disparity index 25.88) were substantially underutilized, accounting for 1.3 percent of employer firms and 0.3 percent of sales.






TABLE 6-2 PRIVATE SECTOR CENSUS DISPARITIES NAICS CODE 42, WHOLESALE TRADE

U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, STATE OF NORTH CAROLINA MARKETPLACE BUSINESS OWNERSHIP

CLASSIFICATION ALL FIRMS

(#) ALL FIRMS, SALES

($1,000) EMPLOYER FIRMS

(#) EMPLOYER FIRMS SALES

($1,000) All Firms 20,408 $174,236,446 9,296 $173,472,709 African American Firms 1,113 $215,730 50 $200,198 Native American Firms1 129 $41,636 11 $37,723 Asian American Firms2 471 $1,771,431 238 $1,745,255 Hispanic American Firms 541 $623,091 119 $574,668 Nonminority Female Firms3 5,638 $9,715,102 2,091 $9,554,344

PERCENTAGE OF MARKETPLACE All Firms 100.00% 100.00% 100.00% 100.00% African American Firms 5.45% 0.12% 0.54% 0.12% Native American Firms1 0.63% 0.02% 0.12% 0.02% Asian American Firms2 2.31% 1.02% 2.56% 1.01% Hispanic American Firms 2.65% 0.36% 1.28% 0.33% Nonminority Female Firms3 27.63% 5.58% 22.49% 5.51%

DISPARITY INDEX All Firms 100.00 100.00 African American Firms 2.27 21.46 Native American Firms1 3.78 18.38 Asian American Firms2 44.05 39.30 Hispanic American Firms 13.49 25.88 Nonminority Female Firms3 20.18 24.49

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms.





NAICS CODE 54: PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES, STATE MARKETPLACE

Table 6-3 shows the availability, sales, and disparity results for professional, scientific, and technical services. Professional, scientific, and technical services require a high degree of expertise and training, was derived from those firms which specialize in performing professional, scientific, and technical activities (such as legal advice, accounting, architecture, engineering, computer services, consulting services, advertising services) for others in NAICS Code 54.

There was a total of 101,233 professional, scientific, and technical services firms (all firms) in the State of North Carolina in 2012, of which 15.2 percent was owned by minorities and 35.2 percent by nonminority females.



Asian American firms (disparity index of 57.55) were substantially underutilized, accounting for three percent of all firms and 1.8 percent of sales.

Hispanic American firms (disparity index of 32.78) were substantially underutilized, accounting for three percent of all firms and one percent of sales.

Nonminority female firms (disparity index of 25.71) were substantially underutilized, accounting for 35.2 percent of all firms and nine percent of sales.

There was a total of 20,852 professional, scientific, and technical services employer firms in the State of North Carolina in 2012, of which 8.8 percent was owned by minorities and 29.3 percent by nonminority female firms.

African American firms (disparity index of 22.19) were substantially underutilized, accounting for four percent of employer firms and 0.9 percent of sales.

Native American firms (disparity index of 20.15) were substantially underutilized, accounting for 0.6 percent of employer firms and 0.1 percent of sales.

Asian American firms (disparity index of 60.63) were substantially underutilized, accounting for 2.7 percent of employer firms and 1.6 percent of sales

Hispanic American firms (disparity index 55.38) were substantially underutilized, accounting for 1.6 percent of employer firms and 0.9 percent of sales.







NAICS CODE 54, PROFESSIONAL, SCIENTIFIC AND TECHNICAL SERVICES U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, STATE OF NORTH CAROLINA MARKETPLACE


ALL FIRMS (#)


EMPLOYER FIRMS (#)


All Firms 101,233 $38,389,831 20,852 $35,620,845 African American Firms 8,480 $455,425 825 $312,722 Native American Firms1 846 $61,575 126 $43,366 Asian American Firms2 3,080 $672,203 562 $582,035 Hispanic American Firms 3,025 $376,014 331 $313,149 Nonminority Female Firms3 35,610 $3,471,478 6,102 $2,616,367








NAICS CODE 56: ADMINISTRATIVE AND SUPPORT AND WASTE MANAGEMENT AND REMEDIATION SERVICES, STATE MARKETPLACE

Table 6-4 shows the availability, sales, and disparity results for administrative and support and waste management and remediation services (such as office administration, hiring and placing of personnel, document preparation and similar clerical services, solicitation, collection, security and surveillance services, cleaning, and waste disposal services) in NAICS Code 56.

There was a total of 79,818 administrative and support and waste management and remediation services firms (all firms) in the State of North Carolina in 2012, of which 31.6 percent was owned by minorities and 34.4 percent by nonminority females.



Asian American firms (disparity index of 57.42) were substantially underutilized, accounting for 1.7 percent of all firms and one percent of sales.

Hispanic American firms (disparity index of 21) were substantially underutilized, accounting for 7.2 percent of all firms and 1.5 percent of sales.

Nonminority female firms (disparity index of 45.13) were substantially underutilized, accounting for 34.4 percent of all firms and 15.5 percent of sales.

There was a total of 10,090 administrative and support and waste management and remediation services employer firms in the State of North Carolina in 2012, of which 11.4 percent was owned by minorities and 26.7 percent by nonminority female firms.

African American firms (disparity index 34.44) were substantially underutilized, accounting for 6.3 percent of employer firms and 2.2 percent of sales.

Native American firms (disparity index of 162.92) were overutilized, accounting for 0.7 percent of employer firms and 1.1 percent of sales.

Asian American firms (disparity index of 46.36) were substantially underutilized, accounting for 1.9 percent of employer firms and 0.9 percent of sales.

Hispanic American firms (disparity index of 42.86) were substantially underutilized, accounting for 2.6 percent of firms and 1.1 percent of sales.

Nonminority female firms (disparity index of 53.59) were substantially underutilized, accounting for 26.7 percent of firms and 14.3 percent of sales.






NAICS CODE 56 ADMINISTRATIVE AND SUPPORT AND WASTE MANAGEMENT AND REMEDIATION SERVICES

U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, STATE OF NORTH CAROLINA MARKETPLACE BUSINESS OWNERSHIP





($1,000) All Firms 79,818 $17,622,318 10,090 $16,378,135 African American Firms 16,660 $539,798 634 $354,471 Native American Firms1 1,418 $202,773 69 $182,470 Asian American Firms2 1,342 $170,139 190 $142,984 Hispanic American Firms 5,800 $268,961 258 $179,478 Nonminority Female Firms3 27,436 $2,733,535 2,691 $2,340,647








NAICS CODE 81: OTHER SERVICES (EXCEPT PUBLIC ADMINISTRATION), STATE MARKETPLACE

Table 6-5 shows the availability, sales, and disparity results for other services (except Public Administration) firms in NAICS Code 81. Firms in this sector primarily engage in equipment and machinery repairing, automotive repair services, electronic and precision equipment repair and maintenance services, providing laundry services, personal care services, and photofinishing services.

There was a total of 114,104 other services (except Public Administration) firms (all firms) in the State of North Carolina in 2012, of which 37.2 percent was owned by minorities and 34.1 percent by nonminority females.



Asian American (disparity index of 70.78) firms were substantially underutilized, accounting for 7.4 percent of all firms and 5.2 percent of sales.


Nonminority female firms (disparity index of 68.32) were substantially underutilized, accounting for 34.1 percent of all firms and 23.3 percent of sales

There was a total of 9,860 administrative and support and waste management and remediation services employer firms in the State of North Carolina in 2012, of which 12.8 percent was owned by minorities and 32 percent by nonminority female firms.


Native American firms (disparity index of 71.30) were substantially underutilized, accounting for 0.6 percent of employer firms and 0.4 percent of sales


Hispanic American firms (disparity index of 47.23) were substantially underutilized, accounting for 1.8 percent of firms and 0.9 percent of sales.

Nonminority female firms (disparity index of 63.01) were substantially underutilized, accounting for 32 percent of employer firms and 20.2 percent of sales.






NAICS CODE 81, OTHER SERVICES (EXCEPT PUBLIC ADMINISTRATION) U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, STATE OF NORTH CAROLINA MARKETPLACE


ALL FIRMS (#)


EMPLOYER FIRMS (#)


All Firms 114,104 $7,920,846 9,860 $5,494,290 African American Firms 27,565 $518,266 402 $122,450 Native American Firms1 2,018 $66,414 54 $21,455 Asian American Firms2 8,444 $414,908 621 $159,390 Hispanic American Firms 4,397 $148,786 181 $47,639 Nonminority Female Firms3 38,948 $1,847,169 3,156 $1,108,027








GREENSBORO-HIGH POINT, NC METRO AREA MARKETPLACE

Table 6-6 through Table 6-10 shows the measures of private sector disparities based on U.S. Census, 2012 SBO data for the population of available firms in the Greensboro-High Point North Carolina metro area by race, ethnicity, and gender for construction; wholesale trade; professional, scientific, and technical services; administrative and support and waste management and remediation services; and other services (except public administration).

Based on the analysis of the U.S. Census, 2012 SBO data, overall there remains a significant gap between the market share of M/WBE firms and their share of the Greensboro-High Point North Carolina metro area business population, where data was available.

NAICS CODE 23: CONSTRUCTION, METRO AREA MARKETPLACE

Table 6-6 shows the availability, sales, and disparity results for construction (NAICS Code 23). There was a total of 5,442 construction firms (all firms113) in the Greensboro-High Point North Carolina metro area in 2012, of which 21 percent was owned by minorities.

Data for African American, Asian American, Hispanic American, and nonminority female all firms were withheld; therefore, private sector disparities were not conducted.

Native American firms (disparity index 10.38) were substantially underutilized, accounting for 1.7 percent of all firms and 0.2 percent of sales.

There was a total of 1,368 construction employer firms114 in the Greensboro-High Point North Carolina metro area in 2012, of which 14.5 percent was owned by minorities.

Data for African American, Native American, Asian American, Hispanic American, and nonminority female employer firms were withheld; therefore, private sector disparities were not conducted.

113 All firms include firms with and without payroll at any time during 2012. 114 Employer firms include firms with payroll at any time during 2012.






NAICS CODE 23, CONSTRUCTION U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS,

GREENSBORO-HIGH POINT, NC METRO AREA MARKETPLACE BUSINESS OWNERSHIP





($1,000) All Firms 5,442 $2,727,773 1,368 $2,547,305 African American Firms 356 S 69 S Native American Firms1 93 $4,840 1 S Asian American Firms2 56 S 2 S Hispanic American Firms 635 S 126 S Nonminority Female Firms3 N/A N/A N/A N/A

PERCENTAGE OF MARKETPLACE All Firms 100.00% 100.00% 100.00% 100.00% African American Firms 6.54% S 5.04% S Native American Firms1 1.71% 0.18% 0.07% S Asian American Firms2 1.03% S 0.15% S Hispanic American Firms 11.67% S 9.21% S Nonminority Female Firms3 N/A N/A N/A N/A

DISPARITY INDEX All Firms 100.00 100.00 African American Firms S S Native American Firms1 10.38 S Asian American Firms2 S S Hispanic American Firms S S Nonminority Female Firms3 N/A N/A

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms, where data was available. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms, where data was available. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms, where data was available. S denotes findings were withheld as the estimates did not meet U.S. Census publication standards. N/A denotes data on business ownership classification group was not available.





NAICS CODE 42: WHOLESALE TRADE, METRO AREA MARKETPLACE

Table 6-7 shows the availability, sales, and disparity results for wholesale trade (NAICS Code 42). There was a total of 2,439 wholesale trade firms (all firms) in the Greensboro-High Point North Carolina metro area in 2012, of which 9.6 percent was owned by minorities.




Data for Native American and nonminority female all firms were withheld; therefore, private sector disparities were not conducted.

There was a total of 1,265 wholesale trade employer firms in the Greensboro-High Point North Carolina metro area in 2012, of which 6.1 percent was owned by minorities.



Hispanic American firms (disparity index of 33.54) were substantially underutilized, accounting for 1.4 percent of employer firms and 0.5 percent of sales.

Data for Native American and nonminority female employer firms were withheld; therefore, private sector disparities were not conducted.





TABLE 6-7 PRIVATE SECTOR CENSUS DISPARITIES NAICS CODE 42, WHOLESALE TRADE

U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, GREENSBORO-HIGH POINT, NC METRO AREA MARKETPLACE


ALL FIRMS (#)


EMPLOYER FIRMS (#)


All Firms 2,439 $24,027,665 1,265 $23,932,387 African American Firms 125 $49,965 24 $47,229 Native American Firms1 N/A N/A N/A N/A Asian American Firms2 57 $380,009 35 $374,923 Hispanic American Firms 51 $134,482 18 $114,218 Nonminority Female Firms3 N/A N/A N/A N/A

PERCENTAGE OF MARKETPLACE All Firms 100.00% 100.00% 100.00% 100.00% African American Firms 5.13% 0.21% 1.90% 0.20% Native American Firms1 N/A N/A N/A N/A Asian American Firms2 2.34% 1.58% 2.77% 1.57% Hispanic American Firms 2.09% 0.56% 1.42% 0.48% Nonminority Female Firms3 N/A N/A N/A N/A

DISPARITY INDEX All Firms 100.00 100.00 African American Firms 4.06 10.40 Native American Firms1 N/A N/A Asian American Firms2 67.67 56.62 Hispanic American Firms 26.77 33.54 Nonminority Female Firms3 N/A N/A

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms, where data was available. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms, where data was available. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms, where data was available. N/A denotes data on business ownership classification group was not available.





NAICS CODE 54: PROFESSIONAL, SCIENTIFIC, AND TECHNICAL SERVICES, METRO AREA MARKETPLACE

Table 6-8 shows the availability, sales, and disparity results for professional, scientific, and technical services (NAICS Code 54). There was a total of 6,944 professional, scientific and technical services firms (all firms) in the Greensboro-High Point North Carolina metro area in 2012, of which 16.2 percent was owned by minorities.



Hispanic American firms (disparity index of 61.79) were substantially underutilized, accounting for three percent of all firms and 1.9 percent of sales.

Data for Native American and nonminority female all firms were withheld; therefore, private sector disparities were not conducted.

There was a total of 1,519 professional, scientific and technical services employer firms in the Greensboro-High Point North Carolina metro area in 2012, of which 8.2 percent was owned by minorities.


Asian American firms (disparity index of 61.20) were substantially underutilized, accounting for two percent of employer firms and 1.2 percent of sales.

Hispanic American firms (disparity index of 103.90) were overutilized, accounting for 1.8 percent of employer firms and 1.9 percent of sales

Data for Native American and nonminority female employer firms withheld; therefore, private sector disparities were not conducted.






NAICS CODE 54, PROFESSIONAL, SCIENTIFIC AND TECHNICAL SERVICES U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS,






($1,000) All Firms 6,944 $2,131,211 1,519 $1,928,795 African American Firms 741 $32,177 66 $15,820 Native American Firms1 N/A N/A N/A N/A Asian American Firms2 172 $26,870 30 $23,314 Hispanic American Firms 211 $40,017 28 $36,940 Nonminority Female Firms3 N/A N/A N/A N/A

PERCENTAGE OF MARKETPLACE All Firms 100.00% 100.00% 100.00% 100.00% African American Firms 10.67% 1.51% 4.34% 0.82% Native American Firms1 N/A N/A N/A N/A Asian American Firms2 2.48% 1.26% 1.97% 1.21% Hispanic American Firms 3.04% 1.88% 1.84% 1.92% Nonminority Female Firms3 N/A N/A N/A N/A

DISPARITY INDEX All Firms 100.00 100.00 African American Firms 14.15 18.88 Native American Firms1 N/A N/A Asian American Firms2 50.90 61.20 Hispanic American Firms 61.79 103.90 Nonminority Female Firms3 N/A N/A

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms, where data was available. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms, where data was available. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms, where data was available. N/A denotes data on business ownership classification group was not available.





NAICS CODE 56: ADMINISTRATIVE AND SUPPORT AND WASTE MANAGEMENT AND REMEDIATION SERVICES, METRO AREA MARKETPLACE

Table 6-9 shows the availability, sales, and disparity results for administrative and support and waste management and remediation services (NAICS Code 56). There was a total 5,727 administrative and support and waste management and remediation services firms (all firms) in the Greensboro-High Point North Carolina metro area in 2012, of which 31.8 percent was owned by minorities.



Data for Native American, Asian American, and nonminority female all firms were withheld; therefore, private sector disparities were not conducted.

There was a total of 783 administrative and support and waste management and remediation services employer firms in the Greensboro-High Point North Carolina metro area in 2012, of which 15.2 percent was owned by minorities.


Data for Native American, Asian American, Hispanic American, and nonminority female employer firms withheld; therefore, private sector disparities were not conducted.






NAICS CODE 56 ADMINISTRATIVE AND SUPPORT AND WASTE MANAGEMENT AND REMEDIATION SERVICES

U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS, GREENSBORO-HIGH POINT, NC METRO AREA MARKETPLACE


ALL FIRMS (#)


EMPLOYER FIRMS (#)


All Firms 5,727 $1,500,159 783 $1,413,625 African American Firms 1,417 $95,724 91 $77,365 Native American Firms1 30 S 4 S Asian American Firms2 74 S 7 a, b, S Hispanic American Firms 299 $5,993 17 S Nonminority Female Firms3 N/A N/A N/A N/A

PERCENTAGE OF MARKETPLACE All Firms 100.00% 100.00% 100.00% 100.00% African American Firms 24.74% 6.38% 11.62% 5.47% Native American Firms1 0.52% S 0.51% S Asian American Firms2 1.29% S 0.89% a, b, S Hispanic American Firms 5.22% 0.40% 2.17% S Nonminority Female Firms3 N/A N/A N/A N/A

DISPARITY INDEX All Firms 100.00 100.00 African American Firms 25.79 47.09 Native American Firms1 S S Asian American Firms2 S a, b, S Hispanic American Firms 7.65 S Nonminority Female Firms3 N/A N/A

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms, where data was available. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms, where data was available. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms, where data was available. S denotes findings were withheld as the estimates did not meet U.S. Census publication standards. a denotes the Employees (#) was 0 to 19 employees. b denotes the Employees (#) was 20 to 99 employees. N/A denotes data on business ownership classification group was not available.





NAICS CODE 81: OTHER SERVICES (EXCEPT PUBLIC ADMINISTRATION), METRO AREA MARKETPLACE

Table 6-10 shows the availability, sales, and disparity results for NAICS Code, other services (except public administration). There was a total 10,279 other services (except public administration) firms (all firms) in the Greensboro-High Point North Carolina metro area in 2012, of which 42.3 percent was owned by minorities.


Native American firms (disparity index of 17.65) were substantially underutilized, accounting for one percent of firms and 0.2 percent of sales.


Data for Hispanic American and nonminority female all firms were withheld; therefore, private sector disparities were not conducted.

There was a total of 824 other services (except public administration) employer firms in the Greensboro-High Point North Carolina metro area in 2012, of which 13.2 percent was owned by minorities.

Data for Native American employer firms were reported as zero; therefore, private sector disparities were not conducted.

Data for African American, Hispanic American, and nonminority female employer firms were withheld; therefore, private sector disparities were not conducted.






NAICS CODE 81, OTHER SERVICES (EXCEPT PUBLIC ADMINISTRATION) U.S. CENSUS 2012 SURVEY OF BUSINESS OWNERS,






($1,000) All Firms 10,279 $694,459 824 $469,278 African American Firms 2,736 $58,067 41 S Native American Firms1 107 $1,276 0 $0 Asian American Firms2 1,226 $37,140 42 $7,118 Hispanic American Firms 282 S 26 S Nonminority Female Firms3 N/A N/A N/A N/A


DISPARITY INDEX All Firms 100.00 100.00 African American Firms 31.41 S Native American Firms1 17.65 - Asian American Firms2 44.84 29.76 Hispanic American Firms S S Nonminority Female Firms3 N/A N/A

Source: MGT of America, Inc. conducted private sector disparities marketplace analyses based on U.S. Census Bureau, 2012 Survey of Business Owners (SBO) data. 1 Native American consists of American Indian- and Alaska Native-owned firms, where data was available. 2 Asian American consists of Asian-owned and Native Hawaiian- and Other Pacific Islander-owned firms, where data was available. 3 Nonminority Female consists of White Female-owned and White Equally Female-/Male-owned firms, where data was available. S denotes findings were withheld as the estimates did not meet U.S. Census publication standards. N/A denotes data on business ownership classification group was not available. - denotes the denominator was zero and thus the values were undefined.





6. ANALYSIS OF RACE, ETHNICITY, AND GENDER EFFECTS ON SELF-EMPLOYMENT RATES The purpose of this analysis is to examine the effects of race and gender, along with other individual economic and demographic characteristics, on individuals’ participation in the private sector as self-employed business operators, and on their earnings as a result of their participation in five categories of private sector business activity in the Greensboro-High Point, NC Combined Metropolitan Statistical Area (CMSA). Findings for minority business enterprises are compared to the self-employment participation and earnings record of nonminority male business owners to determine if a disparity in self-employment rates and earnings exists, and if it is attributable to differences in race, ethnicity, and gender. Adopting the methodology and variables employed by a City of Denver disparity study (see Concrete Works v. City and County of Denver115), we use Public Use Microdata Samples (PUMS) data derived from the 2014 American Community Survey (ACS), to which we apply appropriate regression statistics to draw conclusions.

To guide this investigation, three general research questions were posed. Questions and variables used to respond to each, followed by a report of findings, are reported below:

1. Are racial, ethnic and gender minority groups less likely than nonminority males to be self-employed?

This analysis examined the statistical effects of the following variables on the likelihood of being self-employed in the Greensboro-High Point CMSA: Race, ethnicity, and gender of business owner (African American, Asian American, Hispanic American, Native American, nonminority female, nonminority men), marital status, age, self-reported health-related disabilities, availability of capital (household property value, monthly total mortgage payments, unearned income) and other characteristics (number of individuals over the age of 65 living in household, number of children under the age of 18 living in household) and level of education.

2. Does racial, ethnic and gender status have an impact on individual’s self-employment earnings?

This analysis examined the statistical effects of the following variables on income from self-employment for business owners in the Greensboro-High Point CMSA: Race, ethnicity, and gender of business owner (African American, Asian American, Hispanic American, Native American, nonminority female, nonminority men), marital status, age, self-reported health-related disabilities, and availability of capital (household property value, monthly total mortgage payments, unearned income) and level of education.

115 Concrete Works v. City and County of Denver, 321 F.3 950 (10th Cir. 2003).





3. If M/WBE firms and nonminority male owned firms shared similar traits and marketplace “conditions” (i.e., similar “rewards” in terms of capital and asset accrual), what would be the effect on rates of self-employment by race, ethnicity and gender?

Derived from a similar model employed by a City of Denver disparity study, MGT created a model which leveraged statistical findings in response to the first two questions to determine if race, gender, and ethnic effects derived from those findings would persist if nonminority male demographic and economic characteristics were combined with M/WBE self-employment data. More precisely, in contrast to Question 1, which permitted a comparison of self-employment rates based on demographic and economic characteristics reported by the 2014 census for individual M/WBE categories and nonminority males, respectively, this analysis posed the question, “How would M/WBE rates change, if M/WBE’s operated in a nonminority male business world and how much of this change is attributable to race, gender or ethnicity?”

FINDINGS

1. Are racial, ethnic and gender minority groups less likely than nonminority males to be self-employed?

In all industries, nonminority males were over two and a half times as likely to be self-employed as African Americans.116

In all industries, nonminority males were over two times as likely to be self-employed as nonminority women.

Nonminority males were over three times as likely as African Americans to be self-employed in the professional services industry.

Nonminority males were over eight times as likely as African Americans in the goods and supplies industry.

2. Does racial, ethnic and gender have an impact on an individual’s self-employment earnings?

In the Greensboro-High Point CMSA, all groups reported significantly lower earnings in all business type categories, except for Asian and Native Americans.

Overall, African Americans reported significantly lower earnings than nonminority males: 57.7 percent less.

In the professional services, nonminority women reported significantly lower earnings than nonminority males: 47.1 percent less.

116 These ‘likelihood” characteristics were derived from Exhibit I-1 by calculating the inverse of the reported odds ratios.





The most egregious effect on earnings elasticities was found in the other services for African Americans. In the other services, African Americans earned 60.1 percent less than nonminority males.

3. If M/WBE firms and nonminority males shared similar traits and marketplace “conditions” (i.e., similar “rewards” in terms of capital and asset accrual), what would be the effect on rates of self-employment by race, ethnicity, and gender?

Overall, comparing self-employed nonminority males with self-employed African Americans, over 87 percent of the disparity in self-employment rates was attributable to race differences.

Overall, comparing self-employed nonminority males with self-employed Hispanic Americans, over 81 percent of the disparity in self-employment rates was attributable to race differences.

Comparing self-employed nonminority males with self-employed Hispanic Americans in the construction industry, over 60 percent of the disparity in self-employment rates was attributable to race differences.

Comparing self-employed nonminority males with self-employed Hispanic Americans in the professional services, over 62 percent of the disparity in self-employment rates was attributable to race differences.

Comparing self-employed nonminority males with self-employed African Americans in the other services, over 74 percent of the disparity in self-employment rates was attributable to race differences.

The following details goal, objectives, research basis and questions, findings, and conclusions from the analyses. The goal of this investigation is to examine the effects of race and gender, along with other individual economic and demographic characteristics, on individuals’ participation in the private sector as self-employed business operators, and on their earnings as a result of their participation. Ultimately, MGT will compare these findings to the self-employment participation and earnings record of nonminority male business owners to determine if a disparity in self-employment rates and earnings exists and if it is attributable to racial or gender discrimination in the marketplace. Data for this investigation are provided by the PUMS data derived from the 2014 American Community Survey, to which we apply appropriate regression statistics to draw conclusions. Table 6-11 presents a general picture of self-employment rates by race, median earnings, and sample sizes (n’s) in the Greensboro-High Point CMSA, calculated from the 5-percent PUMS census sample.

The next section will discuss the research basis for this examination to lay the groundwork for a description of the models and methodologies to be employed. This will be followed by a presentation of findings regarding minority status effects on self-employment rates, self-employment earnings, and attributions of these differences to discrimination, per se.





TABLE 6-11 PERCENTAGE SELF-EMPLOYED/2014 EARNINGS

RACIAL, ETHNIC, AND GENDER BUSINESS OWNERSHIP CLASSIFICATION BUSINESS OWNERSHIP

CLASSIFICATION PERCENT OF SELF-

EMPLOYED 2014 SAMPLE CENSUS n 2014 MEDIAN EARNINGS

Non-M/WBE Firms 16.44% 369 $42,000.00 African American Firms 5.22% 30 $28,000.00 Hispanic American Firms 7.61% 21 $20,000.00 Asian American Firms 11.46% 11 $36,000.00 Native American Firms 9.26% 5 $30,000.00 Nonminority Female Firms 7.45% 123 $37,000.00 TOTAL 11.41% 559 $38,000.00

Source: PUMS data from 2014 American Community Survey (Greensboro-High Point, CMSA) and MGT of America, Inc., calculations using SPSS Statistics software.

SELF-EMPLOYMENT RATES AND EARNINGS AS AN ANALOG OF BUSINESS FORMATION AND MAINTENANCE

Research in economics consistently supports the finding of group differences by race and gender in rates of business formation (see Journal of Econometrics, Vol. 61, Issue 1, devoted entirely to the econometrics of labor market discrimination and segregation). For a disparity study, however, the fundamental question is “How much of this difference is due to factors that would appear, at least superficially, to be related to group differences other than race, ethnicity, or gender, and how much can be attributed to discrimination effects related to one’s race/ethnic/gender affiliation?” We know, for instance, most minority groups have a lower median age than do non-Hispanic whites (ACS PUMS, 2014). We also know, in general, the likelihood of being self-employed increases with age (ACS PUMS, 2014). When social scientists speak of nonracial group differences, they are referring to such things as general differences in religious beliefs as these might influence group attitudes toward contraception, and, in turn, both birthrates and median age. A disparity study, therefore, seeks to examine these other important demographic and economic variables in conjunction with race and ethnicity, as they influence group rates of business formation, to determine if we can assert discrimination against minorities is sufficiently present to warrant consideration of public sector legal remedies such as affirmative action and minority set-aside contracting.

Questions about marketplace dynamics affecting self-employment—or, more specifically, the odds of being able to form one’s own business and then to excel (i.e., generate earnings growth)—are at the heart of disparity analysis research. Whereas early disparity studies tended to focus on gross racial disparities, merely documenting these is insufficient for inferring discrimination effects per se without “partialling out” effects due to nondiscriminatory factors. Moreover, to the extent discrimination exists, it is likely to inhibit both the formation of minority business enterprises and their profits and growth. Consequently, earlier disparity study methodology and analysis have failed to account for the effects of discrimination on minority self-employment in at least two ways: (1) a failure to account adequately for the effects of discriminatory barriers minorities face “up front” in attempting to form businesses; and (2) a failure to isolate and methodologically explain discrimination effects once minority businesses are formed.





The next section addresses these shortcomings, utilizing PUMS data derived from the 2014 U.S. Census to answer research questions about the effects of discrimination on self-employment and self-employment earnings using multiple regression statistics.

RESEARCH QUESTIONS, STATISTICAL MODELS, AND METHODS

Two general research questions were posed in the initial analysis:

1) Are racial, ethnic, and gender minority groups less likely than nonminority males to be self-employed?

2) Does racial, ethnic, and gender status have an impact on individuals’ earnings?

A third question, to be addressed later—How much does racial, ethnic, and gender discrimination influence the probability of being self-employed?—draws conclusions based on findings from questions one and two.

To answer the first two questions, we employed two multivariate regression techniques, respectively: logistic regression and linear regression. To understand the appropriate application of these regression techniques, it is helpful to explore in greater detail the questions we are trying to answer. The dependent variables in questions one and two—that is, the phenomena to be explained by influences such as age, race, gender, and disability status, for example (the independent or “explanatory” variables)—are, respectively: the probability of self-employment status (a binary, categorical variable based on two possible values: 0 = not self-employed/1 = self-employed) and 2014 earnings from self-employment (a continuous variable). In our analysis, the choice of regression approach was based on the scale of the dependent variable (in question I, a categorical scale with only two possible values, and in question II, a continuous scale with many possible values). Because binary logistic regression is capable of performing an analysis in which the dependent variable is categorical, it was employed for the analysis of question one.117 To analyze question two, in which the dependent variable is continuous, we used simple linear regression.

DERIVING THE LOGISTIC REGRESSION MODEL FROM THE SIMPLE LINEAR MODEL

The logistic regression model can be derived with reference to the simple linear regression model expressed mathematically as:

Y = β0 + β I XI + β2 X2 + β3 X3 + β4 X4 + β5 X5 + … + ε

117 Logistical regression, or logit, models generate predicted probabilities that are almost identical to those calculated by a probit procedure, used in Concrete Works v. City and County of Denver case. Logit, however, has the added advantage of dealing more effectively with observations at the extremes of a distribution. For a complete explanation, see Interpreting Probability Models (T.F. Liao, Text 101 in the Sage University series).





Where:

Y = a continuous variable (e.g., 2014 earnings from self-employment)

β0 = the constant, representing the value of Y when XI = 0

βI = coefficient representing the magnitude of XI’s effect on Y

XI = the independent variables, such as age, human capital (e.g., level of education), availability of capital, race/ethnicity/gender, etc.

ε = the error term, representing the variance in Y unexplained by XI

This equation may be summarized as:

k

K

kk xYE ∑

=

==1

)( βµ

in which Y is the dependent variable and µ represents the expected values of Y as a result of the effects of β, the explanatory variables. When we study a random distribution of Y using the linear model, we specify its expected values as a linear combination of K unknown parameters and the covariates or explanatory variables. When this model is applied to data in the analysis, we are able to find the statistical link between the dependent variable and the explanatory or independent variables.

Suppose we introduce a new term, η, into the linear model such that:

k

K

kk x∑

=

==1βµη

When the data are randomly distributed, the link between η and µ is linear, and a simple linear regression

can be used. However, to answer the first question, the categorical dependent variable was binomially distributed. Therefore, the link between η and µ became )]1/(log[ µµη −= and logistic regression was

utilized to determine the relationship between the dependent variable and the explanatory variables, calculated as a probability value (e.g., the probability of being self-employed when one is African American). The logistic regression model is expressed mathematically as:

εβαµµ ++=− ni X)]1(1/log[

Where:

(µ/1-µ) = the probability of being self-employed

α = a constant value

βI = coefficient corresponding to independent variables

nX = selected individual characteristic variables, such as age, marital status, education, race, and gender





ε = error term, representing the variance in Y unexplained by XI

This model can now be used to determine the relationship between a single categorical variable (0 = not self-employed/1 = self-employed) and a set of characteristics hypothesized to influence the probability of finding a 0 or 1 value for the categorical variable. The result of this analysis illustrates not only the extent to which a characteristic can increase or decrease the likelihood the categorical variable will be a 0 or a 1, but also whether the effect of the influencing characteristics is positive or negative in relation to being self-employed.

RESULTS OF THE SELF-EMPLOYMENT ANALYSIS

QUESTION ONE: ARE RACIAL, ETHNIC, AND GENDER MINORITY GROUPS LESS LIKELY THAN NONMINORITY MALES TO BE SELF-EMPLOYED?

To derive a set of variables known to predict employment status (self-employed/not self-employed), we used the 2014 U.S. Census ACS 5-percent PUMS data. Binary logistic regression was used to calculate the probability of being self-employed, the dependent variable, with respect to socioeconomic and demographic characteristics selected for their potential to influence the likelihood of self-employment. The sample for the analysis was limited to labor force participants who met to the following criteria:

Resident of the Greensboro-High Point CMSA.

Self-employed in construction, professional services, other services, architecture and engineering,118 or goods and supplies.

Employed full-time (more than 35 hours a week).

18 years of age or older.

Employed in the private sector.

Next, we derived the following variables hypothesized as predictors of employment status:

Race and Gender: African American, Asian American, Hispanic American, Native American, nonminority woman, nonminority male.

Availability of Capital: Homeownership, home value, mortgage rate, unearned income, residual income.

Marital Status.

Ability to Speak English Well.

118 Due to inadequate sample numbers for all races in the architecture and engineering PUMS 2014 data, architecture and engineering was merged with the professional services category.





Disability Status: From individuals’ reports of health-related disabilities.

Age and Age Squared: Squaring the age variable acknowledges the positive, curvilinear relationship between each year of age and earnings.

Owner’s Level of Education.

Number of Individuals Over the Age of 65 Living in Household.

Number of Children Under the Age of 18 Living in Household.

FINDINGS Binary logistic regression analysis provided estimates of the relationship between the independent variables described above and the probability of being self-employed in the four types of business industries. In Table 6-12, odds ratios are presented by minority group, reporting the effect of race, ethnicity, and gender on the odds of being self-employed in 2014, holding all other variables constant. Full regression results for all the variables are presented in Appendix J.

TABLE 6-12 SELF-EMPLOYMENT “ODDS RATIOS” OF MINORITY GROUPS RELATIVE TO

NONMINORITY MALES AFTER CONTROLLING FOR SELECTED DEMOGRAPHIC AND ECONOMIC CHARACTERISTICS


ALL INDUSTRIES

CONSTRUCTION PROFESSIONAL

SERVICES OTHER

SERVICES GOODS & SUPPLIES

African American Firms 0.363 0.418 0.292 0.830 0.121 Hispanic American Firms 0.588 0.471 0.315 0.785 * Asian American Firms 0.707 1.555 0.475 0.753 2.211 Native American Firms 0.667 1.210 * 0.406 * Nonminority Female Firms 0.430 0.606 0.561 0.706 0.761

Source: PUMS data from 2014 American Community Survey (Greensboro-High Point, CMSA) and MGT of America, Inc., calculations using SPSS Statistics software. Note: Bold indicates the estimated “odds ratio” for the group was statistically significant. The architecture and engineering business industry was excluded from this analysis because of the insufficient data. * There were insufficient census numbers available for analysis.

The results reveal the following:

In all industries, nonminority males were over two and a half times as likely to be self-employed as African Americans.119

In all industries, nonminority males were over two times as likely to be self-employed as nonminority women.

Nonminority males were over three times as likely as African Americans to be self-employed in the professional services industry.

119 These ‘likelihood” characteristics were derived from Exhibit I-1 by calculating the inverse of the reported odds ratios.





Nonminority males were over eight times as likely as African Americans in the goods and supplies industry.

QUESTION TWO: DOES RACIAL, ETHNIC, AND GENDER STATUS HAVE AN IMPACT ON INDIVIDUALS’ EARNINGS?

To answer this question, we compared self-employed, minority, and women entrepreneurs’ earnings to those of nonminority males in the Greensboro-High Point CMSA, when the effect of other demographic and economic characteristics was controlled or “neutralized.” That is, we were able to examine the earnings of self-employed individuals of similar education levels, ages, etc., to permit earnings comparisons by race, ethnicity, and gender.

To derive a set of variables known to predict earnings, the dependent variable, we used 2014 wages from employment for self-employed individuals, as reported in the 5 percent PUMS data. These included:

Race and Gender: African American, Asian American, Hispanic American, Native American, nonminority woman, nonminority males.

Availability of Capital: Homeownership, home value, mortgage rate, unearned income, residual income.

Marital Status.

Ability to Speak English Well.

Disability Status: From individuals’ reports of health-related disabilities.

Age and Age Squared: Squaring the age variable acknowledges the positive, curvilinear relationship between each year of age and earnings.

Owner’s Level of Education.

FINDINGS Table 6-13 presents the results of the linear regression model estimating the effects of selected demographic and economic variables on self-employment earnings. Each number (i.e., coefficient) in the exhibit represents a percent change in earnings. For example, the corresponding number for a African Americans in all industries is -.577 meaning that African American firms will earn 57.7 percent less than a nonminority male when the statistical effects of the other variables in the equation are “controlled for.” Full regression results for all the variables are presented in Appendix I.





TABLE 6-13 EARNINGS ELASTICITIES OF MINORITY GROUPS RELATIVE TO NONMINORITY

MALES AFTER CONTROLLING FOR SELECTED DEMOGRAPHIC AND ECONOMIC CHARACTERISTICS


ALL INDUSTRIES

CONSTRUCTION PROFESSIONAL

SERVICES OTHER

SERVICES GOODS & SUPPLIES

African American Firms -0.577 -0.599 -0.399 -0.601 -0.844 Hispanic American Firms -0.631 -0.539 0.113 -0.482 * Asian American Firms -0.426 -0.354 -0.593 -0.503 -0.882 Native American Firms -0.737 -0.664 * -0.585 * Nonminority Female Firms -0.240 -0.388 -0.471 -0.254 -0.428

Source: PUMS data from 2014 American Community Survey (Greensboro-High Point, CMSA) and MGT of America, Inc., calculations using SPSS Statistics software. Note: Bold indicates the estimated “elasticities” for the group were statistically significant. The architecture and engineering business industry was excluded from this analysis because of insufficient data. * There were insufficient census numbers available for analysis.

The results reveal the following:

In the Greensboro-High Point CMSA, all groups reported significantly lower earnings in all business type categories, except for Asian and Native Americans.

Overall, African Americans reported significantly lower earnings than nonminority males: 57.7 percent less.

In the professional services, nonminority women reported significantly lower earnings than nonminority males: 47.1 percent less.

The most egregious effect on earnings elasticities was found in the other services for African Americans. In the other services, African Americans earned 60.1 percent less than nonminority males.

DISPARITIES IN RATES OF SELF-EMPLOYMENT: HOW MUCH CAN BE ATTRIBUTED TO DISCRIMINATION?

Results of the analyses of self-employment rates and 2014 self-employment earnings revealed general disparities between minority and nonminority self-employed individuals whose businesses were located in the Greensboro-High Point CMSA.

Exhibit 6-14 presents the results of these analyses. Column A reports observed employment rates for each racial, ethnic, and gender group, calculated directly from the PUMS 2014 data. To obtain values in columns B and C, we calculated two predicted self-employment rates using the following equation:

)1/()1(Pr1

kkkk xK

k

x eeyob ββ∑=

+==





Where:

)1(Pr =yob = represents the probability of being self-employed

kβ = coefficient corresponding to the independent variables used in the logistic regression analysis of self-employment probabilities

kx = the mean values of these same variables

The first of these predicted self-employment rate calculations (in column B) presents nonminority male self-employment rates as they would be if their characteristics (i.e., kx , or mean values for the independent

variables) were applied to minority market structures (represented for each race by their kβ or odds

coefficient values). The second self-employment rate calculation (in column C) presents minority self-employment rates as they would be if minorities were rewarded in a similar manner as nonminority males in the nonminority male market structure: that is, by multiplying the minority means (i.e., characteristics) by the estimated nonminority coefficients for both race and the other independent variables.

EXHIBIT 6-14 OBSERVED AND PREDICTED SELF-EMPLOYMENT RATES

THE GREENSBORO-HIGH POINT, NC CMSA


OBSERVED SELF-

EMPLOYMENT RATES

WHITE CHARACTERISTICS

AND OWN MARKET

STRUCTURE

OWN CHARACTERISTIC

S AND WHITE MARKET

STRUCTURE

DISPARITY RATIO

(COLUMN A DIVIDED BY COLUMN C)

PORTION OF DIFFERENCE DUE

TO DISCRIMINATION

(A) (B) (C) (D) (E) Overall Non-M/WBE Firms 0.16436526 0.16436526 0.16436526 1.000 African American Firms 0.05217391 0.08242810 0.15021072 0.34733815 0.87383573 Hispanic American Firms 0.07608696 0.12711197 0.14766357 0.51527235 0.81080649 Asian American Firms 0.11458333 0.14902296 0.14650516 0.78211125 0.64123327 Native American Firms 0.09259259 0.14180513 0.14212672 0.65147914 0.69015310 Nonminority Female Firms 0.07445521 0.09632262 0.20340707 0.36604040 n/d Construction Non-M/WBE Firms 0.32051282 0.32051282 0.32051282 1.000 African American Firms 0.13888889 0.21411517 0.39336183 0.35308177 n/d Hispanic American Firms 0.10576923 0.23462151 0.23486602 0.45033859 0.60116712 Asian American Firms 0.42857143 0.50325306 0.26046132 1.64543217 n/d Native American Firms 0.28571429 0.44065549 0.28981649 0.98584552 0.11788433 Nonminority Female Firms 0.27419355 0.28296063 0.47941007 0.57193949 n/d Professional Services Non-M/WBE Firms 0.09653916 0.09653916 0.09653916 1.000 African American Firms 0.02030457 0.05408529 0.14225578 0.14273282 n/d Hispanic American Firms 0.02325581 0.05813032 0.06883781 0.33783490 0.62199660 Asian American Firms 0.06060606 0.08520010 0.18611371 0.32563995 n/d Native American Firms 0.00000000 0.00000000 0.00048064 0.00000000 0.00497867 Nonminority Female Firms 0.03967328 0.09912924 0.11066234 0.35850748 n/d Other Services Non-M/WBE Firms 0.17737430 0.17737430 0.17737430 1.00000000






OBSERVED SELF-

EMPLOYMENT RATES

WHITE CHARACTERISTICS

AND OWN MARKET

STRUCTURE

OWN CHARACTERISTIC

S AND WHITE MARKET

STRUCTURE

DISPARITY RATIO

(COLUMN A DIVIDED BY COLUMN C)

PORTION OF DIFFERENCE DUE

TO DISCRIMINATION

African American Firms 0.10471204 0.18967521 0.15918585 0.65779742 0.74968503 Hispanic American Firms 0.11111111 0.18124307 0.14210857 0.78187479 0.46779308 Asian American Firms 0.11111111 0.17515431 0.13577429 0.81835160 0.37220035 Native American Firms 0.04761905 0.10270111 0.22638082 0.21034931 n/d Nonminority Female Firms 0.12785388 0.16607196 0.23285387 0.54907346 n/d Goods & Supplies Non-M/WBE Firms 0.07617188 0.07617188 0.07617188 1.000 African American Firms 0.00662252 0.01462658 0.01200343 0.55171880 0.07736823 Hispanic American Firms 0.00000000 0.00000000 0.01119549 0.00000000 0.14697666 Asian American Firms 0.10000000 0.21338159 0.03015102 3.31663684 n/d Native American Firms 0.00000000 0.00000000 0.01119549 0.00000000 0.14697666 Nonminority Female Firms 0.05423729 0.08542408 0.10859997 0.49942266 n/d

Source: PUMS data from 2014 American Community Survey and MGT of America, Inc., calculations using SPSS and Microsoft Excel. n/d: No discrimination was found.

Using these calculations, we were able to determine a percentage of the disparities in self-employment between minorities and nonminority males attributable to discrimination by dividing the observed self-employment rate for a particular minority group (column A) by the predicted self-employment rate as it would be if minority groups faced the same market structure as nonminority males (column C). Next, we calculated the difference between the predicted self-employment rate as it would be if minority groups faced the same market structure as nonminority males and the observed self-employment rate for that minority group, and divided this value by the difference between the observed self-employment rate for nonminority males and the self-employment rate for a particular minority group. In the absence of discrimination, this number is zero, which means disparities in self-employment rates between minority groups and nonminority males can be attributed to differences in group characteristics not associated with discrimination. Conversely, as this value approaches 1.0, we are able to attribute disparities increasingly to discrimination in the marketplace.

FINDINGS Examining the results reported in Exhibit 6-14, we found the following:

Overall, comparing self-employed nonminority males with self-employed African Americans, over 87 percent of the disparity in self-employment rates was attributable to race differences.

Overall, comparing self-employed nonminority males with self-employed Hispanic Americans, over 81 percent of the disparity in self-employment rates was attributable to race differences.

Comparing self-employed nonminority males with self-employed Hispanic Americans in the construction industry, over 60 percent of the disparity in self-employment rates was attributable to race differences.





Comparing self-employed nonminority males with self-employed Hispanic Americans in the professional services, over 62 percent of the disparity in self-employment rates was attributable to race differences.

Comparing self-employed nonminority males with self-employed African Americans in the other services, over 74 percent of the disparity in self-employment rates was attributable to race differences.

In general, findings from the PUMS 2014 data indicate minorities were significantly less likely than nonminority males to be self-employed and, if they were self-employed, they earned significantly less in 2014 than did self-employed nonminority males. When self-employment rates were stratified by race and by business type, trends varied within individual race-by-type cells, but disparities persisted, in general, for all minorities and nonminority women. When group self-employment rates were submitted to MGT’s disparity-due-to-minority-status analysis, findings supported the conclusion which disparities for these groups (of adequate sample size to permit interpretation) were likely the result of differences in the marketplace due to race, gender, and ethnicity.120

7. CONCLUSION Section 3 presented a summary of firm utilization at the prime contractor and subcontractor by racial, ethnic and gender classification comparing M/WBE utilization for the District public sector construction projects with commercial construction projects from July 1, 2009 and June 30, 2014. When M/WBE vendor lists were used to identify M/WBE firms for public sector and private sector construction projects, according to the findings from commercial construction projects, substantial M/WBE underutilization was evident in the private sector. When compared to findings from the commercial construction projects, M/WBE firms fared better on District projects.

Capacity alone is not a sufficient explanation for these differences, especially at the subcontractor level in the construction business category, where capacity is a lesser consideration and availability far exceeds the record of utilization, especially in the private sector. This chapter presented statistical evidence that disparities associated with race and gender persist after controls for capacity and business experience are considered. Moreover, the evidence of very small M/WBE utilization on commercial construction projects, supported by anecdotal comments from M/WBE firms (see Chapter 7), supports the claim M/WBE firms face a number steep barriers in seeking work on private sector construction projects. To the extent which M/WBE subcontractor utilization is minimal in the private sector, credence may be given to the proposition established in Croson which government could be a passive participant in private sector discrimination if it did not require contractors who apply for public sector construction projects to solicit and negotiate with M/WBE subcontractors in good faith efforts.

120 Appendix I reports self-employment rates and earnings in greater detail by race, ethnicity, and gender and procurement category.




7 | ANECDOTAL ANALYS IS



The anecdotal analysis was structured to conform to case law in addition to answering a basic research question: Is there qualitative/anecdotal evidence of disparate treatment of M/WBE subcontractors by prime contractors? The collection of anecdotal information is a widely accepted research methodology that is based upon interviews, data collected during focus groups, survey responses, and other anecdotal data collection methods. The collection and analysis of anecdotal data is used in conjunction with other research tools to provide context, and to help explain findings based on quantitative data analysis. The findings in this chapter support the overall underutilization of minority and women firms in the market area. Much of the anecdotal findings indicate that lack of M/WBE program compliance, and the procurement process contributes to perceptions and opinions about disparate treatment in contract awards.

Unlike conclusions derived from other types of analysis in this report, the conclusions derived from anecdotal analysis do not rely solely on quantitative data. Anecdotal analysis also utilizes qualitative data to describe the context of the examined social, political, and economic environment in which all businesses and other relevant entities applicable to the study operate.

The following sections present MGT’s approach to collecting anecdotal data, the methods employed, and the quantitative and qualitative results of the data collected.

1. METHODOLOGY The blueprint for collecting and analyzing anecdotal information for this study was provided by the U.S. Supreme Court in City of Richmond v. J.A. Croson, 488 U.S. 469, 109 S.Ct. 706 (1989) (Croson). Specifically, race-conscious programs must be supported by strong documentation of discrimination, including evidentiary findings that go beyond the demographics of a community. Anecdotal information can bolster the quantitative analyses of contract expenditures to explain whether or not minority business creation, growth, and retention are negatively affected by discrimination. In Croson, the Court held that anecdotal accounts of discrimination could help establish a compelling interest for a local government to institute a race-conscious remedy. Moreover, such information can provide a local entity with a firm basis for fashioning a program that is narrowly tailored to remedy identified forms of marketplace discrimination and other barriers to M/WBE participation in contract opportunities. Further discussion of anecdotal testimony is contained in Chapter 2, Legal Framework.

MGT’s experience conducting disparity studies has shown that utilizing multiple methods of anecdotal data collection provide more comprehensive information than methodologies using a single-pronged approach. For this reason, MGT used a combination of surveys, focus groups, public meetings, and personal interviews to collect anecdotal information and to identify issues that were common to businesses in the market area between the calendar years of July 1, 2009, and June 30, 2014. To ensure a broad representation of firms in the market place, MGT’s sample methodology for the focus groups, interviews, and survey of vendors


1. Methodology

2. Demographics

3. Barriers to Doing Business with Guilford County School District

4. Stakeholder Interviews

5. Access to Capital and Bonding

6. Disparate Treatment and Discrimination

7. Suggested Remedies from Anecdotal Participants

8. Conclusion





included randomly selecting firms from the District’s Master Vendor Database (discussed in Chapter 4). Sample sets were double checked to ensure that firms do not participate in more than one anecdotal activity. The public meetings were open to the public; therefore, chances are that firms that attended the public meetings may have been randomly selected for other anecdotal activities. In conjunction with the quantitative data, MGT was also able to draw inferences from these data as to the prevalence of obstacles perceived as limiting the participation of M/WBEs and other firms in the Guilford County School District’s procurement transactions.

Personal interviews, public meetings, and focus groups collective responses provided in this chapter are not altered for context but are edited for grammar. Otherwise responses were unfiltered or unedited. However, readers should be cautioned that anecdotal comments in this chapter detail the perceptions and opinions of individuals, and the evidentiary weight of these opinions depends on how much they are corroborated by statements of others and the quantitative data in the report.

SURVEY OF VENDORS

The survey of vendors gathered information on business ownership, work performed and/or bid with the District, with primes that have contracts with the District, work bid and/or performed in the private sector, and barriers, perceived or real, that prevented firms from doing business with the District during the study period. MGT attempted to collect data in proportion to the distribution of M/WBEs and non-M/WBEs in the relevant market area. Oppenheim Research, Inc., a HUB certified woman-owned business research firm administered a controlled survey using the Appendix E – Survey of Vendors Instrument. On average, seven attempts were made to contact firms. Throughout this chapter, several charts detail selected survey results. See Appendix F – Survey of Vendors Results for the complete survey results.

In most municipalities, disparity study surveys are commonly plagued by sample size limitations, especially in the case of attempting to gather a representative sample from minority business populations where low minority numbers tend to be insufficient in number to permit a valid and representative sample. This problem is compounded when analyses are stratified further by business type. Insufficient sample size can pose problems for the statistical confidence of the results. For the District’s Native American- and Asian American-owned business representation was extremely low. Although MGT’s goal is to report data that can satisfy the 95 percent confidence level, this does not mean that data should not be reported because of slightly reduced confidence intervals, especially when extreme due diligence has been exercised in attempting to meet the 95 percent standard.

FOCUS GROUPS

MGT facilitated two focus groups with M/WBE and non-M/WBE firms with the assistance of BLWall Consulting, a HUB certified minority-owned firm. The first focus group was held for subcontractor and suppliers on May 13, 2015 at 120 Franklin St., Greensboro, NC. The second focus group included prime firms and was held at the Guilford County Schools Administration Offices at 712 N. Eugene Street, Greensboro, NC on May 14, 2015. BLWall Consulting provided recruitment assistance, administrative support, and coordination. Using the Master Vendor Database, two samples of randomly selected firms were provided





to BLWall Consulting to recruit for the two focus groups. The focus group discussions were voice recorded after all participants agreed to be recorded.

PUBLIC MEETINGS

Area firms, M/WBEs included, that have done business with or attempted to do business with the District or its prime firms were invited to attend one of four public hearings and/or public forum. The public hearing was designed to accept anecdotal comments on their experiences which were recorded by a court reporter. The public forum was designed to provide the business community information about the disparity study and answer any questions about the study. BLWall Consulting co-facilitated the meetings and provided administrative support and management.

All public meetings were held at the Guilford County Schools Administrative Building, 712 N. Eugene St., Greensboro. The first set of public meetings were held on December 9, 2014, and the second were held on May 13 & 14, 2015. The public meetings were advertised in the News and Record, Carolina Peacemaker (minority publication), and Highpoint Enterprise. Press releases were distributed and electronic notices were sent to vendors listed in the District’s directory using Appendix D – Public Meeting Notices. The public hearing was transcribed by CaseWorks, a North Carolina-based court reporting service.

STAKEHOLDERS

MGT staff met with the District’s HUB Advisory Committee to during the project initiation to provide the committee with the project outline, schedule, and solicit their assistance to encourage the business community to participate in the anecdotal data collection activities.

MGT contacted the associations and organizations listed below to inform them of the study, request their assistance to distribute public meeting notices to their members or constituents, and participation in stakeholder interviews. In addition, MGT requested copies of membership or vendor lists from these organizations to create a nonduplicative database that was used to update gaps in the District’s Master Vendor Database. Organization and associations contacted were:

100 Black Men of Triad American Institute of Architects of

Piedmont American Institute of Architects of

Piedmont American Society of Professional Estimators American Subcontractors Association of

Carolinas Association of Building Contractors of the

Carolinas

Carolinas Asian American Chamber of Commerce

Carolinas Associated General Contractors Carolinas Virginia Minority Supplier

Development Council Council of American Minority Professionals Black Pages USA - (North Carolina Markets) Greater Women's Business Council (NC,

SC,GA) Greensboro Chamber of Commerce of

Greater Greensboro





Guilford County Purchasing Department Guilford County Schools - Purchasing

Department Guilford County Schools - Facilities Guilford Technical Community College -

Purchasing Guilford Technical Community College -

HUB Coordinator Hispanic Contractors Association Metrolina Minority Contractors Association

(MMCA) NAACP Alamance-Burlington Chapter NAACP Greensboro Branch National Association of Minority Architects

- N.C. Chapter National Association of Women Business

Owners (NAWBO) - Charlotte National Association of Women Business

Owners (NAWBO) - Raleigh National Association of Women in

Construction (NAWIC)-Piedmont Chapter NC Department of Transportation -

Contractual Services NC Indian Economic Development Initiative NC MWBE Coordinators' Network

North Carolina A&T State University - HUB Coordinator / Facilities

North Carolina A&T State University - HUB Coordinator / Purchasing

North Carolina Institute of Minority Economic Development

North Carolina Office for Historically Underutilized Businesses

North Carolina Plumbing and Heating Contractors

North Carolina Trucking Association North Carolina Society of Engineers Professional Construction Estimator’s of

America – Charlotte Professional Engineers of North Carolina Small Business Technology Development

Center (A&T Office) The Watchful Network United Minority Contractors Association of

NC (UMCNC) University of North Carolina-Greensboro

HUB Coordinator - Facilities University of North Carolina-Greensboro -

Purchasing Women’s Resource Center Greensboro

IN-DEPTH INTERVIEWS

The personal interviews gathered information regarding the firm’s primary line of business, ethnicity and education/training background of the owner, business history, size and gross revenues during selected calendar and/or fiscal years, and information about the firms’ experiences in attempting to do, and conducting business with, the District (both directly as a prime and/or as a subcontractor). The personal interviews—which are structured settings where an interviewer or facilitator uses an interview guide to solicit input from participants—provided more latitude for additional information gathering on issues that are unique to the respondents’ experiences. Interviews were conducted with M/WBEs and non-M/WBEs. The In-depth Interview Guide (Appendix H) included questions designed to establish a profile for each business. Additionally, MGT asked questions related to experiences with the M/WBE program, and instances of disparate treatment and/or discrimination experienced or perceived by the firm while attempting to do or conducting business with the District. BLWall Consulting conducted the M/WBE and non-M/WBE interviews. The interviewer made no attempt to prompt or guide responses from the participants, although follow-up questions were asked to obtain further clarification or information as necessary and appropriate.





At the conclusion of the interviews, each participant was asked to sign an affidavit attesting that their responses were given freely and was true and accurate reflections of their experience with the District.

2. DEMOGRAPHICS The demographic characteristics of participants in the collection of anecdotal information are described in the sections below.

SURVEY OF VENDORS DEMOGRAPHICS

During the months of October and November 2015, a randomly selected list of businesses from the Master Vendor Database were surveyed to solicit information about their firm and experiences during the study period which resulted in 497 completed surveys with owners and representatives. The Survey of Vendors allowed MGT to reach a broader segment of the business population in a more time-efficient and cost-effective manner. Table 7-1 provides the race, ethnicity, and gender of the respondents that participated in the survey.


SURVEY OF VENDORS DEMOGRAPHICS NUMBER OF RESPONDENTS


NUMBER OF RESPONDENTS

PERCENTAGE OF TOTAL

African American 97 19.5% Asian American 5 1.0% Hispanic American 11 2.2% Native American 8 1.6% Nonminority Female 115 22.9% Nonminority Male 257 46.7% Other/Don’t Know121 4 6.0% Total 497 100%

Source: Responses from survey conducted by Oppenheim Research, 2015.

The respondents were asked to identify their primary type of business as either Construction (C), Architecture and Engineering (A&E), Professional Services (PS), Other/Non-Professional Services (OS), and Goods and Supplies (GS). The distribution of the respondents are provided in Figure 7-A. The procurement category definitions are discussed in Chapter 4, Market Area and Utilization Analyses.

121 Participants did not associate their race/ethnicity/gender with the groups selected for the survey or chose not to provide their race/ethnicity/gender.





FIGURE 7-A GUILFORD COUNTY SCHOOLS

SURVEY OF VENDORS DEMOGRAPHICS BUSINESS INDUSTRY


As part of the survey several questions were asked to gather capacity information of the respondents such as number of employees, years in business, and largest contracts or subcontracts. Tables 7-2 through 7-4 and Figure 7-B provide the responses to these questions. Table 7-2 show that 50.1 percent of the firms surveyed have 0-10 employees excluding the owner which mean a majority of firms are small businesses which may have implications for the type and size of projects firms are willing to pursue. Minority and women businesses make up 31.40 percent of firms with 10 or less employees.

C: 19.3%

A&E: 3.4%

PS: 7.4%

OS: 37.8%

GS: 32.0%






SURVEY OF VENDORS DEMOGRAPHICS NUMBER OF EMPLOYEES


Figure 7-B details participant’s responses to the number of years they have been in their primary line of business. Firms that have been in business for 20 or more years represent 83.1 percent of the respondents. M/WBEs account for 37.4 percent.

FIGURE 7-B GUILFORD COUNTY SCHOOLS

SURVEY OF VENDORS DEMOGRAPHICS NUMBER OF YEARS IN BUSINESS


122 Participants did not associate their race/ethnicity/gender with the groups selected for the survey.

186

17 17 133

223

9 11 9 44 0 0 0 00

50

100

150

200

250

20+ Years 16-20 Years 11-15 Years 6-10 Years 0-5 years

M/WBE Non-M/WBE Other

RACE/ETHNICITY/GENDER 0-10 EMPLOYEES

11-20 EMPLOYEES

21-30 EMPLOYEES

31-40 EMPLOYEES

41+ EMPLOYEES

African American 14.1% 4.0% 0.4% 0.0% 0.8% Asian American 0.6% 0.0% 0.0% 0.0% 0.4% Hispanic American 1.2% 0.2% 0.4% 0.0% 0.4% Native American 0.8% 0.2% 0.2% 0.2% 0.2% Nonminority Female 14.7% 3.6% 0.6% 1.0% 3.2% Nonminority Male 18.3% 9.1% 3.6% 2.2% 18.1% Other122 0.4% 0.0% 0.2% 0.0% 0.2% TOTAL 50.1% 17.1% 5.4% 3.4% 23.3%





To gain a better understand of the respondents business we asked if they primarily bid, proposed, or provided quotes as a prime, subcontractor, or both. Survey respondents that indicated they bid as a prime only was 57.1 percent or 284 respondents. Survey respondents that indicated that they were primarily subcontractors2 total 19.5 percent or 97 respondents, and respondents that indicated they bid as both a prime and subcontractor was 23.3 percent or 116 respondents. As the survey continues this question guides the remaining responses on the respondent’s experiences working with the District as a prime, or as a subcontractor working with primes contracted with the District. Further results of responds are provided in Appendix F, Survey of Vendors Results. Table 7-3 shows the responses from primes when asked to indicate their largest contract awarded during the study period, regardless of who awarded the contract. The largest percentage of prime contracts awarded to M/WBEs, as well as nonminority males, are in the “Up to $50,000” range.


SURVEY OF VENDORS DEMOGRAPHICS LARGEST CONTRACT AWARDED- PRIME


Thirty-six percent of the survey participants indicated that they are subcontractors or subconsultants. This includes primes that also work as subcontractors or subconsultants. Detailed in Table 7-4 are the survey responses indicating the range of subcontracts awarded during the study period. For M/WBEs the largest subcontracts are in the “Up to $50,000” range while the nonminority males were awarded slight more subcontracts in the $400,001 - $500,000 range.


RACE/ETHNICITY/GENDER UP TO $50,000

$50,001 -

$100,000

$100,001 -

$200,000

$200,001 -

$300,000

$300,001 -

$400,000

$400,001 -

$500,000

$500,001 - $1

MILLION

> $1 MILLION

African American 11.9% 4.3% 3.7% 0.6% 0.0% 1.5% 0.6% 0.3% Asian American 0.6% 0.3% 1.5% 0.3% 0.0% 0.3% 0.0% 0.0% Hispanic American 0.3% 0.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Native American 0.3% 0.0% 0.0% 0.0% 0.3% 0.0% 0.0% 0.0% Nonminority Female 14.4% 2.8% 3.4% 2.1% 2.1% 2.1% 0.3% 0.0% Nonminority Male 11.6% 3.1% 5.6% 3.4% 2.5% 2.5% 1.2% 0.9% Other123 0.3% 0.0% 0.3% 0.3% 0.9% 0.6% 0.0% 0.0%






SURVEY OF VENDORS DEMOGRAPHICS LARGEST CONTRACT AWARDED - SUBCONTRACTOR


FOCUS GROUP DEMOGRAPHICS

MGT provided BLWall Consulting a randomly selected list of firms that have not been selected for other anecdotal activities from the District’s Master Vendor Database in order to invite those firms to participate in either a focus group for prime vendors or for subcontractors. BLWall Consulting attempted to contact 141 firms to participate and after making several attempts to contact firms, five firms participated in the two focus groups.

The focus group for primes included two construction firms, one architectural firm, and one services firm. The participating firms were non-MWBE large firms with more than 20 years in business and more than 30 employees. The one firm that attended the focus group for subcontractors was an African American-owned other services firm with less than 10 employees.

PUBLIC MEETINGS DEMOGRAPHICS

The public meetings in total had 44 attendees from varying industries, such as construction, trucking, supplies, engineering, nonprofit advocacy, information technology, financial services, and many state or local governmental representatives. Official testimonies were received and recorded from seven attendees.

PERSONAL INTERVIEW DEMOGRAPHICS

The personal interviews were conducted during the months of October through December 2015. To obtain interviewees, a random sample of firms not previously selected from the District’s Master Vendor Database that were not selected for other anecdotal activities were contacted. The interviews were conducted either at the firm owner’s office, at a location designated by the firm’s owner, or via telephone. The recruitment


RACE/ETHNICITY/GENDER UP TO $50,000

$50,001 -

$100,000

$100,001 -

$200,000

$200,001 -

$300,000

$300,001 -

$400,000

$400,001 -

$500,000

$500,001 - $1

MILLION

> $1 MILLION

African American 4.7% 1.5% 0.6% 0.9% 0.3% 0.3% 0.0% 0.0% Asian American 0.0% 0.0% 0.6% 0.3% 0.0% 0.0% 0.0% 0.0% Hispanic American 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Native American 0.0% 0.0% 0.0% 0.0% 0.3% 0.0% 0.0% 0.0% Nonminority Female 6.5% 0.3% 0.9% 0.6% 0.6% 0.6% 0.6% 0.0% Nonminority Male 3.1% 1.2% 1.2% 2.1% 0.6% 3.3% 0.3% 0.3% Other124 0.6% 0.0% 0.3% 0.6% 0.6% 0.0% 0.0% 0.3%





efforts of BLWall Consulting resulted in 42 firms that were interviewed out of the 189 firms provided in the sample.

Of the 42 firms that were interviewed, the ethnic and gender composition of the firms ownership were 16 African Americans, two Hispanic Americans, six nonminority women, and 18 nonminority males.

There were no Native American- nor Asian American-owned firms interviewed.

The industries represented included, but were not limited to, general contracting, specialty trade contractors, promotional items, architectural and engineering, software development consulting, auto parts, security services, landscaping, communications, etc.

3. BARRIERS TO DOING BUSINESS WITH GUILFORD COUNTY SCHOOL DISTRICT

MGT documented participant responses concerning barriers faced in the procurement process and factors that frequently prevented businesses from winning or being awarded contracts. In the normal course of business, entrepreneurs may face certain barriers when establishing and operating a business enterprise and several factors may prevent a business from being selected for a contract or purchase order. This section summarizes the anecdotal responses from the survey of vendors, focus groups, public meetings, and interviews where MGT identified trends in barriers. Detailed results for all respondents and statistically significant differences in M/WBE responses to questions are located in Appendix F – Survey of Vendors Results.

PROCUREMENT PROCESS

In the survey of vendors, 25.8 percent of the M/WBE respondents indicated that competing with large companies is a barrier to doing business with the District. Additional key barriers for M/WBE firms included:

Slow or nonpayment – 16.5 percent.

Limited time given to prepare bid package or quote – 12.3 percent.

Insurance requirements – 10.6 percent.

Contracts too large – 10.2 percent

ANECDOTAL RESPONSES

Focus group, interview, and public meeting anecdotal comments about barriers doing business or attempting to do business with the District or with primes that bid or are contracted with the District are provided below:

An African American owner of a landscaping firm stated that competing with large firms creates a barrier for his firm to compete when he bids as a prime because larger firms have greater access to





capital. When bidding as a subcontractor, primes solicit price quotes but do not contract with his firm.

A nonminority-owned electrical firm owner stated that competing with large firms is a barrier for his company. In addition, he stated that there are not enough M/WBE suppliers with competitive pricing for his firm to meet the M/WBE goals.

A nonminority general contracting firm owner stated that the District’s use of Construction Management at Risk (CM@R) is a barrier for his firm because it reduces the number of projects that his firm normally bids.

A nonminority architecture and engineering firm owner stated that the District tends to select large firms over small firms.

An African American owner of a general contracting firm stated that the lack of notice of purchasing and contracting opportunities creates a barrier to his firm bidding on District projects.

A nonminority woman-owned utility subcontractor stated that prime bidders solicit quotes from her firm just to “meet the good faith effort requirements” but the prime already selected their subcontractors.

The owner of an African American construction management firm stated that prequalification requirements, bonding (both bid and performance/payment), financing, and the selection progress required by the District provide barriers for his firm to do business with the District.

An African American owner of a specialty items firm stated that he has bid on District projects repeatedly but the District selects the same firm each time.

4. STAKEHOLDER INTERVIEWS In addition to receiving anecdotal comments from the business owners, MGT conducted interviews with eight area trade associations and business associations to get their perceptions on the impact of the M/WBE program to its members. During the interview, stakeholders were asked to provide their perceptions on the barriers their members faced doing business or attempting to do business with the District or the District’s prime, M/WBE Program improvement recommendations, and any other comments they felt were relevant to this disparity study.

Each of the stakeholders provide capacity building, advocacy, and/or business development programs to its members or any business owner that has a need for their services. A few of the stakeholders assist M/WBE firms with certification,

When asked if the stakeholders had a working relationship with the District to assist M/WBE firms, many stated they did not but saw the benefit to do so. Overwhelmingly, the stakeholders advocated for an M/WBE coordinator for the District to advocate for M/WBE participation with the District. Stakeholders also





recognized the necessity to expand M/WBE business to the private sector realizing that that will help with business capacity.

A few of the recommendations suggested by the stakeholders include:

Help business understand that contract requirements are in place are not set up as hurdles to do business but to protect tax dollars.

Focus on local business growth and development.

How to do business workshops for all procurement categories.

Improve communication with M/WBE community about potential contract opportunities.

Provide feedback on opportunities not won so stakeholders can provide technical assistance in the areas M/WBE firms had deficiencies.

5. ACCESS TO CAPITAL AND BONDING Survey respondents were asked if they applied for a commercial loan between July 1, 2010, and June 30, 2014, and whether their loan was approved or denied. If their loan was denied, a follow up question asked what they believed was the basis of their denial. Of the 94 (18.9% of the total) respondents that applied for a commercial loan, 36.2 percent were M/WBEs. The denial rate for M/WBEs was 4.7 percent and the primary response to why firms believed they were denied was due to insufficient business history.

The requirement to provide bonding for District projects was asked in survey of vendors. The survey of vendor responses in Table 7-5 reflect that 18.1 percent of the respondents are required to bond projects. Of that 18.1 percent, the average aggregate bonding limit is between $100,000 to $250,000 and $250,000 to $500,000.

TABLE 7-5 GUILFORD COUNTY SCHOOL DISTRICT

AGGREGATE BONDING LIMIT



RACE/ETHNICITY/GENDER BELOW

$100,000

$100,001 -

$250,000

$250,001 -

$500,000

$500,001 - $1

MILLION

$1,000,001 - $1.5

MILLION

$1,500,001 - $3

MILLION

$3,000,001 - $5

MILLION

> $5 MILLION

African American 0.6% 0.4% 0.6% 1.4% 0.2% 0.2% 0.2% 0.4% Asian American 0.0% 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% Hispanic American 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% 0.0% Native American 0.0% 0.2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Nonminority Female 0.4% 0.4% 0.6% 0.6% 0.2% 0.8% 0.0% 0.2% Nonminority Male 0.2% 0.4% 0.4% 1.6% 0.8% 0.6% 0.4% 3.2% Other125 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Total 1.20% 1.40% 1.80% 3.80% 1.20% 1.60% 0.60% 3.80%





6. DISPARATE TREATMENT AND DISCRIMINATION

Anecdotal evidence must determine if M/WBE firms experience disparate treatment or are discriminated against by the agency, primes contracted by an agency, or in the private sector marketplace. Therefore, participants were asked if they experienced discriminatory or disparate behavior by the District, its primes, or in the private sector during the study period. During the personal interviews, 12 of the 42 businesses felt as though were discriminated against by the District, their primes, or in the private sector.

ANECDOTAL RESPONSES

An African American owner of a landscaping firm stated that he feels he is being discriminated against by primes who solicit quotes from him to meet M/WBE requirements than passing his price to another subcontractor to match his price.

An African American owner of a construction firm stated that he felt discriminated against when the prime firm he was contracted with “purposefully” delayed his payments.

An African American owner of a professional services firm stated that she felt that the District discriminated against her by denying her firm the opportunity to bid on a contract they once had because the District received one complaint from a client.

An African American owner of an architecture firm stated that she felt a prime consultant discriminated against her firm by not allowing her to review and confirm the scope of work submitted for her firm. When the project began the prime wanted her firm to perform a scope that was different than what was communicated to the District. Her firm was treated disrespectfully as a result of the conflict in scope.

Table 7-6 illustrates survey of vendor respondents’ experiences of discriminatory behavior from the District, a prime contracted by the District, or while conducting business in the private sector.





TABLE 7-6 GUILFORD COUNTY SCHOOL DISTRICT

DISCRIMINATION BY

DISTRICT BY

PRIMES PRIVATE SECTOR

M/WBE (Prime) 2.5% Non-M/WBE (Prime) 1.9% M/WBE (Subcontractor) 3.0% Non-M/WBE(Subcontractor) 1.2% All M/WBE Firms 10.6% All non-M/WBE Firms 0.8%

Source: Responses from telephone survey conducted by Oppenheim Research, 2014.

With respect to disparate treatment, M/WBE anecdotal respondents reported:

That an informal network precluded their firms from obtaining work in the private sector – 27.5 percent.

Seldom or never being solicited when there were no M/WBE goals – 54.2 percent.

These findings are consistent with the low minority and women business participation identified in Chapter 6, Private Sector Analyses.

7. SUGGESTED REMEDIES FROM ANECDOTAL PARTICIPANTS

While collecting anecdotal data, participants provided their ideas and recommendations for improving the procurement process and increasing M/WBE participation. A few recurring ideas and/or suggested remedies provided by participants are:

Establish M/WBE program compliance – follow up with M/WBE firms to confirm they are they being paid.

Enforce the Good Faith Efforts requirements.

Improve the payment process so that primes are paid within 30 days.

Provide M/WBEs with a list of primes bidding or prequalifying for projects, and provide primes with an updated list of M/WBEs.

Establish a process to use more local businesses.

Improve the methods and frequency of communicating contracting opportunities.

Notify subcontractors/subconsultants that were submitted/proposed with the successful bidder/proposer.

Establish or reevaluate prequalification criteria to include scoring for M/WBE partners.





Establish a vendor rotation for informal bids for frequently procured services and products.

Require a least one M/WBE firm is solicited for informal procurements, particularly at the departmental levels.

Extend the time period to submit bids, quotes, and proposals.

Transparency about the procurement process and open access to any firm interested in learning how to do business with the District.

8. CONCLUSION MGT collected anecdotal information from focus groups, surveys, public meetings, and personal interviews. These activities resulted in 551 business owners or representatives participating in this disparity study process. In comparison, the Ninth Circuit Court of Appeals accepted anecdotal information from 57 interviewees in Coral Construction.

Anecdotal data collection was a challenge due to lack of businesses interested in working with the District or on District projects. The recruiting efforts for each of the anecdotal activities required more time than usual and more attempts to contact firms. The firms that participated in the various anecdotal activities were on average small to mid-size firms and the majority of their work is conducted in the private sector marketplace or with other governmental entities.

As indicated at the beginning of this chapter, MGT sought to answer the research question: Is there qualitative/anecdotal evidence of disparate treatment of M/WBE subcontractors by prime contractors? Based on the anecdotal information gathered, there is a lack of clear cut evidence of disparate treatment by the District directly. Prime firms expressed unhappiness with the procurement process over whether they felt discriminated against by the District. The same cannot be said for M/WBE firms who attempt to do work with primes bidding or work on District projects. M/WBE firms expressed frustration about the use of their firm to meet M/WBE requirements with no “real” intent of primes to contract with their firm.


8 | F INDINGS AND RECOMMENDATIONS



1. INTRODUCTION In August 2014, MGT of America, Inc. (MGT), was retained to conduct a Disparity Study for the Guilford County Schools (the “District”) to provide current data on District programs. In this chapter, MGT provides findings for the District on minority and women business enterprise (M/WBE) utilization and availability. This study consisted of fact-finding to analyze District procurement trends and practices between July 1, 2009, and June 30, 2014; to evaluate the impact of race- and gender-neutral remedial efforts; and to evaluate various options for future program development.

The results of this study and conclusions drawn are presented in detail in Chapters 3 through 7 of this report. This chapter will summarize the evidence on the central research question: Is there factual predicate evidence to support a race- and gender-conscious M/WBE program for the District?

2. FINDINGS

FINDING A: RECENT M/WBE POLICY North Carolina State law encourages the use of good faith efforts by all state universities and public entities to solicit and utilize minority firms to reach a 10 percent participation level on public sector construction projects.126 In keeping with this state statute, the District has had an M/WBE policy for some time.

The District established a 10 percent M/WBE goal in December 1994, which was reaffirmed in 1996. In March 2007, the District adopted a 12.46 percent M/WBE goal for construction, based on a 2003 State of North Carolina Disparity Study. The District goods and services goal remained at 10.0 percent.

The District recognizes State of North Carolina Statewide Uniform Certification (SWUC) certification. Both the District and the State of North Carolina include the disabled and disadvantaged in their definition of M/WBE.

FINDING B: M/WBE SUBCONTRACTOR UTILIZATION AND DISPARITY FOR CONSTRUCTION The dollar value of M/WBE subcontractor utilization for construction on District projects over the study period within the relevant market (the central region of North Carolina) was as follows:

MBEs were awarded construction subcontracts totaling $5.51 million, 17.72 percent of the total construction subcontract dollars; WBEs were awarded $12.55 million in construction subcontracts,

126 North Carolina Statutes § 143-128.3. - Minority Business Participation Administration.


1. Introduction

2. Findings

3. Commendations and Recommendations

4. Conclusion





40.32 percent of the total construction subcontract dollars (Table 8-1). There was disparity for all M/WBE groups except Native Americans and Nonminority Women.

TABLE 8-1 UTLIZATION OF FIRMS ANALYSIS, SUB LEVEL



CONSTRUCTION SUBCONTRACTORS

($) African American Firms $4,054,596 Asian American Firms $0 Hispanic American Firms $1,012,617 Native American Firms $452,767 TOTAL MINORITY FIRMS $5,519,980 Nonminority Female Firms $12,557,244 TOTAL M/WBE FIRMS $18,077,224 TOTAL NON-M/WBE FIRMS $13,066,496 TOTAL FIRMS $31,143,720


CONSTRUCTION SUBCONTRACTORS

(%) African American Firms 13.02% Asian American Firms 0.00% Hispanic American Firms 3.25% Native American Firms 1.45% TOTAL MINORITY FIRMS 17.72% Nonminority Female Firms 40.32% TOTAL M/WBE FIRMS 58.04% TOTAL NON-M/WBE FIRMS 41.96% TOTAL FIRMS 100.00%

Source: MGT developed a Master Payment Database based on dollars expended by Guilford County Schools between July 1, 2009, and June 30, 2014.

FINDING C: M/WBE PRIME UTILIZATION The dollar value of M/WBE prime contractor utilization on District projects over the study period within the relevant market was as follows (Table 8-2):

MBEs received payments on construction prime contracts totaling $7.83 million, 3.10 percent of construction prime contract dollars; WBEs were paid $7.24 million on construction prime contracts, 2.86 percent of construction prime contract dollars. There was disparity for all M/WBE groups.

MBEs received payments on A&E prime contracts totaling $2.64 million, 14.96 percent of A&E prime contract dollars; WBEs were paid $1.10 million in A&E prime contracts, 6.26 percent of A&E prime contract dollars. There was disparity for all M/WBE groups except Native Americans, for whom there was no availability.





MBEs received payments on professional services prime contracts totaling $1.85 million, 7.77 percent of professional services prime contract dollars; WBEs were paid $3.41 million in professional services prime contracts, 14.28 percent of professional services prime contract dollars. There was disparity for all M/WBE groups except Native Americans, for whom there was no availability.

MBEs received payments on other services prime contracts totaling $4.81million, 11.77 percent of other services prime contract dollars; WBEs were paid $3.05 million on other services prime contract contracts, 7.46 percent of other services prime contract dollars. There was disparity for all M/WBE groups.

MBEs received payments on goods prime contracts totaling $4.25 million, 2.54 percent of goods prime contract dollars; WBEs were paid $15.16 million on goods prime contracts, 9.05 percent of goods prime contract dollars. There was disparity for all M/WBE groups.

TABLE 8-2 UTLIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION CONSTRUCTION, ARCHITECTURE & ENGINEERING, PROFESSIONAL SERVICES,

OTHERS SERVICES, GOODS & SUPPLIES


CONSTRUCTION ARCHITECTURE &

ENGINEERING PROFESSIONAL

SERVICES OTHER

SERVICES GOODS AND

SUPPLIES ($) ($) ($) ($) ($)

African American Firms $7,594,919 $1,950,715 $1,690,892 $4,477,439 $4,069,175 Asian American Firms $117,950 $696,918 $112,300 $4,750 $181,364 Hispanic American Firms $125,240 $0 $52,480 $337,126 $1,804 Native American Firms $0 $0 $0 $150 $0 TOTAL MINORITY FIRMS $7,838,109 $2,647,633 $1,855,672 $4,819,466 $4,252,343 Nonminority Female Firms $7,241,880 $1,108,479 $3,411,144 $3,055,135 $15,162,540 TOTAL M/WBE FIRMS $15,079,989 $3,756,112 $5,266,816 $7,874,601 $19,414,883 TOTAL NON-M/WBE FIRMS $238,090,530 $13,941,270 $18,621,532 $33,087,117 $148,215,093 TOTAL FIRMS $253,170,520 $17,697,382 $23,888,348 $40,961,718 $167,629,976


CONSTRUCTION ARCHITECTURE &

ENGINEERING PROFESSIONAL

SERVICES OTHER

SERVICES GOODS AND

SUPPLIES (%) (%) (%) (%) (%)

African American Firms 3.00% 11.02% 7.08% 10.93% 2.43% Asian American Firms 0.05% 3.94% 0.47% 0.01% 0.11% Hispanic American Firms 0.05% 0.00% 0.22% 0.82% 0.00% Native American Firms 0.00% 0.00% 0.00% 0.00% 0.00% TOTAL MINORITY FIRMS 3.10% 14.96% 7.77% 11.77% 2.54% Nonminority Female Firms 2.86% 6.26% 14.28% 7.46% 9.05% TOTAL M/WBE FIRMS 5.96% 21.22% 22.05% 19.22% 11.58% TOTAL NON-M/WBE FIRMS 94.04% 78.78% 77.95% 80.78% 88.42% TOTAL FIRMS 100.00% 100.00% 100.00% 100.00% 100.00%






FINDING D: PRIME M/WBE UILIZATION ACROSS ALL PROCUREMENT CATEGORIES Across all procurement categories MBEs received payments on prime contracts totaling $21.41 million, 4.25 percent of total prime contract dollars; WBEs were paid $29.97 million on total prime contracts, 5.96 percent of total prime contract dollars, for a total M/WBE percentage of 10.21 percent of District prime spending (Table 8-3). MBE subcontractor spending in construction was 1.10 percent of total District spending across all categories; WBE subcontractor spending in construction was 2.49 percent of total District spending across all business categories.

TABLE 8-3 UTLIZATION OF FIRMS ANALYSIS, PRIME LEVEL

DISTRIBUTION OF DOLLARS BY BUSINESS OWNERSHIP CLASSIFICATION ALL PROCUREMENT CATEGORIES COMBINED

BUSINESS OWNERSHIP CLASSIFICATION ALL PROCUREMENT

CATEGORIES ($)

African American Firms $19,783,140 Asian American Firms $1,113,282 Hispanic American Firms $516,650 Native American Firms $150 TOTAL MINORITY FIRMS $21,413,223 Nonminority Female Firms $29,979,178 TOTAL M/WBE FIRMS $51,392,401 TOTAL NON-M/WBE FIRMS $451,955,542 TOTAL FIRMS $503,347,944


(%) African American Firms 3.93% Asian American Firms 0.22% Hispanic American Firms 0.10% Native American Firms 0.00% TOTAL MINORITY FIRMS 4.25% Nonminority Female Firms 5.96% TOTAL M/WBE FIRMS 10.21% TOTAL NON-M/WBE FIRMS 89.79% TOTAL FIRMS 100.00%


FINDING E: REGRESSION ANALYSIS In a statistical analysis of survey data in the Greensboro area that controlled for the effects of variables related to company capacity variables (such as, company capacity, owner level of education, and experience), M/WBE status had a negative effect on 2014 company earnings of African American-, Hispanic American-, and Nonminority Women-owned firms.





FINDING F: DISPARITIES IN SURVEY OF BUSINESS OWNERS DATA In 120 disparity ratios for six procurement categories, for both the state of North Carolina and the Greensboro MSA, only two instances of over-utilization were found for M/WBE groups.

FINDING G: PRIVATE SECTOR COMMERCIAL CONSTRUCTION M/WBE utilization in private sector commercial construction in the Greensboro Metropolitan Statistical Area (MSA) was very low, as measured by data from building permits. From FY 2010 through FY 2014, MBE prime contractors won 3.85 percent of prime permits and WBEs received 3.21 percent of prime permits. MBE subcontractors were issued 2.42 percent of all subcontracting permits and WBEs 2.09 percent of subcontracting permits.

FINDING H: DISPARITIES IN SELF-EMPLOYMENT AND REVENUE EARNINGS Econometric analysis using data from 2014 American Community Survey data for the Greensboro MSA found statistically significant disparities for entry into self-employment for African Americans, Hispanic Americans and nonminority women. There were statistically significant disparities in earnings from self-employment for African Americans, Hispanic Americans and Nonminority Women.

FINDING I: ACCESS TO CAPITAL An econometric analysis of data in the most recent National Survey of Small Business Finance found a statistically significant positive relationship between the probability of loan denial and African American ownership. These results are consistent with data in a 2015 local survey. About 6.3 percent of non-M/WBE loan applicants reported being denied commercial bank loans, as compared to 47.3 percent of African American applicants.

FINDING J: ANECDOTAL COMMENTS Among the M/WBEs who responded to questions about barriers to doing business, the biggest concern for both primes and subcontractors was competing with large firms (13.1 percent of M/WBE primes). Other issues noted by M/WBE respondents included:

PRIMES:

Slow payment – 9.7 percent.

Selection process – 5.1%.

SUBCONTRACTORS

Competing with large firms– 12.7 percent.

With respect to disparate treatment M/WBE respondents in the survey reported:

Discriminatory experiences in dealing with prime contractor – 3.0 percent.

Selected to satisfy good faith efforts requirements and then dropped – 1.7 percent.





With respect to the private sector M/WBE respondents in the survey reported:

Seldom or never solicited for private sector projects – 54.2 percent.

An informal network precluded their firms from obtaining work in the private sector – 27.5 percent.

Discriminatory experiences in dealing with the private sector – 10.6 percent.

It is worth noting that the anecdotal private sector findings are consistent with the statistical results in Findings F, G, and H above.

3. COMMENDATIONS AND RECOMMENDATIONS Most of the following commendations and recommendations are based on multiple findings and do not necessarily tie to one finding. These recommendations also reflect in part that a school district is involved. School districts, while they have large construction programs, do not have the same mission of business development as cities, counties and states.

RECOMMENDATION A: STAFFING In order to increase its efforts on M/WBE inclusion the District will need to fill the existing staff position for a HUB Coordinator. The District needs staff to manage and implement study recommendations and provide oversight and management of the program that results from the study. The HUB Coordinator should have the responsibility to provide program oversight and compliance for all District spending.

RECOMMENDATION B: SUBCONTRACTOR PROJECT GOALS In response to the primary research question this study provides evidence to support an M/WBE program for the District. This conclusion is based primarily on statistical disparities in current M/WBE utilization; regression analysis of race, ethnicity, gender and capacity variables; evidence of discrimination in entry into and earnings from self-employment; very low M/WBE utilization in the building permit evidence; credit disparities; and some anecdotal evidence of disparate treatment. The District should tailor its M/WBE participation policy to remedy these disparities. The core theme should be that prime contractors should document their outreach efforts and the reasons why they may have rejected qualified M/WBEs that were the low-bidding subcontractors.

RECOMMENDATION C: NARROW TAILORED M/WBE PROGRAM Developments in court cases involving federal disadvantaged business enterprise (DBE) programs provide important insight into the design of local M/WBE programs. Federal courts have consistently found DBE regulations in 49 CFR 26 to be narrowly tailored.127 The federal DBE program has the features in Table 8-4

127 Adarand v. Slater, 228 F.3d 1147 (10th Cir. 2000), Gross Seed. v. State of Nebraska, 345 F.3d 968 (8th Cir. 2003); cert denied, 158 L.Ed. 2d 729 (2004).





that contribute to this characterization as a narrowly tailored remedial procurement preference program. The District should adopt these features in any new M/WBE program.

TABLE 8-4 NARROWLY TAILORED M/WBE PROGRAM FEATURES

NARROWLY TAILORED GOAL-SETTING FEATURES DBE Regulations 1. The District should not use M/WBE quotas. 49 CFR 26(43)(a)

2. The District should use race- or gender-conscious set-asides only in extreme cases. 49 CFR 26(43)(b)

3. The District should meet the maximum amount of M/WBE goals through race-neutral means. 49 CFR 26(51)(a)

Source: Suggested features in a proposed narrowly tailored M/WBE program based on USDOT 49 CFR 26.

RECOMMENDATION D: ASPIRATIONAL M/WBE GOALS The District should be commended for its aspirational goals and the revisions of its aspirational goals. The District should consider establishing annual aspirational MBE and WBE goals by business category. Proposed goals are listed in Table 8-5. The proposed goals are based on a weighted average of M/WBE utilization and availability. These aspirational goals should not be applied rigidly to every individual District projects. Instead MBE and WBE goals should vary from project to project. Aspirational goals should be based on relative MBE and WBE availability. The primary means for achieving these aspirational goals should be a SBE program, outreach, and adjustments in District procurement policy in addition to M/WBE project goals.

TABLE 8-5 PROPOSED MBE AND WBE GOALS

MBE GOAL WBE GOAL

Construction 6% 8% Architecture & Engineering 17% 10% Professional Services 9% 15% Other Services 13% 8% Goods 3% 9%

Note: Construction goal includes prime and subcontract dollars.

COMMENDATION AND RECOMMENDATION E: DATA MANAGEMENT The District should be commended for tracking M/WBE utilization; in particular, tracking awards to certified subcontractors.

However, the District could improve the collection and reporting of the data along the following lines:

Collection of subcontractor data for areas other than construction.

Maintain race, ethnicity, gender for non-certified firms.

Have a vendor registration database for outreach and interest.





COMMENDATION F: OUTREACH The District should be commended for its outreach activities such as holding pre-bids conferences, advertising opportunities, past hiring of a HUB coordinator, generating commodity lists for District users to identify M/WBE vendors, holding workshops and one-to-one meetings with M/WBEs, links to state-certified vendors on web site, and working with HUB contractors organizations.

COMMENDATION AND RECOMMENDATION G: DISTRICT WEBSITE The District should be commended for having bid opportunities, vendor applications, vendor information, the purchasing policy manual, HUB Directory, HUB report, disparity study information and MWBE Administrative Policy on its website. A survey of agencies has found the following information on their M/WBE Web sites, which serves as a source of additional ideas for the District: bid tabulations, links to management and technical assistance providers, information on the loan programs, M/WBE newsletters, annual M/WBE program reports, and 90-day forecasts of business opportunities.

RECOMMENDATION H: SBE PROGRAM The District should consider adding a SBE program, including SBE project goals and SBE set-asides. SBE programs have the advantage that they are generally not subject to constitutional challenge. Combining SBE programs and MBE programs has become common across agencies that maintain M/WBE programs. Further ideas on SBE programs are discussed in Selected Practices below.

RECOMMENDATION I: VENDOR ROTATION The District should consider the selective use of vendor rotation to expand utilization of underutilized M/WBE groups. Some political jurisdictions use vendor rotation arrangements to limit habitual repetitive purchases from incumbent majority firms and to ensure that M/WBEs have an opportunity to bid along with majority firms. Generally, a diverse team of firms are prequalified for work and then teams alternate undertaking projects.

4. CONCLUSION This study provides factual predicate evidence for continuing the District M/WBE program. This evidence is based on quantitative and qualitative data from public and private sources. While the District has made significant progress in M/WBE inclusion, any future efforts must be narrowly tailored to rectify the issues identified in this report.

SELECTED PRACTICES OF OTHER M/WBE PROGRAMS

As MGT reviews procurement policies and remedial programs of federal, state and local government M/W/SBE programs we are able to identify policies that promote local small business development. This research affords us the opportunity to create an extensive library of practices that agencies use to include minority, women, small, and disadvantaged businesses in their procurement process. Contained herein is a menu of policies that have worked in some localities, but may not have been effective in others. Some





policies have been discontinued for budgetary reasons. In many instances, it is difficult to determine whether a particular policy is directly responsible for the success of a program.

Such assistance may include direct subsidies to businesses, funds for management and technical assistance to small and new entrepreneurs, mentor-protégé programs, and bonding assistance, as well as collaboration with and support for organizations that provide management and technical assistance to businesses.

A substantial number of these agencies also have procurement preference programs for small business. Some M/W/SBE programs are nominal and some seem to have substantial resources devoted to M/W/SBE program design and implementation. In general, the demand by some courts and some legislation for race-neutral business development policies has increased the resources devoted to race-neutral M/WBE programs.

Provided below are the selected practices we have taken into consideration for Guilford County Schools. There is a focus on M/W/SBE programs for schools, with other types of agencies included as well.

M/WBE Program Data Management

M/WBE Goals

Small Business Aspirational Goals

Small Business Program for Subcontracts

Small Business Prime Contracting Programs

M/W/SBE Inclusion in Financial and Professional Services

HUBZones

DBE Programs

Two Tier Certification Management and Technical Assistance Programs

Financial Assistance

Management and Technical Assistance

M/WBE PROGRAM DATA MANAGEMENT

It is imperative an agency closely monitor the utilization of all businesses by race, ethnicity, and gender over time to determine program effectiveness. Many agencies issues M/WBE annual utilization reports. Some important additional elements of program data management employed by other agencies include:

Separate Reporting of M/WBE Prime Contractor and Subcontractor Utilization. Orange County, FL; City of Charlotte, NC; Port Authority and New York and New Jersey.

Tracking M/WBE and Non-M/WBE Subcontractor Utilization. City of Charlotte, NC; Portsmouth Public Schools.

Tracking M/WBE Utilization in the SBE Program. Los Angeles Unified School District, City of Charlotte, NC; Port Authority and New York and New Jersey, Phoenix, AZ.





M/WBE GOALS

M/WBE ASPIRATIONAL GOALS Portsmouth Public Schools aspirational M/WBE goals are (Table 8-6):

TABLE 8-6 PORTSMOUTH PUBLIC SCHOOLS

PROPOSED M/WBE ASPIRATIONAL GOALS BY PROCUREMENT CATEGORY

Procurement Category Aspirational Goal Construction Prime Contractors 5%

Construction Subcontractors 9%* Professional Services 22%

Other Services 19% Goods 15%

Source: Portsmouth Public Schools Procurement Disparity Study, January 2011

Chicago Public Schools aspirational M/WBE goals are 30 percent MBE and 15 percent WBE for construction and goods and services. 128

Houston Independent School District aspirational M/WBE goals are:

Purchasing - 20% for contracts over $50,000

Professional Services - 25% for contracts over $50,000

Construction - 20% for contracts over $50,000129

Cleveland Public Schools Community Inclusion Plan has Diversity Business Enterprise (DBE, their name for are M/WBEs.) participation goals of:

15% in service contracts,

20% in contracts for goods and supplies and

30% in contracts for construction.130

Charlotte Mecklenburg Schools has the following MBE/WBE/SBE aspirational goals in Table 8-7.

128 http://www.cps.edu/About_CPS/Departments/Pages/BusinessDiversity.aspx. 129 http://www.houstonisd.org/Page/33109. 130 http://net.cmsdnet.net/newschools/CommunityInclusionPlanDescription.pdf





TABLE 8-7 2010 M/W/SBE ASPIRATIONAL GOALS

CHARLOTTE-MECKLENBURG SCHOOLS 131 MBE GOAL WBE GOAL SBE GOAL M/W/SBE GOAL

Construction 10% 6% 5% 21%

Architecture & Engineering 4% 7% 5% 16% Contracted Services (other than Construction)

5% 4% 5% 14%

Goods 3% 3% 5% 11% Source: Minority, Women, and Small Business Enterprise Program, Board of Education Management Oversight Report, August 2014, Charlotte-Mecklenburg Schools.

M/WBE PROJECT GOAL SETTING North Carolina Department of Transportation (NCDOT). The NCDOT regulations emphasize that goals should be set on projects “determined appropriate by the Department [of Transportation].”132 Individual goals are set based on a project’s geographic location, characteristics of the project, the percentage of that type of work that is typically performed by M/WBEs, the areas in which M/WBEs are known to provide services, and the goals set by the North Carolina General Assembly.133 The NCDOT M/WBE regulations specify (although they do not limit to) particular areas for M/WBE goals: clearing and grubbing, hauling and trucking, storm drainage, concrete and masonry construction, guardrail, landscaping, erosion control, reinforcing steel, utility construction, and pavement marking.

The NCDOT goal setting process begins with an engineering estimate of the project to determine what items might reasonably be subcontracted out. Next estimates of the percentage of work that could be potentially performed by DBEs and M/WBEs are developed.134 These estimates are confidential and made available only to the Estimator (and staff), the Provisions Engineer in the Proposals and Contracts Section (and staff), and members of the DBE/M/WBE Committee at the DBE/M/WBE Committee meetings.

Next NCDOT looks at whether there are M/WBEs available based on the NCDOT DBE/M/WBE directory and the location of the project. The NCDOT Directory is a searchable database that classifies firms by location, prime contractor/subcontractor status and six-digit work type.135 The Goal Setting Committee is assisted in this process by Equal Employment Opportunity (EEO) Compliance staff in the Office of Civil Rights. Prime contractors then submit documentation of good faith efforts to achieve the individual project goal. A statement of how they will make efforts to achieve the goal satisfies the good faith effort requirements.

The NCDOT Goal Setting Committee (in collaboration with the EEO Compliance staff) seeks to set goals relative to where there is interest, availability and capacity, beyond mere looking at the certification lists. NCDOT relies on the EEO Compliance staff to provide input on whether existing businesses are fully

131 http://www.cms.k12.nc.us/boe/Management%20Oversight%20Reports%20Schedule/Archive/MWSBE%20Pres.pdf 132 19A NCAC 02D.1108(a). 133 19A NCAC 02D.1108(a). 134 NCDOT, Division of Highways, Roadway Design and Design Services Unit, Policy and Procedure Manual, Chapter 10, at 4. 135 http://apps.dot.state.nc.us/constructionunit/directory/.





occupied. However, if EEO Compliance says M/WBEs are not fully occupied, but prime contractors submit evidence that M/WBEs are fully occupied (for example, with invoices), then NCDOT accepts those explanations. As part of goal setting NCDOT regulations provide that:

A documented excessive subcontractor bid constitutes a basis for not subcontracting with an M/WBE.

A documented record of poor experience constitutes a basis for not subcontracting with an M/WBE.136

In addition, a review of NCDOT DBE and M/WBE goals has been a regular topic at the Associated General Contractors (AGC)-DOT Joint Cooperative Committee meetings.137

Oregon DOT. Oregon DOT uses both "hard goals" and "aspirational targets" for DBE project goal setting. Aspirational targets do not have numerical percentages and are not subject to good faith efforts requirements or risk of rejected bids. “Hard goals” have generally only been applied in ODOT regions with identified DBE availability and disparity. Aspirational DBE targets applied through the state. ODOT staff reported that primes took the aspirational goals seriously, even though there was often no numerical percentage associated with the aspirational goal written in the bid documents.

GOOD FAITH EFFORTS Portsmouth Public Schools, Virginia. The Portsmouth Public Schools require bidders to meet a combination of good faith efforts that equal a numerical value established by the program. Each good faith effort option is assigned a value weighted by the greatest result of possible success of the effort.

SMALL BUSINESS ASPIRATIONAL GOALS

Commitment from the top leadership is a core element of most summaries of policies in other M/W/SBE programs.138 One starting point for such commitment is setting overall aspirational goals separate from project goals. Some agencies use fairly straightforward methods to calculate aspirational goals and other agencies use more involved methodologies.

Los Angeles Unified School District—25 percent SBE goal (since 2003)

136 The last two elements are adopted by the North Carolina DOT. 19A NCAC 02D.1110(7). 137 AGC-DOT Joint Cooperative Committee Meeting Minutes, February 2001 through August 2003. 138 See, e.g., National Women’s Business Council, 1999 NWBC Best Practices Guide: Contracting with Women (July 1999); R. Auskalnis, C. Ketchum and C. Carter, Purchasing From Minority Business Enterprise: Best Practices, Center For Strategic Supply Research 1995).





SMALL BUSINESS PROGRAM FOR SUBCONTRACTS

SMALL BUSINESS PROJECT GOALS City of Charlotte, North Carolina. The City of Charlotte has a comprehensive SBE program including SBE set asides and business assistance.139 In addition, the City of Charlotte sets department goals for SBE utilization, sets SBE goals on formal and informal contracts and makes SBE utilization part of department performance review utilization numbers. The City has a waiver provisions for bidders, but has rejected bids for bidder noncompliance with the SBE program. Charlotte achieved 28.9 percent M/WBE subcontractor utilization in construction and 33.1 percent M/WBE subcontractor utilization in A&E through small business subcontracting goals.140

MANDATORY SUBCONTRACTING As part of their SBE subcontracting program some agencies impose mandatory subcontracting clauses which would promote SBE utilization and be consistent with industry practice

Miami-Dade County Public Schools. The Miami School District policy allows for mandatory subcontracting of up to 40 percent of a contract.

SMALL BUSINESS PRIME CONTRACTING PROGRAMS

BIDDER ROTATION Some political jurisdictions use bidder rotation schemes to limit habitual purchases from majority firms and to ensure that M/W/SBEs have an opportunity to bid along with majority firms. A number of agencies, including the City of Indianapolis, Indiana; Fairfax County, Virginia; the Port Authority of New York and New Jersey; and Miami-Dade County, Florida, use bid rotation to encourage M/W/SBE utilization, particularly in architecture and engineering.

Miami-Dade County, Florida. Miami-Dade County has used small purchase orders for the Community Business Enterprise program and rotated on that basis. In addition, Miami-Dade County has utilized an Equitable Distribution Program, whereby a pool of qualified architecture and engineering professionals are rotated awards of county miscellaneous architecture and engineering services as prime contractors and subcontractors.

SMALL BUSINESS SET-ASIDES Miami-Dade County Public Schools. The Miami-Dade Schools SBE policy includes a sheltered market component. The policy provides that certain contracts can be placed in a sheltered market by the Office of Economic Opportunity and Miami-Dade Schools goal setting committee if: (1) there are at least three SBE/MBEs that are capable and available, (2) there is under-utilization in that business category, and (3) the extent to which the District's SBE prime contractor goals are being achieved. A contract can be removed

139 A description of the Charlotte SBE program can be found at ww.charmeck.org/Departments/Economic+Development/Small+Business/Home.htm. 140 MGT, The City of Charlotte Update Disparity Study, 2011, Exhibit 8-1.





from the sheltered market program if a responsive and responsible bid is not received or the bid received is deemed to be too high in price.

City of Denver. The Defined Selection Pool program puts contracts up to $1 million in a selection pool that can only be bid on by certified SBEs. This program applies to construction and professional service contracts. A SBE is defined as a firm that has revenue less than or equal to 50 percent of the Small Business Administration’s (SBA) small business standard and the owner has a personal net worth of less than $1.3 million. In the 2010 annual report M/WBEs won 73.7 percent of selection pool contracts.141

North Carolina Department of Transportation (NCDOT). In the NCDOT program, small contractors are defined as firms with less than $1.5 million in revenue. There is a small contractor goal of $2 million for each of the 14 NCDOT divisions. The current cap on project size for small contractors is $500,000. For contracts less than $500,000, NCDOT can solicit three informal bids from small business enterprises.142 North Carolina law permits the waiving of bonds and licensing requirements for these small contracts let to SBEs.143 From FY 2008-08, M/WBEs won $29.4 million (20.3 percent) in prime contracts under the North Carolina program.144

Oregon Department of Transportation (ODOT). Under its Small Business Initiative, ODOT started a pilot program targeting small firms in Region I. The program was extended statewide in September 2007. The program initially set aside contracts of less than $75,000 for competition amongst small firms and targeted A&E firms.145 Set asides for architecture and engineering (A&E) and related services were extended to projects of up to $150,000. Set-asides for construction are limited to projects valued at $100,000 or less. The program covers Project Specific contracts and On-Call Contracts.

The selection process for A&E and related services begins with the identification of a small contracting outsourcing opportunity. If there are ten or fewer firms registered in the discipline necessary for the project, all the firms are considered in the selection process. If there are more than ten firms registered in the discipline, then at least five firms are considered. The criteria ODOT may choose for selection include, but are not limited to, qualified firms that have no current or previous prime contracts with ODOT, specific work experience deemed relevant to ODOT requirements and geographic proximity to the project site and/or familiarity with the project site. Firms chosen for further evaluation then are to respond to mini-solicitations, which may include interviews. ODOT reserves to right to use other selection methods, including emergency procurement and direct appointments. After issuing a Notice of Intent to Award ODOT negotiates the statement of work, costs and payment terms with the top ranked firm.

The selection process for construction begins with the identification of a small contracting construction need and the plans and specifications and estimate for that project. If there are three or fewer firms

141 City of Denver, Office of Economic Development, Division of Small Business Opportunities, 2010 Annual Report, at 3. http://www.denvergov.org/Portals/690/documents/DSBO/DSBO%20Annual%20Report-FINAL-2010.pdf. 142 NCGS § 136-28.10(a). 143 NCGS § 136-28.10(b). 144 Equant, Measuring Business Opportunity—A Disparity Study of NCDOT’s State and Federal Programs, 2009, at 138. 145 Procurement authority for the SCPS program derives from ORS § 279A-050(3)(A),(B).





registered in the discipline necessary for the project, all the firms are considered in the selection process. If there are more than three firms registered in the discipline, then at least three firms are invited to bid. The criteria ODOT may choose for selection include, but are not limited to, qualified firms that have no current or previous prime contracts with ODOT, geographic proximity to the project site and firm certification status. The award is then made to the lowest responsive and responsible bid.

SBE BID PREFERENCES A number of agencies have used bid preferences for SBEs [Dade County, Florida; Port Authority of New York and New Jersey SBE Program; Sacramento Municipal Utility District (SMUD); City of Sacramento; City of Oakland; East Bay Municipal Utility District]; and the Washington Suburban Sanitary Commission. SBE bid preferences operate along similar lines as M/WBE bid preferences.

Miami-Dade County Public Schools. The Miami Schools SBE policy allows for evaluation preferences for "best value" contracts in which factors other than price can be considered in selection. In particular, the Miami Schools policy allows for bid preferences of up to 20 percent of total points for an SBE or joint venture with an SBE. SBE prime contractors cannot subcontract more than 49 percent of a contract.

RACE-NEUTRAL JOINT VENTURES City of Atlanta, Georgia. The City of Atlanta requires establishment of joint ventures on large projects of over $10 million.146 Primes are required to create a joint venture with a firm from a different ethnic/gender group in order to ensure prime contracting opportunities for all businesses. This rule applies to women- and minority-owned firms as well as nonminority firms. This rule has resulted in tens of millions of dollars in contract awards to women- and minority-owned firms.

CONSTRUCTION MANAGEMENT, REQUEST FOR PROPOSALS, AND DESIGN-BUILD One method of unbundling in construction is through the use of multi-prime construction contracts in which a construction project is divided into several prime contracts that are then managed by a construction manager at risk. For example, this approach has been used on projects where each prime contractor is responsible for installation and repair in particular areas. The construction manager is responsible for obtaining materials at volume discounts based upon total agency purchases. If one contractor defaults, a change order is issued to another prime contractor working in an adjacent area. The construction manager at risk is responsible for cost overruns that result from prime contractor default.

Construction management also facilitates the rotation of contracts within an area of work. For example, if several subcontractors have the capacity of bidding on an extended work activity (e.g., concrete flat work, traffic control, hauling), the construction manager can rotate contracting opportunities over the duration of the activity.

146 City of Atlanta Ordinance Sec. 2-1450 and Sec. 2-1451.





Using a request for proposal process can provide the flexibility for including M/WBE participation in prime contractor requirements and selection. One of the nonfinancial criteria can be the proposer's approach and past history with M/WBE subcontractor utilization as well as women and minority workforce participation.

A number of agencies around the country, the Charlotte-Mecklenburg School System, the Tri-County Metropolitan Transportation District of Oregon, and the City of Columbia, have had some success with this approach.147

The Colorado DOT has required DBE and Emerging Small Business (ESB) performance plans for bidders on design-build projects. Colorado DOT achieved $187 million in DBE utilization on the $1.2 billion T-REX project using this approach.148

STATE CONTRACTS The use of state contracts can impede M/W/SBE utilization, even when M/W/SBEs are the low bidder. Purchase off of state contracts is particularly an issue with car purchases, a procurement where there can be a significant number of M/W/SBE vendors. Fulton County, Georgia, addressed this problem by removing car purchases from the category of purchases from state contracts.

PURCHASING CARDS A number of agencies promote the utilization of M/W/SBEs on purchasing cards. The City of Hampton Schools, Virginia, for example, requires the purchasing card vendor to report on M/WBE utilization by agency staff. A number of universities, including the University of Wisconsin at Madison target M/WBE vendors for purchasing card transactions for travel.

OTHER SBE PRIME CONTRACTORS ASSISTANCE North Carolina Department of Transportation (NCDOT) Fully Operated Rental Agreements. Under these arrangements, a firm may bid an hourly rate for using certain equipment and the necessary staff. In these field-let contracts, engineers select the firm with the appropriate equipment and the lowest bid rate. If that firm is not available, the engineers select the next lowest hourly rate. This rental agreement technique is used primarily to supplement NCDOT equipment in the event of NCDOT equipment failure or peak demand for NCDOT services. The rental agreement technique is attractive to small contractors because the typical small firm has much better knowledge of its own hourly costs than it does of the costs to complete an entire project.

M/W/SBE INCLUSION IN FINANCIAL AND PROFESSIONAL SERVICES

Port Authority of New York and New Jersey. The Port Authority has encouraged the use of M/W/SBEs in finance through its financial advisory call-in program which targets small firms to serve as a pool of

147 Federal Transit Administration, Lessons Learned #45 (May 2002). www.fta.dot.gov/library/program/ll/man/ll45.html. 148 D. Wilson, Colorado Department of Transportation Statewide Transportation Disparity Study, 2009, at 3-20.





advisors for the Port Authority Chief Financial Officer. The financial advisors address debt issuance, financial advisory services, real estate transactions, and green initiatives. There are three to four firms in each of these categories in the financial advisory call-in program.

The Port Authority of New York and New Jersey’s Specialty Insurance Program sets aside five sets of insurance policies to small brokers, and the Port’s Financial Advisors Call In program pre-qualifies small firms for task orders in financial advisory services, real estate transactions, debt issuance, and green initiatives.

HUBZONES

Another variant of an SBE program provides incentives for SBEs located in distressed areas. For example, under the 1997 Small Business Reauthorization Act, the federal government started the federal HUBZone program. A HUBZone firm is a small business that is: (1) owned and controlled by U.S. citizens; (2) has at least 35 percent of its employees who reside in a HUBZone; and (3) has its principal place of business located in a HUBZone.149 HUBZone programs can serve as a vehicle for encouraging M/WBE contract utilization. Nationally, there are 5,357 female and minority HUBZone firms, representing 56.2 percent of total HUBZone firms.150

DBE PROGRAMS

Following the federal model, some agencies have added DBE programs.151 SBE programs focus on the disadvantage of the business, HUBZone programs focus on the disadvantage of the business location, and DBE programs focus on the disadvantage of the individual operating the business.

State of North Carolina. The State of North Carolina changed the definition of minority used in the state minority construction program to include socially and economically disadvantaged individuals, as defined in the federal rules.152 Socially disadvantaged individuals are those who have been subjected to racial or ethnic prejudice or cultural bias because of their identity as a member of a group without regard to their individual qualities.153 Economically disadvantaged individuals are those socially disadvantaged individuals whose ability to compete in the free enterprise system has been impaired due to diminished capital and credit opportunities as compared to others in the same business area that are not socially disadvantaged.154 This rule permits firms certified under the federal 8(a), DBE, and small disadvantaged business enterprise (S/DBE) programs to be certified as a minority firm in North Carolina. This rule also implies that firms owned by majority males are eligible for the program as there are firms owned by majority males that qualify for

149 13 C.F.R. 126.200 (1999). 150 Based on the SBA pro-net database located at http://pro-net.sba.gov/pro-net/search.html. 151 DBE programs and Airport Concession Disadvantaged Enterprise (ACDBE) programs are required to be developed and implemented as a part of the federal funding process. 152 NC GS § 143-128.2(g). 153 15 USC 637(a)(5). 154 15 USC 637(a)(6)(A).

http://pro-net.sba.gov/pro-net/search.html





the 8(a), DBE, and S/DBE programs by making an individual showing of their social and economic disadvantage.

TWO TIER CERTIFICATION

Miami-Dade County Public Schools. Miami Schools uses the following two-tier definition of small and micro business enterprises (Table 8-8):

TABLE 8-8 REVENUE DEFINITIONS FOR SBE AND MBE MIAMI-DADE COUNTY PUBLIC SCHOOLS

2013

INDUSTRY MICRO BUSINESS

ENTERPRISE SMALL BUSINESS ENTERPRISE

Professional Services

Less than $500,000 Tier 1 - Less than $1,000,000 Tier 2 - Less than $2,000,000

Construction Less than $1,000,000 Tier 1 - Less than $3,000,000 Tier 2 - Less than $6,000,000

Specialty Trade Less than $500,000 Tier 1 - Less than $1,000,000 Tier 2 - Less than $2,000,000

Source: School Board Policy 6320.02; the School Board of Miami-Dade County, Florida Business Enterprise Program Certification Application, September 2013.

FINANCIAL ASSISTANCE

LOAN GUARANTEES Los Angeles Unified School District (LAUSD), California. LAUSD provides firms with loan guarantees of up to the lesser of 50 percent of the contract or $200,000. Loan proceeds can be used for materials, subcontracts and labor costs associated with LAUSD contracts.

PROMPT PAYMENT M/WBE vendors still often report problems with prompt payment, particularly payments from prime contractors to subcontractors. Certain subcontractors that work on an early phase in a project, such as grading, can suffer from retainage withheld on long-lasting projects. There are several prompt payment policies that respond to this problem:

Retainage. North Carolina DOT requires that retainage be released when the tasks/activities for the subcontractors’ phase of work is accepted rather than at the end of the project.155

Two-party check program. To improve access to financing, the Port Authority of New York and New Jersey has a two-party check program in which the port authority writes checks out to the lender and the contractor. This program has not been frequently used according to staff.

155 49 CFR, Part 26.29(b).





BONDING ASSISTANCE Los Angeles Unified School District Contract Bondworks Program. Graduates of the LAUSD Small Business Boot Camp are eligible for bonding and finance guarantees for LAUSD construction contracts. The bond guarantee maximum is $400,000 or, 40 percent of the bond whichever less, per contract, per contractor.

MANAGEMENT AND TECHNICAL ASSISTANCE

A number of agencies hire an outside management and technical assistance provider to provide needed technical services related to business development and performance. Such a contract can be structured to include providing incentives to produce results, such as the number of M/W/SBEs being registered as qualified vendors with the city, the number of M/WBEs graduating from subcontract work to prime contracting, and rewarding firms that utilize M/WBEs in their private sector business activities.

Los Angeles Unified School District Small Business Boot Camp. The eight-week program trains contractors in bonding, prequalification, bidding, scheduling, public contract law, safety plans, labor compliance and financing.

MENTOR-PROTÉGÉ PROGRAMS

New York School Construction Authority Mentor Plan. In this mentor protégé plan firms are eligible for small business loans and bonding assistance upon completion of the program. In addition to loans and bonding the program provides project experience, technical assistance and training, help with business development and accelerated payments. The program targets construction contracts valued up to $750,000 for program participants to bid against each other.156

156 http://www.nycsca.org/Business/GettingStarted/Pages/MentorPrograms.aspx.

Appendix A: Stakeholder Interview Guide



APPENDIX A | STAKEHOLDER INTERVIEW GUIDE



INTERVIEW DETAILS

Organization Name: Date:

Interviewee Name:

Interviewee Title: Interviewee Phone Number: ( )

Interviewee’s Email

Type of Organization:

Interviewer Name:

1. Please describe your membership structure in terms of industries represented, size, ethnic/racial makeup, etc.

2. Does your organization have a working relationship or partnership with the District? If so, how do you work with the District?

3. Are you familiar with the business inclusion program administered by the District? If so, provide your interpretation of the program.

4. Are you aware of any concerns with Minority/Women Business Enterprise certification (definition, process, reciprocity, renewal, etc.)? If so, what are the concerns?

5. Please discuss your organization’s capacity building or business development programs for your members?

7. Are you aware of any barriers minority owned firms [or women-owned firms, or small firms, etc.] face with doing business or trying to do business with the District? If so, what are the barriers?

8. Are you aware of any barriers minority owned firms [or women-owned firms, or small firms, etc.] face with doing business or trying to do business with the private sector? If so, what are the barriers?

9. To your knowledge are M/WBEs treated equal to non-M/WBEs in their ability to get and maintain insurances, bonding, and financing required for contracts? Explain the basis of your response.

10. Is there a “level playing field” between M/WBEs in the industries that your organization represents? Explain the basis of your response.

11. Are you aware of any instances in which the construction work performed by minority-owned [or women-owned, etc.] firms have been subjected to more rigorous or more extensive inspections or testing?

12. Are there any issues that you think are important for the study to address? Why is the issue significant?


APPENDIX A | STAKEHOLDER INTERVIEW GUIDE



13. Do you have recommendations to improve the District procurement processes? If so, what are they?

14. Do you have recommended changes to the District business inclusion program? If so, what are they?

15. Are there any other topics related to the disparity study that you would like to raise at this time? Please explain.

Additional Notes

On behalf of the Guilford County School District, thank you for your participation in this interview. If you have any questions or would like more information about the disparity study please contact Dr. Terrence Young, Chief Information Officer at (336) 370-2308.

Appendix B: Custom Census Survey Instrument



B| CUSTOM CENSUS SURVEY INSTRUMENT

GUILFORD COUNTY SCHOOLS


ENTER THE D&B D-U-N-S NUMBER

Hello. My name is _________, with BLWall Consulting, and we are conducting a 5-minute survey for MGT of America on behalf of Guilford County Schools (Schools) to determine the availability of firms in the marketplace. The purpose of this survey is to help the Schools identify firms interested in conducting business with these agencies.

Is this ___________________ (Company's name)? IF COMPANY NAME VERIFIED, CONTINUE.

Are you the owner or an authorized decision maker in your company? [IF NO] May I speak with that person? [IF NO, SCHEDULE CALL-BACK]?

IF OWNER IS PUT ON THE LINE: CONTINUE

IF TRANSFERRED TO ANOTHER PARTY (CFO, MANAGER, ETC): Are you able to answer questions concerning business practices of this company? IF YES, CONTINUE.

Your company's information has been provided to us from Dun & Bradstreet.

Thank you for agreeing to participate in this research study. Your opinions are important to us, and all of your responses will be kept confidential. If you have any questions regarding the survey, I will be happy to provide you a contact at the end of the survey.

Thank you in advance for your participation.

Q1. What is your title? [REQUIRE ANSWER]

Owner/CEO/President 1 Manager/Financial Officer 2 Other (Specify) 3

Q2. May I have your name just in case we have any further questions? [REQUIRE ANSWER]

(1)





Q3. Let me confirm that, based on information we have from Dun & Bradstreet, this is a for-profit company, as opposed to a nonprofit, foundation or government office?

[REQUIRE ANSWER]

Yes 1 No 2 Don’t Know 9

[IF THE ANSWER TO QUESTION 3 IS NO OR DON’T KNOW, THEN TERMINATE THE CALL PLEASE GO BACK TO Q2 AND TYPE “DISQUALIFIED” AFTER THE FIRST AND LAST NAME.]

Disqualification statement Thank you for your input; however, based on your answers, it appears that you do not qualify for this

survey.

Q4. Let me confirm that, based on the information we have from Dun & Bradstreet, the company’s primary line of business is (READ NAICS WITH CORRESPONDING DESCRIPTIVE TEXT) [REQUIRE ANSWER]


[S – IF Q4 IS NOT 1, SKIP TO Q5]

Q5. Please SPECIFY your company’s Primary Type of work. [REQUIRE ANSWER]

_______________________________________________________________________

Q6. Does your company bid primarily as a prime contractor or consultant? Subcontractor? OR both?

[REQUIRE ANSWER]

Prime Contractor or Consultant 1 Subcontractor or subconsultant 2 Both 3 Don’t Know 9

Q7. Is more than 50 percent of your company owned and controlled by a woman or women?

[REQUIRE ANSWER]






Q8. Is more than 50 percent of your company owned and controlled by a person or people of one of the following racial or ethnic groups? [REQUIRE ANSWER]

Anglo/Caucasian 1 African American 2 Asian American or Pacific Islander 3 Hispanic American 4 Native American/Alaskan Native 5 Other (Specify) 6_________________________________ Don’t Know 9

Q9. Is your company interested in working as a prime contractor or consultant, supplier, or subcontractor to a prime over the next 12 months or near future with Guilford County Schools? [REQUIRE ANSWER]


That completes our interview. Again, thank you for your input and your participation in this important survey.

If you would like more information on the Disparity Study, please contact the Guilford County Schools Chief Information Officer, Terrence Young at (336) 370-2308.

Appendix C: Detailed Disparity Analysis



APPENDIX C| DETAILED DIS PARITY ANALYS IS

GUILFORD COUNTY SCHOOL DISTRICT Final Report | July 20, 2016

P A G E 1

GUILFORD COUNTY SCHOOLS CONSTRUCTION

PRIME DISPARITY ANALYSIS FISCAL YEARS 2010-2014

BUSINESS OWNERSHIP CLASSIFICATION % OF % OF DISPARITY DISPARATE IMPACT DOLLARS AVAILABILITY INDEX OF UTILIZATION CONSTRUCTION African American 3.00% 13.02% 23.04 UNDERUTILIZATION * Native American 0.00% 0.26% 0.00 UNDERUTILIZATION * Asian American 0.05% 1.56% 2.98 UNDERUTILIZATION * Hispanic Americans 0.05% 3.13% 1.58 UNDERUTILIZATION * Nonminority Women 2.86% 19.79% 14.45 UNDERUTILIZATION * Non-M/WBE Firms 94.04% 62.24% 151.10 OVERUTILIZATION

Source: The percentage of dollars is taken from the previously shown utilization analyses. The percentage of availability is taken from previously shown availability of vendors analyses. * The disparity index is the ratio of % utilization to % availability times 100. An asterisk is used to indicate a substantial level of disparity index below 80.00.


CONSTRUCTION SUBCONTRACTOR DISPARITY ANALYSIS

FISCAL YEARS 2010-2014 BUSINESS OWNERSHIP CLASSIFICATION % OF % OF DISPARITY DISPARATE IMPACT DOLLARS AVAILABILITY INDEX OF UTILIZATION CONSTRUCTION African American 13.02% 21.35% 60.99 UNDERUTILIZATION * Native American 1.45% 0.49% 295.12 OVERUTILIZATION Asian American 0.00% 1.48% 0.00 UNDERUTILIZATION * Hispanic Americans 3.25% 3.78% 86.09 UNDERUTILIZATION Nonminority Women 40.32% 26.27% 153.47 OVERUTILIZATION Non-M/WBE Firms 41.96% 46.63% 89.97 UNDERUTILIZATION





P A G E 2

GUILFORD COUNTY SCHOOLS ARCHITECTURE AND ENGINEERING


BUSINESS OWNERSHIP CLASSIFICATION % OF % OF DISPARITY DISPARATE IMPACT DOLLARS AVAILABILITY INDEX OF UTILIZATION ARCHITECTURE AND ENGINEERING African American 11.02% 28.28% 38.97 UNDERUTILIZATION * Native American 0.00% 0.00% 0.00 NOT APPLICABLE 1 Asian American 3.94% 5.05% 77.97 UNDERUTILIZATION * Hispanic Americans 0.00% 3.03% 0.00 UNDERUTILIZATION * Nonminority Women 6.26% 36.36% 17.22 UNDERUTILIZATION * Non-M/WBE Firms 78.78% 27.27% 288.84 OVERUTILIZATION

Source: The percentage of dollars is taken from the previously shown utilization analyses. The percentage of availability is taken from previously shown availability of vendors analyses. 1 Not Applicable indicates that there was no utilization or availability of vendors in this ethnic group. * The disparity index is the ratio of % utilization to % availability times 100. An asterisk is used to indicate a substantial level of disparity index below 80.00.


PROFESSIONAL SERVICES PRIME DISPARITY ANALYSIS

FISCAL YEARS 2010-2014 BUSINESS OWNERSHIP CLASSIFICATION % OF % OF DISPARITY DISPARATE IMPACT DOLLARS AVAILABILITY INDEX OF UTILIZATION PROFESSIONAL SERVICES African American 7.08% 22.51% 31.44 UNDERUTILIZATION * Native American 0.00% 0.00% 0.00 NOT APPLICABLE 1 Asian American 0.47% 2.05% 22.97 UNDERUTILIZATION * Hispanic Americans 0.22% 0.55% 40.26 UNDERUTILIZATION * Nonminority Women 14.28% 24.56% 58.15 UNDERUTILIZATION * Non-M/WBE Firms 77.95% 50.34% 154.85 OVERUTILIZATION

Source: The percentage of dollars is taken from the previously shown utilization analyses. The percentage of availability is taken from previously shown availability of vendors analyses. 1 Not Applicable indicates that there was no utilization or availability of vendors in this ethnic group. * The disparity index is the ratio of % utilization to % availability times 100. An asterisk is used to indicate a substantial level of disparity index below 80.00.




P A G E 3

GUILFORD COUNTY SCHOOLS OTHER SERVICES


BUSINESS OWNERSHIP CLASSIFICATION % OF % OF DISPARITY DISPARATE IMPACT DOLLARS AVAILABILITY INDEX OF UTILIZATION OTHER SERVICES African American 10.93% 19.22% 56.88 UNDERUTILIZATION * Native American 0.00% 0.84% 0.04 UNDERUTILIZATION * Asian American 0.01% 1.37% 0.00 UNDERUTILIZATION * Hispanic Americans 0.82% 2.22% 37.11 UNDERUTILIZATION * Nonminority Women 7.46% 17.95% 41.55 UNDERUTILIZATION * Non-M/WBE Firms 80.78% 58.39% 138.33 OVERUTILIZATION


GUILFORD COUNTY SCHOOLS OTHER SERVICES


BUSINESS OWNERSHIP CLASSIFICATION % OF % OF DISPARITY DISPARATE IMPACT DOLLARS AVAILABILITY INDEX OF UTILIZATION GOODS African American 2.43% 10.14% 23.93 UNDERUTILIZATION * Native American 0.00% 0.09% 0.00 UNDERUTILIZATION * Asian American 0.11% 1.18% 9.19 UNDERUTILIZATION * Hispanic Americans 0.00% 0.91% 0.12 UNDERUTILIZATION * Nonminority Women 9.05% 14.40% 62.80 UNDERUTILIZATION * Non-M/WBE Firms 88.42% 73.28% 120.66 OVERUTILIZATION


Appendix D: Public Meeting Notices



D | PUBL IC MEETING NOTICES




D | PUBL IC MEETING NOTICES



Appendix E: Survey of Vendors Instrument



E | SURVEY OF VENDORS INSTRUMENT


P A G E 1

MGT_Guilford Pre – Test (10/29/15)

Hello, my name is _______ and I am calling on behalf of Guilford County School District to analyze the utilization of area businesses in their contracting.

Is this ____________________________ (Company's name)? IF COMPANY NAME VERIFIED, CONTINUE

Are you the owner or an authorized decision maker in your company?

IF NO - May I speak with that person? IF NO, SCHEDULE CALL BACK IF OWNER IS PUT ON THE LINE: CONTINUE IF TRANSFERRED TO ANOTHER PARTY (CFO, MANAGER, ETC): Are you able to answer questions concerning business practices of this company? IF YES, CONTINUE

The Guilford County School District (District) has contracted with MGT of America and Oppenheim Research to analyze the utilization of area businesses in their contracting with the District. This is a great opportunity for your company to provide feedback regarding your experience doing business with or attempting to do business with the District. It will only take a few minutes of your time and is instrumental to the study's research goals.

IF NEEDED: This survey will gather information on business ownership, work performed and/or bid with the District, bid and/or performed in the private sector, and barriers, perceived or real, that prevented your company from doing business with the District between July 1, 2010 and June 30, 2014. The results of the study will provide the basis, if warranted, recommendations to improve the District's current procurement programs.

Your company has been randomly selected to participate in this survey of business owners to determine the current business climate and help evaluate the procurement of goods and services for the District, the subcontracting practices of prime contractors who do business with the District, and the anecdotal evidence collected from a broad cross section of all interested businesses.

Your information is aggregated for the overall analysis, is used only for the purposes of conducting this study, and will be kept confidential. If you have any questions regarding the survey, I will be happy to provide you a contact at the end of the study.

Q.1 What is your title? [REQUIRE ANSWER]

(5) Owner ...................................................... 1 CEO/President ...................................... 2 Manager/Financial Officer ............... 3 Other ........................................................ 4

[S - IF THE ANSWER IS 1-2, THEN SKIP TO QUESTION 3] [A - IF THE ANSWER TO QUESTION 1 IS NOT 4, THEN SKIP TO QUESTION 3]




P A G E 2

Q.2 Specify OTHER [REQUIRE ANSWER]

________________________________________________ (6-30)

Q.3 Please verify your name just in case we have any further questions?

[REQUIRE ANSWER]

________________________________________________ (31-80)

Q.4 Please specify your company’s primary line of business?

[REQUIRE ANSWER]

(81) Construction (ex: heavy construction, general contracting, carpentry,

electrical, site work, HVAC, drywall, etc.) ........................................................................................ 1 Architecture and Engineering (ex: architecture, engineering, structural

engineering, continuing contracts, surveying, etc.) ................................................................... 2 Professional Services (ex: construction management, attorney,

accountant, consultant, etc.) ................................................................................................................ 3 Non-Professional Services (ex: maintenance services, janitorial,

security, auto repair, etc.) ..................................................................................................................... 4 Goods (ex: supplies, materials, equipment, commodities) .............................................................. 5

[S - IF THE ANSWER IS 2, THEN SKIP TO QUESTION 6] [S - IF THE ANSWER IS 3, THEN SKIP TO QUESTION 7] [S - IF THE ANSWER IS 4, THEN SKIP TO QUESTION 8] [S - IF THE ANSWER IS 5, THEN SKIP TO QUESTION 9]

[A - IF THE ANSWER TO QUESTION 4 IS NOT 1, THEN SKIP TO QUESTION 9999]

Q.5 Please SPECIFY construction type. [REQUIRE ANSWER]

_______________________________________________ (82-381)


Q.6 Please SPECIFY architecture and engineering type. [REQUIRE ANSWER]

______________________________________________ (382-681)


Q.7 Please SPECIFY professional services type. [REQUIRE ANSWER]

______________________________________________ (682-981)


Q.8 Please SPECIFY non-professional services type. [REQUIRE ANSWER]

_____________________________________________ (982-1281)





P A G E 3

Q.9 Please SPECIFY goods type. [REQUIRE ANSWER]

_____________________________________________ (1282-1581)

Q.10 Is more than 50% of the company owned and controlled by a woman or women? [REQUIRE ANSWER]

(1582) Yes ........................ 1 No ......................... 2 Don’t know ........ 3

Q.11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups? [REQUIRE ANSWER]

(1583) Anglo/Caucasian/White ................................... 1 Black/African American .................................... 2 American Indian/Alaskan Native .................. 3 Asian or Pacific Islander ................................... 4 Hispanic or Latino .............................................. 5 Other ....................................................................... 6 Don’t know ........................................................... 7



_____________________________________________ (1584-1633)

Q.13 What is the highest level of education completed by the primary owner of your company? [REQUIRE ANSWER]

(1634) Some high school ...................................... 1 High school graduate .............................. 2 Trade or technical education ................ 3 Some college ............................................... 4 College degree ........................................... 5 Post graduate degree .............................. 6 Don’t know ................................................... 7

Q.14 In what year was your company established? [REQUIRE ANSWER]

________ (1635-1638)




P A G E 4

Q.15 How many combined years of experience do you or the primary owner(s) of your company have in the company’s primary line of business? [REQUIRE ANSWER]

(1639) 0 – 5 years ................ 1 6 – 10 years ............. 2 11 – 15 years ........... 3 16 – 20 years ........... 4 20+ years .................. 5 Don’t know .............. 6

Q.16 In the last three years, what was the average number of employees on your company’s payroll, including full-time and part-time staff? [REQUIRE ANSWER]

(1640) 0 – 10 employees ............... 1 11 – 20 employees ............. 2 21 – 30 employees ............. 3 31 – 40 employees ............. 4 41+ employees ................... 5 Don't know ........................... 6

Q.17 Which of the following categories best approximates your company’s gross revenues for calendar year 2014? [REQUIRE ANSWER]

(1641-1642) Up to $50,000? ......................................... 1 $50,001 to $100,000? ............................. 2 $100,001 to $300,000? .......................... 3 $300,001 to $500,000? .......................... 4 $500,001 to $1 million? ........................ 5 $1,000,001 to $3 million? ..................... 6 $3,000,001 to $5 million? ..................... 7 $5,000,001 to $10 million? .................. 8 Over $10 million? .................................... 9 Don’t know ............................................... 10

Q.18 What percentage of these gross revenues was earned from the District, the private sector, and other public government sector projects? [REQUIRE ANSWER: 3] [ANSWERS MUST TOTAL 100]

District % ................................................................... ______ (1643-1645) Private sector % ...................................................... ______ (1646-1648) Non-district public sector % ............................. ______ (1649-1651)




P A G E 5

Q.19 Does your company hold any of the following certifications from a recognized certification agency? [CHECK ALL THAT APPLY] [REQUIRE ANSWER]

Yes No DK Minority Business Enterprise (MBE) 1 2 3 (1652) Small Business Enterprise (SBE) 1 2 3 (1653) Woman Business Enterprise (WBE) 1 2 3 (1654) Disadvantaged Business Enterprise (DBE) 1 2 3 (1655) HubZone 1 2 3 (1656) 8A 1 2 3 (1657) Other 1 2 3 (1658)

[A - IF ANSWER TO SUB-QUESTION 7 OF Q19 IS NOT 1, SKIP TO Q21]


_____________________________________________ (1659-1708)

Q.21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant or both? [REQUIRE ANSWER]

(1709) Prime contractor/consultant or vendor ........................ 1 Subcontractor/subconsultant or supplier .................... 2 Both ............................................................................................. 3

[A - IF THE ANSWER TO QUESTION 21 IS NOT 1 OR 3, SKIP TO QUESTION 37]

Q.22 In general, which of the following dollar ranges best approximates your company’s largest prime contract awarded between July 1, 2010 and June 30, 2014? [REQUIRE ANSWER]

(1710-1711) None ..................................................... 1 Up to $50,000? ................................. 2 $50,001 to $100,000? ..................... 3 $100,001 to $200,000? .................. 4 $200,001 to $300,000? .................. 5 $300,001 to $400,000? .................. 6 $400,001 to $500,000? .................. 7 $500,001 to $1 million? ................. 8 Over $1 million? ............................... 9 Don’t know ........................................ 10




P A G E 6

Q.23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor? [REQUIRE ANSWER]


Q.24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor? [REQUIRE ANSWER]

Yes No DK Prequalification requirements 1 2 3 (1714) Bid bond requirements 1 2 3 (1715) Performance/payment bond requirements 1 2 3 (1716) Cost of bidding/proposing 1 2 3 (1717) Financing 1 2 3 (1718) Insurance (general liability, professional liability, etc.) 1 2 3 (1719) Price of supplies/materials 1 2 3 (1720) Proposal/bid specifications 1 2 3 (1721) Short or limited time given to prepare bid package or quote 1 2 3 (1722) Limited knowledge of purchasing and contracting policies and procedures 1 2 3 (1723) Lack of experience 1 2 3 (1724) Lack of personnel 1 2 3 (1725) Contract too large 1 2 3 (1726) Selection process/evaluation criteria 1 2 3 (1727) Unnecessary restrictive contract specifications 1 2 3 (1728) Slow payment or non-payment 1 2 3 (1729) Competing with large companies 1 2 3 (1730) Changes in the scope of work (after work began) 1 2 3 (1731) Meeting M/WBE goals or good faith effort requirements 1 2 3 (1732)




P A G E 7

Q.25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed that you were the lowest bidder, and then found out that another firm was actually doing the work? [REQUIRE ANSWER]

(1733) Yes ........................ 1 No ......................... 2 Don’t know ........ 3

Q.26 As a prime contractor/vendor, is your company required to have bonding? [REQUIRE ANSWER]

(1734) Yes ........................ 1 No ......................... 2 Don’t know ........ 3


Q.27 What is your company's current aggregate bonding capacity? [REQUIRE ANSWER]

(1735) Below $100,000? ..................................... 1 $100,001 to $250,000? ......................... 2 $250,001 to $500,000? ......................... 3 $500,001 to $1 million? ....................... 4 $1,000,001 to $1.5 million? ................ 5 $1,500,001 to $3 million? .................... 6 $3,000,001 to $5 million? .................... 7 Over $5 million? ...................................... 8 Don’t know ............................................... 9

Q.28 What is your company's current single limit bonding capacity? [REQUIRE ANSWER]

(1736) Below $100,000? ..................................... 1 $100,001 to $250,000? ......................... 2 $250,001 to $500,000? ......................... 3 $500,001 to $1 million? ....................... 4 $1,000,001 to $1.5 million? ................ 5 $1,500,001 to $3 million? .................... 6 $3,000,001 to $5 million? .................... 7 Over $5 million? ...................................... 8 Don’t know ............................................... 9




P A G E 8

Q.29 As a prime contractor/vendor, did your company experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014? [REQUIRE ANSWER]

(1737) Yes ................................. 1 No .................................. 2 Not Applicable ......... 3 Don’t know ................ 4


Q.30 How did you become aware of the discrimination against your company? [REQUIRE ANSWER]

(1738) Verbal comment ...................................................... 1 Written statement/documents .......................... 2 Action taken against the company .................. 3 Other action .............................................................. 4 Don’t know ................................................................ 5


Q.31 Specify DISCRIMINATORY ACTION [REQUIRE ANSWER]

_____________________________________________ (1739-1838)

Q.32 Which of the following do you consider the primary reason for your company being discriminated against? [REQUIRE ANSWER]

(1839) Owner’s race or ethnicity .............. 1 Owner’s gender ................................. 2 Both race and gender ..................... 3 Other reason ...................................... 4 Don’t know ......................................... 5


Q.33 Specify REASON [REQUIRE ANSWER]

_____________________________________________ (1840-1939)

Q.34 When did the discrimination first occur? [REQUIRE ANSWER]

(1940) During the bidding process ................. 1 During contract negotiations .............. 2 After contract award ............................... 3 All of the above ......................................... 4 Don’t know .................................................. 5




P A G E 9

Q.35 Did you file a complaint? [REQUIRE ANSWER]

(1941) Yes ........................ 1 No ......................... 2 Don’t know ........ 3

Q.36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District? [REQUIRE ANSWER]

(1942) Yes ...... 1 No ....... 2

[A - IF THE ANSWER TO QUESTION 21 IS 1, THEN SKIP TO QUESTION 52]

Q.37 In general, which of the following dollar ranges best approximates your company’s largest subcontract between July 1, 2010 and June 30, 2014? [REQUIRE ANSWER]


Q.38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier? [REQUIRE ANSWER]





P A G E 10

Q.39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District? [REQUIRE ANSWER TO EACH OF THE FOLLOWING]

Yes No DK Performance/payment bond requirements 1 2 3 (1947) Cost of bidding/proposing 1 2 3 (1948) Financing 1 2 3 (1949) Insurance (general liability, professional liability, etc.) 1 2 3 (1950) Price of supplies/materials 1 2 3 (1951) Short or limited time given to prepare bid package or quote 1 2 3 (1952) Lack of experience 1 2 3 (1953) Lack of personnel 1 2 3 (1954) Contract too large 1 2 3 (1955) Slow payment or non-payment 1 2 3 (1956) Competing with large companies 1 2 3 (1957) Solicitation of subcontractor bids after contract award (i.e. bid shopping) 1 2 3 (1958) Awarded scope of work reduced or eliminated 1 2 3 (1959)

Q.40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime contractor for a project with the District, were informed that you were the lowest bidder, and then found out that another subcontractor was actually doing the work? [REQUIRE ANSWER]

(1960) Yes ........................ 1 No ......................... 2 Don’t know ........ 3

Q.41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work? [REQUIRE ANSWER]

(1961) Yes ........................ 1 No ......................... 2 Don’t know ........ 3

Q.42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project? [REQUIRE ANSWER]

(1962) Yes ................................. 1 No .................................. 2 Not Applicable ......... 3 Don’t know ................ 4





P A G E 11

Q.43 How did you become aware of the discrimination against your company?

[REQUIRE ANSWER]




_____________________________________________ (1964-2263)





_____________________________________________ (2265-2564)



Q.48 Did you file a complaint? [REQUIRE ANSWER]

(2566) Yes ........................ 1 No ......................... 2 Don’t know ........ 3




P A G E 12

Q.49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District? [REQUIRE ANSWER]

(2567) Yes ...... 1 No ....... 2

Q.50 Has your company experienced or observed a situation in which a prime contractor/vendor includes minority or woman subcontractors on a bid or proposal to satisfy the “good faith effort” requirements and then drops the company as a subcontractor after winning the award for no legitimate reason? [REQUIRE ANSWER]

Yes No DK District project? 1 2 3 (2568) Non-District project? 1 2 3 (2569)

Q.51 Still talking about prime contractors/consultants or vendors, while doing business or attempting to do business, has your company experienced any of the following as a form of discrimination? [REQUIRE ANSWER]

Yes No DK Harassment 1 2 3 (2570) Unequal or unfair treatment 1 2 3 (2571) Bid shopping or bid manipulation 1 2 3 (2572) Double standards in performance 1 2 3 (2573) Denial of opportunity to bid 1 2 3 (2574) Unfair denial of contract award 1 2 3 (2575) Unfair termination 1 2 3 (2576) Unequal price quotes from suppliers 1 2 3 (2577)

Q.52 Has your company applied for a commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014? [REQUIRE ANSWER]

(2578) Yes ........................ 1 No ......................... 2 Don’t know ........ 3


Q.53 Was your company approved or denied for a commercial (business) bank loan or line of credit? [REQUIRE ANSWER]

(2579) Approved ........... 1 Denied ................. 2 Don’t know ........ 3

[S - IF THE ANSWER IS 3, THEN SKIP TO QUESTION 57] [A - IF THE ANSWER TO QUESTION 53 IS 2, THEN SKIP TO QUESTION 55] [A - IF THE ANSWER TO QUESTION 53 IS 3, THEN SKIP TO QUESTION 57]




P A G E 13

Q.54 What was the highest amount of commercial bank loan your company received? [REQUIRE ANSWER]

(2580) Up to $50,000? .......................................... 1 $50,001 to $100,000? .............................. 2 $100,001 to $300,000? ........................... 3 $300,001 to $500,000? ........................... 4 $500,001 to $1 million? ......................... 5 $1,000,001 to $3 million? ...................... 6 $3,000,001 to $5 million? ...................... 7 $5,000,001 to $10 million? ................... 8 Over $10 million? ..................................... 9 No response/Don’t know ..................... 10

[A - IF THE ANSWER TO QUESTION 53 IS 1, THEN SKIP TO QUESTION 57]

Q.55 Which of the following do you believe was the primary reason for your company being denied a loan? [REQUIRE ANSWER]

(2581) Insufficient documentation .................... 1 Insufficient business history ................... 2 Confusion about the process ................ 3 Race or ethnicity of owner ..................... 4 Gender of owner ........................................ 5 Other ............................................................... 6 Don’t know ................................................... 7



_____________________________________________ (2582-2881)

Q.57 For the following statement, please indicate whether you: agree, neither agree or disagree, or disagree. There is an informal network of prime contractors/vendors and subcontractors that has excluded my company from doing business in the private sector. [REQUIRE ANSWER]

(2882) Strongly agree ........................................ 1 Somewhat agree .................................... 2 Neither agree nor disagree ............... 3 Somewhat disagree .............................. 4 Strongly disagree .................................. 5 Don’t know ............................................... 6




P A G E 14

Q.58 How often do prime contractors/vendors who use your company as a subcontractor on public sector projects with M/WBE goals solicit your company on projects (private or public) without M/WBE goals? [REQUIRE ANSWER]

(2883) Very often .................. 1 Sometimes ................ 2 Seldom ........................ 3 Never ........................... 4 Not applicable ......... 5 Don’t know ................ 6

Q.59 Has your company experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014? [REQUIRE ANSWER]

(2884) Yes ............................................................................. 1 No ............................................................................. 2 Do not work in the private sector ................ 3 Don’t know ............................................................ 4


Q.60 How did you become aware of the discrimination against your company? [REQUIRE ANSWER]




_____________________________________________ (2886-3185)







P A G E 15


_____________________________________________ (3187-3286)



Q.65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District or their primes? [REQUIRE ANSWER]

(3288) Yes ...... 1 No ....... 2




P A G E 16

That completes the survey. On behalf of Guilford County School District, thank you very much for sharing your time and thoughts on this important project. If you would like more information on this study, please contact Dr. Terrance Young, Chief Information Officer, at 336-370-2308.

Q.66 Telephone Number _________________________________(4000-4015)

Q.67 Ref Name ______________________________________(4016-4025)

Q.68 Ref # ___________________________________________(4026-4035) Q.69 Company Name___________________________________(4036-4135)

Q.70 Street ___________________________________________(4136-4185)

Q.71 City ___________________________________________(4186-4210)

Q.72 State ___________________________________________ (4211-4212)

Q.73 Zip ___________________________________________(4213-4222)

Q.74 County __________________________________________(4223-4247)

Q.75 Fax ___________________________________________(4248-4263)

Q.76 Ethnicity_________________________________________ (4264-4293)

Q.77 Vendor #_________________________________________(4294-4303)

Q.78 Interviewer _____________________________________ (4304-4307)

Q.79 Date ___________________________________________(4308-4316)

Q.80 Time ___________________________________________(4317-4322)

Q.81 Duration ______________________________________(4323-4328)

Q.82 Call Result ______________________________________(4329-4330)

Appendix F: Survey of Vendors Results


GUILFORD COUNTY SCHOOL DISTRICT DISPARITY STUDY F | SURVEY OF VENDORS RESULTS

GUILFORD COUNTY SCHOOL DISTRICTFinal Report | July 20, 2016 PAGE 1

Frequency Percent Valid PercentCumulative

Percent

African American Firms 97 19.5 19.5 19.5Asian American Firms 5 1.0 1.0 20.5Hispanic American Firms 11 2.2 2.2 22.7Native American Firms 8 1.6 1.6 24.3Nonminority Female Firms 115 23.1 23.1 47.5Non-M/WBE Firms 257 51.7 51.7 99.2Other Firms 4 .8 .8 100.0Total 497 100.0 100.0





Nonminority Female Firms

Non-M/WBE Firms Other Firms

Count 72 3 8 4 59 81 2 229% within Q1 What is your title? 31.4% 1.3% 3.5% 1.7% 25.8% 35.4% .9% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

74.2% 60.0% 72.7% 50.0% 51.3% 31.5% 50.0% 46.1%

% of Total 14.5% .6% 1.6% .8% 11.9% 16.3% .4% 46.1%Count 7 0 1 1 18 28 1 56% within Q1 What is your title? 12.5% 0.0% 1.8% 1.8% 32.1% 50.0% 1.8% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

7.2% 0.0% 9.1% 12.5% 15.7% 10.9% 25.0% 11.3%

% of Total 1.4% 0.0% .2% .2% 3.6% 5.6% .2% 11.3%Count 15 2 2 3 34 142 1 199% within Q1 What is your title? 7.5% 1.0% 1.0% 1.5% 17.1% 71.4% .5% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

15.5% 40.0% 18.2% 37.5% 29.6% 55.3% 25.0% 40.0%

% of Total 3.0% .4% .4% .6% 6.8% 28.6% .2% 40.0%Count 3 0 0 0 4 6 0 13% within Q1 What is your title? 23.1% 0.0% 0.0% 0.0% 30.8% 46.2% 0.0% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

3.1% 0.0% 0.0% 0.0% 3.5% 2.3% 0.0% 2.6%

% of Total .6% 0.0% 0.0% 0.0% .8% 1.2% 0.0% 2.6%Count 97 5 11 8 115 257 4 497% within Q1 What is your title? 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 22 2 3 1 20 47 1 96% within Q4 Please specify your company's primary line of business?

22.9% 2.1% 3.1% 1.0% 20.8% 49.0% 1.0% 100.0%

% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

22.7% 40.0% 27.3% 12.5% 17.4% 18.3% 25.0% 19.3%

% of Total 4.4% .4% .6% .2% 4.0% 9.5% .2% 19.3%

Race, Ethnicity, Gender Classification (Business Ownership Classification)

Valid

Q1 What is your title? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ1 What is your title? Owner

CEO/President

Manager/Financial Officer

Other, Please Specify

Total

Q4 Please specify your company's primary line of business? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ4 Please specify your company's primary line of business?

Construction (heavy construction, general contracting, carpentry, electrical, site work, HVAC, drywall, etc.)



Count 5 0 0 0 3 9 0 17% within Q4 Please specify your company's primary line of business?

29.4% 0.0% 0.0% 0.0% 17.6% 52.9% 0.0% 100.0%


5.2% 0.0% 0.0% 0.0% 2.6% 3.5% 0.0% 3.4%

% of Total 1.0% 0.0% 0.0% 0.0% .6% 1.8% 0.0% 3.4%Count 10 1 1 1 14 10 0 37% within Q4 Please specify your company's primary line of business?

27.0% 2.7% 2.7% 2.7% 37.8% 27.0% 0.0% 100.0%


10.3% 20.0% 9.1% 12.5% 12.2% 3.9% 0.0% 7.4%

% of Total 2.0% .2% .2% .2% 2.8% 2.0% 0.0% 7.4%Count 49 2 5 4 40 85 3 188% within Q4 Please specify your company's primary line of business?

26.1% 1.1% 2.7% 2.1% 21.3% 45.2% 1.6% 100.0%


50.5% 40.0% 45.5% 50.0% 34.8% 33.1% 75.0% 37.8%

% of Total 9.9% .4% 1.0% .8% 8.0% 17.1% .6% 37.8%Count 11 0 2 2 38 106 0 159% within Q4 Please specify your company's primary line of business?

6.9% 0.0% 1.3% 1.3% 23.9% 66.7% 0.0% 100.0%


11.3% 0.0% 18.2% 25.0% 33.0% 41.2% 0.0% 32.0%

% of Total 2.2% 0.0% .4% .4% 7.6% 21.3% 0.0% 32.0%Count 97 5 11 8 115 257 4 497% within Q4 Please specify your company's primary line of business?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 29 1 1 4 115 2 1 153% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

19.0% .7% .7% 2.6% 75.2% 1.3% .7% 100.0%


29.9% 20.0% 9.1% 50.0% 100.0% .8% 25.0% 30.8%

% of Total 5.8% .2% .2% .8% 23.1% .4% .2% 30.8%Count 67 4 10 4 0 243 2 330% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

20.3% 1.2% 3.0% 1.2% 0.0% 73.6% .6% 100.0%


69.1% 80.0% 90.9% 50.0% 0.0% 94.6% 50.0% 66.4%

% of Total 13.5% .8% 2.0% .8% 0.0% 48.9% .4% 66.4%

Architecture & Engineering (architecture, engineering, structural, continuing contracts, surveying, etc.)

Professional Services (construction management, attorney, accountant, consultant, etc.)

Non-Professional Services (maintenance services, janitorial, security, auto repair, etc.)

Q10 Is more than 50% of your company owned and controlled by a woman or women?

Yes

No

Goods (supplies, materials, equipment, commodities, etc.)

Total

Q10 Is more than 50% of your company owned and controlled by a woman or women? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total



Count 1 0 0 0 0 12 1 14% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

7.1% 0.0% 0.0% 0.0% 0.0% 85.7% 7.1% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 4.7% 25.0% 2.8%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 2.4% .2% 2.8%Count 97 5 11 8 115 257 4 497% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 0 0 0 0 114 232 0 346% within Q11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

0.0% 0.0% 0.0% 0.0% 32.9% 67.1% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 99.1% 90.3% 0.0% 69.6%

% of Total 0.0% 0.0% 0.0% 0.0% 22.9% 46.7% 0.0% 69.6%Count 97 0 0 0 0 0 0 97% within Q11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 19.5%


0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 100.0%


0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 1.6%


0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 1.0%


0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 100.0%


0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 2.2%

% of Total 0.0% 0.0% 2.2% 0.0% 0.0% 0.0% 0.0% 2.2%

Don't Know

Total

Q11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

Anglo/Caucasian/White

Black/African American

American Indian/Alaskan Native

Asian or Pacific Islander

Hispanic or Latino



Count 0 0 0 0 1 15 4 20% within Q11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

0.0% 0.0% 0.0% 0.0% 5.0% 75.0% 20.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 5.8% 100.0% 4.0%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 3.0% .8% 4.0%Count 0 0 0 0 0 10 0 10% within Q11 Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% 3.9% 0.0% 2.0%


19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 1 0 1 1 0 5% within Q13 What is the highest level of education completed by the primary owner of your company?

40.0% 0.0% 20.0% 0.0% 20.0% 20.0% 0.0% 100.0%


2.1% 0.0% 9.1% 0.0% .9% .4% 0.0% 1.0%

% of Total .4% 0.0% .2% 0.0% .2% .2% 0.0% 1.0%Count 9 0 3 2 22 23 0 59% within Q13 What is the highest level of education completed by the primary owner of your company?

15.3% 0.0% 5.1% 3.4% 37.3% 39.0% 0.0% 100.0%


9.3% 0.0% 27.3% 25.0% 19.1% 8.9% 0.0% 11.9%

% of Total 1.8% 0.0% .6% .4% 4.4% 4.6% 0.0% 11.9%Count 4 0 1 1 2 4 0 12% within Q13 What is the highest level of education completed by the primary owner of your company?

33.3% 0.0% 8.3% 8.3% 16.7% 33.3% 0.0% 100.0%


4.1% 0.0% 9.1% 12.5% 1.7% 1.6% 0.0% 2.4%

% of Total .8% 0.0% .2% .2% .4% .8% 0.0% 2.4%

Other

Q13 What is the highest level of education completed by the primary owner of your company?

Some High School

High School Graduate

Trade or Technical Education

Don't Know

Total

Q13 What is the highest level of education completed by the primary owner of your company? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total



Count 17 1 1 1 11 30 0 61% within Q13 What is the highest level of education completed by the primary owner of your company?

27.9% 1.6% 1.6% 1.6% 18.0% 49.2% 0.0% 100.0%


17.5% 20.0% 9.1% 12.5% 9.6% 11.7% 0.0% 12.3%

% of Total 3.4% .2% .2% .2% 2.2% 6.0% 0.0% 12.3%Count 44 2 2 2 54 136 4 244% within Q13 What is the highest level of education completed by the primary owner of your company?

18.0% .8% .8% .8% 22.1% 55.7% 1.6% 100.0%


45.4% 40.0% 18.2% 25.0% 47.0% 52.9% 100.0% 49.1%

% of Total 8.9% .4% .4% .4% 10.9% 27.4% .8% 49.1%Count 20 2 3 1 23 39 0 88% within Q13 What is the highest level of education completed by the primary owner of your company?

22.7% 2.3% 3.4% 1.1% 26.1% 44.3% 0.0% 100.0%


20.6% 40.0% 27.3% 12.5% 20.0% 15.2% 0.0% 17.7%

% of Total 4.0% .4% .6% .2% 4.6% 7.8% 0.0% 17.7%Count 1 0 0 1 2 24 0 28% within Q13 What is the highest level of education completed by the primary owner of your company?

3.6% 0.0% 0.0% 3.6% 7.1% 85.7% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 1.7% 9.3% 0.0% 5.6%

% of Total .2% 0.0% 0.0% .2% .4% 4.8% 0.0% 5.6%Count 97 5 11 8 115 257 4 497% within Q13 What is the highest level of education completed by the primary owner of your company?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 0 0 0 0 5 26 1 32% within Q14 In what year was your company established (range)?

0.0% 0.0% 0.0% 0.0% 15.6% 81.3% 3.1% 100.0%


0.0% 0.0% 0.0% 0.0% 4.3% 10.1% 25.0% 6.4%

% of Total 0.0% 0.0% 0.0% 0.0% 1.0% 5.2% .2% 6.4%Count 5 0 0 0 12 55 0 72% within Q14 In what year was your company established (range)?

6.9% 0.0% 0.0% 0.0% 16.7% 76.4% 0.0% 100.0%


5.2% 0.0% 0.0% 0.0% 10.4% 21.4% 0.0% 14.5%

% of Total 1.0% 0.0% 0.0% 0.0% 2.4% 11.1% 0.0% 14.5%

Some College

College Degree

Post Graduate Degree

Don't Know

Total

Q14 In what year was your company established (range)? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ14 In what year was your company established (range)?

Prior to 1940

1940 to 1969



Count 3 0 0 1 9 45 0 58% within Q14 In what year was your company established (range)?

5.2% 0.0% 0.0% 1.7% 15.5% 77.6% 0.0% 100.0%


3.1% 0.0% 0.0% 12.5% 7.8% 17.5% 0.0% 11.7%

% of Total .6% 0.0% 0.0% .2% 1.8% 9.1% 0.0% 11.7%Count 4 3 1 1 16 54 1 80% within Q14 In what year was your company established (range)?

5.0% 3.8% 1.3% 1.3% 20.0% 67.5% 1.3% 100.0%


4.1% 60.0% 9.1% 12.5% 13.9% 21.0% 25.0% 16.1%

% of Total .8% .6% .2% .2% 3.2% 10.9% .2% 16.1%Count 24 2 3 2 28 43 2 104% within Q14 In what year was your company established (range)?

23.1% 1.9% 2.9% 1.9% 26.9% 41.3% 1.9% 100.0%


24.7% 40.0% 27.3% 25.0% 24.3% 16.7% 50.0% 20.9%

% of Total 4.8% .4% .6% .4% 5.6% 8.7% .4% 20.9%Count 50 0 6 3 35 27 0 121% within Q14 In what year was your company established (range)?

41.3% 0.0% 5.0% 2.5% 28.9% 22.3% 0.0% 100.0%


51.5% 0.0% 54.5% 37.5% 30.4% 10.5% 0.0% 24.3%

% of Total 10.1% 0.0% 1.2% .6% 7.0% 5.4% 0.0% 24.3%Count 11 0 1 1 10 6 0 29% within Q14 In what year was your company established (range)?

37.9% 0.0% 3.4% 3.4% 34.5% 20.7% 0.0% 100.0%


11.3% 0.0% 9.1% 12.5% 8.7% 2.3% 0.0% 5.8%

% of Total 2.2% 0.0% .2% .2% 2.0% 1.2% 0.0% 5.8%Count 0 0 0 0 0 1 0 1% within Q14 In what year was your company established (range)?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .2% 0.0% .2%Count 97 5 11 8 115 257 4 497% within Q14 In what year was your company established (range)?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

1990 to 1999

2000 to 2009

2010 to 2014

2015

Total

1970 to 1979

1980 to 1989









Count 0 0 1 1 1 4 0 7% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

0.0% 0.0% 14.3% 14.3% 14.3% 57.1% 0.0% 100.0%


0.0% 0.0% 9.1% 12.5% .9% 1.6% 0.0% 1.4%

% of Total 0.0% 0.0% .2% .2% .2% .8% 0.0% 1.4%Count 6 0 0 2 5 9 0 22% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

27.3% 0.0% 0.0% 9.1% 22.7% 40.9% 0.0% 100.0%


6.2% 0.0% 0.0% 25.0% 4.3% 3.5% 0.0% 4.4%

% of Total 1.2% 0.0% 0.0% .4% 1.0% 1.8% 0.0% 4.4%Count 5 0 3 1 8 11 0 28% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

17.9% 0.0% 10.7% 3.6% 28.6% 39.3% 0.0% 100.0%


5.2% 0.0% 27.3% 12.5% 7.0% 4.3% 0.0% 5.6%

% of Total 1.0% 0.0% .6% .2% 1.6% 2.2% 0.0% 5.6%Count 8 0 2 0 7 9 0 26% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

30.8% 0.0% 7.7% 0.0% 26.9% 34.6% 0.0% 100.0%


8.2% 0.0% 18.2% 0.0% 6.1% 3.5% 0.0% 5.2%

% of Total 1.6% 0.0% .4% 0.0% 1.4% 1.8% 0.0% 5.2%Count 78 5 5 4 94 223 4 413% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

18.9% 1.2% 1.2% 1.0% 22.8% 54.0% 1.0% 100.0%


80.4% 100.0% 45.5% 50.0% 81.7% 86.8% 100.0% 83.1%

% of Total 15.7% 1.0% 1.0% .8% 18.9% 44.9% .8% 83.1%Count 0 0 0 0 0 1 0 1% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .2% 0.0% .2%

Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

0-5 years

6-10 years

11-15 years

16-20 years

20+ years

Don't Know



Count 97 5 11 8 115 257 4 497% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 70 3 6 4 73 91 2 249% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

28.1% 1.2% 2.4% 1.6% 29.3% 36.5% .8% 100.0%


72.2% 60.0% 54.5% 50.0% 63.5% 35.4% 50.0% 50.1%

% of Total 14.1% .6% 1.2% .8% 14.7% 18.3% .4% 50.1%Count 20 0 1 1 18 45 0 85% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

23.5% 0.0% 1.2% 1.2% 21.2% 52.9% 0.0% 100.0%


20.6% 0.0% 9.1% 12.5% 15.7% 17.5% 0.0% 17.1%

% of Total 4.0% 0.0% .2% .2% 3.6% 9.1% 0.0% 17.1%Count 2 0 2 1 3 18 1 27% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

7.4% 0.0% 7.4% 3.7% 11.1% 66.7% 3.7% 100.0%


2.1% 0.0% 18.2% 12.5% 2.6% 7.0% 25.0% 5.4%

% of Total .4% 0.0% .4% .2% .6% 3.6% .2% 5.4%Count 0 0 0 1 5 11 0 17% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

0.0% 0.0% 0.0% 5.9% 29.4% 64.7% 0.0% 100.0%


0.0% 0.0% 0.0% 12.5% 4.3% 4.3% 0.0% 3.4%

% of Total 0.0% 0.0% 0.0% .2% 1.0% 2.2% 0.0% 3.4%Count 4 2 2 1 16 90 1 116% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

3.4% 1.7% 1.7% .9% 13.8% 77.6% .9% 100.0%


4.1% 40.0% 18.2% 12.5% 13.9% 35.0% 25.0% 23.3%

% of Total .8% .4% .4% .2% 3.2% 18.1% .2% 23.3%

41+ employees

Total

Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

0-10 employees

11-20 employees

21-30 employees

31-40 employees



Count 1 0 0 0 0 2 0 3% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

33.3% 0.0% 0.0% 0.0% 0.0% 66.7% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .6%

% of Total .2% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .6%Count 97 5 11 8 115 257 4 497% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 36 2 1 0 11 8 0 58% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

62.1% 3.4% 1.7% 0.0% 19.0% 13.8% 0.0% 100.0%


37.1% 40.0% 9.1% 0.0% 9.6% 3.1% 0.0% 11.7%

% of Total 7.2% .4% .2% 0.0% 2.2% 1.6% 0.0% 11.7%Count 12 0 2 1 10 12 0 37% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

32.4% 0.0% 5.4% 2.7% 27.0% 32.4% 0.0% 100.0%


12.4% 0.0% 18.2% 12.5% 8.7% 4.7% 0.0% 7.4%

% of Total 2.4% 0.0% .4% .2% 2.0% 2.4% 0.0% 7.4%Count 18 0 2 1 24 23 0 68% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

26.5% 0.0% 2.9% 1.5% 35.3% 33.8% 0.0% 100.0%


18.6% 0.0% 18.2% 12.5% 20.9% 8.9% 0.0% 13.7%


23.8% 2.4% 0.0% 2.4% 31.0% 38.1% 2.4% 100.0%


10.3% 20.0% 0.0% 12.5% 11.3% 6.2% 25.0% 8.5%

% of Total 2.0% .2% 0.0% .2% 2.6% 3.2% .2% 8.5%

Don't Know

Total

Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total

Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

Up to $50,000?

$50,001 to $100,000?

$100,001 to $300,000?

$300,001 to $500,000?




13.7% 0.0% 2.0% 2.0% 33.3% 49.0% 0.0% 100.0%


7.2% 0.0% 9.1% 12.5% 14.8% 9.7% 0.0% 10.3%


1.4% 0.0% 2.8% 4.2% 25.4% 64.8% 1.4% 100.0%


1.0% 0.0% 18.2% 37.5% 15.7% 17.9% 25.0% 14.3%

% of Total .2% 0.0% .4% .6% 3.6% 9.3% .2% 14.3%Count 4 0 1 0 1 28 1 35% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

11.4% 0.0% 2.9% 0.0% 2.9% 80.0% 2.9% 100.0%


4.1% 0.0% 9.1% 0.0% .9% 10.9% 25.0% 7.0%

% of Total .8% 0.0% .2% 0.0% .2% 5.6% .2% 7.0%Count 1 1 0 0 3 17 0 22% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

4.5% 4.5% 0.0% 0.0% 13.6% 77.3% 0.0% 100.0%


1.0% 20.0% 0.0% 0.0% 2.6% 6.6% 0.0% 4.4%

% of Total .2% .2% 0.0% 0.0% .6% 3.4% 0.0% 4.4%Count 3 1 0 0 4 53 0 61% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

4.9% 1.6% 0.0% 0.0% 6.6% 86.9% 0.0% 100.0%


3.1% 20.0% 0.0% 0.0% 3.5% 20.6% 0.0% 12.3%

% of Total .6% .2% 0.0% 0.0% .8% 10.7% 0.0% 12.3%Count 5 0 2 1 14 29 1 52% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

9.6% 0.0% 3.8% 1.9% 26.9% 55.8% 1.9% 100.0%


5.2% 0.0% 18.2% 12.5% 12.2% 11.3% 25.0% 10.5%

% of Total 1.0% 0.0% .4% .2% 2.8% 5.8% .2% 10.5%

Don't Know

$500,001 to $1 million?

$1,000,001 to $3 million?

$3,000,001 to $5 million?

$5,000,001 to $10 million?

Over $10 million?




19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 34 3 5 6 34 69 1 152% within Q18 What percentage of gross revenues was earned from the District?

22.4% 2.0% 3.3% 3.9% 22.4% 45.4% .7% 100.0%


35.1% 60.0% 45.5% 75.0% 29.6% 26.8% 25.0% 30.6%

% of Total 6.8% .6% 1.0% 1.2% 6.8% 13.9% .2% 30.6%Count 39 0 2 2 59 153 3 258% within Q18 What percentage of gross revenues was earned from the District?

15.1% 0.0% .8% .8% 22.9% 59.3% 1.2% 100.0%


40.2% 0.0% 18.2% 25.0% 51.3% 59.5% 75.0% 51.9%

% of Total 7.8% 0.0% .4% .4% 11.9% 30.8% .6% 51.9%Count 8 0 2 0 8 7 0 25% within Q18 What percentage of gross revenues was earned from the District?

32.0% 0.0% 8.0% 0.0% 32.0% 28.0% 0.0% 100.0%


8.2% 0.0% 18.2% 0.0% 7.0% 2.7% 0.0% 5.0%

% of Total 1.6% 0.0% .4% 0.0% 1.6% 1.4% 0.0% 5.0%Count 10 1 1 0 5 16 0 33% within Q18 What percentage of gross revenues was earned from the District?

30.3% 3.0% 3.0% 0.0% 15.2% 48.5% 0.0% 100.0%


10.3% 20.0% 9.1% 0.0% 4.3% 6.2% 0.0% 6.6%

% of Total 2.0% .2% .2% 0.0% 1.0% 3.2% 0.0% 6.6%Count 3 1 0 0 1 3 0 8% within Q18 What percentage of gross revenues was earned from the District?

37.5% 12.5% 0.0% 0.0% 12.5% 37.5% 0.0% 100.0%


3.1% 20.0% 0.0% 0.0% .9% 1.2% 0.0% 1.6%

% of Total .6% .2% 0.0% 0.0% .2% .6% 0.0% 1.6%Count 3 0 1 0 8 9 0 21% within Q18 What percentage of gross revenues was earned from the District?

14.3% 0.0% 4.8% 0.0% 38.1% 42.9% 0.0% 100.0%


3.1% 0.0% 9.1% 0.0% 7.0% 3.5% 0.0% 4.2%

% of Total .6% 0.0% .2% 0.0% 1.6% 1.8% 0.0% 4.2%

Q18 What percentage of gross revenues was earned from the District?

No Percentage of Gross Revenue

1% to 15%

16% to 25%

26% to 50%

51% to 74%

75% to 100%

Total

Q18 What percentage of gross revenues was earned from the District? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total



Count 97 5 11 8 115 257 4 497% within Q18 What percentage of gross revenues was earned from the District?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 1 2 5 17 0 28% within Q18 What percentage of these gross revenues was earned from the Private Sector?

10.7% 0.0% 3.6% 7.1% 17.9% 60.7% 0.0% 100.0%


3.1% 0.0% 9.1% 25.0% 4.3% 6.6% 0.0% 5.6%

% of Total .6% 0.0% .2% .4% 1.0% 3.4% 0.0% 5.6%Count 11 1 0 1 10 9 0 32% within Q18 What percentage of these gross revenues was earned from the Private Sector?

34.4% 3.1% 0.0% 3.1% 31.3% 28.1% 0.0% 100.0%


11.3% 20.0% 0.0% 12.5% 8.7% 3.5% 0.0% 6.4%

% of Total 2.2% .2% 0.0% .2% 2.0% 1.8% 0.0% 6.4%Count 5 1 0 0 8 11 0 25% within Q18 What percentage of these gross revenues was earned from the Private Sector?

20.0% 4.0% 0.0% 0.0% 32.0% 44.0% 0.0% 100.0%


5.2% 20.0% 0.0% 0.0% 7.0% 4.3% 0.0% 5.0%

% of Total 1.0% .2% 0.0% 0.0% 1.6% 2.2% 0.0% 5.0%Count 18 1 1 1 13 48 0 82% within Q18 What percentage of these gross revenues was earned from the Private Sector?

22.0% 1.2% 1.2% 1.2% 15.9% 58.5% 0.0% 100.0%


18.6% 20.0% 9.1% 12.5% 11.3% 18.7% 0.0% 16.5%

% of Total 3.6% .2% .2% .2% 2.6% 9.7% 0.0% 16.5%Count 9 0 1 1 10 15 1 37% within Q18 What percentage of these gross revenues was earned from the Private Sector?

24.3% 0.0% 2.7% 2.7% 27.0% 40.5% 2.7% 100.0%


9.3% 0.0% 9.1% 12.5% 8.7% 5.8% 25.0% 7.4%

% of Total 1.8% 0.0% .2% .2% 2.0% 3.0% .2% 7.4%Count 51 2 8 3 69 157 3 293% within Q18 What percentage of these gross revenues was earned from the Private Sector?

17.4% .7% 2.7% 1.0% 23.5% 53.6% 1.0% 100.0%


52.6% 40.0% 72.7% 37.5% 60.0% 61.1% 75.0% 59.0%

% of Total 10.3% .4% 1.6% .6% 13.9% 31.6% .6% 59.0%

Total

Q18 What percentage of these gross revenues was earned from the Private Sector? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ18 What percentage of these gross revenues was earned from the Private Sector?


1% to 15%

16% to 25%

26% to 50%

51% to 74%

75% to 100%



Count 97 5 11 8 115 257 4 497% within Q18 What percentage of these gross revenues was earned from the Private Sector?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 42 2 7 1 42 82 0 176% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

23.9% 1.1% 4.0% .6% 23.9% 46.6% 0.0% 100.0%


43.3% 40.0% 63.6% 12.5% 36.5% 31.9% 0.0% 35.4%

% of Total 8.5% .4% 1.4% .2% 8.5% 16.5% 0.0% 35.4%Count 14 1 2 2 34 76 1 130% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

10.8% .8% 1.5% 1.5% 26.2% 58.5% .8% 100.0%


14.4% 20.0% 18.2% 25.0% 29.6% 29.6% 25.0% 26.2%

% of Total 2.8% .2% .4% .4% 6.8% 15.3% .2% 26.2%Count 8 0 1 0 9 28 3 49% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

16.3% 0.0% 2.0% 0.0% 18.4% 57.1% 6.1% 100.0%


8.2% 0.0% 9.1% 0.0% 7.8% 10.9% 75.0% 9.9%

% of Total 1.6% 0.0% .2% 0.0% 1.8% 5.6% .6% 9.9%Count 20 1 1 2 15 39 0 78% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

25.6% 1.3% 1.3% 2.6% 19.2% 50.0% 0.0% 100.0%


20.6% 20.0% 9.1% 25.0% 13.0% 15.2% 0.0% 15.7%

% of Total 4.0% .2% .2% .4% 3.0% 7.8% 0.0% 15.7%Count 4 0 0 0 6 10 0 20% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

20.0% 0.0% 0.0% 0.0% 30.0% 50.0% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 5.2% 3.9% 0.0% 4.0%

% of Total .8% 0.0% 0.0% 0.0% 1.2% 2.0% 0.0% 4.0%Count 9 1 0 3 9 22 0 44% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

20.5% 2.3% 0.0% 6.8% 20.5% 50.0% 0.0% 100.0%


9.3% 20.0% 0.0% 37.5% 7.8% 8.6% 0.0% 8.9%

% of Total 1.8% .2% 0.0% .6% 1.8% 4.4% 0.0% 8.9%

Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?


1% to 15%

16% to 25%

26% to 50%

51% to 74%

75% to 100%

Total

Q18 What percentage of these gross revenues was earned from the Non-District Public Sector? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total



Count 97 5 11 8 115 257 4 497% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 51 4 3 4 19 5 0 86% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

59.3% 4.7% 3.5% 4.7% 22.1% 5.8% 0.0% 100.0%


52.6% 80.0% 27.3% 50.0% 16.5% 1.9% 0.0% 17.3%

% of Total 10.3% .8% .6% .8% 3.8% 1.0% 0.0% 17.3%Count 45 1 8 3 95 241 4 397% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

11.3% .3% 2.0% .8% 23.9% 60.7% 1.0% 100.0%


46.4% 20.0% 72.7% 37.5% 82.6% 93.8% 100.0% 79.9%

% of Total 9.1% .2% 1.6% .6% 19.1% 48.5% .8% 79.9%Count 1 0 0 1 1 11 0 14% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

7.1% 0.0% 0.0% 7.1% 7.1% 78.6% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% .9% 4.3% 0.0% 2.8%

% of Total .2% 0.0% 0.0% .2% .2% 2.2% 0.0% 2.8%Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

Yes

No

Don't Know

Total









Count 41 3 1 1 24 46 1 117% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

35.0% 2.6% .9% .9% 20.5% 39.3% .9% 100.0%


42.3% 60.0% 9.1% 12.5% 20.9% 17.9% 25.0% 23.5%

% of Total 8.2% .6% .2% .2% 4.8% 9.3% .2% 23.5%Count 55 2 10 6 89 201 3 366% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

15.0% .5% 2.7% 1.6% 24.3% 54.9% .8% 100.0%


56.7% 40.0% 90.9% 75.0% 77.4% 78.2% 75.0% 73.6%

% of Total 11.1% .4% 2.0% 1.2% 17.9% 40.4% .6% 73.6%Count 1 0 0 1 2 10 0 14% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

7.1% 0.0% 0.0% 7.1% 14.3% 71.4% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 1.7% 3.9% 0.0% 2.8%

% of Total .2% 0.0% 0.0% .2% .4% 2.0% 0.0% 2.8%Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 15 1 1 1 46 3 1 68% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

22.1% 1.5% 1.5% 1.5% 67.6% 4.4% 1.5% 100.0%


15.5% 20.0% 9.1% 12.5% 40.0% 1.2% 25.0% 13.7%

% of Total 3.0% .2% .2% .2% 9.3% .6% .2% 13.7%

Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

Yes

No

Don't Know

Total

Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

Yes



Count 80 4 10 6 68 247 3 418% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

19.1% 1.0% 2.4% 1.4% 16.3% 59.1% .7% 100.0%


82.5% 80.0% 90.9% 75.0% 59.1% 96.1% 75.0% 84.1%

% of Total 16.1% .8% 2.0% 1.2% 13.7% 49.7% .6% 84.1%Count 2 0 0 1 1 7 0 11% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

18.2% 0.0% 0.0% 9.1% 9.1% 63.6% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% .9% 2.7% 0.0% 2.2%

% of Total .4% 0.0% 0.0% .2% .2% 1.4% 0.0% 2.2%Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 26 1 0 2 7 2 0 38% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

68.4% 2.6% 0.0% 5.3% 18.4% 5.3% 0.0% 100.0%


26.8% 20.0% 0.0% 25.0% 6.1% .8% 0.0% 7.6%

% of Total 5.2% .2% 0.0% .4% 1.4% .4% 0.0% 7.6%Count 70 4 11 5 105 247 4 446% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

15.7% .9% 2.5% 1.1% 23.5% 55.4% .9% 100.0%


72.2% 80.0% 100.0% 62.5% 91.3% 96.1% 100.0% 89.7%

% of Total 14.1% .8% 2.2% 1.0% 21.1% 49.7% .8% 89.7%Count 1 0 0 1 3 8 0 13% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

7.7% 0.0% 0.0% 7.7% 23.1% 61.5% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 2.6% 3.1% 0.0% 2.6%

% of Total .2% 0.0% 0.0% .2% .6% 1.6% 0.0% 2.6%

No

Don't Know

Total

Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

Yes

No

Don't Know



Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 33 1 1 3 13 5 0 56% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

58.9% 1.8% 1.8% 5.4% 23.2% 8.9% 0.0% 100.0%


34.0% 20.0% 9.1% 37.5% 11.3% 1.9% 0.0% 11.3%

% of Total 6.6% .2% .2% .6% 2.6% 1.0% 0.0% 11.3%Count 62 4 10 4 102 241 4 427% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

14.5% .9% 2.3% .9% 23.9% 56.4% .9% 100.0%


63.9% 80.0% 90.9% 50.0% 88.7% 93.8% 100.0% 85.9%

% of Total 12.5% .8% 2.0% .8% 20.5% 48.5% .8% 85.9%Count 2 0 0 1 0 11 0 14% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

14.3% 0.0% 0.0% 7.1% 0.0% 78.6% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% 0.0% 4.3% 0.0% 2.8%

% of Total .4% 0.0% 0.0% .2% 0.0% 2.2% 0.0% 2.8%Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 9 2 0 0 2 1 0 14% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

64.3% 14.3% 0.0% 0.0% 14.3% 7.1% 0.0% 100.0%


9.3% 40.0% 0.0% 0.0% 1.7% .4% 0.0% 2.8%

% of Total 1.8% .4% 0.0% 0.0% .4% .2% 0.0% 2.8%

Total

Q19 Does your company hold any HubZone certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any HubZone certifications from a recognized certification agency?

Yes

No

Don't Know

Total

Q19 Does your company hold any 8A certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any 8A certifications from a recognized certification agency?

Yes



Count 87 3 11 7 113 247 4 472% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

18.4% .6% 2.3% 1.5% 23.9% 52.3% .8% 100.0%


89.7% 60.0% 100.0% 87.5% 98.3% 96.1% 100.0% 95.0%

% of Total 17.5% .6% 2.2% 1.4% 22.7% 49.7% .8% 95.0%Count 1 0 0 1 0 9 0 11% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

9.1% 0.0% 0.0% 9.1% 0.0% 81.8% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 0.0% 3.5% 0.0% 2.2%

% of Total .2% 0.0% 0.0% .2% 0.0% 1.8% 0.0% 2.2%Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 1 0 1 3 9 0 17% within Q19 Does your company hold any other certifications from a recognized certification agency?

17.6% 5.9% 0.0% 5.9% 17.6% 52.9% 0.0% 100.0%


3.1% 20.0% 0.0% 12.5% 2.6% 3.5% 0.0% 3.4%

% of Total .6% .2% 0.0% .2% .6% 1.8% 0.0% 3.4%Count 93 4 11 6 112 241 4 471% within Q19 Does your company hold any other certifications from a recognized certification agency?

19.7% .8% 2.3% 1.3% 23.8% 51.2% .8% 100.0%


95.9% 80.0% 100.0% 75.0% 97.4% 93.8% 100.0% 94.8%

% of Total 18.7% .8% 2.2% 1.2% 22.5% 48.5% .8% 94.8%Count 1 0 0 1 0 7 0 9% within Q19 Does your company hold any other certifications from a recognized certification agency?

11.1% 0.0% 0.0% 11.1% 0.0% 77.8% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 0.0% 2.7% 0.0% 1.8%

% of Total .2% 0.0% 0.0% .2% 0.0% 1.4% 0.0% 1.8%Count 97 5 11 8 115 257 4 497% within Q19 Does your company hold any other certifications from a recognized certification agency?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

No

Don't Know

Total

Q19 Does your company hold any other certifications from a recognized certification agency? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ19 Does your company hold any other certifications from a recognized certification agency?

Yes

No

Don't Know

Total









Count 47 2 9 6 65 152 3 284% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

16.5% .7% 3.2% 2.1% 22.9% 53.5% 1.1% 100.0%


48.5% 40.0% 81.8% 75.0% 56.5% 59.1% 75.0% 57.1%

% of Total 9.5% .4% 1.8% 1.2% 13.1% 30.6% .6% 57.1%Count 18 2 1 1 23 51 1 97% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

18.6% 2.1% 1.0% 1.0% 23.7% 52.6% 1.0% 100.0%


18.6% 40.0% 9.1% 12.5% 20.0% 19.8% 25.0% 19.5%

% of Total 3.6% .4% .2% .2% 4.6% 10.3% .2% 19.5%Count 32 1 1 1 27 54 0 116% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

27.6% .9% .9% .9% 23.3% 46.6% 0.0% 100.0%


33.0% 20.0% 9.1% 12.5% 23.5% 21.0% 0.0% 23.3%

% of Total 6.4% .2% .2% .2% 5.4% 10.9% 0.0% 23.3%Count 97 5 11 8 115 257 4 497% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 8 0 2 0 8 17 0 35% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

22.9% 0.0% 5.7% 0.0% 22.9% 48.6% 0.0% 100.0%


8.2% 0.0% 18.2% 0.0% 7.0% 6.6% 0.0% 7.0%

% of Total 1.6% 0.0% .4% 0.0% 1.6% 3.4% 0.0% 7.0%

Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

Prime contractor/consultant or vendor

Subcontractor/subconsultant or supplier

Both

Total

Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

None




25.0% 0.0% 3.7% 2.2% 31.6% 37.5% 0.0% 100.0%


35.1% 0.0% 45.5% 37.5% 37.4% 19.8% 0.0% 27.4%

% of Total 6.8% 0.0% 1.0% .6% 8.7% 10.3% 0.0% 27.4%Count 10 1 0 2 13 24 0 50% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

20.0% 2.0% 0.0% 4.0% 26.0% 48.0% 0.0% 100.0%


10.3% 20.0% 0.0% 25.0% 11.3% 9.3% 0.0% 10.1%

% of Total 2.0% .2% 0.0% .4% 2.6% 4.8% 0.0% 10.1%Count 5 0 1 0 5 11 0 22% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

22.7% 0.0% 4.5% 0.0% 22.7% 50.0% 0.0% 100.0%


5.2% 0.0% 9.1% 0.0% 4.3% 4.3% 0.0% 4.4%

% of Total 1.0% 0.0% .2% 0.0% 1.0% 2.2% 0.0% 4.4%Count 6 0 1 0 4 7 0 18% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

33.3% 0.0% 5.6% 0.0% 22.2% 38.9% 0.0% 100.0%


6.2% 0.0% 9.1% 0.0% 3.5% 2.7% 0.0% 3.6%

% of Total 1.2% 0.0% .2% 0.0% .8% 1.4% 0.0% 3.6%Count 6 0 0 0 3 4 0 13% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

46.2% 0.0% 0.0% 0.0% 23.1% 30.8% 0.0% 100.0%


6.2% 0.0% 0.0% 0.0% 2.6% 1.6% 0.0% 2.6%

% of Total 1.2% 0.0% 0.0% 0.0% .6% .8% 0.0% 2.6%Count 0 0 1 0 2 10 0 13% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

0.0% 0.0% 7.7% 0.0% 15.4% 76.9% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 1.7% 3.9% 0.0% 2.6%

% of Total 0.0% 0.0% .2% 0.0% .4% 2.0% 0.0% 2.6%

Up to $50,000?

$50,001 to $100,000?

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?

$400,001 to $500,000?




5.6% 0.0% 0.0% 5.6% 11.1% 77.8% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 1.7% 5.4% 0.0% 3.6%

% of Total .2% 0.0% 0.0% .2% .4% 2.8% 0.0% 3.6%Count 3 2 0 0 7 50 2 64% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

4.7% 3.1% 0.0% 0.0% 10.9% 78.1% 3.1% 100.0%


3.1% 40.0% 0.0% 0.0% 6.1% 19.5% 50.0% 12.9%

% of Total .6% .4% 0.0% 0.0% 1.4% 10.1% .4% 12.9%Count 6 0 0 1 5 18 1 31% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

19.4% 0.0% 0.0% 3.2% 16.1% 58.1% 3.2% 100.0%


6.2% 0.0% 0.0% 12.5% 4.3% 7.0% 25.0% 6.2%

% of Total 1.2% 0.0% 0.0% .2% 1.0% 3.6% .2% 6.2%Count 18 2 1 1 23 51 1 97% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

18.6% 2.1% 1.0% 1.0% 23.7% 52.6% 1.0% 100.0%


18.6% 40.0% 9.1% 12.5% 20.0% 19.8% 25.0% 19.5%

% of Total 3.6% .4% .2% .2% 4.6% 10.3% .2% 19.5%Count 97 5 11 8 115 257 4 497% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

No Response

Total

$500,001 to $1 million?

Over $1 million?

Don't Know









Count 7 0 2 0 9 14 0 32% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

21.9% 0.0% 6.3% 0.0% 28.1% 43.8% 0.0% 100.0%


7.2% 0.0% 18.2% 0.0% 7.8% 5.4% 0.0% 6.4%

% of Total 1.4% 0.0% .4% 0.0% 1.8% 2.8% 0.0% 6.4%Count 32 0 4 4 44 61 0 145% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

22.1% 0.0% 2.8% 2.8% 30.3% 42.1% 0.0% 100.0%


33.0% 0.0% 36.4% 50.0% 38.3% 23.7% 0.0% 29.2%

% of Total 6.4% 0.0% .8% .8% 8.9% 12.3% 0.0% 29.2%Count 8 0 0 1 7 18 0 34% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

23.5% 0.0% 0.0% 2.9% 20.6% 52.9% 0.0% 100.0%


8.2% 0.0% 0.0% 12.5% 6.1% 7.0% 0.0% 6.8%

% of Total 1.6% 0.0% 0.0% .2% 1.4% 3.6% 0.0% 6.8%Count 2 1 1 0 2 10 0 16% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

12.5% 6.3% 6.3% 0.0% 12.5% 62.5% 0.0% 100.0%


2.1% 20.0% 9.1% 0.0% 1.7% 3.9% 0.0% 3.2%

% of Total .4% .2% .2% 0.0% .4% 2.0% 0.0% 3.2%Count 6 0 2 1 1 4 0 14% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

42.9% 0.0% 14.3% 7.1% 7.1% 28.6% 0.0% 100.0%


6.2% 0.0% 18.2% 12.5% .9% 1.6% 0.0% 2.8%

% of Total 1.2% 0.0% .4% .2% .2% .8% 0.0% 2.8%Count 1 0 0 0 1 1 0 3% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

33.3% 0.0% 0.0% 0.0% 33.3% 33.3% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% .4% 0.0% .6%

% of Total .2% 0.0% 0.0% 0.0% .2% .2% 0.0% .6%

Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

None

Up to $50,000?

$50,001 to $100,000?

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?



Count 1 0 0 0 0 3 0 4% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

25.0% 0.0% 0.0% 0.0% 0.0% 75.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 1.2% 0.0% .8%

% of Total .2% 0.0% 0.0% 0.0% 0.0% .6% 0.0% .8%Count 0 0 0 0 1 6 0 7% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

0.0% 0.0% 0.0% 0.0% 14.3% 85.7% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 2.3% 0.0% 1.4%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 1.2% 0.0% 1.4%Count 3 2 0 0 6 19 1 31% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

9.7% 6.5% 0.0% 0.0% 19.4% 61.3% 3.2% 100.0%


3.1% 40.0% 0.0% 0.0% 5.2% 7.4% 25.0% 6.2%

% of Total .6% .4% 0.0% 0.0% 1.2% 3.8% .2% 6.2%Count 5 0 1 1 6 17 1 31% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

16.1% 0.0% 3.2% 3.2% 19.4% 54.8% 3.2% 100.0%


5.2% 0.0% 9.1% 12.5% 5.2% 6.6% 25.0% 6.2%

% of Total 1.0% 0.0% .2% .2% 1.2% 3.4% .2% 6.2%Count 32 2 1 1 38 104 2 180% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Don't Know

No Response

Total

$400,001 to $500,000?

$500,001 to $1 million?

Over $1 million?









Count 4 0 0 0 4 5 0 13% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

30.8% 0.0% 0.0% 0.0% 30.8% 38.5% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 3.5% 1.9% 0.0% 2.6%

% of Total .8% 0.0% 0.0% 0.0% .8% 1.0% 0.0% 2.6%Count 61 3 10 7 73 148 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

20.1% 1.0% 3.3% 2.3% 24.0% 48.7% .7% 100.0%


62.9% 60.0% 90.9% 87.5% 63.5% 57.6% 50.0% 61.2%

% of Total 12.3% .6% 2.0% 1.4% 14.7% 29.8% .4% 61.2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 7 0 1 0 1 4 0 13% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

53.8% 0.0% 7.7% 0.0% 7.7% 30.8% 0.0% 100.0%


7.2% 0.0% 9.1% 0.0% .9% 1.6% 0.0% 2.6%

% of Total 1.4% 0.0% .2% 0.0% .2% .8% 0.0% 2.6%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


Total


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

Yes

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

Yes

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements? * Race, Ethnicity, Gender Classification (Business Ownership Classification)



Count 58 3 9 7 76 149 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

19.1% 1.0% 3.0% 2.3% 25.0% 49.0% .7% 100.0%


59.8% 60.0% 81.8% 87.5% 66.1% 58.0% 50.0% 61.2%

% of Total 11.7% .6% 1.8% 1.4% 15.3% 30.0% .4% 61.2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 0 0 3 1 0 7% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

42.9% 0.0% 0.0% 0.0% 42.9% 14.3% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% 2.6% .4% 0.0% 1.4%

% of Total .6% 0.0% 0.0% 0.0% .6% .2% 0.0% 1.4%Count 62 3 10 7 74 152 2 310% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

20.0% 1.0% 3.2% 2.3% 23.9% 49.0% .6% 100.0%


63.9% 60.0% 90.9% 87.5% 64.3% 59.1% 50.0% 62.4%

% of Total 12.5% .6% 2.0% 1.4% 14.9% 30.6% .4% 62.4%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 1 0 2 4 0 9% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

22.2% 0.0% 11.1% 0.0% 22.2% 44.4% 0.0% 100.0%


2.1% 0.0% 9.1% 0.0% 1.7% 1.6% 0.0% 1.8%

% of Total .4% 0.0% .2% 0.0% .4% .8% 0.0% 1.8%Count 63 3 9 7 75 149 2 308% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

20.5% 1.0% 2.9% 2.3% 24.4% 48.4% .6% 100.0%


64.9% 60.0% 81.8% 87.5% 65.2% 58.0% 50.0% 62.0%

% of Total 12.7% .6% 1.8% 1.4% 15.1% 30.0% .4% 62.0%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

Yes

No

No Response

Total









Count 4 0 2 0 5 1 0 12% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

33.3% 0.0% 16.7% 0.0% 41.7% 8.3% 0.0% 100.0%


4.1% 0.0% 18.2% 0.0% 4.3% .4% 0.0% 2.4%

% of Total .8% 0.0% .4% 0.0% 1.0% .2% 0.0% 2.4%Count 61 3 8 7 72 151 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

20.1% 1.0% 2.6% 2.3% 23.7% 49.7% .7% 100.0%


62.9% 60.0% 72.7% 87.5% 62.6% 58.8% 50.0% 61.2%

% of Total 12.3% .6% 1.6% 1.4% 14.5% 30.4% .4% 61.2%Count 0 0 0 0 0 1 0 1% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .2% 0.0% .2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 9 0 1 0 4 5 0 19% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

47.4% 0.0% 5.3% 0.0% 21.1% 26.3% 0.0% 100.0%


9.3% 0.0% 9.1% 0.0% 3.5% 1.9% 0.0% 3.8%

% of Total 1.8% 0.0% .2% 0.0% .8% 1.0% 0.0% 3.8%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

Yes

No

Don't Know

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

Yes



Count 56 3 9 7 73 148 2 298% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

18.8% 1.0% 3.0% 2.3% 24.5% 49.7% .7% 100.0%


57.7% 60.0% 81.8% 87.5% 63.5% 57.6% 50.0% 60.0%

% of Total 11.3% .6% 1.8% 1.4% 14.7% 29.8% .4% 60.0%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 0 0 1 0 3 9 0 13% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

0.0% 0.0% 7.7% 0.0% 23.1% 69.2% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 2.6% 3.5% 0.0% 2.6%

% of Total 0.0% 0.0% .2% 0.0% .6% 1.8% 0.0% 2.6%Count 65 3 9 7 74 144 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

21.4% 1.0% 3.0% 2.3% 24.3% 47.4% .7% 100.0%


67.0% 60.0% 81.8% 87.5% 64.3% 56.0% 50.0% 61.2%

% of Total 13.1% .6% 1.8% 1.4% 14.9% 29.0% .4% 61.2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 1 1 4 12 1 22% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

13.6% 0.0% 4.5% 4.5% 18.2% 54.5% 4.5% 100.0%


3.1% 0.0% 9.1% 12.5% 3.5% 4.7% 25.0% 4.4%

% of Total .6% 0.0% .2% .2% .8% 2.4% .2% 4.4%Count 62 3 9 6 73 141 1 295% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

21.0% 1.0% 3.1% 2.0% 24.7% 47.8% .3% 100.0%


63.9% 60.0% 81.8% 75.0% 63.5% 54.9% 25.0% 59.4%

% of Total 12.5% .6% 1.8% 1.2% 14.7% 28.4% .2% 59.4%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

Yes

No

No Response

Total









Count 7 0 1 0 6 14 0 28% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

25.0% 0.0% 3.6% 0.0% 21.4% 50.0% 0.0% 100.0%


7.2% 0.0% 9.1% 0.0% 5.2% 5.4% 0.0% 5.6%

% of Total 1.4% 0.0% .2% 0.0% 1.2% 2.8% 0.0% 5.6%Count 58 3 9 7 71 139 2 289% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

20.1% 1.0% 3.1% 2.4% 24.6% 48.1% .7% 100.0%


59.8% 60.0% 81.8% 87.5% 61.7% 54.1% 50.0% 58.1%

% of Total 11.7% .6% 1.8% 1.4% 14.3% 28.0% .4% 58.1%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 2 0 11 6 0 23% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

17.4% 0.0% 8.7% 0.0% 47.8% 26.1% 0.0% 100.0%


4.1% 0.0% 18.2% 0.0% 9.6% 2.3% 0.0% 4.6%

% of Total .8% 0.0% .4% 0.0% 2.2% 1.2% 0.0% 4.6%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

Yes

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

Yes



Count 61 3 8 7 65 147 2 293% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

20.8% 1.0% 2.7% 2.4% 22.2% 50.2% .7% 100.0%


62.9% 60.0% 72.7% 87.5% 56.5% 57.2% 50.0% 59.0%

% of Total 12.3% .6% 1.6% 1.4% 13.1% 29.6% .4% 59.0%Count 0 0 0 0 1 0 0 1% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 0 0 1 0 4 3 0 8% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

0.0% 0.0% 12.5% 0.0% 50.0% 37.5% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 3.5% 1.2% 0.0% 1.6%

% of Total 0.0% 0.0% .2% 0.0% .8% .6% 0.0% 1.6%

No

Don't Know

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

Yes



Count 65 3 9 7 73 150 2 309% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

21.0% 1.0% 2.9% 2.3% 23.6% 48.5% .6% 100.0%


67.0% 60.0% 81.8% 87.5% 63.5% 58.4% 50.0% 62.2%

% of Total 13.1% .6% 1.8% 1.4% 14.7% 30.2% .4% 62.2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 1 0 2 2 0 8% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

37.5% 0.0% 12.5% 0.0% 25.0% 25.0% 0.0% 100.0%


3.1% 0.0% 9.1% 0.0% 1.7% .8% 0.0% 1.6%

% of Total .6% 0.0% .2% 0.0% .4% .4% 0.0% 1.6%Count 62 3 9 7 75 151 2 309% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

20.1% 1.0% 2.9% 2.3% 24.3% 48.9% .6% 100.0%


63.9% 60.0% 81.8% 87.5% 65.2% 58.8% 50.0% 62.2%

% of Total 12.5% .6% 1.8% 1.4% 15.1% 30.4% .4% 62.2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 0 0 5 5 0 14% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

28.6% 0.0% 0.0% 0.0% 35.7% 35.7% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 4.3% 1.9% 0.0% 2.8%

% of Total .8% 0.0% 0.0% 0.0% 1.0% 1.0% 0.0% 2.8%Count 61 3 10 7 72 148 2 303% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

20.1% 1.0% 3.3% 2.3% 23.8% 48.8% .7% 100.0%


62.9% 60.0% 90.9% 87.5% 62.6% 57.6% 50.0% 61.0%

% of Total 12.3% .6% 2.0% 1.4% 14.5% 29.8% .4% 61.0%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

Yes

No

No Response

Total









Count 6 0 1 1 4 14 0 26% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

23.1% 0.0% 3.8% 3.8% 15.4% 53.8% 0.0% 100.0%


6.2% 0.0% 9.1% 12.5% 3.5% 5.4% 0.0% 5.2%

% of Total 1.2% 0.0% .2% .2% .8% 2.8% 0.0% 5.2%Count 59 3 9 6 73 139 2 291% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

20.3% 1.0% 3.1% 2.1% 25.1% 47.8% .7% 100.0%


60.8% 60.0% 81.8% 75.0% 63.5% 54.1% 50.0% 58.6%

% of Total 11.9% .6% 1.8% 1.2% 14.7% 28.0% .4% 58.6%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 6 0 0 0 8 11 0 25% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

24.0% 0.0% 0.0% 0.0% 32.0% 44.0% 0.0% 100.0%


6.2% 0.0% 0.0% 0.0% 7.0% 4.3% 0.0% 5.0%

% of Total 1.2% 0.0% 0.0% 0.0% 1.6% 2.2% 0.0% 5.0%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

Yes

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

Yes



Count 59 3 10 7 69 142 2 292% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

20.2% 1.0% 3.4% 2.4% 23.6% 48.6% .7% 100.0%


60.8% 60.0% 90.9% 87.5% 60.0% 55.3% 50.0% 58.8%

% of Total 11.9% .6% 2.0% 1.4% 13.9% 28.6% .4% 58.8%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 10 0 2 0 11 9 0 32% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

31.3% 0.0% 6.3% 0.0% 34.4% 28.1% 0.0% 100.0%


10.3% 0.0% 18.2% 0.0% 9.6% 3.5% 0.0% 6.4%

% of Total 2.0% 0.0% .4% 0.0% 2.2% 1.8% 0.0% 6.4%Count 55 3 8 7 66 142 2 283% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

19.4% 1.1% 2.8% 2.5% 23.3% 50.2% .7% 100.0%


56.7% 60.0% 72.7% 87.5% 57.4% 55.3% 50.0% 56.9%

% of Total 11.1% .6% 1.6% 1.4% 13.3% 28.6% .4% 56.9%Count 0 0 0 0 0 2 0 2% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .4%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .4%

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

Yes

No

Don't Know



Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 16 0 1 2 12 13 0 44% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

36.4% 0.0% 2.3% 4.5% 27.3% 29.5% 0.0% 100.0%


16.5% 0.0% 9.1% 25.0% 10.4% 5.1% 0.0% 8.9%

% of Total 3.2% 0.0% .2% .4% 2.4% 2.6% 0.0% 8.9%Count 49 3 9 5 64 140 2 272% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

18.0% 1.1% 3.3% 1.8% 23.5% 51.5% .7% 100.0%


50.5% 60.0% 81.8% 62.5% 55.7% 54.5% 50.0% 54.7%

% of Total 9.9% .6% 1.8% 1.0% 12.9% 28.2% .4% 54.7%Count 0 0 0 0 1 0 0 1% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

Yes

No

Don't Know

No Response



Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 1 0 1 4 0 8% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

25.0% 0.0% 12.5% 0.0% 12.5% 50.0% 0.0% 100.0%


2.1% 0.0% 9.1% 0.0% .9% 1.6% 0.0% 1.6%

% of Total .4% 0.0% .2% 0.0% .2% .8% 0.0% 1.6%Count 63 3 9 7 76 149 2 309% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

20.4% 1.0% 2.9% 2.3% 24.6% 48.2% .6% 100.0%


64.9% 60.0% 81.8% 87.5% 66.1% 58.0% 50.0% 62.2%

% of Total 12.7% .6% 1.8% 1.4% 15.3% 30.0% .4% 62.2%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

Yes

No

No Response

Total









Count 2 0 2 0 0 12 0 16% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

12.5% 0.0% 12.5% 0.0% 0.0% 75.0% 0.0% 100.0%


2.1% 0.0% 18.2% 0.0% 0.0% 4.7% 0.0% 3.2%

% of Total .4% 0.0% .4% 0.0% 0.0% 2.4% 0.0% 3.2%Count 63 3 8 7 77 141 2 301% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

20.9% 1.0% 2.7% 2.3% 25.6% 46.8% .7% 100.0%


64.9% 60.0% 72.7% 87.5% 67.0% 54.9% 50.0% 60.6%

% of Total 12.7% .6% 1.6% 1.4% 15.5% 28.4% .4% 60.6%Count 32 2 1 1 38 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 1 0 3 4 0 12% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

33.3% 0.0% 8.3% 0.0% 25.0% 33.3% 0.0% 100.0%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

Yes

No

No Response

Total

Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

Yes




4.1% 0.0% 9.1% 0.0% 2.6% 1.6% 0.0% 2.4%

% of Total .8% 0.0% .2% 0.0% .6% .8% 0.0% 2.4%Count 60 3 9 7 73 146 2 300% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

20.0% 1.0% 3.0% 2.3% 24.3% 48.7% .7% 100.0%


61.9% 60.0% 81.8% 87.5% 63.5% 56.8% 50.0% 60.4%

% of Total 12.1% .6% 1.8% 1.4% 14.7% 29.4% .4% 60.4%Count 1 0 0 0 1 3 0 5% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

20.0% 0.0% 0.0% 0.0% 20.0% 60.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 1.2% 0.0% 1.0%

% of Total .2% 0.0% 0.0% 0.0% .2% .6% 0.0% 1.0%Count 32 2 1 1 38 104 2 180% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 22 1 1 1 18 47 0 90% within Q26 As a prime contractor/vendor, is your company required to have bonding?

24.4% 1.1% 1.1% 1.1% 20.0% 52.2% 0.0% 100.0%


22.7% 20.0% 9.1% 12.5% 15.7% 18.3% 0.0% 18.1%

% of Total 4.4% .2% .2% .2% 3.6% 9.5% 0.0% 18.1%

No

Don't Know

No Response

Total

Q26 As a prime contractor/vendor, is your company required to have bonding? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ26 As a prime contractor/vendor, is your company required to have bonding?

Yes



Count 43 2 8 6 59 100 2 220% within Q26 As a prime contractor/vendor, is your company required to have bonding?

19.5% .9% 3.6% 2.7% 26.8% 45.5% .9% 100.0%


44.3% 40.0% 72.7% 75.0% 51.3% 38.9% 50.0% 44.3%

% of Total 8.7% .4% 1.6% 1.2% 11.9% 20.1% .4% 44.3%Count 0 0 1 0 0 6 0 7% within Q26 As a prime contractor/vendor, is your company required to have bonding?

0.0% 0.0% 14.3% 0.0% 0.0% 85.7% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 0.0% 2.3% 0.0% 1.4%

% of Total 0.0% 0.0% .2% 0.0% 0.0% 1.2% 0.0% 1.4%Count 32 2 1 1 38 104 2 180% within Q26 As a prime contractor/vendor, is your company required to have bonding?

17.8% 1.1% .6% .6% 21.1% 57.8% 1.1% 100.0%


33.0% 40.0% 9.1% 12.5% 33.0% 40.5% 50.0% 36.2%

% of Total 6.4% .4% .2% .2% 7.6% 20.9% .4% 36.2%Count 97 5 11 8 115 257 4 497% within Q26 As a prime contractor/vendor, is your company required to have bonding?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 0 0 2 1 0 6% within Q27 What is your company's current aggregate bonding capacity?

50.0% 0.0% 0.0% 0.0% 33.3% 16.7% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% 1.7% .4% 0.0% 1.2%

% of Total .6% 0.0% 0.0% 0.0% .4% .2% 0.0% 1.2%Count 2 0 0 1 2 2 0 7% within Q27 What is your company's current aggregate bonding capacity?

28.6% 0.0% 0.0% 14.3% 28.6% 28.6% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% 1.7% .8% 0.0% 1.4%

% of Total .4% 0.0% 0.0% .2% .4% .4% 0.0% 1.4%Count 3 0 1 0 3 2 0 9% within Q27 What is your company's current aggregate bonding capacity?

33.3% 0.0% 11.1% 0.0% 33.3% 22.2% 0.0% 100.0%


3.1% 0.0% 9.1% 0.0% 2.6% .8% 0.0% 1.8%

% of Total .6% 0.0% .2% 0.0% .6% .4% 0.0% 1.8%Count 7 1 0 0 3 8 0 19% within Q27 What is your company's current aggregate bonding capacity?

36.8% 5.3% 0.0% 0.0% 15.8% 42.1% 0.0% 100.0%


7.2% 20.0% 0.0% 0.0% 2.6% 3.1% 0.0% 3.8%

% of Total 1.4% .2% 0.0% 0.0% .6% 1.6% 0.0% 3.8%

No

Don't Know

No Response

Total

Q27 What is your company's current aggregate bonding capacity? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ27 What is your company's current aggregate bonding capacity?

Below $100,000

$100,001 to $250,000

$250,001 to $500,000

$500,001 to $1 million



Count 1 0 0 0 1 4 0 6% within Q27 What is your company's current aggregate bonding capacity?

16.7% 0.0% 0.0% 0.0% 16.7% 66.7% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 1.6% 0.0% 1.2%


12.5% 0.0% 0.0% 0.0% 50.0% 37.5% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 3.5% 1.2% 0.0% 1.6%


33.3% 0.0% 0.0% 0.0% 0.0% 66.7% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .6%

% of Total .2% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .6%Count 2 0 0 0 1 16 0 19% within Q27 What is your company's current aggregate bonding capacity?

10.5% 0.0% 0.0% 0.0% 5.3% 84.2% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% 6.2% 0.0% 3.8%

% of Total .4% 0.0% 0.0% 0.0% .2% 3.2% 0.0% 3.8%Count 2 0 0 0 2 10 0 14% within Q27 What is your company's current aggregate bonding capacity?

14.3% 0.0% 0.0% 0.0% 14.3% 71.4% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 1.7% 3.9% 0.0% 2.8%

% of Total .4% 0.0% 0.0% 0.0% .4% 2.0% 0.0% 2.8%Count 75 4 10 7 97 209 4 406% within Q27 What is your company's current aggregate bonding capacity?

18.5% 1.0% 2.5% 1.7% 23.9% 51.5% 1.0% 100.0%


77.3% 80.0% 90.9% 87.5% 84.3% 81.3% 100.0% 81.7%

% of Total 15.1% .8% 2.0% 1.4% 19.5% 42.1% .8% 81.7%Count 97 5 11 8 115 257 4 497% within Q27 What is your company's current aggregate bonding capacity?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 0 0 2 1 0 6% within Q28 What is your company's current single limit bonding capacity?

50.0% 0.0% 0.0% 0.0% 33.3% 16.7% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% 1.7% .4% 0.0% 1.2%

% of Total .6% 0.0% 0.0% 0.0% .4% .2% 0.0% 1.2%

$1,000,001 to $1.5 million

$1,500,001 to $3 million

$3,000,001 to $5 million

Over $5 million?

Don't Know

No Response

Total

Q28 What is your company's current single limit bonding capacity? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ28 What is your company's current single limit bonding capacity?

Below $100,000




33.3% 0.0% 0.0% 11.1% 33.3% 22.2% 0.0% 100.0%


3.1% 0.0% 0.0% 12.5% 2.6% .8% 0.0% 1.8%

% of Total .6% 0.0% 0.0% .2% .6% .4% 0.0% 1.8%Count 5 0 1 0 3 4 0 13% within Q28 What is your company's current single limit bonding capacity?

38.5% 0.0% 7.7% 0.0% 23.1% 30.8% 0.0% 100.0%


5.2% 0.0% 9.1% 0.0% 2.6% 1.6% 0.0% 2.6%

% of Total 1.0% 0.0% .2% 0.0% .6% .8% 0.0% 2.6%Count 4 1 0 0 3 5 0 13% within Q28 What is your company's current single limit bonding capacity?

30.8% 7.7% 0.0% 0.0% 23.1% 38.5% 0.0% 100.0%


4.1% 20.0% 0.0% 0.0% 2.6% 1.9% 0.0% 2.6%

% of Total .8% .2% 0.0% 0.0% .6% 1.0% 0.0% 2.6%Count 2 0 0 0 0 7 0 9% within Q28 What is your company's current single limit bonding capacity?

22.2% 0.0% 0.0% 0.0% 0.0% 77.8% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 0.0% 2.7% 0.0% 1.8%

% of Total .4% 0.0% 0.0% 0.0% 0.0% 1.4% 0.0% 1.8%Count 0 0 0 0 3 2 0 5% within Q28 What is your company's current single limit bonding capacity?

0.0% 0.0% 0.0% 0.0% 60.0% 40.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 2.6% .8% 0.0% 1.0%

% of Total 0.0% 0.0% 0.0% 0.0% .6% .4% 0.0% 1.0%Count 0 0 0 0 0 2 0 2% within Q28 What is your company's current single limit bonding capacity?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .4%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .4%Count 2 0 0 0 1 16 0 19% within Q28 What is your company's current single limit bonding capacity?

10.5% 0.0% 0.0% 0.0% 5.3% 84.2% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% 6.2% 0.0% 3.8%

% of Total .4% 0.0% 0.0% 0.0% .2% 3.2% 0.0% 3.8%Count 3 0 0 0 3 8 0 14% within Q28 What is your company's current single limit bonding capacity?

21.4% 0.0% 0.0% 0.0% 21.4% 57.1% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% 2.6% 3.1% 0.0% 2.8%

% of Total .6% 0.0% 0.0% 0.0% .6% 1.6% 0.0% 2.8%Count 75 4 10 7 97 210 4 407% within Q28 What is your company's current single limit bonding capacity?

18.4% 1.0% 2.5% 1.7% 23.8% 51.6% 1.0% 100.0%


77.3% 80.0% 90.9% 87.5% 84.3% 81.7% 100.0% 81.9%

% of Total 15.1% .8% 2.0% 1.4% 19.5% 42.3% .8% 81.9%

$1,000,001 to $1.5 million

$1,500,001 to $3 million

$3,000,001 to $5 million

Over $5 million?

Don't Know

No Response

$100,001 to $250,000

$250,001 to $500,000





19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 2 0 2 5 0 11% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

18.2% 0.0% 18.2% 0.0% 18.2% 45.5% 0.0% 100.0%


2.1% 0.0% 18.2% 0.0% 1.7% 1.9% 0.0% 2.2%

% of Total .4% 0.0% .4% 0.0% .4% 1.0% 0.0% 2.2%Count 72 2 7 7 84 195 3 370% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

19.5% .5% 1.9% 1.9% 22.7% 52.7% .8% 100.0%


74.2% 40.0% 63.6% 87.5% 73.0% 75.9% 75.0% 74.4%

% of Total 14.5% .4% 1.4% 1.4% 16.9% 39.2% .6% 74.4%Count 4 1 1 0 5 3 0 14% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

28.6% 7.1% 7.1% 0.0% 35.7% 21.4% 0.0% 100.0%


4.1% 20.0% 9.1% 0.0% 4.3% 1.2% 0.0% 2.8%

% of Total .8% .2% .2% 0.0% 1.0% .6% 0.0% 2.8%Count 1 0 0 0 1 3 0 5% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

20.0% 0.0% 0.0% 0.0% 20.0% 60.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 1.2% 0.0% 1.0%

% of Total .2% 0.0% 0.0% 0.0% .2% .6% 0.0% 1.0%Count 18 2 1 1 23 51 1 97% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

18.6% 2.1% 1.0% 1.0% 23.7% 52.6% 1.0% 100.0%


18.6% 40.0% 9.1% 12.5% 20.0% 19.8% 25.0% 19.5%

% of Total 3.6% .4% .2% .2% 4.6% 10.3% .2% 19.5%

Total

Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

Yes

No

Don't Know

Not Applicable

No Response



Count 97 5 11 8 115 257 4 497% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 1 0 2 0 0 2 0 5% within Q30 How did you become aware of the discrimination against your company?

20.0% 0.0% 40.0% 0.0% 0.0% 40.0% 0.0% 100.0%


1.0% 0.0% 18.2% 0.0% 0.0% .8% 0.0% 1.0%

% of Total .2% 0.0% .4% 0.0% 0.0% .4% 0.0% 1.0%Count 1 0 0 0 1 1 0 3% within Q30 How did you become aware of the discrimination against your company?

33.3% 0.0% 0.0% 0.0% 33.3% 33.3% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% .4% 0.0% .6%

% of Total .2% 0.0% 0.0% 0.0% .2% .2% 0.0% .6%Count 0 0 0 0 1 2 0 3% within Q30 How did you become aware of the discrimination against your company?

0.0% 0.0% 0.0% 0.0% 33.3% 66.7% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% .8% 0.0% .6%

% of Total 0.0% 0.0% 0.0% 0.0% .2% .4% 0.0% .6%Count 95 5 9 8 113 252 4 486% within Q30 How did you become aware of the discrimination against your company?

19.5% 1.0% 1.9% 1.6% 23.3% 51.9% .8% 100.0%


97.9% 100.0% 81.8% 100.0% 98.3% 98.1% 100.0% 97.8%

% of Total 19.1% 1.0% 1.8% 1.6% 22.7% 50.7% .8% 97.8%Count 97 5 11 8 115 257 4 497% within Q30 How did you become aware of the discrimination against your company?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Q30 How did you become aware of the discrimination against your company?

Verbal comment

Action taken against the company

Other Action

No Response

Total

Total

Q30 How did you become aware of the discrimination against your company? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total









Count 1 0 1 0 1 0 0 3% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

33.3% 0.0% 33.3% 0.0% 33.3% 0.0% 0.0% 100.0%


1.0% 0.0% 9.1% 0.0% .9% 0.0% 0.0% .6%

% of Total .2% 0.0% .2% 0.0% .2% 0.0% 0.0% .6%Count 0 0 1 0 1 2 0 4% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

0.0% 0.0% 25.0% 0.0% 25.0% 50.0% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% .9% .8% 0.0% .8%

% of Total 0.0% 0.0% .2% 0.0% .2% .4% 0.0% .8%Count 0 0 0 0 0 3 0 3% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 0.0% .6%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .6% 0.0% .6%Count 1 0 0 0 0 0 0 1% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 95 5 9 8 113 252 4 486% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

19.5% 1.0% 1.9% 1.6% 23.3% 51.9% .8% 100.0%


97.9% 100.0% 81.8% 100.0% 98.3% 98.1% 100.0% 97.8%

% of Total 19.1% 1.0% 1.8% 1.6% 22.7% 50.7% .8% 97.8%Count 97 5 11 8 115 257 4 497% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 1 0 0 0 1 2 0 4% within Q34 When did the discrimination first occur?

25.0% 0.0% 0.0% 0.0% 25.0% 50.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% .8% 0.0% .8%

% of Total .2% 0.0% 0.0% 0.0% .2% .4% 0.0% .8%

Q32 Which of the following do you consider the primary reason for your company being discriminated against? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ32 Which of the following do you consider the primary reason for your company being discriminated against?

Owner's Race or Ethnicity

Both race and gender

Don't Know

Some other reason

No Response

Total

Q34 When did the discrimination first occur? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ34 When did the discrimination first occur?

During the bidding process




100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 0 0 1 0 1 0 0 2% within Q34 When did the discrimination first occur?

0.0% 0.0% 50.0% 0.0% 50.0% 0.0% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% .9% 0.0% 0.0% .4%

% of Total 0.0% 0.0% .2% 0.0% .2% 0.0% 0.0% .4%Count 0 0 1 0 0 3 0 4% within Q34 When did the discrimination first occur?

0.0% 0.0% 25.0% 0.0% 0.0% 75.0% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 0.0% 1.2% 0.0% .8%

% of Total 0.0% 0.0% .2% 0.0% 0.0% .6% 0.0% .8%Count 95 5 9 8 113 252 4 486% within Q34 When did the discrimination first occur?

19.5% 1.0% 1.9% 1.6% 23.3% 51.9% .8% 100.0%


97.9% 100.0% 81.8% 100.0% 98.3% 98.1% 100.0% 97.8%

% of Total 19.1% 1.0% 1.8% 1.6% 22.7% 50.7% .8% 97.8%Count 97 5 11 8 115 257 4 497% within Q34 When did the discrimination first occur?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 0 0 2 1 0 5% within Q35 Did you file a complaint? 40.0% 0.0% 0.0% 0.0% 40.0% 20.0% 0.0% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

2.1% 0.0% 0.0% 0.0% 1.7% .4% 0.0% 1.0%

% of Total .4% 0.0% 0.0% 0.0% .4% .2% 0.0% 1.0%Count 0 0 2 0 0 4 0 6% within Q35 Did you file a complaint? 0.0% 0.0% 33.3% 0.0% 0.0% 66.7% 0.0% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

0.0% 0.0% 18.2% 0.0% 0.0% 1.6% 0.0% 1.2%

% of Total 0.0% 0.0% .4% 0.0% 0.0% .8% 0.0% 1.2%Count 95 5 9 8 113 252 4 486% within Q35 Did you file a complaint? 19.5% 1.0% 1.9% 1.6% 23.3% 51.9% .8% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

97.9% 100.0% 81.8% 100.0% 98.3% 98.1% 100.0% 97.8%

% of Total 19.1% 1.0% 1.8% 1.6% 22.7% 50.7% .8% 97.8%Count 97 5 11 8 115 257 4 497% within Q35 Did you file a complaint? 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

No Response

Total

Q35 Did you file a complaint? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total

During contract negotiations

After contract award

All of the above

Q35 Did you file a complaint? Yes

No

No Response

Total









Count 2 0 0 0 2 4 0 8% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

25.0% 0.0% 0.0% 0.0% 25.0% 50.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 1.7% 1.6% 0.0% 1.6%

% of Total .4% 0.0% 0.0% 0.0% .4% .8% 0.0% 1.6%Count 0 0 2 0 0 1 0 3% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

0.0% 0.0% 66.7% 0.0% 0.0% 33.3% 0.0% 100.0%


0.0% 0.0% 18.2% 0.0% 0.0% .4% 0.0% .6%

% of Total 0.0% 0.0% .4% 0.0% 0.0% .2% 0.0% .6%Count 95 5 9 8 113 252 4 486% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

19.5% 1.0% 1.9% 1.6% 23.3% 51.9% .8% 100.0%


97.9% 100.0% 81.8% 100.0% 98.3% 98.1% 100.0% 97.8%

% of Total 19.1% 1.0% 1.8% 1.6% 22.7% 50.7% .8% 97.8%Count 97 5 11 8 115 257 4 497% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 7 1 0 0 5 5 0 18% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

38.9% 5.6% 0.0% 0.0% 27.8% 27.8% 0.0% 100.0%


7.2% 20.0% 0.0% 0.0% 4.3% 1.9% 0.0% 3.6%

% of Total 1.4% .2% 0.0% 0.0% 1.0% 1.0% 0.0% 3.6%


TotalQ36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

Yes

No

No Response

Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District? * Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total

Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014 * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

None




27.0% 2.2% 1.1% 0.0% 21.3% 47.2% 1.1% 100.0%


24.7% 40.0% 9.1% 0.0% 16.5% 16.3% 25.0% 17.9%

% of Total 4.8% .4% .2% 0.0% 3.8% 8.5% .2% 17.9%Count 5 0 0 0 9 16 0 30% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

16.7% 0.0% 0.0% 0.0% 30.0% 53.3% 0.0% 100.0%


5.2% 0.0% 0.0% 0.0% 7.8% 6.2% 0.0% 6.0%

% of Total 1.0% 0.0% 0.0% 0.0% 1.8% 3.2% 0.0% 6.0%Count 5 0 0 0 2 5 0 12% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

41.7% 0.0% 0.0% 0.0% 16.7% 41.7% 0.0% 100.0%


5.2% 0.0% 0.0% 0.0% 1.7% 1.9% 0.0% 2.4%

% of Total 1.0% 0.0% 0.0% 0.0% .4% 1.0% 0.0% 2.4%Count 4 0 0 0 3 2 0 9% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

44.4% 0.0% 0.0% 0.0% 33.3% 22.2% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 2.6% .8% 0.0% 1.8%

% of Total .8% 0.0% 0.0% 0.0% .6% .4% 0.0% 1.8%Count 1 0 1 0 2 2 0 6% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

16.7% 0.0% 16.7% 0.0% 33.3% 33.3% 0.0% 100.0%


1.0% 0.0% 9.1% 0.0% 1.7% .8% 0.0% 1.2%

% of Total .2% 0.0% .2% 0.0% .4% .4% 0.0% 1.2%Count 2 0 0 0 1 3 0 6% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

33.3% 0.0% 0.0% 0.0% 16.7% 50.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% 1.2% 0.0% 1.2%

% of Total .4% 0.0% 0.0% 0.0% .2% .6% 0.0% 1.2%

Up to $50,000?

$50,001 to $100,000?

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?

$400,001 to $500,000?




7.7% 0.0% 0.0% 7.7% 23.1% 61.5% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 2.6% 3.1% 0.0% 2.6%

% of Total .2% 0.0% 0.0% .2% .6% 1.6% 0.0% 2.6%Count 1 0 0 1 5 15 0 22% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

4.5% 0.0% 0.0% 4.5% 22.7% 68.2% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 4.3% 5.8% 0.0% 4.4%

% of Total .2% 0.0% 0.0% .2% 1.0% 3.0% 0.0% 4.4%Count 1 0 0 0 3 7 0 11% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

9.1% 0.0% 0.0% 0.0% 27.3% 63.6% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 2.6% 2.7% 0.0% 2.2%

% of Total .2% 0.0% 0.0% 0.0% .6% 1.4% 0.0% 2.2%Count 46 2 9 6 63 152 3 281% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 7 1 0 0 6 4 0 18% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

38.9% 5.6% 0.0% 0.0% 33.3% 22.2% 0.0% 100.0%


7.2% 20.0% 0.0% 0.0% 5.2% 1.6% 0.0% 3.6%

% of Total 1.4% .2% 0.0% 0.0% 1.2% .8% 0.0% 3.6%

No Response

Total

Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total

$500,001 to $1 million?

Over $1 million?

Don't Know

Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

None




23.6% 1.9% .9% .9% 22.6% 49.1% .9% 100.0%


25.8% 40.0% 9.1% 12.5% 20.9% 20.2% 25.0% 21.3%

% of Total 5.0% .4% .2% .2% 4.8% 10.5% .2% 21.3%Count 1 0 0 0 6 15 0 22% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

4.5% 0.0% 0.0% 0.0% 27.3% 68.2% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 5.2% 5.8% 0.0% 4.4%

% of Total .2% 0.0% 0.0% 0.0% 1.2% 3.0% 0.0% 4.4%Count 4 0 0 0 3 2 0 9% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

44.4% 0.0% 0.0% 0.0% 33.3% 22.2% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 2.6% .8% 0.0% 1.8%

% of Total .8% 0.0% 0.0% 0.0% .6% .4% 0.0% 1.8%Count 7 0 0 1 3 5 0 16% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

43.8% 0.0% 0.0% 6.3% 18.8% 31.3% 0.0% 100.0%


7.2% 0.0% 0.0% 12.5% 2.6% 1.9% 0.0% 3.2%

% of Total 1.4% 0.0% 0.0% .2% .6% 1.0% 0.0% 3.2%Count 1 0 0 0 1 6 0 8% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

12.5% 0.0% 0.0% 0.0% 12.5% 75.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 2.3% 0.0% 1.6%

% of Total .2% 0.0% 0.0% 0.0% .2% 1.2% 0.0% 1.6%Count 0 0 1 0 0 2 0 3% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

0.0% 0.0% 33.3% 0.0% 0.0% 66.7% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 0.0% .8% 0.0% .6%

% of Total 0.0% 0.0% .2% 0.0% 0.0% .4% 0.0% .6%Count 3 0 0 0 1 2 0 6% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

50.0% 0.0% 0.0% 0.0% 16.7% 33.3% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% .9% .8% 0.0% 1.2%

% of Total .6% 0.0% 0.0% 0.0% .2% .4% 0.0% 1.2%

Up to $50,000?

$50,001 to $100,000?

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?

$400,001 to $500,000?

$500,001 to $1 million?




7.7% 0.0% 0.0% 0.0% 30.8% 61.5% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 3.5% 3.1% 0.0% 2.6%


13.3% 0.0% 0.0% 0.0% 26.7% 60.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 3.5% 3.5% 0.0% 3.0%


16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 6 0 0 0 3 4 0 13% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

46.2% 0.0% 0.0% 0.0% 23.1% 30.8% 0.0% 100.0%


6.2% 0.0% 0.0% 0.0% 2.6% 1.6% 0.0% 2.6%

% of Total 1.2% 0.0% 0.0% 0.0% .6% .8% 0.0% 2.6%Count 45 3 2 2 49 101 1 203% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

22.2% 1.5% 1.0% 1.0% 24.1% 49.8% .5% 100.0%


46.4% 60.0% 18.2% 25.0% 42.6% 39.3% 25.0% 40.8%

% of Total 9.1% .6% .4% .4% 9.9% 20.3% .2% 40.8%

Don't Know

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


Total

Over $1 million?

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

Yes

No



Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 0 0 2 3 0 9% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

44.4% 0.0% 0.0% 0.0% 22.2% 33.3% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 1.7% 1.2% 0.0% 1.8%

% of Total .8% 0.0% 0.0% 0.0% .4% .6% 0.0% 1.8%Count 47 3 2 2 50 102 1 207% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

22.7% 1.4% 1.0% 1.0% 24.2% 49.3% .5% 100.0%


48.5% 60.0% 18.2% 25.0% 43.5% 39.7% 25.0% 41.6%

% of Total 9.5% .6% .4% .4% 10.1% 20.5% .2% 41.6%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

Yes

No

No Response

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing? * Race, Ethnicity, Gender Classification (Business Ownership Classification)



Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 6 0 0 0 4 1 0 11% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

54.5% 0.0% 0.0% 0.0% 36.4% 9.1% 0.0% 100.0%


6.2% 0.0% 0.0% 0.0% 3.5% .4% 0.0% 2.2%

% of Total 1.2% 0.0% 0.0% 0.0% .8% .2% 0.0% 2.2%Count 45 3 2 2 48 104 1 205% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

22.0% 1.5% 1.0% 1.0% 23.4% 50.7% .5% 100.0%


46.4% 60.0% 18.2% 25.0% 41.7% 40.5% 25.0% 41.2%

% of Total 9.1% .6% .4% .4% 9.7% 20.9% .2% 41.2%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

Yes

No

No Response

Total









Count 6 0 1 0 4 2 1 14% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

42.9% 0.0% 7.1% 0.0% 28.6% 14.3% 7.1% 100.0%


6.2% 0.0% 9.1% 0.0% 3.5% .8% 25.0% 2.8%

% of Total 1.2% 0.0% .2% 0.0% .8% .4% .2% 2.8%Count 45 3 1 2 48 103 0 202% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

22.3% 1.5% .5% 1.0% 23.8% 51.0% 0.0% 100.0%


46.4% 60.0% 9.1% 25.0% 41.7% 40.1% 0.0% 40.6%

% of Total 9.1% .6% .2% .4% 9.7% 20.7% 0.0% 40.6%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 6 0 0 0 3 2 1 12% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

50.0% 0.0% 0.0% 0.0% 25.0% 16.7% 8.3% 100.0%


6.2% 0.0% 0.0% 0.0% 2.6% .8% 25.0% 2.4%

% of Total 1.2% 0.0% 0.0% 0.0% .6% .4% .2% 2.4%

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

Yes



Count 45 3 2 2 49 103 0 204% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

22.1% 1.5% 1.0% 1.0% 24.0% 50.5% 0.0% 100.0%


46.4% 60.0% 18.2% 25.0% 42.6% 40.1% 0.0% 41.0%

% of Total 9.1% .6% .4% .4% 9.9% 20.7% 0.0% 41.0%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 11 0 0 0 4 8 0 23% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

47.8% 0.0% 0.0% 0.0% 17.4% 34.8% 0.0% 100.0%


11.3% 0.0% 0.0% 0.0% 3.5% 3.1% 0.0% 4.6%

% of Total 2.2% 0.0% 0.0% 0.0% .8% 1.6% 0.0% 4.6%Count 40 3 2 2 48 97 1 193% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

20.7% 1.6% 1.0% 1.0% 24.9% 50.3% .5% 100.0%


41.2% 60.0% 18.2% 25.0% 41.7% 37.7% 25.0% 38.8%

% of Total 8.0% .6% .4% .4% 9.7% 19.5% .2% 38.8%

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

Yes

No



Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 0 0 1 2 0 6% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

50.0% 0.0% 0.0% 0.0% 16.7% 33.3% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% .9% .8% 0.0% 1.2%

% of Total .6% 0.0% 0.0% 0.0% .2% .4% 0.0% 1.2%Count 48 3 2 2 51 103 1 210% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

22.9% 1.4% 1.0% 1.0% 24.3% 49.0% .5% 100.0%


49.5% 60.0% 18.2% 25.0% 44.3% 40.1% 25.0% 42.3%

% of Total 9.7% .6% .4% .4% 10.3% 20.7% .2% 42.3%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 0 0 2 2 0 7% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

42.9% 0.0% 0.0% 0.0% 28.6% 28.6% 0.0% 100.0%


3.1% 0.0% 0.0% 0.0% 1.7% .8% 0.0% 1.4%

% of Total .6% 0.0% 0.0% 0.0% .4% .4% 0.0% 1.4%Count 48 3 2 2 50 103 1 209% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

23.0% 1.4% 1.0% 1.0% 23.9% 49.3% .5% 100.0%


49.5% 60.0% 18.2% 25.0% 43.5% 40.1% 25.0% 42.1%

% of Total 9.7% .6% .4% .4% 10.1% 20.7% .2% 42.1%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

Yes

No

No Response

Total









Count 8 0 0 0 7 4 1 20% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

40.0% 0.0% 0.0% 0.0% 35.0% 20.0% 5.0% 100.0%


8.2% 0.0% 0.0% 0.0% 6.1% 1.6% 25.0% 4.0%

% of Total 1.6% 0.0% 0.0% 0.0% 1.4% .8% .2% 4.0%Count 43 3 2 2 45 101 0 196% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

21.9% 1.5% 1.0% 1.0% 23.0% 51.5% 0.0% 100.0%


44.3% 60.0% 18.2% 25.0% 39.1% 39.3% 0.0% 39.4%

% of Total 8.7% .6% .4% .4% 9.1% 20.3% 0.0% 39.4%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 10 0 1 0 5 5 1 22% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

45.5% 0.0% 4.5% 0.0% 22.7% 22.7% 4.5% 100.0%


10.3% 0.0% 9.1% 0.0% 4.3% 1.9% 25.0% 4.4%

% of Total 2.0% 0.0% .2% 0.0% 1.0% 1.0% .2% 4.4%

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

Yes



Count 41 3 1 2 47 100 0 194% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

21.1% 1.5% .5% 1.0% 24.2% 51.5% 0.0% 100.0%


42.3% 60.0% 9.1% 25.0% 40.9% 38.9% 0.0% 39.0%

% of Total 8.2% .6% .2% .4% 9.5% 20.1% 0.0% 39.0%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 18 0 0 0 12 13 0 43% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

41.9% 0.0% 0.0% 0.0% 27.9% 30.2% 0.0% 100.0%


18.6% 0.0% 0.0% 0.0% 10.4% 5.1% 0.0% 8.7%

% of Total 3.6% 0.0% 0.0% 0.0% 2.4% 2.6% 0.0% 8.7%Count 33 3 2 2 40 92 1 173% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

19.1% 1.7% 1.2% 1.2% 23.1% 53.2% .6% 100.0%


34.0% 60.0% 18.2% 25.0% 34.8% 35.8% 25.0% 34.8%

% of Total 6.6% .6% .4% .4% 8.0% 18.5% .2% 34.8%

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

Yes

No



Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 3 0 1 0 5 10 1 20% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

15.0% 0.0% 5.0% 0.0% 25.0% 50.0% 5.0% 100.0%


3.1% 0.0% 9.1% 0.0% 4.3% 3.9% 25.0% 4.0%

% of Total .6% 0.0% .2% 0.0% 1.0% 2.0% .2% 4.0%Count 48 3 1 2 47 95 0 196% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

24.5% 1.5% .5% 1.0% 24.0% 48.5% 0.0% 100.0%


49.5% 60.0% 9.1% 25.0% 40.9% 37.0% 0.0% 39.4%

% of Total 9.7% .6% .2% .4% 9.5% 19.1% 0.0% 39.4%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 1 0 6 4 0 13% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

15.4% 0.0% 7.7% 0.0% 46.2% 30.8% 0.0% 100.0%


2.1% 0.0% 9.1% 0.0% 5.2% 1.6% 0.0% 2.6%

% of Total .4% 0.0% .2% 0.0% 1.2% .8% 0.0% 2.6%Count 49 3 1 2 46 101 1 203% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

24.1% 1.5% .5% 1.0% 22.7% 49.8% .5% 100.0%


50.5% 60.0% 9.1% 25.0% 40.0% 39.3% 25.0% 40.8%

% of Total 9.9% .6% .2% .4% 9.3% 20.3% .2% 40.8%Count 46 2 9 6 63 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

Yes

No

No Response

Total









Count 6 0 1 0 4 8 0 19% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

31.6% 0.0% 5.3% 0.0% 21.1% 42.1% 0.0% 100.0%


6.2% 0.0% 9.1% 0.0% 3.5% 3.1% 0.0% 3.8%

% of Total 1.2% 0.0% .2% 0.0% .8% 1.6% 0.0% 3.8%Count 45 3 1 2 47 97 1 196% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

23.0% 1.5% .5% 1.0% 24.0% 49.5% .5% 100.0%


46.4% 60.0% 9.1% 25.0% 40.9% 37.7% 25.0% 39.4%

% of Total 9.1% .6% .2% .4% 9.5% 19.5% .2% 39.4%Count 0 0 0 0 1 0 0 1% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .2%Count 46 2 9 6 63 152 3 281% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

Yes

No

Don't Know

No Response

Total









Count 21 1 1 1 15 31 0 70% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

30.0% 1.4% 1.4% 1.4% 21.4% 44.3% 0.0% 100.0%


21.6% 20.0% 9.1% 12.5% 13.0% 12.1% 0.0% 14.1%

% of Total 4.2% .2% .2% .2% 3.0% 6.2% 0.0% 14.1%Count 30 2 1 1 37 72 1 144% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

20.8% 1.4% .7% .7% 25.7% 50.0% .7% 100.0%


30.9% 40.0% 9.1% 12.5% 32.2% 28.0% 25.0% 29.0%

% of Total 6.0% .4% .2% .2% 7.4% 14.5% .2% 29.0%Count 0 0 0 0 0 2 0 2% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .4%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .4%Count 46 2 9 6 63 152 3 281% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 0 1 2 3 0 10% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

40.0% 0.0% 0.0% 10.0% 20.0% 30.0% 0.0% 100.0%


4.1% 0.0% 0.0% 12.5% 1.7% 1.2% 0.0% 2.0%

% of Total .8% 0.0% 0.0% .2% .4% .6% 0.0% 2.0%

Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

Yes

No

Don't Know

No Response

Total

Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

Yes



Count 43 3 2 1 47 98 1 195% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

22.1% 1.5% 1.0% .5% 24.1% 50.3% .5% 100.0%


44.3% 60.0% 18.2% 12.5% 40.9% 38.1% 25.0% 39.2%

% of Total 8.7% .6% .4% .2% 9.5% 19.7% .2% 39.2%Count 4 0 0 0 3 4 0 11% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

36.4% 0.0% 0.0% 0.0% 27.3% 36.4% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 2.6% 1.6% 0.0% 2.2%

% of Total .8% 0.0% 0.0% 0.0% .6% .8% 0.0% 2.2%Count 46 2 9 6 63 152 3 281% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

16.4% .7% 3.2% 2.1% 22.4% 54.1% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 54.8% 59.1% 75.0% 56.5%

% of Total 9.3% .4% 1.8% 1.2% 12.7% 30.6% .6% 56.5%Count 97 5 11 8 115 257 4 497% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%








40.0% 0.0% 0.0% 20.0% 20.0% 20.0% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% .9% .4% 0.0% 1.0%

% of Total .4% 0.0% 0.0% .2% .2% .2% 0.0% 1.0%Count 1 0 0 0 1 0 0 2% within Q43 How did you become aware of the discrimination against your company?

50.0% 0.0% 0.0% 0.0% 50.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .4%

% of Total .2% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .4%

No

Not Applicable

No Response

Total


TotalQ43 How did you become aware of the discrimination against your company?

Verbal Comment

Action Taken Against Company




0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .4%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .4%Count 1 0 0 0 0 0 0 1% within Q43 How did you become aware of the discrimination against your company?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 93 5 11 7 113 254 4 487% within Q43 How did you become aware of the discrimination against your company?

19.1% 1.0% 2.3% 1.4% 23.2% 52.2% .8% 100.0%


95.9% 100.0% 100.0% 87.5% 98.3% 98.8% 100.0% 98.0%


19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%








50.0% 0.0% 0.0% 0.0% 25.0% 25.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% .4% 0.0% .8%

% of Total .4% 0.0% 0.0% 0.0% .2% .2% 0.0% .8%Count 0 0 0 0 0 1 0 1% within Q45 Which of the following do you consider the primary reason for your company being discriminated against?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%


50.0% 0.0% 0.0% 25.0% 25.0% 0.0% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% .9% 0.0% 0.0% .8%

% of Total .4% 0.0% 0.0% .2% .2% 0.0% 0.0% .8%

Don't Know

Other Action

Q45 Which of the following do you consider the primary reason for your company being discriminated against?

Owner's race or ethnicity


Don't Know

No Response

Total

Q45 Which of the following do you consider the primary reason for your company being discriminated against? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total




0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%


19.1% 1.0% 2.3% 1.4% 23.2% 52.2% .8% 100.0%


95.9% 100.0% 100.0% 87.5% 98.3% 98.8% 100.0% 98.0%

% of Total 18.7% 1.0% 2.2% 1.4% 22.7% 51.1% .8% 98.0%Count 97 5 11 8 115 257 4 497% within Q45 Which of the following do you consider the primary reason for your company being discriminated against?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%








66.7% 0.0% 0.0% 0.0% 33.3% 0.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .6%

% of Total .4% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .6%Count 1 0 0 0 1 0 0 2% within Q47 When did the discrimination first occur?

50.0% 0.0% 0.0% 0.0% 50.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .4%

% of Total .2% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .4%Count 0 0 0 1 0 1 0 2% within Q47 When did the discrimination first occur?

0.0% 0.0% 0.0% 50.0% 0.0% 50.0% 0.0% 100.0%


0.0% 0.0% 0.0% 12.5% 0.0% .4% 0.0% .4%

% of Total 0.0% 0.0% 0.0% .2% 0.0% .2% 0.0% .4%Count 1 0 0 0 0 2 0 3% within Q47 When did the discrimination first occur?

33.3% 0.0% 0.0% 0.0% 0.0% 66.7% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .6%

% of Total .2% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .6%Count 93 5 11 7 113 254 4 487% within Q47 When did the discrimination first occur?

19.1% 1.0% 2.3% 1.4% 23.2% 52.2% .8% 100.0%


95.9% 100.0% 100.0% 87.5% 98.3% 98.8% 100.0% 98.0%

% of Total 18.7% 1.0% 2.2% 1.4% 22.7% 51.1% .8% 98.0%

Some other reason

No Response

No Response

Total

Q47 When did the discrimination first occur? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)





All of the above




19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 1 0 0 1 0 0 0 2% within Q48 Did you file a complaint? 50.0% 0.0% 0.0% 50.0% 0.0% 0.0% 0.0% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

1.0% 0.0% 0.0% 12.5% 0.0% 0.0% 0.0% .4%

% of Total .2% 0.0% 0.0% .2% 0.0% 0.0% 0.0% .4%Count 3 0 0 0 2 3 0 8% within Q48 Did you file a complaint? 37.5% 0.0% 0.0% 0.0% 25.0% 37.5% 0.0% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

3.1% 0.0% 0.0% 0.0% 1.7% 1.2% 0.0% 1.6%

% of Total .6% 0.0% 0.0% 0.0% .4% .6% 0.0% 1.6%Count 93 5 11 7 113 254 4 487% within Q48 Did you file a complaint? 19.1% 1.0% 2.3% 1.4% 23.2% 52.2% .8% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

95.9% 100.0% 100.0% 87.5% 98.3% 98.8% 100.0% 98.0%

% of Total 18.7% 1.0% 2.2% 1.4% 22.7% 51.1% .8% 98.0%Count 97 5 11 8 115 257 4 497% within Q48 Did you file a complaint? 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%% within Race, Ethnicity, Gender Classification (Business Ownership Classification)

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%








40.0% 0.0% 0.0% 0.0% 20.0% 40.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% .8% 0.0% 1.0%

% of Total .4% 0.0% 0.0% 0.0% .2% .4% 0.0% 1.0%Count 2 0 0 1 1 1 0 5% within Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

40.0% 0.0% 0.0% 20.0% 20.0% 20.0% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% .9% .4% 0.0% 1.0%

% of Total .4% 0.0% 0.0% .2% .2% .2% 0.0% 1.0%

Total

Q48 Did you file a complaint? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total



Yes

No


No

No Response

Total

Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District? * Race, Ethnicity, Gender Classification (Business Ownership Classification)




19.1% 1.0% 2.3% 1.4% 23.2% 52.2% .8% 100.0%


95.9% 100.0% 100.0% 87.5% 98.3% 98.8% 100.0% 98.0%

% of Total 18.7% 1.0% 2.2% 1.4% 22.7% 51.1% .8% 98.0%Count 97 5 11 8 115 257 4 497% within Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 0 0 2 1 0 5% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

40.0% 0.0% 0.0% 0.0% 40.0% 20.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 1.7% .4% 0.0% 1.0%

% of Total .4% 0.0% 0.0% 0.0% .4% .2% 0.0% 1.0%Count 49 3 2 2 49 101 1 207% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

23.7% 1.4% 1.0% 1.0% 23.7% 48.8% .5% 100.0%


50.5% 60.0% 18.2% 25.0% 42.6% 39.3% 25.0% 41.6%

% of Total 9.9% .6% .4% .4% 9.9% 20.3% .2% 41.6%Count 0 0 0 0 0 3 0 3% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 0.0% .6%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .6% 0.0% .6%

No Response

Total

Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

Yes

No

Don't Know



Count 46 2 9 6 64 152 3 282% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 0 1 3 3 0 11% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

36.4% 0.0% 0.0% 9.1% 27.3% 27.3% 0.0% 100.0%


4.1% 0.0% 0.0% 12.5% 2.6% 1.2% 0.0% 2.2%

% of Total .8% 0.0% 0.0% .2% .6% .6% 0.0% 2.2%Count 47 3 2 1 48 99 1 201% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

23.4% 1.5% 1.0% .5% 23.9% 49.3% .5% 100.0%


48.5% 60.0% 18.2% 12.5% 41.7% 38.5% 25.0% 40.4%

% of Total 9.5% .6% .4% .2% 9.7% 19.9% .2% 40.4%Count 0 0 0 0 0 3 0 3% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% 1.2% 0.0% .6%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .6% 0.0% .6%

No Response

Total

Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

Yes

No

Don't Know



Count 46 2 9 6 64 152 3 282% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 5 0 0 0 1 0 0 6% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

83.3% 0.0% 0.0% 0.0% 16.7% 0.0% 0.0% 100.0%


5.2% 0.0% 0.0% 0.0% .9% 0.0% 0.0% 1.2%

% of Total 1.0% 0.0% 0.0% 0.0% .2% 0.0% 0.0% 1.2%Count 46 3 2 2 50 105 1 209% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

22.0% 1.4% 1.0% 1.0% 23.9% 50.2% .5% 100.0%


47.4% 60.0% 18.2% 25.0% 43.5% 40.9% 25.0% 42.1%

% of Total 9.3% .6% .4% .4% 10.1% 21.1% .2% 42.1%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%

No Response

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 7 0 0 1 1 3 0 12% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

58.3% 0.0% 0.0% 8.3% 8.3% 25.0% 0.0% 100.0%


7.2% 0.0% 0.0% 12.5% .9% 1.2% 0.0% 2.4%

% of Total 1.4% 0.0% 0.0% .2% .2% .6% 0.0% 2.4%Count 43 3 2 1 50 102 1 202% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

21.3% 1.5% 1.0% .5% 24.8% 50.5% .5% 100.0%


44.3% 60.0% 18.2% 12.5% 43.5% 39.7% 25.0% 40.6%

% of Total 8.7% .6% .4% .2% 10.1% 20.5% .2% 40.6%Count 1 0 0 0 0 0 0 1% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

Yes

No

Don't Know

No Response



Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 0 0 5 11 0 20% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

20.0% 0.0% 0.0% 0.0% 25.0% 55.0% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 4.3% 4.3% 0.0% 4.0%

% of Total .8% 0.0% 0.0% 0.0% 1.0% 2.2% 0.0% 4.0%Count 47 3 2 2 46 94 1 195% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

24.1% 1.5% 1.0% 1.0% 23.6% 48.2% .5% 100.0%


48.5% 60.0% 18.2% 25.0% 40.0% 36.6% 25.0% 39.2%

% of Total 9.5% .6% .4% .4% 9.3% 18.9% .2% 39.2%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

Yes

No

No Response

Total









Count 4 0 0 1 1 5 0 11% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

36.4% 0.0% 0.0% 9.1% 9.1% 45.5% 0.0% 100.0%


4.1% 0.0% 0.0% 12.5% .9% 1.9% 0.0% 2.2%

% of Total .8% 0.0% 0.0% .2% .2% 1.0% 0.0% 2.2%Count 47 3 2 1 50 100 1 204% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

23.0% 1.5% 1.0% .5% 24.5% 49.0% .5% 100.0%


48.5% 60.0% 18.2% 12.5% 43.5% 38.9% 25.0% 41.0%

% of Total 9.5% .6% .4% .2% 10.1% 20.1% .2% 41.0%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 5 0 0 0 2 2 0 9% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

55.6% 0.0% 0.0% 0.0% 22.2% 22.2% 0.0% 100.0%


5.2% 0.0% 0.0% 0.0% 1.7% .8% 0.0% 1.8%

% of Total 1.0% 0.0% 0.0% 0.0% .4% .4% 0.0% 1.8%

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

Yes

No

No Response

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

Yes



Count 46 3 2 2 49 103 1 206% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

22.3% 1.5% 1.0% 1.0% 23.8% 50.0% .5% 100.0%


47.4% 60.0% 18.2% 25.0% 42.6% 40.1% 25.0% 41.4%

% of Total 9.3% .6% .4% .4% 9.9% 20.7% .2% 41.4%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 5 0 0 1 2 3 0 11% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

45.5% 0.0% 0.0% 9.1% 18.2% 27.3% 0.0% 100.0%


5.2% 0.0% 0.0% 12.5% 1.7% 1.2% 0.0% 2.2%

% of Total 1.0% 0.0% 0.0% .2% .4% .6% 0.0% 2.2%Count 46 3 2 1 49 102 1 204% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

22.5% 1.5% 1.0% .5% 24.0% 50.0% .5% 100.0%


47.4% 60.0% 18.2% 12.5% 42.6% 39.7% 25.0% 41.0%

% of Total 9.3% .6% .4% .2% 9.9% 20.5% .2% 41.0%

No

No Response

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

Yes

No



Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 2 0 0 0 0 0 0 2% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .4%Count 49 3 2 2 51 105 1 213% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

23.0% 1.4% .9% .9% 23.9% 49.3% .5% 100.0%


50.5% 60.0% 18.2% 25.0% 44.3% 40.9% 25.0% 42.9%

% of Total 9.9% .6% .4% .4% 10.3% 21.1% .2% 42.9%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%

No Response

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

Yes

No

No Response



Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 0 0 0 0 3 4 1 8% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

0.0% 0.0% 0.0% 0.0% 37.5% 50.0% 12.5% 100.0%


0.0% 0.0% 0.0% 0.0% 2.6% 1.6% 25.0% 1.6%

% of Total 0.0% 0.0% 0.0% 0.0% .6% .8% .2% 1.6%Count 51 3 2 2 48 101 0 207% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

24.6% 1.4% 1.0% 1.0% 23.2% 48.8% 0.0% 100.0%


52.6% 60.0% 18.2% 25.0% 41.7% 39.3% 0.0% 41.6%

% of Total 10.3% .6% .4% .4% 9.7% 20.3% 0.0% 41.6%Count 46 2 9 6 64 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

16.3% .7% 3.2% 2.1% 22.7% 53.9% 1.1% 100.0%


47.4% 40.0% 81.8% 75.0% 55.7% 59.1% 75.0% 56.7%

% of Total 9.3% .4% 1.8% 1.2% 12.9% 30.6% .6% 56.7%Count 97 5 11 8 115 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

Yes

No

No Response

Total









Count 19 1 2 2 23 47 0 94% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

20.2% 1.1% 2.1% 2.1% 24.5% 50.0% 0.0% 100.0%


19.6% 20.0% 18.2% 25.0% 20.0% 18.3% 0.0% 18.9%

% of Total 3.8% .2% .4% .4% 4.6% 9.5% 0.0% 18.9%Count 74 4 9 4 89 185 4 369% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

20.1% 1.1% 2.4% 1.1% 24.1% 50.1% 1.1% 100.0%


76.3% 80.0% 81.8% 50.0% 77.4% 72.0% 100.0% 74.2%

% of Total 14.9% .8% 1.8% .8% 17.9% 37.2% .8% 74.2%Count 4 0 0 2 3 25 0 34% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

11.8% 0.0% 0.0% 5.9% 8.8% 73.5% 0.0% 100.0%


4.1% 0.0% 0.0% 25.0% 2.6% 9.7% 0.0% 6.8%

% of Total .8% 0.0% 0.0% .4% .6% 5.0% 0.0% 6.8%Count 97 5 11 8 115 257 4 497% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 10 1 2 1 22 44 0 80% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

12.5% 1.3% 2.5% 1.3% 27.5% 55.0% 0.0% 100.0%


10.3% 20.0% 18.2% 12.5% 19.1% 17.1% 0.0% 16.1%

% of Total 2.0% .2% .4% .2% 4.4% 8.9% 0.0% 16.1%Count 9 0 0 1 1 3 0 14% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

64.3% 0.0% 0.0% 7.1% 7.1% 21.4% 0.0% 100.0%


9.3% 0.0% 0.0% 12.5% .9% 1.2% 0.0% 2.8%

% of Total 1.8% 0.0% 0.0% .2% .2% .6% 0.0% 2.8%

Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

Yes

No

Don't Know

Total

Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

Approved

Denied



Count 0 0 0 0 0 1 0 1% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .2% 0.0% .2%Count 78 4 9 6 92 209 4 402% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

19.4% 1.0% 2.2% 1.5% 22.9% 52.0% 1.0% 100.0%


80.4% 80.0% 81.8% 75.0% 80.0% 81.3% 100.0% 80.9%

% of Total 15.7% .8% 1.8% 1.2% 18.5% 42.1% .8% 80.9%Count 97 5 11 8 115 257 4 497% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 4 0 1 0 5 6 0 16% within Q54 What was the highest amount of commercial bank loan your company received?

25.0% 0.0% 6.3% 0.0% 31.3% 37.5% 0.0% 100.0%


4.1% 0.0% 9.1% 0.0% 4.3% 2.3% 0.0% 3.2%

% of Total .8% 0.0% .2% 0.0% 1.0% 1.2% 0.0% 3.2%Count 4 0 0 0 9 5 0 18% within Q54 What was the highest amount of commercial bank loan your company received?

22.2% 0.0% 0.0% 0.0% 50.0% 27.8% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 7.8% 1.9% 0.0% 3.6%

% of Total .8% 0.0% 0.0% 0.0% 1.8% 1.0% 0.0% 3.6%Count 1 0 0 0 3 5 0 9% within Q54 What was the highest amount of commercial bank loan your company received?

11.1% 0.0% 0.0% 0.0% 33.3% 55.6% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 2.6% 1.9% 0.0% 1.8%

% of Total .2% 0.0% 0.0% 0.0% .6% 1.0% 0.0% 1.8%Count 0 0 0 0 2 8 0 10% within Q54 What was the highest amount of commercial bank loan your company received?

0.0% 0.0% 0.0% 0.0% 20.0% 80.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 1.7% 3.1% 0.0% 2.0%

% of Total 0.0% 0.0% 0.0% 0.0% .4% 1.6% 0.0% 2.0%

Don't Know

No Response

Total

Q54 What was the highest amount of commercial bank loan your company received? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ54 What was the highest amount of commercial bank loan your company received?

Up to $50,000?

$50,001 to $100,000?

$100,001 to $300,000?

$300,001 to $500,000?



Count 1 1 0 1 0 7 0 10% within Q54 What was the highest amount of commercial bank loan your company received?

10.0% 10.0% 0.0% 10.0% 0.0% 70.0% 0.0% 100.0%


1.0% 20.0% 0.0% 12.5% 0.0% 2.7% 0.0% 2.0%

% of Total .2% .2% 0.0% .2% 0.0% 1.4% 0.0% 2.0%Count 0 0 0 0 1 5 0 6% within Q54 What was the highest amount of commercial bank loan your company received?

0.0% 0.0% 0.0% 0.0% 16.7% 83.3% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 1.9% 0.0% 1.2%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 1.0% 0.0% 1.2%Count 0 0 0 0 0 1 0 1% within Q54 What was the highest amount of commercial bank loan your company received?

0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% 0.0% .2% 0.0% .2%Count 0 0 1 0 0 0 0 1% within Q54 What was the highest amount of commercial bank loan your company received?

0.0% 0.0% 100.0% 0.0% 0.0% 0.0% 0.0% 100.0%


0.0% 0.0% 9.1% 0.0% 0.0% 0.0% 0.0% .2%

% of Total 0.0% 0.0% .2% 0.0% 0.0% 0.0% 0.0% .2%Count 0 0 0 0 2 7 0 9% within Q54 What was the highest amount of commercial bank loan your company received?

0.0% 0.0% 0.0% 0.0% 22.2% 77.8% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% 1.7% 2.7% 0.0% 1.8%

% of Total 0.0% 0.0% 0.0% 0.0% .4% 1.4% 0.0% 1.8%Count 87 4 9 7 93 213 4 417% within Q54 What was the highest amount of commercial bank loan your company received?

20.9% 1.0% 2.2% 1.7% 22.3% 51.1% 1.0% 100.0%


89.7% 80.0% 81.8% 87.5% 80.9% 82.9% 100.0% 83.9%

% of Total 17.5% .8% 1.8% 1.4% 18.7% 42.9% .8% 83.9%Count 97 5 11 8 115 257 4 497% within Q54 What was the highest amount of commercial bank loan your company received?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

$500,001 to $1 million?

$1,000,001 to $3 million?

$5,000,001 to $10 million?

Over $10 million?

No Response/Don't Know

Not Applicable

Total









Count 1 0 0 0 0 0 0 1% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 4 0 0 0 1 1 0 6% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

66.7% 0.0% 0.0% 0.0% 16.7% 16.7% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% .9% .4% 0.0% 1.2%

% of Total .8% 0.0% 0.0% 0.0% .2% .2% 0.0% 1.2%Count 2 0 0 0 0 0 0 2% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .4%Count 2 0 0 1 0 2 0 5% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

40.0% 0.0% 0.0% 20.0% 0.0% 40.0% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% 0.0% .8% 0.0% 1.0%

% of Total .4% 0.0% 0.0% .2% 0.0% .4% 0.0% 1.0%Count 88 5 11 7 114 254 4 483% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

18.2% 1.0% 2.3% 1.4% 23.6% 52.6% .8% 100.0%


90.7% 100.0% 100.0% 87.5% 99.1% 98.8% 100.0% 97.2%

% of Total 17.7% 1.0% 2.2% 1.4% 22.9% 51.1% .8% 97.2%Count 97 5 11 8 115 257 4 497% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 23 0 2 1 12 6 0 44% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

52.3% 0.0% 4.5% 2.3% 27.3% 13.6% 0.0% 100.0%


23.7% 0.0% 18.2% 12.5% 10.4% 2.3% 0.0% 8.9%

% of Total 4.6% 0.0% .4% .2% 2.4% 1.2% 0.0% 8.9%

Q55 Which of the following do you believe was the primary reason for your being denied a loan? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ55 Which of the following do you believe was the primary reason for your being denied a loan?

Insufficient documentation

Insufficient business history

Race or ethnicity of owner

Other, please specify

Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

Strongly Agree

No Response

Total

Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total



Count 15 1 0 1 10 14 1 42% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

35.7% 2.4% 0.0% 2.4% 23.8% 33.3% 2.4% 100.0%


15.5% 20.0% 0.0% 12.5% 8.7% 5.4% 25.0% 8.5%

% of Total 3.0% .2% 0.0% .2% 2.0% 2.8% .2% 8.5%Count 18 1 3 1 28 57 0 108% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

16.7% .9% 2.8% .9% 25.9% 52.8% 0.0% 100.0%


18.6% 20.0% 27.3% 12.5% 24.3% 22.2% 0.0% 21.7%

% of Total 3.6% .2% .6% .2% 5.6% 11.5% 0.0% 21.7%Count 19 2 5 2 25 59 0 112% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

17.0% 1.8% 4.5% 1.8% 22.3% 52.7% 0.0% 100.0%


19.6% 40.0% 45.5% 25.0% 21.7% 23.0% 0.0% 22.5%

% of Total 3.8% .4% 1.0% .4% 5.0% 11.9% 0.0% 22.5%Count 21 1 1 3 39 116 3 184% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

11.4% .5% .5% 1.6% 21.2% 63.0% 1.6% 100.0%


21.6% 20.0% 9.1% 37.5% 33.9% 45.1% 75.0% 37.0%

% of Total 4.2% .2% .2% .6% 7.8% 23.3% .6% 37.0%Count 1 0 0 0 1 5 0 7% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

14.3% 0.0% 0.0% 0.0% 14.3% 71.4% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 1.9% 0.0% 1.4%

% of Total .2% 0.0% 0.0% 0.0% .2% 1.0% 0.0% 1.4%Count 97 5 11 8 115 257 4 497% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Somewhat Agree

Neither agree nor disagree

Somewhat disagree

Strongly disagree

Don't Know

Total









Count 8 0 0 0 5 15 0 28% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

28.6% 0.0% 0.0% 0.0% 17.9% 53.6% 0.0% 100.0%


8.2% 0.0% 0.0% 0.0% 4.3% 5.8% 0.0% 5.6%

% of Total 1.6% 0.0% 0.0% 0.0% 1.0% 3.0% 0.0% 5.6%Count 14 1 1 0 9 13 0 38% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

36.8% 2.6% 2.6% 0.0% 23.7% 34.2% 0.0% 100.0%


14.4% 20.0% 9.1% 0.0% 7.8% 5.1% 0.0% 7.6%

% of Total 2.8% .2% .2% 0.0% 1.8% 2.6% 0.0% 7.6%Count 11 0 2 1 16 35 1 66% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

16.7% 0.0% 3.0% 1.5% 24.2% 53.0% 1.5% 100.0%


11.3% 0.0% 18.2% 12.5% 13.9% 13.6% 25.0% 13.3%

% of Total 2.2% 0.0% .4% .2% 3.2% 7.0% .2% 13.3%Count 43 2 6 4 43 101 1 200% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

21.5% 1.0% 3.0% 2.0% 21.5% 50.5% .5% 100.0%


44.3% 40.0% 54.5% 50.0% 37.4% 39.3% 25.0% 40.2%

% of Total 8.7% .4% 1.2% .8% 8.7% 20.3% .2% 40.2%Count 20 2 2 2 38 85 2 151% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

13.2% 1.3% 1.3% 1.3% 25.2% 56.3% 1.3% 100.0%


20.6% 40.0% 18.2% 25.0% 33.0% 33.1% 50.0% 30.4%

% of Total 4.0% .4% .4% .4% 7.6% 17.1% .4% 30.4%Count 1 0 0 1 4 8 0 14% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

7.1% 0.0% 0.0% 7.1% 28.6% 57.1% 0.0% 100.0%


1.0% 0.0% 0.0% 12.5% 3.5% 3.1% 0.0% 2.8%

% of Total .2% 0.0% 0.0% .2% .8% 1.6% 0.0% 2.8%

Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals? * Race, Ethnicity, Gender Classification (Business Ownership Classification)


TotalQ58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

Very Often

Sometimes

Seldom

Never

Not Applicable

Don't Know



Count 97 5 11 8 115 257 4 497% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 17 0 2 1 5 2 0 27% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

63.0% 0.0% 7.4% 3.7% 18.5% 7.4% 0.0% 100.0%


17.5% 0.0% 18.2% 12.5% 4.3% .8% 0.0% 5.4%

% of Total 3.4% 0.0% .4% .2% 1.0% .4% 0.0% 5.4%Count 77 5 9 7 109 251 4 462% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

16.7% 1.1% 1.9% 1.5% 23.6% 54.3% .9% 100.0%


79.4% 100.0% 81.8% 87.5% 94.8% 97.7% 100.0% 93.0%

% of Total 15.5% 1.0% 1.8% 1.4% 21.9% 50.5% .8% 93.0%Count 1 0 0 0 1 2 0 4% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

25.0% 0.0% 0.0% 0.0% 25.0% 50.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% .8% 0.0% .8%

% of Total .2% 0.0% 0.0% 0.0% .2% .4% 0.0% .8%Count 2 0 0 0 0 2 0 4% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

50.0% 0.0% 0.0% 0.0% 0.0% 50.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% 0.0% .8% 0.0% .8%

% of Total .4% 0.0% 0.0% 0.0% 0.0% .4% 0.0% .8%Count 97 5 11 8 115 257 4 497% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

Yes

No

Do not work in the private sector

Don't Know

Total

Total

Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total










75.0% 0.0% 16.7% 0.0% 0.0% 8.3% 0.0% 100.0%


9.3% 0.0% 18.2% 0.0% 0.0% .4% 0.0% 2.4%

% of Total 1.8% 0.0% .4% 0.0% 0.0% .2% 0.0% 2.4%Count 4 0 0 0 4 0 0 8% within Q60 How did you become aware of the discrimination against your company?

50.0% 0.0% 0.0% 0.0% 50.0% 0.0% 0.0% 100.0%


4.1% 0.0% 0.0% 0.0% 3.5% 0.0% 0.0% 1.6%

% of Total .8% 0.0% 0.0% 0.0% .8% 0.0% 0.0% 1.6%Count 3 0 0 1 1 1 0 6% within Q60 How did you become aware of the discrimination against your company?

50.0% 0.0% 0.0% 16.7% 16.7% 16.7% 0.0% 100.0%


3.1% 0.0% 0.0% 12.5% .9% .4% 0.0% 1.2%

% of Total .6% 0.0% 0.0% .2% .2% .2% 0.0% 1.2%Count 1 0 0 0 0 0 0 1% within Q60 How did you become aware of the discrimination against your company?

100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 80 5 9 7 110 255 4 470% within Q60 How did you become aware of the discrimination against your company?

17.0% 1.1% 1.9% 1.5% 23.4% 54.3% .9% 100.0%


82.5% 100.0% 81.8% 87.5% 95.7% 99.2% 100.0% 94.6%


19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%







Count 6 0 2 0 0 1 0 9% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

66.7% 0.0% 22.2% 0.0% 0.0% 11.1% 0.0% 100.0%


6.2% 0.0% 18.2% 0.0% 0.0% .4% 0.0% 1.8%

% of Total 1.2% 0.0% .4% 0.0% 0.0% .2% 0.0% 1.8%



Verbal comment

Action taken against company

Don't Know

Other Action

No Response

Total

Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?




Count 0 0 0 0 1 0 0 1% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 100.0%


0.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .2%

% of Total 0.0% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .2%Count 8 0 0 0 1 0 0 9% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

88.9% 0.0% 0.0% 0.0% 11.1% 0.0% 0.0% 100.0%


8.2% 0.0% 0.0% 0.0% .9% 0.0% 0.0% 1.8%

% of Total 1.6% 0.0% 0.0% 0.0% .2% 0.0% 0.0% 1.8%Count 2 0 0 1 2 1 0 6% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

33.3% 0.0% 0.0% 16.7% 33.3% 16.7% 0.0% 100.0%


2.1% 0.0% 0.0% 12.5% 1.7% .4% 0.0% 1.2%

% of Total .4% 0.0% 0.0% .2% .4% .2% 0.0% 1.2%Count 1 0 0 0 1 0 0 2% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

50.0% 0.0% 0.0% 0.0% 50.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .4%

% of Total .2% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .4%Count 80 5 9 7 110 255 4 470% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

17.0% 1.1% 1.9% 1.5% 23.4% 54.3% .9% 100.0%


82.5% 100.0% 81.8% 87.5% 95.7% 99.2% 100.0% 94.6%

% of Total 16.1% 1.0% 1.8% 1.4% 22.1% 51.3% .8% 94.6%Count 97 5 11 8 115 257 4 497% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Owner's gender


Don't Know

Some other reason

No Response

Total









Count 4 0 1 1 1 2 0 9% within Q64 When did the discrimination first occur (private sector)? 44.4% 0.0% 11.1% 11.1% 11.1% 22.2% 0.0% 100.0%


4.1% 0.0% 9.1% 12.5% .9% .8% 0.0% 1.8%

% of Total .8% 0.0% .2% .2% .2% .4% 0.0% 1.8%Count 2 0 0 0 1 0 0 3% within Q64 When did the discrimination first occur (private sector)? 66.7% 0.0% 0.0% 0.0% 33.3% 0.0% 0.0% 100.0%


2.1% 0.0% 0.0% 0.0% .9% 0.0% 0.0% .6%

% of Total .4% 0.0% 0.0% 0.0% .2% 0.0% 0.0% .6%Count 2 0 1 0 0 0 0 3% within Q64 When did the discrimination first occur (private sector)? 66.7% 0.0% 33.3% 0.0% 0.0% 0.0% 0.0% 100.0%


2.1% 0.0% 9.1% 0.0% 0.0% 0.0% 0.0% .6%

% of Total .4% 0.0% .2% 0.0% 0.0% 0.0% 0.0% .6%Count 8 0 0 0 3 0 0 11% within Q64 When did the discrimination first occur (private sector)? 72.7% 0.0% 0.0% 0.0% 27.3% 0.0% 0.0% 100.0%


8.2% 0.0% 0.0% 0.0% 2.6% 0.0% 0.0% 2.2%

% of Total 1.6% 0.0% 0.0% 0.0% .6% 0.0% 0.0% 2.2%Count 1 0 0 0 0 0 0 1% within Q64 When did the discrimination first occur (private sector)? 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0%


1.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% .2%Count 80 5 9 7 110 255 4 470% within Q64 When did the discrimination first occur (private sector)? 17.0% 1.1% 1.9% 1.5% 23.4% 54.3% .9% 100.0%


82.5% 100.0% 81.8% 87.5% 95.7% 99.2% 100.0% 94.6%

% of Total 16.1% 1.0% 1.8% 1.4% 22.1% 51.3% .8% 94.6%Count 97 5 11 8 115 257 4 497% within Q64 When did the discrimination first occur (private sector)? 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Q64 When did the discrimination first occur (private sector)?




All of the above

Don't Know

No Response

Q64 When did the discrimination first occur (private sector)? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

Total

Total









Count 4 0 1 0 3 1 0 9% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

44.4% 0.0% 11.1% 0.0% 33.3% 11.1% 0.0% 100.0%


4.1% 0.0% 9.1% 0.0% 2.6% .4% 0.0% 1.8%

% of Total .8% 0.0% .2% 0.0% .6% .2% 0.0% 1.8%Count 13 0 1 1 2 2 0 19% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

68.4% 0.0% 5.3% 5.3% 10.5% 10.5% 0.0% 100.0%


13.4% 0.0% 9.1% 12.5% 1.7% .8% 0.0% 3.8%

% of Total 2.6% 0.0% .2% .2% .4% .4% 0.0% 3.8%Count 80 5 9 7 110 254 4 469% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

17.1% 1.1% 1.9% 1.5% 23.5% 54.2% .9% 100.0%


82.5% 100.0% 81.8% 87.5% 95.7% 98.8% 100.0% 94.4%

% of Total 16.1% 1.0% 1.8% 1.4% 22.1% 51.1% .8% 94.4%Count 97 5 11 8 115 257 4 497% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 19.5% 1.0% 2.2% 1.6% 23.1% 51.7% .8% 100.0%

Total

Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes? * Race, Ethnicity, Gender Classification (Business Ownership Classification) Race, Ethnicity, Gender Classification (Business Ownership Classification)

TotalQ65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

Yes

No

No Response

GUILFORD COUNTY SCHOOL DISTRICT DISPARITY STUDY F | SURVEY OF VENDOR RESULTS


Frequency Percent Valid PercentCumulative

Percent

African American Firms 97 19.5 19.5 19.5Asian American Firms 5 1.0 1.0 20.5Hispanic American Firms 11 2.2 2.2 22.7Native American Firms 8 1.6 1.6 24.3Nonminority Female Firms 115 23.1 23.1 47.5Non-M/WBE Firms 257 51.7 51.7 99.2Other Firms 4 .8 .8 100.0Total 497 100.0 100.0

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 146 81 2 229% within Q1 What is your title? 63.8% 35.4% .9% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

61.9% 31.5% 50.0% 46.1%

% of Total 29.4% 16.3% .4% 46.1%Count 27 28 1 56% within Q1 What is your title? 48.2% 50.0% 1.8% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

11.4% 10.9% 25.0% 11.3%

% of Total 5.4% 5.6% .2% 11.3%Count 56 142 1 199% within Q1 What is your title? 28.1% 71.4% .5% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

23.7% 55.3% 25.0% 40.0%

% of Total 11.3% 28.6% .2% 40.0%Count 7 6 0 13% within Q1 What is your title? 53.8% 46.2% 0.0% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

3.0% 2.3% 0.0% 2.6%

% of Total 1.4% 1.2% 0.0% 2.6%Count 236 257 4 497% within Q1 What is your title? 47.5% 51.7% .8% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 48 47 1 96% within Q4 Please specify your company's primary line of business?

50.0% 49.0% 1.0% 100.0%

% within M/WBE or Non-M/WBE Classification (not based on certification)

20.3% 18.3% 25.0% 19.3%

% of Total 9.7% 9.5% .2% 19.3%Count 8 9 0 17% within Q4 Please specify your company's primary line of business?

47.1% 52.9% 0.0% 100.0%


3.4% 3.5% 0.0% 3.4%

% of Total 1.6% 1.8% 0.0% 3.4%Count 27 10 0 37% within Q4 Please specify your company's primary line of business?

73.0% 27.0% 0.0% 100.0%


11.4% 3.9% 0.0% 7.4%


53.2% 45.2% 1.6% 100.0%


42.4% 33.1% 75.0% 37.8%

% of Total 20.1% 17.1% .6% 37.8%

Q1 What is your title? * M/WBE or Non-M/WBE Classification (not based on certification)


Valid

M/WBE or Non-M/WBE Classification (not based on certification)

TotalQ1 What is your title? Owner

CEO/President

Manager/Financial Officer

Other, Please Specify

Total

Q4 Please specify your company's primary line of business? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ4 Please specify your company's primary line of business?

Construction (heavy construction, general contracting, carpentry, electrical, site work, HVAC, drywall, etc.)

Architecture & Engineering (architecture, engineering, structural, continuing contracts, surveying, etc.)

Professional Services (construction management, attorney, accountant, consultant, etc.)

Non-Professional Services (maintenance services, janitorial, security, auto repair, etc.)



Count 53 106 0 159% within Q4 Please specify your company's primary line of business?

33.3% 66.7% 0.0% 100.0%


22.5% 41.2% 0.0% 32.0%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 150 2 1 153% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

98.0% 1.3% .7% 100.0%


63.6% .8% 25.0% 30.8%

% of Total 30.2% .4% .2% 30.8%Count 85 243 2 330% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

25.8% 73.6% .6% 100.0%


36.0% 94.6% 50.0% 66.4%

% of Total 17.1% 48.9% .4% 66.4%Count 1 12 1 14% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

7.1% 85.7% 7.1% 100.0%


.4% 4.7% 25.0% 2.8%

% of Total .2% 2.4% .2% 2.8%Count 236 257 4 497% within Q10 Is more than 50% of your company owned and controlled by a woman or women?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 114 232 0 346% within Q11 Is more than 50% of the company owned or controlled by one of the following racial or ethnic groups?

32.9% 67.1% 0.0% 100.0%


48.3% 90.3% 0.0% 69.6%

% of Total 22.9% 46.7% 0.0% 69.6%Count 97 0 0 97% within Q11 Is more than 50% of the company owned or controlled by one of the following racial or ethnic groups?

100.0% 0.0% 0.0% 100.0%


41.1% 0.0% 0.0% 19.5%


100.0% 0.0% 0.0% 100.0%


3.4% 0.0% 0.0% 1.6%

% of Total 1.6% 0.0% 0.0% 1.6%

Q10 Is more than 50% of your company owned and controlled by a woman or women? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ10 Is more than 50% of your company owned and controlled by a woman or women?

Yes

No

Don't Know

Total

Q11 Is more than 50% of the company owned or controlled by one of the following racial or ethnic groups? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ11 Is more than 50% of the company owned or controlled by one of the following racial or ethnic groups?

Anglo/Caucasian/White

Black/African American

American Indian/Alaskan Native

Goods (supplies, materials, equipment, commodities, etc.)

Total



Count 5 0 0 5% within Q11 Is more than 50% of the company owned or controlled by one of the following racial or ethnic groups?

100.0% 0.0% 0.0% 100.0%


2.1% 0.0% 0.0% 1.0%


100.0% 0.0% 0.0% 100.0%


4.7% 0.0% 0.0% 2.2%


0.0% 100.0% 0.0% 100.0%


0.0% 3.9% 0.0% 2.0%


5.0% 75.0% 20.0% 100.0%


.4% 5.8% 100.0% 4.0%

% of Total .2% 3.0% .8% 4.0%Count 236 257 4 497% within Q11 Is more than 50% of the company owned or controlled by one of the following racial or ethnic groups?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 1 0 5% within Q13 What is the highest level of education completed by the primary owner of your company?

80.0% 20.0% 0.0% 100.0%


1.7% .4% 0.0% 1.0%

% of Total .8% .2% 0.0% 1.0%Count 36 23 0 59% within Q13 What is the highest level of education completed by the primary owner of your company?

61.0% 39.0% 0.0% 100.0%


15.3% 8.9% 0.0% 11.9%

% of Total 7.2% 4.6% 0.0% 11.9%Count 8 4 0 12% within Q13 What is the highest level of education completed by the primary owner of your company?

66.7% 33.3% 0.0% 100.0%


3.4% 1.6% 0.0% 2.4%

% of Total 1.6% .8% 0.0% 2.4%Count 31 30 0 61% within Q13 What is the highest level of education completed by the primary owner of your company?

50.8% 49.2% 0.0% 100.0%


13.1% 11.7% 0.0% 12.3%


42.6% 55.7% 1.6% 100.0%


44.1% 52.9% 100.0% 49.1%

% of Total 20.9% 27.4% .8% 49.1%

Asian or Pacific Islander

Trade or Technical Education

Some College

College Degree

Hispanic or Latino

Don't Know

Other

Total

Q13 What is the highest level of education completed by the primary owner of your company? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ13 What is the highest level of education completed by the primary owner of your company?

Some High School

High School Graduate



Count 49 39 0 88% within Q13 What is the highest level of education completed by the primary owner of your company?

55.7% 44.3% 0.0% 100.0%


20.8% 15.2% 0.0% 17.7%


14.3% 85.7% 0.0% 100.0%


1.7% 9.3% 0.0% 5.6%

% of Total .8% 4.8% 0.0% 5.6%Count 236 257 4 497% within Q13 What is the highest level of education completed by the primary owner of your company?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 5 26 1 32% within Q14 In what year was your company established (range)?

15.6% 81.3% 3.1% 100.0%


2.1% 10.1% 25.0% 6.4%

% of Total 1.0% 5.2% .2% 6.4%Count 17 55 0 72% within Q14 In what year was your company established (range)?

23.6% 76.4% 0.0% 100.0%


7.2% 21.4% 0.0% 14.5%

% of Total 3.4% 11.1% 0.0% 14.5%Count 13 45 0 58% within Q14 In what year was your company established (range)?

22.4% 77.6% 0.0% 100.0%


5.5% 17.5% 0.0% 11.7%


31.3% 67.5% 1.3% 100.0%


10.6% 21.0% 25.0% 16.1%


56.7% 41.3% 1.9% 100.0%


25.0% 16.7% 50.0% 20.9%


77.7% 22.3% 0.0% 100.0%


39.8% 10.5% 0.0% 24.3%


79.3% 20.7% 0.0% 100.0%


9.7% 2.3% 0.0% 5.8%


0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%

% of Total 0.0% .2% 0.0% .2%

Post Graduate Degree

Don't Know

Total

Q14 In what year was your company established (range)? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ14 In what year was your company established (range)?

Prior to 1940

1940 to 1969

1970 to 1979

1980 to 1989

1990 to 1999

2000 to 2009

2010 to 2014

2015



Count 236 257 4 497% within Q14 In what year was your company established (range)?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 3 4 0 7% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

42.9% 57.1% 0.0% 100.0%


1.3% 1.6% 0.0% 1.4%

% of Total .6% .8% 0.0% 1.4%Count 13 9 0 22% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

59.1% 40.9% 0.0% 100.0%


5.5% 3.5% 0.0% 4.4%

% of Total 2.6% 1.8% 0.0% 4.4%Count 17 11 0 28% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

60.7% 39.3% 0.0% 100.0%


7.2% 4.3% 0.0% 5.6%


65.4% 34.6% 0.0% 100.0%


7.2% 3.5% 0.0% 5.2%


45.0% 54.0% 1.0% 100.0%


78.8% 86.8% 100.0% 83.1%

% of Total 37.4% 44.9% .8% 83.1%Count 0 1 0 1% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%

% of Total 0.0% .2% 0.0% .2%Count 236 257 4 497% within Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

20+ years

Don't Know

Total

Total

Q15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ15 How many combined years of experience do you or the primary owner(s) of your company have in the company's primary line of business?

0-5 years

6-10 years

11-15 years

16-20 years



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 156 91 2 249% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

62.7% 36.5% .8% 100.0%


66.1% 35.4% 50.0% 50.1%

% of Total 31.4% 18.3% .4% 50.1%Count 40 45 0 85% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

47.1% 52.9% 0.0% 100.0%


16.9% 17.5% 0.0% 17.1%

% of Total 8.0% 9.1% 0.0% 17.1%Count 8 18 1 27% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

29.6% 66.7% 3.7% 100.0%


3.4% 7.0% 25.0% 5.4%


35.3% 64.7% 0.0% 100.0%


2.5% 4.3% 0.0% 3.4%

% of Total 1.2% 2.2% 0.0% 3.4%Count 25 90 1 116% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

21.6% 77.6% .9% 100.0%


10.6% 35.0% 25.0% 23.3%


33.3% 66.7% 0.0% 100.0%


.4% .8% 0.0% .6%

% of Total .2% .4% 0.0% .6%Count 236 257 4 497% within Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

31-40 employees

41+ employees

Don't Know

Total

Q16 In the last three years, what was the average number of employees on your company's payroll, including full-time and part-time staff?

0-10 employees

11-20 employees

21-30 employees



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 50 8 0 58% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

86.2% 13.8% 0.0% 100.0%


21.2% 3.1% 0.0% 11.7%

% of Total 10.1% 1.6% 0.0% 11.7%Count 25 12 0 37% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

67.6% 32.4% 0.0% 100.0%


10.6% 4.7% 0.0% 7.4%


66.2% 33.8% 0.0% 100.0%


19.1% 8.9% 0.0% 13.7%


59.5% 38.1% 2.4% 100.0%


10.6% 6.2% 25.0% 8.5%

% of Total 5.0% 3.2% .2% 8.5%Count 26 25 0 51% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

51.0% 49.0% 0.0% 100.0%


11.0% 9.7% 0.0% 10.3%


33.8% 64.8% 1.4% 100.0%


10.2% 17.9% 25.0% 14.3%


17.1% 80.0% 2.9% 100.0%


2.5% 10.9% 25.0% 7.0%


22.7% 77.3% 0.0% 100.0%


2.1% 6.6% 0.0% 4.4%

% of Total 1.0% 3.4% 0.0% 4.4%

$50,001 to $100,000?

$100,001 to $300,000?

$300,001 to $500,000?

$500,001 to $1 million?

$1,000,001 to $3 million?

$3,000,001 to $5 million?

Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

Up to $50,000?

$5,000,001 to $10 million?



Count 8 53 0 61% within Q17 Which of the following categories best approximate your company's gross revenues for calendar year 2014?

13.1% 86.9% 0.0% 100.0%


3.4% 20.6% 0.0% 12.3%


42.3% 55.8% 1.9% 100.0%


9.3% 11.3% 25.0% 10.5%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 82 69 1 152% within Q18 What percentage of gross revenues was earned from the District?

53.9% 45.4% .7% 100.0%


34.7% 26.8% 25.0% 30.6%

% of Total 16.5% 13.9% .2% 30.6%Count 102 153 3 258% within Q18 What percentage of gross revenues was earned from the District?

39.5% 59.3% 1.2% 100.0%


43.2% 59.5% 75.0% 51.9%

% of Total 20.5% 30.8% .6% 51.9%Count 18 7 0 25% within Q18 What percentage of gross revenues was earned from the District?

72.0% 28.0% 0.0% 100.0%


7.6% 2.7% 0.0% 5.0%

% of Total 3.6% 1.4% 0.0% 5.0%Count 17 16 0 33% within Q18 What percentage of gross revenues was earned from the District?

51.5% 48.5% 0.0% 100.0%


7.2% 6.2% 0.0% 6.6%


62.5% 37.5% 0.0% 100.0%


2.1% 1.2% 0.0% 1.6%

% of Total 1.0% .6% 0.0% 1.6%Count 12 9 0 21% within Q18 What percentage of gross revenues was earned from the District?

57.1% 42.9% 0.0% 100.0%


5.1% 3.5% 0.0% 4.2%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

1% to 15%

16% to 25%

26% to 50%

51% to 74%

75% to 100%

Total

Over $10 million?

Don't Know

Total

Q18 What percentage of gross revenues was earned from the District? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ18 What percentage of gross revenues was earned from the District?




MWBE FirmsNon-M/WBE

Firms Other Firms

Count 11 17 0 28% within Q18 What percentage of these gross revenues was earned from the Private Sector?

39.3% 60.7% 0.0% 100.0%


4.7% 6.6% 0.0% 5.6%

% of Total 2.2% 3.4% 0.0% 5.6%Count 23 9 0 32% within Q18 What percentage of these gross revenues was earned from the Private Sector?

71.9% 28.1% 0.0% 100.0%


9.7% 3.5% 0.0% 6.4%


56.0% 44.0% 0.0% 100.0%


5.9% 4.3% 0.0% 5.0%


41.5% 58.5% 0.0% 100.0%


14.4% 18.7% 0.0% 16.5%


56.8% 40.5% 2.7% 100.0%


8.9% 5.8% 25.0% 7.4%

% of Total 4.2% 3.0% .2% 7.4%Count 133 157 3 293% within Q18 What percentage of these gross revenues was earned from the Private Sector?

45.4% 53.6% 1.0% 100.0%


56.4% 61.1% 75.0% 59.0%

% of Total 26.8% 31.6% .6% 59.0%Count 236 257 4 497% within Q18 What percentage of these gross revenues was earned from the Private Sector?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 94 82 0 176% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

53.4% 46.6% 0.0% 100.0%


39.8% 31.9% 0.0% 35.4%

% of Total 18.9% 16.5% 0.0% 35.4%Count 53 76 1 130% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

40.8% 58.5% .8% 100.0%


22.5% 29.6% 25.0% 26.2%

% of Total 10.7% 15.3% .2% 26.2%

Q18 What percentage of these gross revenues was earned from the Private Sector? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ18 What percentage of these gross revenues was earned from the Private Sector?


1% to 15%

16% to 25%

26% to 50%

51% to 74%

75% to 100%

Total

Q18 What percentage of these gross revenues was earned from the Non-District Public Sector? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ18 What percentage of these gross revenues was earned from the Non-District Public Sector?


1% to 15%



Count 18 28 3 49% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

36.7% 57.1% 6.1% 100.0%


7.6% 10.9% 75.0% 9.9%

% of Total 3.6% 5.6% .6% 9.9%Count 39 39 0 78% within Q18 What percentage of these gross revenues was earned from the Non-District Public Sector?

50.0% 50.0% 0.0% 100.0%


16.5% 15.2% 0.0% 15.7%


50.0% 50.0% 0.0% 100.0%


4.2% 3.9% 0.0% 4.0%


50.0% 50.0% 0.0% 100.0%


9.3% 8.6% 0.0% 8.9%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 81 5 0 86% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

94.2% 5.8% 0.0% 100.0%


34.3% 1.9% 0.0% 17.3%

% of Total 16.3% 1.0% 0.0% 17.3%Count 152 241 4 397% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

38.3% 60.7% 1.0% 100.0%


64.4% 93.8% 100.0% 79.9%

% of Total 30.6% 48.5% .8% 79.9%Count 3 11 0 14% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

21.4% 78.6% 0.0% 100.0%


1.3% 4.3% 0.0% 2.8%

% of Total .6% 2.2% 0.0% 2.8%Count 236 257 4 497% within Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency?

75% to 100%

Total

Q19 Does your company hold any Minority Business Enterprise (MBE) certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

16% to 25%

26% to 50%

51% to 74%

Yes

No

Don't Know

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 70 46 1 117% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

59.8% 39.3% .9% 100.0%


29.7% 17.9% 25.0% 23.5%

% of Total 14.1% 9.3% .2% 23.5%Count 162 201 3 366% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

44.3% 54.9% .8% 100.0%


68.6% 78.2% 75.0% 73.6%

% of Total 32.6% 40.4% .6% 73.6%Count 4 10 0 14% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

28.6% 71.4% 0.0% 100.0%


1.7% 3.9% 0.0% 2.8%

% of Total .8% 2.0% 0.0% 2.8%Count 236 257 4 497% within Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 64 3 1 68% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

94.1% 4.4% 1.5% 100.0%


27.1% 1.2% 25.0% 13.7%

% of Total 12.9% .6% .2% 13.7%Count 168 247 3 418% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

40.2% 59.1% .7% 100.0%


71.2% 96.1% 75.0% 84.1%

% of Total 33.8% 49.7% .6% 84.1%Count 4 7 0 11% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

36.4% 63.6% 0.0% 100.0%


1.7% 2.7% 0.0% 2.2%

% of Total .8% 1.4% 0.0% 2.2%Count 236 257 4 497% within Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency?

Yes

No

Don't Know

Total

Q19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification)

Q19 Does your company hold any Small Business Enterprise (SBE) certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification)


Total


TotalQ19 Does your company hold any Woman Business Enterprise (WBE) certifications from a recognized certification agency?

Yes

No

Don't Know



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 36 2 0 38% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

94.7% 5.3% 0.0% 100.0%


15.3% .8% 0.0% 7.6%

% of Total 7.2% .4% 0.0% 7.6%Count 195 247 4 446% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

43.7% 55.4% .9% 100.0%


82.6% 96.1% 100.0% 89.7%

% of Total 39.2% 49.7% .8% 89.7%Count 5 8 0 13% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

38.5% 61.5% 0.0% 100.0%


2.1% 3.1% 0.0% 2.6%

% of Total 1.0% 1.6% 0.0% 2.6%Count 236 257 4 497% within Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 51 5 0 56% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

91.1% 8.9% 0.0% 100.0%


21.6% 1.9% 0.0% 11.3%

% of Total 10.3% 1.0% 0.0% 11.3%Count 182 241 4 427% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

42.6% 56.4% .9% 100.0%


77.1% 93.8% 100.0% 85.9%

% of Total 36.6% 48.5% .8% 85.9%Count 3 11 0 14% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

21.4% 78.6% 0.0% 100.0%


1.3% 4.3% 0.0% 2.8%

% of Total .6% 2.2% 0.0% 2.8%Count 236 257 4 497% within Q19 Does your company hold any HubZone certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q19 Does your company hold any HubZone certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

Total

Q19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ19 Does your company hold any Disadvantaged Business Enterprise (DBE) certifications from a recognized certification agency?

Yes

No

Don't Know

Total

Q19 Does your company hold any HubZone certifications from a recognized certification agency?

Yes

No

Don't Know

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 13 1 0 14% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

92.9% 7.1% 0.0% 100.0%


5.5% .4% 0.0% 2.8%

% of Total 2.6% .2% 0.0% 2.8%Count 221 247 4 472% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

46.8% 52.3% .8% 100.0%


93.6% 96.1% 100.0% 95.0%

% of Total 44.5% 49.7% .8% 95.0%Count 2 9 0 11% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

18.2% 81.8% 0.0% 100.0%


.8% 3.5% 0.0% 2.2%

% of Total .4% 1.8% 0.0% 2.2%Count 236 257 4 497% within Q19 Does your company hold any 8A certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 9 0 17% within Q19 Does your company hold any other certifications from a recognized certification agency?

47.1% 52.9% 0.0% 100.0%


3.4% 3.5% 0.0% 3.4%

% of Total 1.6% 1.8% 0.0% 3.4%Count 226 241 4 471% within Q19 Does your company hold any other certifications from a recognized certification agency?

48.0% 51.2% .8% 100.0%


95.8% 93.8% 100.0% 94.8%

% of Total 45.5% 48.5% .8% 94.8%Count 2 7 0 9% within Q19 Does your company hold any other certifications from a recognized certification agency?

22.2% 77.8% 0.0% 100.0%


.8% 2.7% 0.0% 1.8%

% of Total .4% 1.4% 0.0% 1.8%Count 236 257 4 497% within Q19 Does your company hold any other certifications from a recognized certification agency?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

Total

Q19 Does your company hold any other certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ19 Does your company hold any other certifications from a recognized certification agency?

Yes

No

Don't Know


TotalQ19 Does your company hold any 8A certifications from a recognized certification agency?

Yes

No

Don't Know

Q19 Does your company hold any 8A certifications from a recognized certification agency? * M/WBE or Non-M/WBE Classification (not based on certification)



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 129 152 3 284% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

45.4% 53.5% 1.1% 100.0%


54.7% 59.1% 75.0% 57.1%

% of Total 26.0% 30.6% .6% 57.1%Count 45 51 1 97% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

46.4% 52.6% 1.0% 100.0%


19.1% 19.8% 25.0% 19.5%

% of Total 9.1% 10.3% .2% 19.5%Count 62 54 0 116% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

53.4% 46.6% 0.0% 100.0%


26.3% 21.0% 0.0% 23.3%

% of Total 12.5% 10.9% 0.0% 23.3%Count 236 257 4 497% within Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 18 17 0 35% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

51.4% 48.6% 0.0% 100.0%


7.6% 6.6% 0.0% 7.0%

% of Total 3.6% 3.4% 0.0% 7.0%Count 85 51 0 136% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

62.5% 37.5% 0.0% 100.0%


36.0% 19.8% 0.0% 27.4%


52.0% 48.0% 0.0% 100.0%


11.0% 9.3% 0.0% 10.1%

% of Total 5.2% 4.8% 0.0% 10.1%

Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014? * M/WBE or Non-M/WBE Classification (not based on certification)


Q21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ21 Does your company bid primarily as a prime contractor/consultant or vendor, subcontractor/subconsultant/supplier or both?

Prime contractor/consultant or vendor

Subcontractor/subconsultant or supplier

Both

Total

TotalQ22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

None

Up to $50,000?

$50,001 to $100,000?



Count 11 11 0 22% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

50.0% 50.0% 0.0% 100.0%


4.7% 4.3% 0.0% 4.4%


61.1% 38.9% 0.0% 100.0%


4.7% 2.7% 0.0% 3.6%


69.2% 30.8% 0.0% 100.0%


3.8% 1.6% 0.0% 2.6%

% of Total 1.8% .8% 0.0% 2.6%Count 3 10 0 13% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

23.1% 76.9% 0.0% 100.0%


1.3% 3.9% 0.0% 2.6%

% of Total .6% 2.0% 0.0% 2.6%Count 4 14 0 18% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

22.2% 77.8% 0.0% 100.0%


1.7% 5.4% 0.0% 3.6%

% of Total .8% 2.8% 0.0% 3.6%Count 12 50 2 64% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

18.8% 78.1% 3.1% 100.0%


5.1% 19.5% 50.0% 12.9%

% of Total 2.4% 10.1% .4% 12.9%Count 12 18 1 31% within Q22 In general, which of the following dollar ranges best approximate your company's largest prime contract awarded between July 1, 2010 and June 30, 2014?

38.7% 58.1% 3.2% 100.0%


5.1% 7.0% 25.0% 6.2%


46.4% 52.6% 1.0% 100.0%


19.1% 19.8% 25.0% 19.5%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?

$400,001 to $500,000?

$500,001 to $1 million?

Over $1 million?

Don't Know

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 18 14 0 32% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

56.3% 43.8% 0.0% 100.0%


7.6% 5.4% 0.0% 6.4%

% of Total 3.6% 2.8% 0.0% 6.4%Count 84 61 0 145% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

57.9% 42.1% 0.0% 100.0%


35.6% 23.7% 0.0% 29.2%


47.1% 52.9% 0.0% 100.0%


6.8% 7.0% 0.0% 6.8%


37.5% 62.5% 0.0% 100.0%


2.5% 3.9% 0.0% 3.2%


71.4% 28.6% 0.0% 100.0%


4.2% 1.6% 0.0% 2.8%

% of Total 2.0% .8% 0.0% 2.8%Count 2 1 0 3% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

66.7% 33.3% 0.0% 100.0%


.8% .4% 0.0% .6%

% of Total .4% .2% 0.0% .6%Count 1 3 0 4% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

25.0% 75.0% 0.0% 100.0%


.4% 1.2% 0.0% .8%

% of Total .2% .6% 0.0% .8%Count 1 6 0 7% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

14.3% 85.7% 0.0% 100.0%


.4% 2.3% 0.0% 1.4%

% of Total .2% 1.2% 0.0% 1.4%

Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

$400,001 to $500,000?

None

Up to $50,000?

$50,001 to $100,000?

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?

Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

$500,001 to $1 million?



Count 11 19 1 31% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

35.5% 61.3% 3.2% 100.0%


4.7% 7.4% 25.0% 6.2%

% of Total 2.2% 3.8% .2% 6.2%Count 13 17 1 31% within Q23 Between July 1, 2010 and June 30, 2014, what was the company's average dollar range for bids, proposals, or quotes as a prime contractor or vendor?

41.9% 54.8% 3.2% 100.0%


5.5% 6.6% 25.0% 6.2%


41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 5 0 13% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

61.5% 38.5% 0.0% 100.0%


3.4% 1.9% 0.0% 2.6%

% of Total 1.6% 1.0% 0.0% 2.6%Count 154 148 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

50.7% 48.7% .7% 100.0%


65.3% 57.6% 50.0% 61.2%

% of Total 31.0% 29.8% .4% 61.2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements?

Yes

No

No Response

Over $1 million?

Don't Know

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime contractor/vendor: Prequalification requirements? * M/WBE or Non-M/WBE Classification (not based on certification)



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 4 0 13% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

69.2% 30.8% 0.0% 100.0%


3.8% 1.6% 0.0% 2.6%

% of Total 1.8% .8% 0.0% 2.6%Count 153 149 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

50.3% 49.0% .7% 100.0%


64.8% 58.0% 50.0% 61.2%

% of Total 30.8% 30.0% .4% 61.2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 6 1 0 7% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

85.7% 14.3% 0.0% 100.0%


2.5% .4% 0.0% 1.4%

% of Total 1.2% .2% 0.0% 1.4%Count 156 152 2 310% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

50.3% 49.0% .6% 100.0%


66.1% 59.1% 50.0% 62.4%

% of Total 31.4% 30.6% .4% 62.4%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

Yes

No

No Response

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Bid bond requirements?

Yes

No

No Response



Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Performance / payment bond requirements?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 5 4 0 9% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

55.6% 44.4% 0.0% 100.0%


2.1% 1.6% 0.0% 1.8%

% of Total 1.0% .8% 0.0% 1.8%Count 157 149 2 308% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

51.0% 48.4% .6% 100.0%


66.5% 58.0% 50.0% 62.0%

% of Total 31.6% 30.0% .4% 62.0%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 11 1 0 12% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

91.7% 8.3% 0.0% 100.0%


4.7% .4% 0.0% 2.4%

% of Total 2.2% .2% 0.0% 2.4%Count 151 151 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

49.7% 49.7% .7% 100.0%


64.0% 58.8% 50.0% 61.2%

% of Total 30.4% 30.4% .4% 61.2%

Total

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Cost bidding / proposing?

Yes

No

No Response

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

Yes

No



Count 0 1 0 1% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%

% of Total 0.0% .2% 0.0% .2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Financing?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 14 5 0 19% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

73.7% 26.3% 0.0% 100.0%


5.9% 1.9% 0.0% 3.8%

% of Total 2.8% 1.0% 0.0% 3.8%Count 148 148 2 298% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

49.7% 49.7% .7% 100.0%


62.7% 57.6% 50.0% 60.0%

% of Total 29.8% 29.8% .4% 60.0%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 9 0 13% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

30.8% 69.2% 0.0% 100.0%


1.7% 3.5% 0.0% 2.6%

% of Total .8% 1.8% 0.0% 2.6%

Total

Total

Don't Know

No Response

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

Yes

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Insurance?

Yes

No

No Response



Count 158 144 2 304% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

52.0% 47.4% .7% 100.0%


66.9% 56.0% 50.0% 61.2%

% of Total 31.8% 29.0% .4% 61.2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Price of supplies / materials?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 12 1 22% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

40.9% 54.5% 4.5% 100.0%


3.8% 4.7% 25.0% 4.4%

% of Total 1.8% 2.4% .2% 4.4%Count 153 141 1 295% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

51.9% 47.8% .3% 100.0%


64.8% 54.9% 25.0% 59.4%


41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 14 14 0 28% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

50.0% 50.0% 0.0% 100.0%


5.9% 5.4% 0.0% 5.6%

% of Total 2.8% 2.8% 0.0% 5.6%

Total

Total

No

No Response

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

Yes

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Proposal / Bid specifications?

Yes

No

No Response



Count 148 139 2 289% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

51.2% 48.1% .7% 100.0%


62.7% 54.1% 50.0% 58.1%

% of Total 29.8% 28.0% .4% 58.1%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Short or limited time to prepare bid package?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 17 6 0 23% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

73.9% 26.1% 0.0% 100.0%


7.2% 2.3% 0.0% 4.6%

% of Total 3.4% 1.2% 0.0% 4.6%Count 144 147 2 293% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

49.1% 50.2% .7% 100.0%


61.0% 57.2% 50.0% 59.0%

% of Total 29.0% 29.6% .4% 59.0%Count 1 0 0 1% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Limited knowledge of purchasing and contracting policies and procedures?

Yes

No

Don't Know

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 5 3 0 8% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

62.5% 37.5% 0.0% 100.0%


2.1% 1.2% 0.0% 1.6%

% of Total 1.0% .6% 0.0% 1.6%Count 157 150 2 309% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

50.8% 48.5% .6% 100.0%


66.5% 58.4% 50.0% 62.2%

% of Total 31.6% 30.2% .4% 62.2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 6 2 0 8% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

75.0% 25.0% 0.0% 100.0%


2.5% .8% 0.0% 1.6%

% of Total 1.2% .4% 0.0% 1.6%Count 156 151 2 309% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

50.5% 48.9% .6% 100.0%


66.1% 58.8% 50.0% 62.2%

% of Total 31.4% 30.4% .4% 62.2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of experience?

Yes

No

No Response

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Lack of personnel?

Yes

No

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 5 0 14% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

64.3% 35.7% 0.0% 100.0%


3.8% 1.9% 0.0% 2.8%

% of Total 1.8% 1.0% 0.0% 2.8%Count 153 148 2 303% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

50.5% 48.8% .7% 100.0%


64.8% 57.6% 50.0% 61.0%

% of Total 30.8% 29.8% .4% 61.0%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 12 14 0 26% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

46.2% 53.8% 0.0% 100.0%


5.1% 5.4% 0.0% 5.2%

% of Total 2.4% 2.8% 0.0% 5.2%Count 150 139 2 291% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

51.5% 47.8% .7% 100.0%


63.6% 54.1% 50.0% 58.6%

% of Total 30.2% 28.0% .4% 58.6%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Contract too large?

Yes

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Selection process / evaluation criteria?

Yes

No

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 14 11 0 25% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

56.0% 44.0% 0.0% 100.0%


5.9% 4.3% 0.0% 5.0%

% of Total 2.8% 2.2% 0.0% 5.0%Count 148 142 2 292% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

50.7% 48.6% .7% 100.0%


62.7% 55.3% 50.0% 58.8%

% of Total 29.8% 28.6% .4% 58.8%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 23 9 0 32% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

71.9% 28.1% 0.0% 100.0%


9.7% 3.5% 0.0% 6.4%

% of Total 4.6% 1.8% 0.0% 6.4%Count 139 142 2 283% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

49.1% 50.2% .7% 100.0%


58.9% 55.3% 50.0% 56.9%

% of Total 28.0% 28.6% .4% 56.9%Count 0 2 0 2% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

0.0% 100.0% 0.0% 100.0%


0.0% .8% 0.0% .4%

% of Total 0.0% .4% 0.0% .4%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Unnecessary restrictive contract specifications?

Yes

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

Yes

No

Don't Know



Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Slow payment or nonpayment?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 31 13 0 44% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

70.5% 29.5% 0.0% 100.0%


13.1% 5.1% 0.0% 8.9%

% of Total 6.2% 2.6% 0.0% 8.9%Count 130 140 2 272% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

47.8% 51.5% .7% 100.0%


55.1% 54.5% 50.0% 54.7%

% of Total 26.2% 28.2% .4% 54.7%Count 1 0 0 1% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Competing with large companies?

Yes

No

Don't Know

No Response

Total

No Response



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 4 0 8% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

50.0% 50.0% 0.0% 100.0%


1.7% 1.6% 0.0% 1.6%

% of Total .8% .8% 0.0% 1.6%Count 158 149 2 309% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

51.1% 48.2% .6% 100.0%


66.9% 58.0% 50.0% 62.2%

% of Total 31.8% 30.0% .4% 62.2%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 12 0 16% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

25.0% 75.0% 0.0% 100.0%


1.7% 4.7% 0.0% 3.2%

% of Total .8% 2.4% 0.0% 3.2%Count 158 141 2 301% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

52.5% 46.8% .7% 100.0%


66.9% 54.9% 50.0% 60.6%

% of Total 31.8% 28.4% .4% 60.6%Count 74 104 2 180% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Changes in scope of work (after work began)?

Yes

No

No Response

Total

Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

Yes

No

No Response



Count 236 257 4 497% within Q24 In your experience, have any of the following been a barrier to attempting to do work or working on District projects as a prime: Meeting MWBE goals and good faith effort requirements?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 4 0 12% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

66.7% 33.3% 0.0% 100.0%


3.4% 1.6% 0.0% 2.4%

% of Total 1.6% .8% 0.0% 2.4%Count 152 146 2 300% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

50.7% 48.7% .7% 100.0%


64.4% 56.8% 50.0% 60.4%

% of Total 30.6% 29.4% .4% 60.4%Count 2 3 0 5% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

40.0% 60.0% 0.0% 100.0%


.8% 1.2% 0.0% 1.0%

% of Total .4% .6% 0.0% 1.0%Count 74 104 2 180% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

Q25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ25 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid or proposal for a District contract, were informed you were the lowest bidder, and then found out another firm was actually doing the work?

Yes

No

Don't Know

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 43 47 0 90% within Q26 As a prime contractor/vendor, is your company required to have bonding?

47.8% 52.2% 0.0% 100.0%


18.2% 18.3% 0.0% 18.1%

% of Total 8.7% 9.5% 0.0% 18.1%Count 118 100 2 220% within Q26 As a prime contractor/vendor, is your company required to have bonding?

53.6% 45.5% .9% 100.0%


50.0% 38.9% 50.0% 44.3%

% of Total 23.7% 20.1% .4% 44.3%Count 1 6 0 7% within Q26 As a prime contractor/vendor, is your company required to have bonding?

14.3% 85.7% 0.0% 100.0%


.4% 2.3% 0.0% 1.4%

% of Total .2% 1.2% 0.0% 1.4%Count 74 104 2 180% within Q26 As a prime contractor/vendor, is your company required to have bonding?

41.1% 57.8% 1.1% 100.0%


31.4% 40.5% 50.0% 36.2%

% of Total 14.9% 20.9% .4% 36.2%Count 236 257 4 497% within Q26 As a prime contractor/vendor, is your company required to have bonding?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 5 1 0 6% within Q27 What is your company's current aggregate bonding capacity?

83.3% 16.7% 0.0% 100.0%


2.1% .4% 0.0% 1.2%

% of Total 1.0% .2% 0.0% 1.2%Count 5 2 0 7% within Q27 What is your company's current aggregate bonding capacity?

71.4% 28.6% 0.0% 100.0%


2.1% .8% 0.0% 1.4%


77.8% 22.2% 0.0% 100.0%


3.0% .8% 0.0% 1.8%


57.9% 42.1% 0.0% 100.0%


4.7% 3.1% 0.0% 3.8%

% of Total 2.2% 1.6% 0.0% 3.8%Count 2 4 0 6% within Q27 What is your company's current aggregate bonding capacity?

33.3% 66.7% 0.0% 100.0%


.8% 1.6% 0.0% 1.2%

% of Total .4% .8% 0.0% 1.2%

Total

Q27 What is your company's current aggregate bonding capacity? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

Q26 As a prime contractor/vendor, is your company required to have bonding? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ26 As a prime contractor/vendor, is your company required to have bonding?

Yes

No

Don't Know

No Response

TotalQ27 What is your company's current aggregate bonding capacity?

Below $100,000

$100,001 to $250,000

$250,001 to $500,000


$1,000,001 to $1.5 million



Count 5 3 0 8% within Q27 What is your company's current aggregate bonding capacity?

62.5% 37.5% 0.0% 100.0%


2.1% 1.2% 0.0% 1.6%


33.3% 66.7% 0.0% 100.0%


.4% .8% 0.0% .6%

% of Total .2% .4% 0.0% .6%Count 3 16 0 19% within Q27 What is your company's current aggregate bonding capacity?

15.8% 84.2% 0.0% 100.0%


1.3% 6.2% 0.0% 3.8%

% of Total .6% 3.2% 0.0% 3.8%Count 4 10 0 14% within Q27 What is your company's current aggregate bonding capacity?

28.6% 71.4% 0.0% 100.0%


1.7% 3.9% 0.0% 2.8%

% of Total .8% 2.0% 0.0% 2.8%Count 193 209 4 406% within Q27 What is your company's current aggregate bonding capacity?

47.5% 51.5% 1.0% 100.0%


81.8% 81.3% 100.0% 81.7%

% of Total 38.8% 42.1% .8% 81.7%Count 236 257 4 497% within Q27 What is your company's current aggregate bonding capacity?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 5 1 0 6% within Q28 What is your company's current single limit bonding capacity?

83.3% 16.7% 0.0% 100.0%


2.1% .4% 0.0% 1.2%

% of Total 1.0% .2% 0.0% 1.2%Count 7 2 0 9% within Q28 What is your company's current single limit bonding capacity?

77.8% 22.2% 0.0% 100.0%


3.0% .8% 0.0% 1.8%


69.2% 30.8% 0.0% 100.0%


3.8% 1.6% 0.0% 2.6%


61.5% 38.5% 0.0% 100.0%


3.4% 1.9% 0.0% 2.6%

% of Total 1.6% 1.0% 0.0% 2.6%

Don't Know

No Response

Total

Q28 What is your company's current single limit bonding capacity? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

Total

$1,500,001 to $3 million

$3,000,001 to $5 million

Over $5 million?

Q28 What is your company's current single limit bonding capacity?

Below $100,000

$100,001 to $250,000

$250,001 to $500,000




Count 2 7 0 9% within Q28 What is your company's current single limit bonding capacity?

22.2% 77.8% 0.0% 100.0%


.8% 2.7% 0.0% 1.8%

% of Total .4% 1.4% 0.0% 1.8%Count 3 2 0 5% within Q28 What is your company's current single limit bonding capacity?

60.0% 40.0% 0.0% 100.0%


1.3% .8% 0.0% 1.0%

% of Total .6% .4% 0.0% 1.0%Count 0 2 0 2% within Q28 What is your company's current single limit bonding capacity?

0.0% 100.0% 0.0% 100.0%


0.0% .8% 0.0% .4%

% of Total 0.0% .4% 0.0% .4%Count 3 16 0 19% within Q28 What is your company's current single limit bonding capacity?

15.8% 84.2% 0.0% 100.0%


1.3% 6.2% 0.0% 3.8%

% of Total .6% 3.2% 0.0% 3.8%Count 6 8 0 14% within Q28 What is your company's current single limit bonding capacity?

42.9% 57.1% 0.0% 100.0%


2.5% 3.1% 0.0% 2.8%

% of Total 1.2% 1.6% 0.0% 2.8%Count 193 210 4 407% within Q28 What is your company's current single limit bonding capacity?

47.4% 51.6% 1.0% 100.0%


81.8% 81.7% 100.0% 81.9%

% of Total 38.8% 42.3% .8% 81.9%Count 236 257 4 497% within Q28 What is your company's current single limit bonding capacity?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 6 5 0 11% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

54.5% 45.5% 0.0% 100.0%


2.5% 1.9% 0.0% 2.2%

% of Total 1.2% 1.0% 0.0% 2.2%Count 172 195 3 370% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

46.5% 52.7% .8% 100.0%


72.9% 75.9% 75.0% 74.4%

% of Total 34.6% 39.2% .6% 74.4%Count 11 3 0 14% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

78.6% 21.4% 0.0% 100.0%


4.7% 1.2% 0.0% 2.8%

% of Total 2.2% .6% 0.0% 2.8%

Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

Yes

No

Don't Know

$3,000,001 to $5 million

Over $5 million?

Don't Know

No Response

Total

Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

$1,000,001 to $1.5 million

$1,500,001 to $3 million



Count 2 3 0 5% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

40.0% 60.0% 0.0% 100.0%


.8% 1.2% 0.0% 1.0%

% of Total .4% .6% 0.0% 1.0%Count 45 51 1 97% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

46.4% 52.6% 1.0% 100.0%


19.1% 19.8% 25.0% 19.5%

% of Total 9.1% 10.3% .2% 19.5%Count 236 257 4 497% within Q29 As a prime contractor/vendor did you experience discriminatory behavior by the District when attempting to work or in working on a project between 2010 and 2014?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 3 2 0 5% within Q30 How did you become aware of the discrimination against your company?

60.0% 40.0% 0.0% 100.0%


1.3% .8% 0.0% 1.0%

% of Total .6% .4% 0.0% 1.0%Count 2 1 0 3% within Q30 How did you become aware of the discrimination against your company?

66.7% 33.3% 0.0% 100.0%


.8% .4% 0.0% .6%

% of Total .4% .2% 0.0% .6%Count 1 2 0 3% within Q30 How did you become aware of the discrimination against your company?

33.3% 66.7% 0.0% 100.0%


.4% .8% 0.0% .6%

% of Total .2% .4% 0.0% .6%Count 230 252 4 486% within Q30 How did you become aware of the discrimination against your company?

47.3% 51.9% .8% 100.0%


97.5% 98.1% 100.0% 97.8%

% of Total 46.3% 50.7% .8% 97.8%Count 236 257 4 497% within Q30 How did you become aware of the discrimination against your company?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

Not Applicable

No Response

Total

Q30 How did you become aware of the discrimination against your company? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)


Verbal comment

Action taken against the company

Other Action

No Response



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 3 0 0 3% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

100.0% 0.0% 0.0% 100.0%


1.3% 0.0% 0.0% .6%

% of Total .6% 0.0% 0.0% .6%Count 2 2 0 4% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

50.0% 50.0% 0.0% 100.0%


.8% .8% 0.0% .8%

% of Total .4% .4% 0.0% .8%Count 0 3 0 3% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

0.0% 100.0% 0.0% 100.0%


0.0% 1.2% 0.0% .6%

% of Total 0.0% .6% 0.0% .6%Count 1 0 0 1% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%


47.3% 51.9% .8% 100.0%


97.5% 98.1% 100.0% 97.8%

% of Total 46.3% 50.7% .8% 97.8%Count 236 257 4 497% within Q32 Which of the following do you consider the primary reason for your company being discriminated against?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q32 Which of the following do you consider the primary reason for your company being discriminated against? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ32 Which of the following do you consider the primary reason for your company being discriminated against?

Owner's Race or Ethnicity


Don't Know

Some other reason

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 2 2 0 4% within Q34 When did the discrimination first occur?

50.0% 50.0% 0.0% 100.0%


.8% .8% 0.0% .8%

% of Total .4% .4% 0.0% .8%Count 1 0 0 1% within Q34 When did the discrimination first occur?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 2 0 0 2% within Q34 When did the discrimination first occur?

100.0% 0.0% 0.0% 100.0%


.8% 0.0% 0.0% .4%


25.0% 75.0% 0.0% 100.0%


.4% 1.2% 0.0% .8%


47.3% 51.9% .8% 100.0%


97.5% 98.1% 100.0% 97.8%

% of Total 46.3% 50.7% .8% 97.8%Count 236 257 4 497% within Q34 When did the discrimination first occur?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 1 0 5% within Q35 Did you file a complaint? 80.0% 20.0% 0.0% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

1.7% .4% 0.0% 1.0%

% of Total .8% .2% 0.0% 1.0%Count 2 4 0 6% within Q35 Did you file a complaint? 33.3% 66.7% 0.0% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

.8% 1.6% 0.0% 1.2%

% of Total .4% .8% 0.0% 1.2%Count 230 252 4 486% within Q35 Did you file a complaint? 47.3% 51.9% .8% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

97.5% 98.1% 100.0% 97.8%

% of Total 46.3% 50.7% .8% 97.8%Count 236 257 4 497% within Q35 Did you file a complaint? 47.5% 51.7% .8% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 4 0 8% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

50.0% 50.0% 0.0% 100.0%


1.7% 1.6% 0.0% 1.6%

% of Total .8% .8% 0.0% 1.6%


No

No Response

No Response

Total

Q35 Did you file a complaint? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

Total

Q34 When did the discrimination first occur? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)





All of the above

Total

Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District? * M/WBE or Non-M/WBE Classification (not based on certification)



Yes




66.7% 33.3% 0.0% 100.0%


.8% .4% 0.0% .6%

% of Total .4% .2% 0.0% .6%Count 230 252 4 486% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

47.3% 51.9% .8% 100.0%


97.5% 98.1% 100.0% 97.8%

% of Total 46.3% 50.7% .8% 97.8%Count 236 257 4 497% within Q36 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 13 5 0 18% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

72.2% 27.8% 0.0% 100.0%


5.5% 1.9% 0.0% 3.6%

% of Total 2.6% 1.0% 0.0% 3.6%Count 46 42 1 89% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

51.7% 47.2% 1.1% 100.0%


19.5% 16.3% 25.0% 17.9%

% of Total 9.3% 8.5% .2% 17.9%Count 14 16 0 30% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

46.7% 53.3% 0.0% 100.0%


5.9% 6.2% 0.0% 6.0%


58.3% 41.7% 0.0% 100.0%


3.0% 1.9% 0.0% 2.4%


77.8% 22.2% 0.0% 100.0%


3.0% .8% 0.0% 1.8%

% of Total 1.4% .4% 0.0% 1.8%Count 4 2 0 6% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

66.7% 33.3% 0.0% 100.0%


1.7% .8% 0.0% 1.2%

% of Total .8% .4% 0.0% 1.2%

Total

Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014 * M/WBE or Non-M/WBE Classification (not based on certification)

No

No Response


TotalQ37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

None

Up to $50,000?

$50,001 to $100,000?

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?



Count 3 3 0 6% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

50.0% 50.0% 0.0% 100.0%


1.3% 1.2% 0.0% 1.2%

% of Total .6% .6% 0.0% 1.2%Count 5 8 0 13% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

38.5% 61.5% 0.0% 100.0%


2.1% 3.1% 0.0% 2.6%


31.8% 68.2% 0.0% 100.0%


3.0% 5.8% 0.0% 4.4%


36.4% 63.6% 0.0% 100.0%


1.7% 2.7% 0.0% 2.2%

% of Total .8% 1.4% 0.0% 2.2%Count 126 152 3 281% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q37 In general, which of the following dollar ranges best approximate your company's largest subcontract between July 1, 2010 and June 30, 2014

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 14 4 0 18% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

77.8% 22.2% 0.0% 100.0%


5.9% 1.6% 0.0% 3.6%

% of Total 2.8% .8% 0.0% 3.6%Count 53 52 1 106% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

50.0% 49.1% .9% 100.0%


22.5% 20.2% 25.0% 21.3%

% of Total 10.7% 10.5% .2% 21.3%Count 7 15 0 22% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

31.8% 68.2% 0.0% 100.0%


3.0% 5.8% 0.0% 4.4%

% of Total 1.4% 3.0% 0.0% 4.4%

Over $1 million?

Don't Know

No Response

Total

Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

$400,001 to $500,000?

$500,001 to $1 million?

Up to $50,000?

$50,001 to $100,000?

Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

None



Count 7 2 0 9% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

77.8% 22.2% 0.0% 100.0%


3.0% .8% 0.0% 1.8%

% of Total 1.4% .4% 0.0% 1.8%Count 11 5 0 16% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

68.8% 31.3% 0.0% 100.0%


4.7% 1.9% 0.0% 3.2%

% of Total 2.2% 1.0% 0.0% 3.2%Count 2 6 0 8% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

25.0% 75.0% 0.0% 100.0%


.8% 2.3% 0.0% 1.6%

% of Total .4% 1.2% 0.0% 1.6%Count 1 2 0 3% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

33.3% 66.7% 0.0% 100.0%


.4% .8% 0.0% .6%

% of Total .2% .4% 0.0% .6%Count 4 2 0 6% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

66.7% 33.3% 0.0% 100.0%


1.7% .8% 0.0% 1.2%

% of Total .8% .4% 0.0% 1.2%Count 5 8 0 13% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

38.5% 61.5% 0.0% 100.0%


2.1% 3.1% 0.0% 2.6%


40.0% 60.0% 0.0% 100.0%


2.5% 3.5% 0.0% 3.0%


44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q38 Between July 1, 2010 and June 30, 2014, what was the average dollar range for bids, proposals, or quotes as a subcontractor or supplier?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Over $1 million?

Don't Know

No Response

Total

$100,001 to $200,000?

$200,001 to $300,000?

$300,001 to $400,000?

$400,001 to $500,000?

$500,001 to $1 million?



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 4 0 13% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

69.2% 30.8% 0.0% 100.0%


3.8% 1.6% 0.0% 2.6%

% of Total 1.8% .8% 0.0% 2.6%Count 101 101 1 203% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

49.8% 49.8% .5% 100.0%


42.8% 39.3% 25.0% 40.8%

% of Total 20.3% 20.3% .2% 40.8%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 6 3 0 9% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

66.7% 33.3% 0.0% 100.0%


2.5% 1.2% 0.0% 1.8%

% of Total 1.2% .6% 0.0% 1.8%Count 104 102 1 207% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

50.2% 49.3% .5% 100.0%


44.1% 39.7% 25.0% 41.6%

% of Total 20.9% 20.5% .2% 41.6%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Yes

No

No Response

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Performance/payment bond requirements?



Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Cost bidding / proposing?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 10 1 0 11% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

90.9% 9.1% 0.0% 100.0%


4.2% .4% 0.0% 2.2%

% of Total 2.0% .2% 0.0% 2.2%Count 100 104 1 205% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

48.8% 50.7% .5% 100.0%


42.4% 40.5% 25.0% 41.2%

% of Total 20.1% 20.9% .2% 41.2%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 11 2 1 14% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

78.6% 14.3% 7.1% 100.0%


4.7% .8% 25.0% 2.8%

% of Total 2.2% .4% .2% 2.8%Count 99 103 0 202% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

49.0% 51.0% 0.0% 100.0%


41.9% 40.1% 0.0% 40.6%

% of Total 19.9% 20.7% 0.0% 40.6%

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Yes

No

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Financing?



Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Insurance?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 2 1 12% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

75.0% 16.7% 8.3% 100.0%


3.8% .8% 25.0% 2.4%

% of Total 1.8% .4% .2% 2.4%Count 101 103 0 204% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

49.5% 50.5% 0.0% 100.0%


42.8% 40.1% 0.0% 41.0%

% of Total 20.3% 20.7% 0.0% 41.0%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 15 8 0 23% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

65.2% 34.8% 0.0% 100.0%


6.4% 3.1% 0.0% 4.6%

% of Total 3.0% 1.6% 0.0% 4.6%

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

Yes

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Price of supplies / materials?



Count 95 97 1 193% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

49.2% 50.3% .5% 100.0%


40.3% 37.7% 25.0% 38.8%

% of Total 19.1% 19.5% .2% 38.8%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Short or limited time given to prepare bid package or quote?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 2 0 6% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

66.7% 33.3% 0.0% 100.0%


1.7% .8% 0.0% 1.2%

% of Total .8% .4% 0.0% 1.2%Count 106 103 1 210% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

50.5% 49.0% .5% 100.0%


44.9% 40.1% 25.0% 42.3%

% of Total 21.3% 20.7% .2% 42.3%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of experience?

Yes

No

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 5 2 0 7% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

71.4% 28.6% 0.0% 100.0%


2.1% .8% 0.0% 1.4%

% of Total 1.0% .4% 0.0% 1.4%Count 105 103 1 209% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

50.2% 49.3% .5% 100.0%


44.5% 40.1% 25.0% 42.1%

% of Total 21.1% 20.7% .2% 42.1%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 15 4 1 20% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

75.0% 20.0% 5.0% 100.0%


6.4% 1.6% 25.0% 4.0%

% of Total 3.0% .8% .2% 4.0%Count 95 101 0 196% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

48.5% 51.5% 0.0% 100.0%


40.3% 39.3% 0.0% 39.4%

% of Total 19.1% 20.3% 0.0% 39.4%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel?

Yes

No

No Response

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Lack of personnel? * M/WBE or Non-M/WBE Classification (not based on certification)

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Contract too large?

Yes

No

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 16 5 1 22% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

72.7% 22.7% 4.5% 100.0%


6.8% 1.9% 25.0% 4.4%

% of Total 3.2% 1.0% .2% 4.4%Count 94 100 0 194% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

48.5% 51.5% 0.0% 100.0%


39.8% 38.9% 0.0% 39.0%

% of Total 18.9% 20.1% 0.0% 39.0%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 30 13 0 43% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

69.8% 30.2% 0.0% 100.0%


12.7% 5.1% 0.0% 8.7%

% of Total 6.0% 2.6% 0.0% 8.7%Count 80 92 1 173% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

46.2% 53.2% .6% 100.0%


33.9% 35.8% 25.0% 34.8%

% of Total 16.1% 18.5% .2% 34.8%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Slow payment or nonpayment?

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

Yes

No

No Response



Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Competing with large companies?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 10 1 20% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

45.0% 50.0% 5.0% 100.0%


3.8% 3.9% 25.0% 4.0%

% of Total 1.8% 2.0% .2% 4.0%Count 101 95 0 196% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

51.5% 48.5% 0.0% 100.0%


42.8% 37.0% 0.0% 39.4%

% of Total 20.3% 19.1% 0.0% 39.4%Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 4 0 13% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

69.2% 30.8% 0.0% 100.0%


3.8% 1.6% 0.0% 2.6%

% of Total 1.8% .8% 0.0% 2.6%Count 101 101 1 203% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

49.8% 49.8% .5% 100.0%


42.8% 39.3% 25.0% 40.8%

% of Total 20.3% 20.3% .2% 40.8%

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Solicitation of subcontractor bids after contract award?

Yes

No

No Response

Total

Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

Yes

No



Count 126 152 3 281% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q39 In your experience, have any of the following been a barrier to attempting to do work or working on projects as a subcontractor with primes for the District: Awarded scope of work reduced or eliminated?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 11 8 0 19% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

57.9% 42.1% 0.0% 100.0%


4.7% 3.1% 0.0% 3.8%

% of Total 2.2% 1.6% 0.0% 3.8%Count 98 97 1 196% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

50.0% 49.5% .5% 100.0%


41.5% 37.7% 25.0% 39.4%

% of Total 19.7% 19.5% .2% 39.4%Count 1 0 0 1% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 126 152 3 281% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total


TotalQ40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work?

Yes

No

Don't Know

No Response

No Response

Total

Q40 Between July 1, 2010 and June 30, 2014, has your company ever submitted a bid with a prime for a project with the District, were informed you were the lowest bidder, and found out another sub was actually doing the work? * M/WBE or Non-M/WBE Classification (not based on certification)



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 39 31 0 70% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

55.7% 44.3% 0.0% 100.0%


16.5% 12.1% 0.0% 14.1%

% of Total 7.8% 6.2% 0.0% 14.1%Count 71 72 1 144% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

49.3% 50.0% .7% 100.0%


30.1% 28.0% 25.0% 29.0%

% of Total 14.3% 14.5% .2% 29.0%Count 0 2 0 2% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

0.0% 100.0% 0.0% 100.0%


0.0% .8% 0.0% .4%

% of Total 0.0% .4% 0.0% .4%Count 126 152 3 281% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 7 3 0 10% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

70.0% 30.0% 0.0% 100.0%


3.0% 1.2% 0.0% 2.0%

% of Total 1.4% .6% 0.0% 2.0%Count 96 98 1 195% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

49.2% 50.3% .5% 100.0%


40.7% 38.1% 25.0% 39.2%

% of Total 19.3% 19.7% .2% 39.2%Count 7 4 0 11% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

63.6% 36.4% 0.0% 100.0%


3.0% 1.6% 0.0% 2.2%

% of Total 1.4% .8% 0.0% 2.2%

Total

Q41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ41 As a subcontractor, do prime contractors on District projects require your company to have a bond for your type of work?

Yes

No

Don't Know

No Response

Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

Yes

No

Not Applicable



Count 126 152 3 281% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

44.8% 54.1% 1.1% 100.0%


53.4% 59.1% 75.0% 56.5%

% of Total 25.4% 30.6% .6% 56.5%Count 236 257 4 497% within Q42 As a subcontractor, did your company experience discriminatory behavior between July 1, 2010 and June 30, 2014 from a prime contractor/vendor working or bidding/proposing on a District project?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms


80.0% 20.0% 0.0% 100.0%


1.7% .4% 0.0% 1.0%

% of Total .8% .2% 0.0% 1.0%Count 2 0 0 2% within Q43 How did you become aware of the discrimination against your company?

100.0% 0.0% 0.0% 100.0%


.8% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% .4%Count 0 2 0 2% within Q43 How did you become aware of the discrimination against your company?

0.0% 100.0% 0.0% 100.0%


0.0% .8% 0.0% .4%

% of Total 0.0% .4% 0.0% .4%Count 1 0 0 1% within Q43 How did you become aware of the discrimination against your company?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%


47.0% 52.2% .8% 100.0%


97.0% 98.8% 100.0% 98.0%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms


75.0% 25.0% 0.0% 100.0%


1.3% .4% 0.0% .8%

% of Total .6% .2% 0.0% .8%

Q45 Which of the following do you consider the primary reason for your company being discriminated against?

No Response

Total


certification)


Verbal Comment

Action Taken Against Company

Don't Know

Other Action


No Response

Total

Q45 Which of the following do you consider the primary reason for your company being discriminated against? * M/WBE or Non-M/WBE Classification (not based on certification)


Total




0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%


100.0% 0.0% 0.0% 100.0%


1.7% 0.0% 0.0% .8%


0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%


47.0% 52.2% .8% 100.0%


97.0% 98.8% 100.0% 98.0%

% of Total 46.1% 51.1% .8% 98.0%Count 236 257 4 497% within Q45 Which of the following do you consider the primary reason for your company being discriminated against?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 3 0 0 3% within Q47 When did the discrimination first occur?

100.0% 0.0% 0.0% 100.0%


1.3% 0.0% 0.0% .6%


100.0% 0.0% 0.0% 100.0%


.8% 0.0% 0.0% .4%


50.0% 50.0% 0.0% 100.0%


.4% .4% 0.0% .4%


33.3% 66.7% 0.0% 100.0%


.4% .8% 0.0% .6%


47.0% 52.2% .8% 100.0%


97.0% 98.8% 100.0% 98.0%

% of Total 46.1% 51.1% .8% 98.0%Count 236 257 4 497% within Q47 When did the discrimination first occur?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total


Don't Know

Some other reason

No Response

Total

Q47 When did the discrimination first occur? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)





All of the above

No Response



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 2 0 0 2% within Q48 Did you file a complaint? 100.0% 0.0% 0.0% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

.8% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% .4%Count 5 3 0 8% within Q48 Did you file a complaint? 62.5% 37.5% 0.0% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

2.1% 1.2% 0.0% 1.6%

% of Total 1.0% .6% 0.0% 1.6%Count 229 254 4 487% within Q48 Did you file a complaint? 47.0% 52.2% .8% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

97.0% 98.8% 100.0% 98.0%

% of Total 46.1% 51.1% .8% 98.0%Count 236 257 4 497% within Q48 Did you file a complaint? 47.5% 51.7% .8% 100.0%% within M/WBE or Non-M/WBE Classification (not based on certification)

100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms


60.0% 40.0% 0.0% 100.0%


1.3% .8% 0.0% 1.0%

% of Total .6% .4% 0.0% 1.0%Count 4 1 0 5% within Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

80.0% 20.0% 0.0% 100.0%


1.7% .4% 0.0% 1.0%

% of Total .8% .2% 0.0% 1.0%Count 229 254 4 487% within Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

47.0% 52.2% .8% 100.0%


97.0% 98.8% 100.0% 98.0%

% of Total 46.1% 51.1% .8% 98.0%Count 236 257 4 497% within Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 4 1 0 5% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

80.0% 20.0% 0.0% 100.0%


1.7% .4% 0.0% 1.0%

% of Total .8% .2% 0.0% 1.0%

Total

Total

Q49 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company has experienced by the District? * M/WBE or Non-M/WBE Classification (not based on certification)



Yes

No

No Response

Q48 Did you file a complaint? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ48 Did you file a complaint? Yes

No

No Response

Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

Yes



Count 105 101 1 207% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

50.7% 48.8% .5% 100.0%


44.5% 39.3% 25.0% 41.6%

% of Total 21.1% 20.3% .2% 41.6%Count 0 3 0 3% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

0.0% 100.0% 0.0% 100.0%


0.0% 1.2% 0.0% .6%

% of Total 0.0% .6% 0.0% .6%Count 127 152 3 282% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? District project

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 3 0 11% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

72.7% 27.3% 0.0% 100.0%


3.4% 1.2% 0.0% 2.2%

% of Total 1.6% .6% 0.0% 2.2%Count 101 99 1 201% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

50.2% 49.3% .5% 100.0%


42.8% 38.5% 25.0% 40.4%

% of Total 20.3% 19.9% .2% 40.4%Count 0 3 0 3% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

0.0% 100.0% 0.0% 100.0%


0.0% 1.2% 0.0% .6%

% of Total 0.0% .6% 0.0% .6%

Total

No

Don't Know

No Response

Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

Yes

No

Don't Know



Count 127 152 3 282% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q50 Has your company experienced or observed a prime including a MWBE sub on a bid or proposal to satisfy the GFE requirements and then drops the sub after winning the award for no legitimate reason? Non-District project

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 6 0 0 6% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

100.0% 0.0% 0.0% 100.0%


2.5% 0.0% 0.0% 1.2%

% of Total 1.2% 0.0% 0.0% 1.2%Count 103 105 1 209% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

49.3% 50.2% .5% 100.0%


43.6% 40.9% 25.0% 42.1%

% of Total 20.7% 21.1% .2% 42.1%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 3 0 12% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

75.0% 25.0% 0.0% 100.0%


3.8% 1.2% 0.0% 2.4%

% of Total 1.8% .6% 0.0% 2.4%

Total

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Harassment?

Yes

No

No Response

No Response

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

Yes



Count 99 102 1 202% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

49.0% 50.5% .5% 100.0%


41.9% 39.7% 25.0% 40.6%

% of Total 19.9% 20.5% .2% 40.6%Count 1 0 0 1% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal or unfair treatment?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 9 11 0 20% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

45.0% 55.0% 0.0% 100.0%


3.8% 4.3% 0.0% 4.0%

% of Total 1.8% 2.2% 0.0% 4.0%Count 100 94 1 195% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

51.3% 48.2% .5% 100.0%


42.4% 36.6% 25.0% 39.2%

% of Total 20.1% 18.9% .2% 39.2%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Bid shopping or bid manipulation?

Yes

No

No Response

No

Don't Know

No Response

Total

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 6 5 0 11% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

54.5% 45.5% 0.0% 100.0%


2.5% 1.9% 0.0% 2.2%

% of Total 1.2% 1.0% 0.0% 2.2%Count 103 100 1 204% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

50.5% 49.0% .5% 100.0%


43.6% 38.9% 25.0% 41.0%

% of Total 20.7% 20.1% .2% 41.0%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 7 2 0 9% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

77.8% 22.2% 0.0% 100.0%


3.0% .8% 0.0% 1.8%

% of Total 1.4% .4% 0.0% 1.8%Count 102 103 1 206% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

49.5% 50.0% .5% 100.0%


43.2% 40.1% 25.0% 41.4%

% of Total 20.5% 20.7% .2% 41.4%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Double standards in performance?

Yes

No

No Response

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

Yes

No

No Response



Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Denial of opportunity to bid?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 3 0 11% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

72.7% 27.3% 0.0% 100.0%


3.4% 1.2% 0.0% 2.2%

% of Total 1.6% .6% 0.0% 2.2%Count 101 102 1 204% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

49.5% 50.0% .5% 100.0%


42.8% 39.7% 25.0% 41.0%

% of Total 20.3% 20.5% .2% 41.0%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 2 0 0 2% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

100.0% 0.0% 0.0% 100.0%


.8% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% .4%Count 107 105 1 213% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

50.2% 49.3% .5% 100.0%


45.3% 40.9% 25.0% 42.9%

% of Total 21.5% 21.1% .2% 42.9%

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award? * M/WBE or Non-M/WBE Classification (not based on certification)

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

Yes

No

TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair denial of contract award?

Yes

No

No Response

Total




Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unfair termination?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 3 4 1 8% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

37.5% 50.0% 12.5% 100.0%


1.3% 1.6% 25.0% 1.6%

% of Total .6% .8% .2% 1.6%Count 106 101 0 207% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

51.2% 48.8% 0.0% 100.0%


44.9% 39.3% 0.0% 41.6%

% of Total 21.3% 20.3% 0.0% 41.6%Count 127 152 3 282% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

45.0% 53.9% 1.1% 100.0%


53.8% 59.1% 75.0% 56.7%

% of Total 25.6% 30.6% .6% 56.7%Count 236 257 4 497% within Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 47 47 0 94% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

50.0% 50.0% 0.0% 100.0%


19.9% 18.3% 0.0% 18.9%

% of Total 9.5% 9.5% 0.0% 18.9%

Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

Yes

Total

Q51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers? * M/WBE or Non-M/WBE Classification (not based on certification)


No Response

TotalQ51 Still talking about primes or vendors, while doing business or attempting to do business, have you experienced any of the following as a form of discrimination: Unequal price quotes from suppliers?

Yes

No

No Response

Total



Count 180 185 4 369% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

48.8% 50.1% 1.1% 100.0%


76.3% 72.0% 100.0% 74.2%

% of Total 36.2% 37.2% .8% 74.2%Count 9 25 0 34% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

26.5% 73.5% 0.0% 100.0%


3.8% 9.7% 0.0% 6.8%

% of Total 1.8% 5.0% 0.0% 6.8%Count 236 257 4 497% within Q52 Has your company applied for commercial (business) bank loan or line of credit between July 1, 2010 and June 30, 2014?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 36 44 0 80% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

45.0% 55.0% 0.0% 100.0%


15.3% 17.1% 0.0% 16.1%

% of Total 7.2% 8.9% 0.0% 16.1%Count 11 3 0 14% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

78.6% 21.4% 0.0% 100.0%


4.7% 1.2% 0.0% 2.8%

% of Total 2.2% .6% 0.0% 2.8%Count 0 1 0 1% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%

% of Total 0.0% .2% 0.0% .2%Count 189 209 4 402% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

47.0% 52.0% 1.0% 100.0%


80.1% 81.3% 100.0% 80.9%

% of Total 38.0% 42.1% .8% 80.9%Count 236 257 4 497% within Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Total

No

Don't Know

Total

Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit?

Approved

Denied

Don't Know

No Response

Q53 Was your company approved or denied for a commercial (business) bank loan or line of credit? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 10 6 0 16% within Q54 What was the highest amount of commercial bank loan your company received?

62.5% 37.5% 0.0% 100.0%


4.2% 2.3% 0.0% 3.2%

% of Total 2.0% 1.2% 0.0% 3.2%Count 13 5 0 18% within Q54 What was the highest amount of commercial bank loan your company received?

72.2% 27.8% 0.0% 100.0%


5.5% 1.9% 0.0% 3.6%

% of Total 2.6% 1.0% 0.0% 3.6%Count 4 5 0 9% within Q54 What was the highest amount of commercial bank loan your company received?

44.4% 55.6% 0.0% 100.0%


1.7% 1.9% 0.0% 1.8%

% of Total .8% 1.0% 0.0% 1.8%Count 2 8 0 10% within Q54 What was the highest amount of commercial bank loan your company received?

20.0% 80.0% 0.0% 100.0%


.8% 3.1% 0.0% 2.0%


30.0% 70.0% 0.0% 100.0%


1.3% 2.7% 0.0% 2.0%


16.7% 83.3% 0.0% 100.0%


.4% 1.9% 0.0% 1.2%


0.0% 100.0% 0.0% 100.0%


0.0% .4% 0.0% .2%

% of Total 0.0% .2% 0.0% .2%Count 1 0 0 1% within Q54 What was the highest amount of commercial bank loan your company received?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 2 7 0 9% within Q54 What was the highest amount of commercial bank loan your company received?

22.2% 77.8% 0.0% 100.0%


.8% 2.7% 0.0% 1.8%


48.0% 51.1% 1.0% 100.0%


84.7% 82.9% 100.0% 83.9%

% of Total 40.2% 42.9% .8% 83.9%Count 236 257 4 497% within Q54 What was the highest amount of commercial bank loan your company received?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q54 What was the highest amount of commercial bank loan your company received? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ54 What was the highest amount of commercial bank loan your company received?

Up to $50,000?

$50,001 to $100,000?

$100,001 to $300,000?

$300,001 to $500,000?

$500,001 to $1 million?

$1,000,001 to $3 million?

$5,000,001 to $10 million?

Over $10 million?

No Response/Don't Know

Not Applicable

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 1 0 0 1% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 5 1 0 6% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

83.3% 16.7% 0.0% 100.0%


2.1% .4% 0.0% 1.2%

% of Total 1.0% .2% 0.0% 1.2%Count 2 0 0 2% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

100.0% 0.0% 0.0% 100.0%


.8% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% .4%Count 3 2 0 5% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

60.0% 40.0% 0.0% 100.0%


1.3% .8% 0.0% 1.0%

% of Total .6% .4% 0.0% 1.0%Count 225 254 4 483% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

46.6% 52.6% .8% 100.0%


95.3% 98.8% 100.0% 97.2%

% of Total 45.3% 51.1% .8% 97.2%Count 236 257 4 497% within Q55 Which of the following do you believe was the primary reason for your being denied a loan?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 38 6 0 44% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

86.4% 13.6% 0.0% 100.0%


16.1% 2.3% 0.0% 8.9%

% of Total 7.6% 1.2% 0.0% 8.9%Count 27 14 1 42% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

64.3% 33.3% 2.4% 100.0%


11.4% 5.4% 25.0% 8.5%

% of Total 5.4% 2.8% .2% 8.5%Count 51 57 0 108% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

47.2% 52.8% 0.0% 100.0%


21.6% 22.2% 0.0% 21.7%

% of Total 10.3% 11.5% 0.0% 21.7%Count 53 59 0 112% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

47.3% 52.7% 0.0% 100.0%


22.5% 23.0% 0.0% 22.5%

% of Total 10.7% 11.9% 0.0% 22.5%

Total

Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector? * M/WBE or Non-M/WBE Classification (not based on certification)

Q55 Which of the following do you believe was the primary reason for your being denied a loan?

Insufficient documentation

Insufficient business history

Race or ethnicity of owner

Other, please specify

No Response

Q55 Which of the following do you believe was the primary reason for your being denied a loan? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

Total


TotalQ57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

Strongly Agree

Somewhat Agree

Neither agree nor disagree

Somewhat disagree



Count 65 116 3 184% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

35.3% 63.0% 1.6% 100.0%


27.5% 45.1% 75.0% 37.0%

% of Total 13.1% 23.3% .6% 37.0%Count 2 5 0 7% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

28.6% 71.4% 0.0% 100.0%


.8% 1.9% 0.0% 1.4%

% of Total .4% 1.0% 0.0% 1.4%Count 236 257 4 497% within Q57 There is an informal network of primes and subs that has excluded my company from doing business in the private sector?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 13 15 0 28% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

46.4% 53.6% 0.0% 100.0%


5.5% 5.8% 0.0% 5.6%

% of Total 2.6% 3.0% 0.0% 5.6%Count 25 13 0 38% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

65.8% 34.2% 0.0% 100.0%


10.6% 5.1% 0.0% 7.6%

% of Total 5.0% 2.6% 0.0% 7.6%Count 30 35 1 66% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

45.5% 53.0% 1.5% 100.0%


12.7% 13.6% 25.0% 13.3%

% of Total 6.0% 7.0% .2% 13.3%Count 98 101 1 200% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

49.0% 50.5% .5% 100.0%


41.5% 39.3% 25.0% 40.2%


42.4% 56.3% 1.3% 100.0%


27.1% 33.1% 50.0% 30.4%


42.9% 57.1% 0.0% 100.0%


2.5% 3.1% 0.0% 2.8%

% of Total 1.2% 1.6% 0.0% 2.8%

Total

Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals? * M/WBE or Non-M/WBE Classification (not based on certification)

Strongly disagree

Don't Know


TotalQ58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

Very Often

Sometimes

Seldom

Never

Not Applicable

Don't Know



Count 236 257 4 497% within Q58 How often do primes who use your company as a sub on public sector projects with MWBE goals solicit your company on projects (private or public) without MWBE goals?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 25 2 0 27% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

92.6% 7.4% 0.0% 100.0%


10.6% .8% 0.0% 5.4%

% of Total 5.0% .4% 0.0% 5.4%Count 207 251 4 462% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

44.8% 54.3% .9% 100.0%


87.7% 97.7% 100.0% 93.0%

% of Total 41.6% 50.5% .8% 93.0%Count 2 2 0 4% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

50.0% 50.0% 0.0% 100.0%


.8% .8% 0.0% .8%

% of Total .4% .4% 0.0% .8%Count 2 2 0 4% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

50.0% 50.0% 0.0% 100.0%


.8% .8% 0.0% .8%

% of Total .4% .4% 0.0% .8%Count 236 257 4 497% within Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms


91.7% 8.3% 0.0% 100.0%


4.7% .4% 0.0% 2.4%

% of Total 2.2% .2% 0.0% 2.4%Count 8 0 0 8% within Q60 How did you become aware of the discrimination against your company?

100.0% 0.0% 0.0% 100.0%


3.4% 0.0% 0.0% 1.6%

% of Total 1.6% 0.0% 0.0% 1.6%Count 5 1 0 6% within Q60 How did you become aware of the discrimination against your company?

83.3% 16.7% 0.0% 100.0%


2.1% .4% 0.0% 1.2%

% of Total 1.0% .2% 0.0% 1.2%

Total

Q59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014? * M/WBE or Non-M/WBE Classification (not based on certification)


TotalQ59 Have you experienced discriminatory behavior when attempting to do work or working in the private sector between 2010 and 2014?

Yes

No

Do not work in the private sector

Don't Know

Total


certification)


Verbal comment

Action taken against company

Don't Know




100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%


44.9% 54.3% .9% 100.0%


89.4% 99.2% 100.0% 94.6%


47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 1 0 9% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

88.9% 11.1% 0.0% 100.0%


3.4% .4% 0.0% 1.8%

% of Total 1.6% .2% 0.0% 1.8%Count 1 0 0 1% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 9 0 0 9% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

100.0% 0.0% 0.0% 100.0%


3.8% 0.0% 0.0% 1.8%

% of Total 1.8% 0.0% 0.0% 1.8%Count 5 1 0 6% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

83.3% 16.7% 0.0% 100.0%


2.1% .4% 0.0% 1.2%

% of Total 1.0% .2% 0.0% 1.2%Count 2 0 0 2% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

100.0% 0.0% 0.0% 100.0%


.8% 0.0% 0.0% .4%

% of Total .4% 0.0% 0.0% .4%Count 211 255 4 470% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

44.9% 54.3% .9% 100.0%


89.4% 99.2% 100.0% 94.6%

% of Total 42.5% 51.3% .8% 94.6%Count 236 257 4 497% within Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Other Action

Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ?


Owner's gender


Don't Know

Some other reason

No Response

No Response

Total

Q62 Which of the following do you consider the primary reason for your company being discriminated against (private sector) ? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 7 2 0 9% within Q64 When did the discrimination first occur (private sector)? 77.8% 22.2% 0.0% 100.0%


3.0% .8% 0.0% 1.8%

% of Total 1.4% .4% 0.0% 1.8%Count 3 0 0 3% within Q64 When did the discrimination first occur (private sector)? 100.0% 0.0% 0.0% 100.0%


1.3% 0.0% 0.0% .6%

% of Total .6% 0.0% 0.0% .6%Count 3 0 0 3% within Q64 When did the discrimination first occur (private sector)? 100.0% 0.0% 0.0% 100.0%


1.3% 0.0% 0.0% .6%

% of Total .6% 0.0% 0.0% .6%Count 11 0 0 11% within Q64 When did the discrimination first occur (private sector)? 100.0% 0.0% 0.0% 100.0%


4.7% 0.0% 0.0% 2.2%

% of Total 2.2% 0.0% 0.0% 2.2%Count 1 0 0 1% within Q64 When did the discrimination first occur (private sector)? 100.0% 0.0% 0.0% 100.0%


.4% 0.0% 0.0% .2%

% of Total .2% 0.0% 0.0% .2%Count 211 255 4 470% within Q64 When did the discrimination first occur (private sector)? 44.9% 54.3% .9% 100.0%


89.4% 99.2% 100.0% 94.6%

% of Total 42.5% 51.3% .8% 94.6%Count 236 257 4 497% within Q64 When did the discrimination first occur (private sector)? 47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q64 When did the discrimination first occur (private sector)? * M/WBE or Non-M/WBE Classification (not based on certification) M/WBE or Non-M/WBE Classification (not based on

certification)

TotalQ64 When did the discrimination first occur (private sector)?




All of the above

Don't Know

No Response

Total



MWBE FirmsNon-M/WBE

Firms Other Firms

Count 8 1 0 9% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

88.9% 11.1% 0.0% 100.0%


3.4% .4% 0.0% 1.8%

% of Total 1.6% .2% 0.0% 1.8%Count 17 2 0 19% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

89.5% 10.5% 0.0% 100.0%


7.2% .8% 0.0% 3.8%

% of Total 3.4% .4% 0.0% 3.8%Count 211 254 4 469% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

45.0% 54.2% .9% 100.0%


89.4% 98.8% 100.0% 94.4%

% of Total 42.5% 51.1% .8% 94.4%Count 236 257 4 497% within Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

47.5% 51.7% .8% 100.0%


100.0% 100.0% 100.0% 100.0%

% of Total 47.5% 51.7% .8% 100.0%

Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes?

Yes

No

No Response

Total

Q65 Are you willing to speak directly to MGT to provide more detail of the alleged discrimination your company experienced by the District or their primes? * M/WBE or Non-M/WBE Classification (not based on certification)


Total

Appendix G: Survey of Vendors Regression Analysis



APPENDIX G | SURVEY OF VENDORS REGRESS ION ANALYS IS



G.1 INTRODUCTION Whereas Chapters 4.0 and 5.0 reported findings of disparity and nondisparity related to the utilization of vendors for Guilford County Schools District’s (District) procurement activities according to selected race, ethnicity, and gender categories, this section reports findings from a telephone survey (survey of vendors) of a sample of 4181 firms representative of the District’s vendors examined in the study to assess race, ethnicity, and gender effects on vendor revenue during the 2014 tax year. To determine these effects, MGT applied a multivariate regression model to survey findings.

There are two key questions for consideration in this analysis: 1. Do minority- and woman-owned firms tend to earn significantly less revenue than firms owned by nonminority males? 2. If “yes,” are their lower revenues due to race or gender status or to other factors?

Case law and social science research provide some guidance for addressing these questions. From research literature, we know that in addition to race and gender, factors such as firm capacity, owner experience, and education bear a relation to a firm’s gross revenues. When multiple factors come into play, sometimes a multivariate statistical analysis can improve our understanding of more complex relationships among factors affecting company earnings. In this study, we employ linear regression to analyze variables, including race and gender that can affect a firm’s success.

G.2 OVERVIEW OF MULTIVARIATE REGRESSION AND DESCRIPTION OF ANALYTICAL MODEL

Multivariate regression was employed to examine the influence of selected company and business characteristics, especially owner race and gender, on 2014 gross revenues reported by 497 firms participating in a survey of vendors administered via telephone during October 2015 through December 2015. For this analysis, gross revenue was the dependent variable, or the variable to be explained by the presence, absence, or strength of “selected characteristics” variables, known as “independent” or “explanatory” variables.

Since disparity analysis is an established domain of research, the selection of the independent company characteristics variables for this study was based on an extensive review of disparity study research literature.

1 In order to provide an accurate and complete regression analysis some responses had to be removed. For example if a person surveyed did not answer the revenue or race question, this response was removed. This number reflects those changes.

A P P E N D I X S E C T I O N S

1. Introduction

2. Overview of Multivariate Regression and Description of Analytical Model

3. Assessing Variables in the Model

4. Multivariate Regression Model Results

5. Summary of Survey Findings





Most economic studies of discrimination are based on the seminal work of Nobel Prize recipient Gary Becker, “The Economics of Discrimination.”2 Becker was the first to define discrimination in financial and economic terms. Since Becker, labor economists and statistical researchers including Blinder and Oaxaca, Corcoran and Duncan, Gwaltney and Long, Reimers, Saunders, Darity and Myers, Hanuschek, Hirsch, Topel and Blau, and others have adopted a standard in disparity study research of using company earnings, or revenue, as the dependent variable in race and gender discrimination analysis.3 Comparable worth studies have also proposed regression models using gross revenue as the dependent variable for policy analysis,4 and the U.S. Department of Commerce employs regression analysis (included in 48 CFR 19) to establish price evaluation adjustments for small disadvantaged businesses in federal procurement programs.5

Timothy Bates6 used at least five general determinants, including firm capacity, managerial ability, manager/owner experience, and demographic characteristics such as race and gender, to explain statistical variations in firm gross revenues. These are elaborated below in terms of the dependent/independent variable relationship regression seeks to resolve.

DEPENDENT VARIABLE For this analysis, the dependent variable (the variable to be explained by the independent variables in the model) was defined operationally as “firm 2014 gross revenues.” Ideally, this variable is measured as the exact dollar figure for gross revenues. However, years of experience in conducting information and opinion surveys with companies have shown us that firms tend to be reluctant to release precise dollar figures but more responsive when inquiries about earnings are presented as a dollar range. Accordingly, to encourage greater participation in this study’s survey of vendors, nine company gross revenue categories were defined, ranging from Category 1, “Up to $50,000” to Category 9, “More than $10 million.”

INDEPENDENT VARIABLES

The independent (i.e., explanatory) variables were those characteristics hypothesized as contributing to the variation in the dependent variable (2014 gross revenues). For this study, independent variables included:

Number of full-time employees – The more employees a company has, the greater product volume it is likely to have to generate higher revenues.

Private Contracting – It is argued the percent of total revenue from private sector sources is an indicator of a company’s capacity.

2 Becker, Gary. 1971, second edition. “The Economics of Discrimination.” The University of Chicago Press, Chicago, p. 167. 3 “Race and Gender Discrimination Across Urban Labor Markets,” 1996. Ed. Susan Schmitz. Garland Publishers, New York, New York, p. 184. 4 Gunderson, Morley. 1994. “Male-Female Wage Differentials and Policy Responses.” In “Equal Employment Opportunity: Labor Market Discrimination and Public Policy,” pp. 207-227. 5 “Federal Acquisition Regulations for Small Disadvantaged Businesses; Notice and Rules.” June 30, 1998. Memorandum for Office of Federal Procurement Policy, Economic and Statistics Administration, Department of Commerce. 6 Bates, Timothy. “The Declining Status of Minorities in the New York City Construction Industry.” Reprinted from Economic Development Quarterly, Vol. 12, No. 1, February 1998, pp. 88-100.





Owner’s years of experience – The longer a company owner has been in a particular business, the more likely it is that the owner has knowledge of how to acquire contracts and the skills and experience to succeed in that business.

Owner’s level of education – The research literature consistently reports a positive relationship between education and level of income.

Age of company – It is argued a company’s longevity is an indicator of both success and the owner’s managerial ability.

Race/ethnic group/gender of firm owners – The proposition to be tested was whether there was a statistically significant relationship between race, ethnicity, and gender classification of minority firm owners and firm revenue. In the analysis, the category “Non-M/WBE” served as a reference group against which all other race and gender groups were compared.

Finally, since companies tend to be organized around a business concentration (e.g., Construction or Professional Services), the business industry category was introduced as a moderator variable to determine if the model, given adequate sample size, behaved differently as a predictor of gross revenue when respondents’ line of business was considered.

Participants’ responses to the survey provided the data to examine the relative importance of these factors. The operational relationship between these constructs (i.e., firm capacity, capability, experience, race, and gender) and measures derived from survey items is presented in Table G-1.

TABLE G-1 MODEL CONSTRUCTIONS, VARIABLES, AND MEASURES

MODEL CONSTRUCTS VARIABLES MEASURES

CAPACITY Number of Employees Number of Full-time and Part-time Employees Reported Private Contracting % Total Revenue from Private Sources

OWNER'S MANAGERIAL ABILITY

Owner’s Education Level of Education (from “some high school” to “postgraduate degree”)

Owner’s Experience Years of Experience Company Age 2015 Minus Reported “Year of Establishment”

DEMOGRAPHICS Business Owner Groups

African American, Hispanic American, Asian American, Native American, Nonminority Woman, and Non-M/WBE Firms

Gender of Company Owner

Gender of Company Majority Owner or Shareholder

Source: Guilford County Schools District survey of vendors results.

EXPLORING VARIABLE RELATIONSHIPS: HOW REGRESSION ANALYSIS WORKS Multiple regression analysis permits simultaneous examination not only of the effects on the dependent variable of all independent variables in the multivariate model, but also the effect of each unique variable (i.e., controlling for the effects of the other independent variables in the equation). The effect of each predictor (independent) variable on the dependent variable is expressed as the magnitude of the change in the dependent variable (Y) for each unit change in the independent variable (X) plus an “error term.” Since the independent variable is never a perfect predictor of the dependent variable—that is, X is expressed as





an imperfect predictor of Y such that one unit change in X never leads to one unit change in Y—the “error term,” ε, is postulated to acknowledge the residual change in the value of Y that X cannot explain.

The goal in sound regression modeling, therefore, is to minimize residual values associated with the independent variables and to maximize their explanatory power. In other words, a good model that seeks to explain what causes revenue earnings, in this case, will hypothesize a combination of independent variables based on solid research findings having sufficient explanatory power to account for case-by-case differences in company revenue, while minimizing that portion of variation in revenue values that the independent variable cannot explain (i.e., minimizing the difference between Y values predicted by the X’s in the model and actual Y values).

G.3 ASSESSING VARIABLES IN THE MODEL As suggested earlier, in a model with multiple independent, or predictor, variables, the effect of each individual independent variable is expressed as the expected change in the dependent variable (y) for each unit change in the independent variable (x), holding constant (or controlling for) the values of all the other independent variables (i.e., the effect on Y of the other X’s in the equation). When X and Y values are plotted on a graph, linear regression attempts to find a straight line of best fit (also known as the least-squares line) that minimizes the differences between actual Y and predicted Y values as a function of X. The slope of this line represents the statistical relationship between the predicted values of Y based on X. The point at which this regression line crosses the Y axis (otherwise known as the constant) represents the predicted value of Y when X = 0. If the effect of X on Y is determined to be statistically significant (e.g., a significance level of p < 0.05 asserts that the calculated relationship between X and Y could occur due to chance only 5 times in 100), it can be asserted that X may indeed play a role in determining the value of Y (in the case of this study, company revenues). For example, if the slope coefficient of the variable representing one of the specific racial groups is determined to be statistically significant, then, all other things being equal, the hypothesis that race of the owner of a firm affects the annual revenue of the firm has only a 5 percent chance of being false. In disparity research, theory asserts that the negative effect of race on revenue earnings associated with being a minority-owned business is likely a product of discrimination.

MULTIVARIATE REGRESSION MODEL

Mathematically, the multivariate linear regression model is expressed as:

Y = β0 + β I XI + β2 X2 + β3 X3 + β4 X4 + β5 X5 + … + ε

Where: Y = annual firm gross revenues

β0 = the constant, representing the value of Y when XI = 0

βI = coefficient representing the magnitude of XI’s effect on Y

XI = the independent variables, such as capacity, experience, managerial ability, race, and gender

ε = the error term, representing the variance in Y unexplained by Xl





This equation describes the hypothesized relationship between the dependent variable and the independent variables and was used to test the hypothesis that there is no difference in 2014 revenue earnings for M/WBE firms when compared with non-M/WBE firms. Traditionally, the hypothesis of no difference (known as the null hypothesis) is represented as: H0 : Y1 = Y2.

We can reject the null hypothesis if the analysis indicates that race and gender have been found to affect firm revenue (i.e., H1 : Y1 ≠ Y2, the alternate hypothesis). Results are statistically significant if it is determined that the probability of achieving this difference due to chance was less than 5 in 100 (i.e., p < 0.05).

G.4 MULTIVARIATE REGRESSION MODEL RESULTS The regression model tested the effects of selected demographic and business characteristic variables on revenue earnings elicited from firms participating in the study. According to the following categories presented in Table G-2:7

TABLE G-2 SURVEY OF VENDORS DATA

GROSS REVENUE CATEGORIES

GROSS REVENUE CATEGORIES

1 Up to $50,000 4 $300,001 to $500,000 7 $3,000,001 to $5 million

2 $50,001 to $100,000 5 $500,001 to $1 million 8 $5,000,001 to $10 million

3 $100,001 to $300,000 6 $1,000,001 to $3 million 9 Greater than $10 million


Once the architecture and engineering business category was removed from the regression model, the tests for multicollinearity among independent variables and variance inflation due to outlier observations revealed no substantive problems with the data.8 These adjustments yielded values for the variables listed in Table G-3.


7 Despite the ordinal nature of the dependent variable, findings are reported based on a linear regression analysis; specifically, Ordinary Least Squares (OLS). Menard (1995) notes this as an acceptable and common practice, “particularly when the dependent variable has five or more [ordered] categories. Since this [OLS] is probably the easiest approach for readers to understand, sometimes other approaches are tried, just to confirm that the use of OLS does not…distort the findings.” In this case, the nine categories of revenue were also analyzed using ordered Logit (SPSS 11.5), with nearly identical findings to those achieved with OLS with respect to magnitude of effect of the independent variables and both sign and significance. For further discussion, see Menard, S., “Applied logistic regression analysis,” (Sage university papers series. Quantitative applications in the social sciences; no. 07-106), Thousand Oaks, California: Sage Publications, 1995. 8 Multicollinearity refers to excessive intercorrelation among the independent variables in a multiple regression model, which obscures the effect of each on the dependent variable to the extent that they behave as one variable and may measure two highly correlated components of the same theoretical factor. Outliers are observations in a data set that are substantially different from the bulk of the data, perhaps because of a data entry error or some other cause that would reasonably explain a data anomaly.





RESULTS OF REGRESSION ANALYSIS

CAPACITY Unstandardized Coefficients Standardized Coefficients

B Std. Error Beta (Constant) 3.463 0.795 African American Firms (n=92) -1.477 0.234 -0.242 Native American Firms (n=6) -0.266 0.707 -0.012 Asian American Firms (n=5) -1.200 0.578 -0.069 Hispanic American Firms (n=9) -0.985 0.755 -0.042 Nonminority Female Firms (n=100) -0.638 0.214 -0.107 Company Age 0.017 0.004 0.158 # of Employees 0.806 0.061 0.498 High School -0.484 0.532 -0.067 Some College -0.587 0.530 -0.081 College Degree 0.028 0.502 0.005 Owners Years of Experience 0.073 0.097 0.025 Construction 0.037 0.448 0.006 Professional Services -1.234 0.510 -0.126 Nonprofessional Services -0.894 0.430 -0.171 Goods -0.669 0.442 -0.121 Private Sector Contracting -0.001 0.003 -0.018


RESULTS The model testing the effects of the variables listed in Table G-3 on revenue reported by companies

participating in the survey of vendors explained 59.2 percent of the variance of the revenue variable (such as R2

j = 0.592, F = 36.336, p≤ 0.000).

When controlling for the effects of variables related to company demographics (i.e. company capacity, ownership level of education and experience), M/WBE status had a significant impact on 2014 company earnings for African Americans, Hispanic Americans, and nonminority females.

Among the company characteristics variables, other than M/WBE status, revenue for all groups increased as a function of number of employees and owner’s education.

The business industry categories professional services and nonprofessional services had a significant impact on company revenues.

DERIVING PREDICTED REVENUE: RACE, GENDER, ETHNICITY CLASSIFICATION Values from Table G-3 were inserted into the regression model in order to derive predicted revenue categories for each race, ethnicity, and gender classification. The following equation illustrates how predicted revenue would be calculated for an African American in the Construction industry business category.9

9 To derive coefficients for the race, ethnicity, and gender classifications, the “Non-M/WBE” category was used as the reference variable, coded as value “0.”





Gross Revenues = 3.463 –1.477 African American + 0.017 Company Age + 0.806 Number of Employees – 0.484 High School – 0.587 Some College + 0.028 College Degree + 0.073 Owner’s Experience – 0.001 percent of revenue from Private Sector Contracting.

For instance, using Table G-4 below to interpret the effect or race, ethnicity, and gender classification on predicted gross revenue for an African American in the Construction industry category, holding all other variables constant, we would add the value of the constant (3.463) to the coefficient value for an African American (-1.477) to obtain a predicted revenue value of 2.0223 (rounded to 2, representing the category “$50,001 to $100,000”). Similarly, to derive the effect or race, ethnicity, and gender classification on predicted gross revenue for an African American in the Goods industry category, holding all other variables constant, we would simply note the value of the constant and add it to the African American coefficient and the Goods coefficient (1.316, rounded to 1, representing the category “Up to $50,000”).


GROSS REVENUE CATEGORIES FROM SURVEY OF VENDORS

GROSS REVENUE CATEGORIES 1 Up to $50,000 4 $300,001 to $500,000 7 $3,000,001 to $5 million 2 $50,001 to $100,000 5 $500,001 to $1 million 8 $5,000,001 to $10 million 3 $100,001 to $300,000 6 $1,000,001 to $3 million 9 Greater than $10 million


G.5 SUMMARY OF SURVEY FINDINGS Regarding the positive significant effects of the non-race, ethnicity, and gender classification variables—company age and number of employees—it would be expected that a firm’s revenue might be positively related to its size and age, supporting the logical conclusion that larger, more established firms tend to do more business. However, even when these impacts were considered, majority of the M/WBE firms

OVERALL CONSTRUCTIONPROFESSIONAL

SERVICESNONPROFESSIONAL

SERVICESGOODS

Nonminority Male Firms (n=206) 2 3 2 3 3

African American Firms (n=92) 1 2 1 2 1

Native American Firms (n=6) 2 3 2 3 3

Asian American Firms (n=5) 2 2 1 2 2

Hispanic American Firms (n=9) 2 3 1 2 2

Nonminority Female Firms (n=100) 2 3 2 3 2

0

1

2

3

4





responding to the survey of vendors earned less revenue in 2014 than did their non-M/WBE counterparts, supporting the conclusion that M/WBE status is negatively related to earnings when compared with earnings for non-M/WBEs.

Appendix H: In-Depth Interview Guide



APPENDIX H | IN-DEPTH INTERVIEW GUIDE



READ: The purpose of this interview is to gather information on your experiences, perceptions, and points of view on doing business or attempting to do business with the Guilford County School District (District), its prime vendors, and in the private sector. Your responses and comments should focus on the time period between 2010 and 2014. At the conclusion of the interview you will be asked to sign an Affidavit attesting to the fact the information you have provided was given freely and represent an accurate reflection of your experiences doing business or attempting to do business with the District. Please note that all interviews are confidential—responses to the interviews will be aggregated and summarized and any remarks or comments made during the interview will not attributed to any individual respondent.

Q1. Please specify your company’s primary line of business? (Try to get a good feel for what they do.)

1. Construction (general contracting, construction management, carpentry, site work, electrical, etc.) Specify ______________________________________________________________________________________________

2. Architecture and Engineering (architecture, engineering, civil engineering, environmental engineering, mechanical engineering, etc.) Specify ________________________________________________

3. Professional Services (accounting, legal services, consulting, etc.) Specify ________________________ ______________________________________________________________________________________________________

4. Non-Professional Services (security, janitorial services, auto repair, maintenance services, landscaping, etc.) Specify ___________________________________________________________________________

5. Goods, Equipment, Supplies (commodities, computers, vehicles, furniture, etc.) Specify ______________________________________________________________________________________________________

6. Other: Specify ______________________________________________________________________________________

Q2. How many combined years of experience do you or the primary owner(s) of your firm have in your primary line of business?

0 – 5 years 1 6 – 10 years 2 11 – 15 years 3 16 – 20 years 4 20 + years 5

Q3. Between 2010 and 2014, what was the average number of employees on your company’s payroll, including full-time and part-time staff? 0 - 10 1 11 - 20 2 21 - 30 3 31 - 40 4 41+ 5





Q4. Is more than 50 percent of your company woman-owned and controlled?


Q5. Is more than 50 percent of the company owned and controlled by one of the following racial or ethnic groups? [Get as much detail as possible.]

Anglo/Caucasian/White 1 Black / African American 2 American Indian/Alaskan Native 3 Asian 4 Hispanic or Latino 5 Native Hawaiian/ Pacific Islander 6 Don’t Know 7 Specify: Other 8

Q6. In what year was your business established or purchased by the most recent owner (s)?

Q7. Does your company bid primarily as a prime contractor/consultant or vendor? Subcontractor? OR both?

Prime Contractor/Consultant or Vendor 1 Subcontractor or subconsultant 2 Both 3

Q8. Which of the following categories best approximates your company’s gross revenues for calendar year 2014?

Up to $50,000? 1 $50,001 to $100,000? 2 $100,001 to $300,000? 3 $300,001 to $500,000? 4 $500,001 to $1 million? 5 $1,000,001 to $3 million? 6 $3,000,001 to $5 million? 7 $5,000,001 to $10 million? 8 Over $10 million? 9 Don’t Know 10

Q9. What percentage of these gross revenues was earned from any of the District, the private sector, and other public government sector projects? (Must total 100%)

District _____% Private Sector _____% Other Public Sector _____%





Q10. Does your company hold any of the following certifications? (Check all that apply.)

Yes (1) No (2) Don’t Know (3) None (4)

1. Minority Business Enterprise (MBE)

2. Small Business Enterprise (SBE)

3. Woman Business Enterprise (WBE)

4. Disadvantaged Business Enterprise (DBE) Q11. How do you find out about opportunities to quote, bid, or propose on the District’s projects/contracts?

For example, do you use their website, attend Procurement Fairs, contacted by the District or primes, etc.

Q11a. Give specifics on the effectiveness of the methods you indicated.





IF INTERVIEWEE IS A PRIME:

Q12. How has your M/WBE certification assisted your firm in winning contracts?

Q12a. If so, how has certification assisted your firm?

Q13. Between 2010 and 2014, indicate a range of the number of times you have been awarded a contract or purchase order with the District as a prime contractor/consultant or vendor?

None 1 1-10 times 2 11-25 times 3 26-50 times 4 51-100 times 5 Over 100 times 6 Don’t Know 7

Q14. Have you ever protested a bid, proposal, or contract awarded by the District?


14a. If yes, please provide as much detail as possible on why and the results.

Q15. Has the M/WBE or Purchasing Staff provided assistance to understand the M/WBE requirements or identifying M/WBE firms on District projects?

Q15a. If so, and what assistance have you received?





Q16. In your experience, have any of the following been a barrier to attempting to do work or working on any of the District’s projects as a prime contractor/consultant or vendor:

Yes (1) No (2) Don’t

Know (3)

1. Prequalification requirements

2. Bid bond requirement

3. Performance/payment bond requirement

4. Cost of bidding/proposing

5. Financing

6. Insurance (general liability, professional liability, etc.)

7. Price of supplies/materials

8. Proposal/Bid specifications

9. Short or limited time given to prepare bid package or quote

10. Limited knowledge of purchasing contracting policies and procedures

11. Lack of experience

12. Lack of personnel

13. Contract too large

14. Selection process/evaluation criteria

15. Unnecessary restrictive contract specifications

16. Slow payment or nonpayment

17. Competing with large companies

18. Changes in the scope of work (after work began)

19. Meeting M/WBE goals or good faith effort requirements

Q16a. Please explain why the items you selected are barriers.

Q17. As a prime contractor/consultant or vendor did you experience discriminatory behavior by the District when attempting to do work or working on their projects between 2010 and 2014?

Yes 1 No 2 Don’t Know 3 Not Applicable 4

Q17a. If yes, explain how you felt you were discriminated and why? (Ask if they have documented evidence to support their response)





Q18. Has the District’s M/WBE program impacted your firm’s ability to win contracts? If so, explain how.


Q18a. If so, how have the program impacted your business?





IF INTERVIEWEE IS A SUBCONTRACTOR

Q19. Between 2010 and 2014, indicate a range of the number of times you have been awarded a subcontract or purchase order with primes on the District’s projects or contracts.

None 1 1-10 times 2 11-25 times 3 26-50 times 4 51-100 times 5 Over 100 times 6 Don’t Know 7

Q20. How often do prime contractors/consultants or vendors who use your firm as a subcontractor on public-sector projects with M/WBE goals solicit your firm on projects (private or public) without M/WBE goals?

Very Often 1 Sometimes 2 Seldom 3 Never 4 Don’t know 5

Q21. As a subcontractor did you experience discriminatory behavior between 2010 and 2014 from a prime contractor/consultant or vendor when attempting to do work or working on any of the District’s projects?

Yes 1 No 2 Don’t Know 3 Not Applicable 4





Q22. In your experience, have any of the following been a barrier to attempting to work or working on projects as a subcontractor with primes on any the District’s projects or contracts:

Yes (1) No (2) Don’t

Know (3)

1. Performance/payment bond requirement

2. Cost of bidding/proposing

3. Financing

4. Insurance (general liability, professional liability, etc.)

5. Price of supplies/materials

6. Short or limited time given to prepare bid estimate or quote

7. Lack of experience

8. Lack of personnel

9. Contract too large

10. Slow payment or nonpayment

11. Competing with large companies

12. Solicitation of subcontractor bids after contract award (i.e. bid shopping)

13. Awarded scope of work reduced or eliminated

Q22a. Please explain why you think the items you selected are barriers.

Q23. Do you feel there is an informal network of prime contractors or vendors that has excluded your company from doing business in the private sector?

Yes 1 No 2

23a. If yes, do you feel the informal network has had an effect upon you winning contracts?

Yes 1 No 2

Q24. Has the District’s M/WBE program impacted your firm’s ability to win contracts? If so, which agency and explain how.


Q24a. If so, how have the program impacted your business?





Q25. Between 2010 and 2014, have you ever submitted a bid with a prime contractor for a project with the District, were informed that you were the lowest bidder, and then found out that another subcontractor was actually doing the work.


Q25a. If yes, please provide details on what happened.

Q26. As a subcontractor did you experience discriminatory behavior between 2010 and 2014 from a prime contractor/consultant or vendor when attempting to do work or working on any of the District’s projects or contracts?


Q26a. If yes, explain how you felt you were discriminated and why?





ALL INTERVIEWEES

Q27. Have you experienced or observed a situation in which a prime contractor/consultant or vendor includes minority or woman subcontractors on a bid or proposal to satisfy the “good faith effort” requirements, and then drops the company as a subcontractor after winning the award for no legitimate reason?


Q28. Do you have any recommendations on how the District can improve the procurement and/or selection process?

Q28a. If so, what are your recommendations?

Q29. In your opinion, what are the biggest obstacles faced by M/WBE businesses in securing contracts with the District or the District’s prime contractors/vendors? Please specify the obstacles.

Q30. Should the District continue their M/WBE program, what recommendations would you want to see in their program?

Q31. Have you experienced access to capital as being an impediment to securing contracts with the District or subcontracts on the District’s projects or contracts?

Yes 1 No 2

Q31a. If yes, describe how?

Q32. Have you experienced bonding as being an impediment to securing contracts with the District or subcontracts on the District’s projects or contracts?

Yes 1 No 2

Q32a. If yes, describe how?

Q33. Is there anything that we have not covered that you feel will be helpful to this study?

Yes 1 No 2

Q33a. If yes, please explain.





AFFIDAVIT

__________________________________________ (interviewee) HEREBY ACKNOWLEDGE THAT THE INFORMATION I GAVE IS TRUE AND AN ACCURATE REFLECTION OF MY PAST EXPERIENCES IN PROCUREMENT AND BUSINESS OPPORTUNITIES WITH THE GUILFORD COUNTY SCHOOL DISTRICT. ADDITIONALLY, THIS INFORMATION WAS GIVEN FREELY AND I HAVE NOT BEEN COERCED OR RECEIVED ANY REMUNERATION FOR MY COMMENTS.

_____________________________________________

SIGNATURE

_________________________

DATE

_____________________________________________

SIGNATURE OF INTERVIEWER AS WITNESS

_________________________

DATE

Appendix I-1: Focus Group Survey – Primes



I -1 | FOCUS GROUP SURVEY – PRIMES



Q1. Please specify your company’s primary line of business? [REQUIRE ANSWER]

1. Construction (general contractor, construction manager, construction manager at risk, program management, etc.): _________________________________________________________________________________

2. Architecture and Engineering (architecture, engineering, structural, land surveying, building inspection, etc.): ____________________________________________________________________________________

3. Services (consulting, hazardous waste removal and remediation, janitorial services, security services, printing, accounting, legal services, etc.): __________________________________________________

4. Goods (books, computers, furniture, auto parts, etc.) _______________________________________________

5. Other: Specify ______________________________________________________________________________________

Q2. In your company’s primary line of business, how many years of experience does the primary owner(s) of your firm have? ____ [REQUIRE ANSWER]


Q3. On average, in the last three years how many employees has your company kept on the payroll, including full-time and part-time staff? [REQUIRE ANSWER]

0 - 10 1 11 - 20 2 21 - 30 3 31 - 40 4 41+ 5

Q4 What is the highest level of education completed by the primary owner of your company? [REQUIRE ANSWER]

Some high school 1 High school graduate 2 Trade or technical education 3 Some college 4 College degree 5 Post graduate degree 6 Don’t know 99





Q5. Does your company hold any of the following certifications? Check all that applies.

Minority Business Enterprise (MBE) 1 Woman Business Enterprise (WBE) 2 Small Business Enterprise (SBE) 3 Disadvantaged Business Enterprise (DBE) 4 HubZone 5 8A 6 Other 7 Specify

Q6. Is more than 50% of your company owned and controlled by a woman or women? [REQUIRE ANSWER]


Q7. Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

Anglo/Caucasian/White 1 Black or African American 2 Asian 3 Hispanic or Latino 4 American Indian/Alaskan Native 5 Native Hawaiian/Other 6 Pacific Islander Group 7 Other 8 Specify: No Response/Don’t Know 99







Q9. The following list of factors may prevent companies from bidding, proposing, quoting or obtaining work on a District project. In your experience, have any of the following been a barrier to obtaining work as a prime contractor/consultant or vendor on projects for the District:

[REQUIRE ANSWER TO EACH OF THE FOLLOWING]

Yes (1) No (2) N/A (3)

Prequalification requirements (1)

Bid bond requirement (2)

Performance/payment bond requirement (3)

Cost of bidding/proposing (4)

Financing (5)

Insurance (general liability, professional liability, etc.) (6)

Price of supplies/materials (7)

Proposal/Bid specifications (8)

Limited time given to prepare bid package or quote (9)

Limited knowledge of purchasing contracting policies and procedures (10)

Lack of experience (11)

Lack of personnel (12)

Contract too large (13)

Selection process (14)

Unnecessary restrictive contract specifications (15)

Slow payment or nonpayment (16)

Competing with large companies (17)





Q10. Between July 1, 2010 and June 30, 2014, has your company applied, been approved, or denied for any of the following items?


Applied Approved or Denied Denial Category Yes1 No2 Approved1 Denied2 N/A9 ID IBH C RE G O

a. Business start-up loan? ____ ____ ____ ____ ____ __ ____ __ __ __ __ b. Operating capital loan? ____ ____ ____ ____ ____ __ ____ __ __ __ __ c. Performance bond? ____ ____ ____ ____ ____ __ ____ __ __ __ __ d. Bid bond? ____ ____ ____ ____ ____ __ ____ __ __ __ __ e. Equipment loan? ____ ____ ____ ____ ____ __ ____ __ __ __ __

f. Commercial liability insurance?

____ ____ ____ ____ ____ __ ____ __ __ __ __

g. Professional liability insurance?

____ ____ ____ ____ ____ __ ____ __ __ __ __

Q11. Please indicate the extent to which you agree that between July 1, 2010 and June 30, 2014, your company experienced discrimination from the District due to the race, ethnicity, or gender of the company’s owner(s)?

Strongly Agree 1 Somewhat Agree 2 Neither Agree Nor Disagree 3 Somewhat Disagree 4 Strongly Disagree 5

Denial Category

(ID)- Insufficient Documentation

(IBH)- Insufficient Business History

(C)- Confusion about Process

(RE)- Race or Ethnic Origin

(G)- Gender of Owner

(O)- Other, please specify





Q12. Please indicate your level of agreement or disagreement, on a scale of 1 to 5 where 1 represents “Strongly Agree” and 5 represents “Strongly Disagree” with each of the following statements or “Don’t Know” represented as DK*.


Response Strongly

Agree 1

Agree 2

Neither 3

Disagree4

Strongly Disagre

e5 DK*

99

a There is an informal network of prime contractors/businesses and subcontractors in Guilford County.

____ ____ ____ ____ ____ ____

b Double standards in qualification and performance make it more difficult for minority-, and women-owned businesses to win bids or contracts.

____ ____ ____ ____ ____ ____

c

Sometimes, prime contractors/businesses will include minority, or women subcontractors on a bid to meet the “good faith effort” requirement, and then drop the company as a subcontractor after winning the award.

____ ____ ____ ____ ____ ____

d In general, minority-, and women-owned businesses tend to be viewed by the general public as less competent than non-minority male businesses.

____ ____ ____ ____ ____ ____

e

Some non-minority (male) prime contractors/businesses change their bidding procedures when they are not required to hire minority-and women-owned businesses as subcontractor.

____ ____ ____ ____ ____ ____

f The time and resources required to respond to an invitation to bid process is lengthy and costly.

____ ____ ____ ____ ____ ____

g

A non-minority (male) business will hire affiliate companies to circumvent outreach and contracting with legitimate minority-, and women -owned businesses as subcontractors.

____ ____ ____ ____ ____ ____

H My firm usually receives unequal price quotes from suppliers than my non-minority competitors.

____ ____ ____ ____ ____ ____





Q13. Which of the following categories best approximates your company’s largest prime contract awarded between July 1, 2010 and June 30, 2014?

Not applicable 1 Up to $50,000? 2 $50,001 to $100,000? 3 $100,001 to $200,000? 4 $200,001 to $300,000? 5 $300,001 to $400,000? 6 $400,001 to $500,000? 7 $500,001 to $1 million? 8 Over $1 million? 9 Don’t Know 99

Q14. Are you required to have bonding for the type of work your company bids?


Q14a. If yes, what is your current aggregate bonding limit?

Below $100,000 1 $100,001 to $250,000 2 $250,001 to $500,000 3 $500,001 to $1,000,000 4 $1,000,001 to $1,500,000 5 $1,500,001 to $3,000,000 6 $3,000,001 to $5,000,000 7 Over$ 5 million 8 Don’t know 99

Q14b. What is your current single project bonding limit?


Thank you for your valuable comments.

Appendix I-2: Focus Group Survey – Subcontractors



I -2 | FOCUS GROUP SURVEY – SUBCONTRACTORS



Q1. Please specify your company’s primary line of business? [REQUIRE ANSWER]

1. Construction (general contractor, carpentry, electrical, site work, HVAC, drywall, mechanical, hauling, painting, concrete, etc.): ____________________________________________________________________

2. Architecture and Engineering (architecture, engineering, structural, land surveying, building inspection, etc.): ____________________________________________________________________________________

3. Services (consulting, hazardous waste removal and remediation, janitorial services, security services, printing, accounting, legal services, etc.): __________________________________________________

4. Goods (books, computers, furniture, auto parts, etc.) _______________________________________________

5. Other: Specify ______________________________________________________________________________________

Q2. In your company’s primary line of business, how many years of experience does the primary owner(s) of your firm have? ____ [REQUIRE ANSWER]


Q3. On average, in the last three years how many employees has your company kept on the payroll, including full-time and part-time staff? [REQUIRE ANSWER]

0 - 10 1 11 - 20 2 21 - 30 3 31 - 40 4 41+ 5

Q4 What is the highest level of education completed by the primary owner of your company? [REQUIRE ANSWER]

Some high school 1 High school graduate 2 Trade or technical education 3 Some college 4 College degree 5 Post graduate degree 6 Don’t know 99





Q5. Does your company hold any of the following certifications? Check all that applies.

Minority Business Enterprise (MBE) 1 Woman Business Enterprise (WBE) 2 Small Business Enterprise (SBE) 3 Disadvantaged Business Enterprise (DBE) 4 HubZone 5 8A 6 Other 7 Specify

Q6. Is more than 50% of your company owned and controlled by a woman or women? [REQUIRE ANSWER]


Q7. Is more than 50% of the company owned and controlled by one of the following racial or ethnic groups?

Anglo/Caucasian/White 1 Black or African American 2 Asian 3 Hispanic or Latino 4 American Indian/Alaskan Native 5 Native Hawaiian/Other 6 Pacific Islander Group 7 Other 8 Specify: No Response/Don’t Know 99







Q9. The following list of factors may prevent companies from bidding, proposing, or obtaining work on a District project. In your experience, have any of the following been a barrier to obtaining work as a subcontractor/subconsultant to a prime contractor/consultant on projects for the District:


Yes (1) No (2) N/A (3)

Prequalification requirements (1)

Bid bond requirement (2)

Performance/payment bond requirement (3)

Cost of bidding/proposing (4)

Financing (5)

Insurance (general liability, professional liability, etc.) (6)

Price of supplies/materials (7)

Proposal/Bid specifications (8)

Limited time given to prepare bid package or quote (9)

Limited knowledge of purchasing contracting policies and procedures (10)

Lack of experience (11)

Lack of personnel (12)

Contract too large (13)

Selection process (14)

Unnecessary restrictive contract specifications (15)

Slow payment or nonpayment (16)

Competing with large companies (17)





Q10. Between July 1, 2010 and June 30, 2014, has your company applied, been approved, or denied for any of the following items?


Applied Approved or Denied Denial Category Yes1 No2 Approved1 Denied2 N/A9 ID IBH C RE G O

a. Business start-up loan? ____ ____ ____ ____ ____ __ ____ __ __ __ __ b. Operating capital loan? ____ ____ ____ ____ ____ __ ____ __ __ __ __ c. Performance bond? ____ ____ ____ ____ ____ __ ____ __ __ __ __ d. Bid bond? ____ ____ ____ ____ ____ __ ____ __ __ __ __ e. Equipment loan? ____ ____ ____ ____ ____ __ ____ __ __ __ __

f. Commercial liability insurance?

____ ____ ____ ____ ____ __ ____ __ __ __ __

g. Professional liability insurance?

____ ____ ____ ____ ____ __ ____ __ __ __ __

Q11. Please indicate the extent to which you agree that between July 1, 2010 and June 30, 2014, your company experienced discrimination due to the race, ethnicity, or gender of the company’s owner(s) from a prime contractors/consultants working on District projects?

Strongly Agree 1 Somewhat Agree 2 Neither Agree Nor Disagree 3 Somewhat Disagree 4 Strongly Disagree 5

Denial Category

(ID)- Insufficient Documentation

(IBH)- Insufficient Business History

(C)- Confusion about Process

(RE)- Race or Ethnic Origin

(G)- Gender of Owner

(O)- Other, please specify





Q12. Please indicate your level of agreement or disagreement, on a scale of 1 to 5 where 1 represents “Strongly Agree” and 5 represents “Strongly Disagree” with each of the following statements or “Don’t Know” represented as DK*.


Response Strongly

Agree 1

Agree 2

Neither 3

Disagree4

Strongly Disagre

e5 DK*

99

a There is an informal network of prime contractors/businesses and subcontractors in Guilford County.

____ ____ ____ ____ ____ ____

b Double standards in qualification and performance make it more difficult for minority-, and women-owned businesses to win bids or contracts.

____ ____ ____ ____ ____ ____

c

Sometimes, prime contractors/businesses will include minority, or women subcontractors on a bid to meet the “good faith effort” requirement, and then drop the company as a subcontractor after winning the award.

____ ____ ____ ____ ____ ____

d

In general, minority-, and women-owned businesses tend to be viewed by the general public as less competent than non-minority male businesses.

____ ____ ____ ____ ____ ____

e

Some non-minority (male) prime contractors/businesses change their bidding procedures when they are not required to hire minority-and women-owned businesses as subcontractor.

____ ____ ____ ____ ____ ____

f The time and resources required to respond to an invitation to bid process is lengthy and costly. ____ ____ ____ ____ ____ ____

g

A non-minority (male) business will hire affiliate companies to circumvent outreach and contracting with legitimate minority-, and women -owned businesses as subcontractors.

____ ____ ____ ____ ____ ____

H My firm usually receives unequal price quotes from suppliers than my non-minority competitors. ____ ____ ____ ____ ____ ____





Q13. Which of the following categories best approximates your company’s largest subcontract awarded between July 1, 2010 and June 30, 2014?

Not applicable 1 Up to $50,000? 2 $50,001 to $100,000? 3 $100,001 to $200,000? 4 $200,001 to $300,000? 5 $300,001 to $400,000? 6 $400,001 to $500,000? 7 $500,001 to $1 million? 8 Over $1 million? 9 Don’t Know 99

Q14. Are you required to have bonding for the type of work your company bids?


Q14a. If yes, what is your current aggregate bonding limit?


Q14b. What is your current single project bonding limit?


Thank you for your valuable comments.

Appendix J: Public Use Microdata Sample (PUMS) Regression Analysis



J | PUBL IC USE MICRODATA SAMPLE (PUMS ) REGRESS ION ANALYS IS



EXHIBIT J-A RESULTS OF LOGISTIC REGRESSION

EXPLANATION OF RESULTS AND VARIABLES LOGISTIC REGRESSION OUTPUT

Below, variable names and operational definitions are provided. When interpreting Exhibits J-1 to J-5, the third column— Exp (B) — is the most informative index with regard to the influence of the independent variables on the likelihood of being self-employed. From the inverse of this value, we can interpret a likelihood value of its effect on self-employment. For example the Exp (B) for an African American is .363 from Exhibit J-1, the inverse of this is 2.75. This means that a nonminority male is 2.75 times more likely to be self-employed than an African American. Columns A and B are reported as a matter of convention to give the reader another indicator of both the magnitude of the variable’s effect and the direction of the effect (“-“ suggests the greater the negative B value the more it depresses the likelihood of being self-employed, and vice versa for a positive B value. It is noteworthy that theoretically “race-neutral” variables (e.g., marital status) tend to impact the likelihood of self-employment positively and that the race/ethnicity/gender variables, in general, tend to have a negative effect on self-employment.

Variables

Race, ethnicity, and gender indicator variables: African American Asian American Hispanic American Native American Sex: Nonminority woman or not

Other indicator variables: Marital Status: Married or not Age Age2: age squared. Used to acknowledge the positive, curvilinear relationship between each year of age and self-employment. Disability: Individuals self-reported health-related disabilities. Tenure: Owns their own home Value: Household property value. Mortgage: Monthly total mortgage payments. Unearn: Unearned income, such as interests and dividends. Resdinc: Household income less individuals’ personal income. P65: Number of individuals over the age of 65 living in the household. P18: Number of children under the age of 18 living in the household. Some College: Some college education College Graduate: College degree More than College: Professional or graduate degree





EXHIBIT J-1 RESULTS OF LOGISTIC REGRESSION

OVERALL

B Sig. Exp (B)African American -1.014 0.000 0.363Hispanic American -0.531 0.031 0.588Asian American -0.347 0.307 0.707Native American -0.405 0.405 0.667Sex (1=Female) -0.843 0.000 0.430Marital Status (1=Married) 0.107 0.362 1.112Age 0.118 0.000 1.125Age2 -0.001 0.007 0.999Disability (1=Yes) 0.216 0.213 1.241Tenure (1=Yes) 0.582 0.000 1.790Value 0.000 0.028 1.000Mortgage 0.000 0.000 1.000Unearn 0.000 0.001 1.000Resdinc 0.000 0.495 1.000P65 -0.072 0.535 0.931P18 0.246 0.027 1.279Some College (1=Yes) 0.680 0.013 1.974College Graduate (1=Yes) -0.338 0.440 0.713More than College (1=Yes) 0.115 0.288 1.122

Number of Observations 4898Chi-squared statistic (df=19) 323.974Log Likelihood -3136.78

Greensboro-High Point, NC CMSA

Source: The Public Use Microdata Samples (PUMS) data from 2014 American Community Survey and Calculations using SPSS. Note: BOLD statistically significant at p < .05. Estimation was conducted using the Binary Logistic command on SPSS. The Binary Logistic command performs binary logistic regressions and reports estimated coefficients and odds ratios that measure the effect on the probability of each one-unit increase in the included variables.






CONSTRUCTION

B Sig. Exp (B)African American -0.872 0.094 0.418Hispanic American -0.754 0.041 0.471Asian American 0.442 0.584 1.555Native American 0.190 0.769 1.210Sex (1=Female) -0.501 0.132 0.606Marital Status (1=Married) -0.052 0.819 0.949Age 0.070 0.190 1.072Age2 0.000 0.619 1.000Disability (1=Yes) 0.205 0.565 1.228Tenure (1=Yes) 0.789 0.002 2.201Value 0.000 0.021 1.000Mortgage 0.000 0.457 1.000Unearn 0.000 0.684 1.000Resdinc 0.000 0.587 1.000P65 -0.267 0.268 0.766P18 0.292 0.196 1.339Some College (1=Yes) 0.218 0.605 1.244College Graduate (1=Yes) -0.987 0.130 0.373More than College (1=Yes) 0.048 0.818 1.049










B Sig. Exp (B)African American -1.232 0.025 0.292Hispanic American -1.155 0.273 0.315Asian American -0.744 0.358 0.475Native American -18.942 0.999 0.000Sex (1=Female) -0.577 0.023 0.561Marital Status (1=Married) -0.205 0.493 0.815Age 0.099 0.217 1.104Age2 0.000 0.597 1.000Disability (1=Yes) -0.129 0.793 0.879Tenure (1=Yes) 0.527 0.118 1.694Value 0.000 0.942 1.000Mortgage 0.000 0.001 1.000Unearn 0.000 0.003 1.000Resdinc 0.000 0.639 1.000P65 -0.020 0.940 0.980P18 0.814 0.004 2.258Some College (1=Yes) 1.714 0.017 5.551College Graduate (1=Yes) -18.003 0.999 0.000More than College (1=Yes) -0.644 0.081 0.525









OTHER SERVICES

B Sig. Exp (B)African American -0.186 0.490 0.830Hispanic American -0.242 0.535 0.785Asian American -0.284 0.615 0.753Native American -0.902 0.388 0.406Sex (1=Female) -0.348 0.059 0.706Marital Status (1=Married) 0.363 0.058 1.438Age 0.242 0.000 1.274Age2 -0.002 0.000 0.998Disability (1=Yes) 0.306 0.259 1.358Tenure (1=Yes) 0.206 0.379 1.228Value 0.000 0.008 1.000Mortgage 0.000 0.655 1.000Unearn 0.000 0.053 1.000Resdinc 0.000 0.511 1.000P65 0.088 0.646 1.092P18 0.121 0.499 1.129Some College (1=Yes) 0.471 0.430 1.602College Graduate (1=Yes) -0.164 0.797 0.848More than College (1=Yes) 0.108 0.542 1.114









GOODS AND SUPPLIES

B Sig. Exp (B)African American -2.112 0.040 0.121Hispanic American -18.324 0.997 0.000Asian American 0.794 0.318 2.211Native American -18.599 0.999 0.000Sex (1=Female) -0.273 0.401 0.761Marital Status (1=Married) 0.230 0.510 1.258Age -0.046 0.587 0.955Age2 0.001 0.301 1.001Disability (1=Yes) -0.127 0.820 0.880Tenure (1=Yes) 0.902 0.023 2.463Value 0.000 0.609 1.000Mortgage 0.001 0.029 1.001Unearn 0.000 0.254 1.000Resdinc 0.000 0.880 1.000P65 -0.382 0.271 0.683P18 0.391 0.260 1.479Some College (1=Yes) 0.481 0.540 1.618College Graduate (1=Yes) -17.745 0.999 0.000More than College (1=Yes) -0.190 0.571 0.827








EXHIBIT J-B RESULTS OF LINEAR REGRESSION

EXPLANATION OF RESULTS AND VARIABLES

Below, variable names and operational definitions are provided. When interpreting the linear regression Exhibits J-6 to J-10, the first column— Unstandardized B — is the most informative index with regard to the influence of the independent variables on the earnings of a self-employed individual. Each number in this column represents a percent change in earnings. For example the corresponding number for an African American is -.577, from Exhibit J-6, meaning that an African American will earn 57.7 percent less than a nonminority male. The other four columns are reported in order to give the reader another indicator of both the magnitude of the variable’s effect and the direction of the effect. Std. Error reports the standard deviation in the sampling distribution. Standardized B reports the standard deviation change in the dependent variable from on standard deviation increase in the independent variable. The t and Sig. columns simply report the level and strength of a variable’s significance.

Variables

Race, ethnicity and gender indicator variables: African American Asian American Hispanic American Native American Nonminority Woman

Other indicator variables: Marital Status: Married or not Disability: Individuals self-reported health-related disabilities. Age Age2: age squared. Used to acknowledge the positive, curvilinear relationship between each year of age and self-employment. Speaks English Well: Person’s ability to speak English if not a native speaker. Some College: Some college education College Graduate: College degree More than College: Professional or graduate degree





EXHIBIT J-6 RESULTS OF LINEAR REGRESSION

OVERALL

B Std. Error B t Sig.African American -0.577 0.165 -0.141 -3.506 0.000Hispanic American -0.631 0.239 -0.130 -2.637 0.009Asian American -0.426 0.277 -0.064 -1.540 0.124Native American -0.737 0.388 -0.075 -1.901 0.058

-0.240 0.091 -0.108 -2.629 0.0090.340 0.087 0.157 3.895 0.000

Disability (1=Yes) -0.391 0.135 -0.118 -2.904 0.004Age 0.035 0.022 0.427 1.618 0.106Age2 0.000 0.000 -0.329 -1.247 0.213

0.149 0.187 0.039 0.795 0.427Some College (1=Yes) -0.583 0.214 -0.115 -2.731 0.007

-0.344 0.331 -0.042 -1.039 0.299-0.387 0.083 -0.188 -4.647 0.000

Constant 9.600 0.533 17.999 0.000

Greensboro-High Point, NC CMSAStandardized

More than College (1=Yes)

Unstandardized

Nonminority Women (1=Female)Marital Status (1=Married)

Speaks English Well (1=Yes)

College Graduate (1=Yes)

Source: The Public Use Microdata Samples (PUMS) data from 2014 American Community Survey and Calculations using SPSS. Note: BOLD statistically significant at p < .05.






CONSTRUCTION


-0.388 0.180 -0.146 -2.160 0.0320.586 0.121 0.345 4.840 0.000

Disability (1=Yes) 0.267 0.192 0.100 1.389 0.167Age -0.001 0.026 -0.013 -0.032 0.975Age2 0.000 0.000 0.059 0.146 0.884

0.201 0.263 0.069 0.764 0.446Some College (1=Yes) -0.467 0.254 -0.137 -1.838 0.068

-0.388 0.364 -0.073 -1.064 0.289-0.094 0.108 -0.060 -0.868 0.386

Constant 10.048 0.647 15.531 0.000

More than College (1=Yes)College Graduate (1=Yes)

Greensboro-High Point, NC CMSAStandardizedUnstandardized










B Std. Error B t Sig.African American -0.399 0.555 -0.079 -0.718 0.475Hispanic American 0.113 1.299 0.011 0.087 0.931Asian American -0.593 0.726 -0.084 -0.817 0.416

-0.471 0.233 -0.221 -2.024 0.0460.465 0.276 0.183 1.688 0.095

Disability (1=Yes) -0.722 0.445 -0.173 -1.622 0.109Age 0.080 0.084 0.848 0.950 0.345Age2 -0.001 0.001 -0.850 -0.942 0.349

0.073 0.763 0.013 0.096 0.924Some College (1=Yes) -0.984 0.609 -0.169 -1.616 0.110

-0.638 0.386 -0.183 -1.654 0.102

Constant 9.269 2.139 4.333 0.000



Greensboro-High Point, NC CMSAUnstandardized Standardized








OTHER SERVICES


-0.254 0.134 -0.130 -1.892 0.0600.120 0.138 0.058 0.867 0.387

Disability (1=Yes) -0.494 0.197 -0.167 -2.511 0.013Age 0.045 0.039 0.541 1.136 0.257Age2 0.000 0.000 -0.428 -0.906 0.366

0.065 0.265 0.019 0.245 0.807Some College (1=Yes) -0.291 0.450 -0.046 -0.646 0.519

0.207 0.481 0.028 0.431 0.667-0.354 0.132 -0.186 -2.682 0.008

Constant 9.461 0.963 9.826 0.000

More than College (1=Yes)College Graduate (1=Yes)










GOODS AND SUPPLIES

B Std. Error B t Sig.African American -0.844 1.174 -0.114 -0.719 0.476Asian American -0.882 1.276 -0.168 -0.691 0.493

-0.428 0.299 -0.199 -1.434 0.1580.034 0.299 0.015 0.113 0.910

Disability (1=Yes) -1.491 0.574 -0.393 -2.596 0.013Age 0.158 0.074 2.096 2.127 0.039Age2 -0.002 0.001 -2.047 -2.166 0.035

0.877 1.065 0.202 0.823 0.415Some College (1=Yes) -1.277 0.635 -0.243 -2.011 0.050

-0.069 0.289 -0.031 -0.240 0.811

Constant 7.164 1.798 3.983 0.000






Appendix K: Detailed Market Area Analysis


GU IL FOR D CO UN TY SCH OOL D IS TRIC T D ISP ARIT Y ST UDY

APPEN DI X K | DE TAILE D M ARKE T ARE A ANAL YS IS

GUILFORD COUNTY SCHOOLS FINAL REPORT | JULY 20, 2016

P A G E 1

TABLE K-1 GUILFORD COUNTY SCHOOLS

ARCHITECTURE AND ENGINEERING MARKET AREA ANALYSIS FISCAL YEARS 2010-2014

County, State # of

Contracts % of

Contracts # of Firms

% of Firms

Dollars

% of Dollars

Cum%1

GUILFORD, NC* 379 52.57% 35 48.61% $7,856,431 44.33% 44.33% MECKLENBURG, NC 51 7.07% 9 12.50% $5,350,970 30.19% 74.52% WAKE, NC 79 10.96% 12 16.67% $2,728,844 15.40% 89.92% FORSYTH, NC** 166 23.02% 6 8.33% $1,078,586 6.09% 96.00% DURHAM, NC 24 3.33% 2 2.78% $566,223 3.19% 99.20% UNION, NC 12 1.66% 1 1.39% $116,328 0.66% 99.85% 2 FREDERICK, MD 1 0.14% 1 1.39% $20,884 0.12% 99.97% TRAVIS, TX 2 0.28% 1 1.39% $3,769 0.02% 99.99% RICHMOND CITY, VA 2 0.28% 1 1.39% $880 0.00% 100.00% CRAWFORD, KS 2 0.28% 2 2.78% $551 0.00% 100.00% ORLEANS, LA 1 0.14% 1 1.39% $86 0.00% 100.00% FAIRFAX, VA 2 0.28% 1 1.39% $44 0.00% 100.00%

Total 721 100.00% 72 100.00% $17,723,597 100.00% Source: Guilford County Schools Master Encumbrance Database 1 Cumulative total of percent of dollars in market area. 2 Counties above the line are included in the relevant market area *MSA Counties **CSA Counties




P A G E 2


CONSTRUCTION MARKET AREA ANALYSIS FISCAL YEARS 2010-2014

County, State

# of Contracts

% of Contracts

# of Firms

% of Firms

Dollars

% of Dollars

Cum%1

GUILFORD, NC* 2,502 62.27% 206 48.47% $118,510,997 41.75% 41.75% FORSYTH, NC** 655 16.30% 30 7.06% $46,155,376 16.26% 58.01% WAKE, NC 133 3.31% 31 7.29% $35,028,849 12.34% 70.35% MECKLENBURG, NC 93 2.31% 28 6.59% $26,049,903 9.18% 79.53% DURHAM, NC 23 0.57% 5 1.18% $9,915,035 3.49% 83.02% ALAMANCE, NC** 37 0.92% 10 2.35% $8,630,507 3.04% 86.06% ROWAN, NC 19 0.47% 1 0.24% $4,076,944 1.44% 87.50% DAVIDSON, NC** 30 0.75% 6 1.41% $1,505,148 0.53% 88.03% RANDOLPH, NC* 156 3.88% 14 3.29% $1,717,835 0.61% 88.63% ROCKINGHAM, NC* 108 2.69% 13 3.06% $590,590 0.21% 88.84% FRANKLIN, NC 2 0.05% 1 0.24% $334,293 0.12% 88.96% DAVIE, NC 8 0.20% 1 0.24% $178,160 0.06% 89.02% ORANGE, NC 9 0.22% 3 0.71% $162,003 0.06% 89.08% CHATHAM, NC 7 0.17% 2 0.47% $74,511 0.03% 89.10% GRANVILLE, NC 8 0.20% 1 0.24% $71,712 0.03% 89.13% CASWELL, NC 18 0.45% 1 0.24% $48,208 0.02% 89.15% CABARRUS, NC 6 0.15% 3 0.71% $44,947 0.02% 89.16% PERSON, NC 9 0.22% 1 0.24% $28,660 0.01% 89.17% YADKIN, NC** 5 0.12% 3 0.71% $26,381 0.01% 89.18% STOKES, NC** 3 0.07% 1 0.24% $8,558 0.00% 89.18% UNION, NC 2 0.05% 1 0.24% $8,548 0.00% 89.19% SURRY, NC** 2 0.05% 1 0.24% $3,354 0.00% 89.19% 2

CATAWBA, NC 3 0.07% 2 0.47% $7,003,385 2.47% 91.65% IREDELL, NC 8 0.20% 5 1.18% $3,873,097 1.36% 93.02% BUNCOMBE, NC 2 0.05% 1 0.24% $404,300 0.14% 93.16% NEW HANOVER, NC 12 0.30% 1 0.24% $402,084 0.14% 93.30% ROBESON, NC 1 0.02% 1 0.24% $52,060 0.02% 93.32% GASTON, NC 3 0.07% 2 0.47% $38,983 0.01% 93.34% LENOIR, NC 3 0.07% 3 0.71% $24,269 0.01% 93.34%




P A G E 3

TABLE K-2 (CONT.) GUILFORD COUNTY SCHOOLS

MARKET AREA ANALYSIS CONSTRUCTION FY 2010 – 2014

County, State # of

Contracts % of


% of Firms

Dollars

% of Dollars

Cum%1

WILKES, NC 1 0.02% 1 0.24% $4,481 0.00% 93.35% JOHNSTON, NC 1 0.02% 1 0.24% $3,841 0.00% 93.35% WAYNE, NC 1 0.02% 1 0.24% $857 0.00% 93.35% LANCASTER, SC 2 0.05% 1 0.24% $13,857,917 4.88% 98.23% SUMMIT, OH 6 0.15% 1 0.24% $2,915,826 1.03% 99.26% BUCKS, PA 11 0.27% 1 0.24% $582,730 0.21% 99.46% WHITFIELD, GA 41 1.02% 1 0.24% $513,861 0.18% 99.64% PALM BEACH, FL 11 0.27% 1 0.24% $490,968 0.17% 99.82% SANTA CLARA, CA 5 0.12% 1 0.24% $126,455 0.04% 99.86% GREENVILLE, SC 2 0.05% 1 0.24% $100,857 0.04% 99.90% HILLSBOROUGH, FL 2 0.05% 1 0.24% $85,003 0.03% 99.93% ROCKINGHAM, NH 2 0.05% 1 0.24% $63,709 0.02% 99.95% ORANGE, FL 1 0.02% 1 0.24% $22,410 0.01% 99.96% GRAYSON, VA 1 0.02% 1 0.24% $14,275 0.01% 99.96% CHESTERFIELD, VA 1 0.02% 1 0.24% $13,772 0.00% 99.97% NEW CASTLE, DE 1 0.02% 1 0.24% $12,557 0.00% 99.97% LAKE, IL 5 0.12% 1 0.24% $9,295 0.00% 99.97% FAIRFAX, VA 21 0.52% 1 0.24% $8,675 0.00% 99.98% ROANOKE CITY, VA 1 0.02% 1 0.24% $7,365 0.00% 99.98% MIDDLESEX, MA 3 0.07% 2 0.47% $6,995 0.00% 99.98% MADISON, OH 6 0.15% 1 0.24% $6,348 0.00% 99.98% SHELBY, TN 1 0.02% 1 0.24% $6,300 0.00% 99.99% TOMPKINS, NY 1 0.02% 1 0.24% $5,000 0.00% 99.99% WHATCOM, WA 1 0.02% 1 0.24% $4,759 0.00% 99.99% MERCER, NJ 1 0.02% 1 0.24% $4,475 0.00% 99.99% JOHNSON, GA 1 0.02% 1 0.24% $4,121 0.00% 99.99% NEW YORK, NY 1 0.02% 1 0.24% $3,863 0.00% 99.99% ORLEANS, LA 2 0.05% 1 0.24% $3,848 0.00% 100.00% FRANKLIN, MA 1 0.02% 1 0.24% $1,530 0.00% 100.00% KINGS, NY 1 0.02% 1 0.24% $1,457 0.00% 100.00% ALBEMARLE, VA 1 0.02% 1 0.24% $1,363 0.00% 100.00% DALLAS, TX 1 0.02% 1 0.24% $1,109 0.00% 100.00% SUMNER, TN 1 0.02% 1 0.24% $1,105 0.00% 100.00% COOK, IL 1 0.02% 1 0.24% $1,075 0.00% 100.00% WORCESTER, MA 1 0.02% 1 0.24% $987 0.00% 100.00% MONMOUTH, NJ 1 0.02% 1 0.24% $955 0.00% 100.00% FRANKLIN, OH 1 0.02% 1 0.24% $835 0.00% 100.00% ALLEGHENY, PA 1 0.02% 1 0.24% $810 0.00% 100.00% HENNEPIN, MN 1 0.02% 1 0.24% $777 0.00% 100.00% CHEROKEE, GA 1 0.02% 1 0.24% $585 0.00% 100.00% DUBUQUE, IA 1 0.02% 1 0.24% $220 0.00% 100.00%




P A G E 4


MARKET AREA ANALYSIS CONSTRUCTION FY 2010 – 2014

County, State # of

Contracts % of


% of Firms

Dollars

% of Dollars

Cum%1

DOUGLAS, NE 1 0.02% 1 0.24% $132 0.00% 100.00% BEAVER, PA 1 0.02% 1 0.24% $124 0.00% 100.00% LOS ANGELES, CA 1 0.02% 1 0.24% $102 0.00% 100.00% COMAL, TX 1 0.02% 1 0.24% $100 0.00% 100.00% ALEXANDRIA CITY, VA 1 0.02% 1 0.24% $20 0.00% 100.00%

Total 4,018 100.00% 425 100.00% $283,862,546 100.00% Source: Guilford County Schools Master Encumbrance Database. 1 Cumulative total of percent of dollars in market area. 2 Counties above the line are included in the relevant market area. *MSA Counties **CSA Counties




P A G E 5

TABLE K-3

GUILFORD COUNTY SCHOOLS MARKET AREA ANALYSIS PROFESSIONAL SERVICES

FY 2010-2014

County, State # of

Contracts % of


% of Firms

Dollars

% of Dollars

Cum%1

GUILFORD, NC* 898 41.21% 343 39.79% $17,878,219 66.34% 66.34% WAKE, NC 170 7.80% 48 5.57% $827,492 3.07% 69.42% FORSYTH, NC** 127 5.83% 45 5.22% $643,293 2.39% 71.80% MECKLENBURG, NC 140 6.42% 34 3.94% $2,352,927 8.73% 80.53% DURHAM, NC 65 2.98% 16 1.86% $687,273 2.55% 83.08% ALAMANCE, NC** 23 1.06% 15 1.74% $34,654 0.13% 83.21% ROCKINGHAM, NC* 28 1.28% 14 1.62% $422,811 1.57% 84.78% ORANGE, NC 17 0.78% 13 1.51% $30,219 0.11% 84.89% RANDOLPH, NC* 26 1.19% 12 1.39% $190,386 0.71% 85.60% DAVIDSON, NC** 13 0.60% 8 0.93% $557,643 2.07% 87.67% SURRY, NC** 2 0.09% 2 0.23% $6,851 0.03% 87.70% DAVIE, NC** 13 0.60% 1 0.12% $247,690 0.92% 88.62% UNION, NC 1 0.05% 1 0.12% $5,168 0.02% 88.63% YADKIN, NC** 3 0.14% 1 0.12% $750 0.00% 88.64% ROWAN, NC 3 0.14% 1 0.12% $585 0.00% 88.64% WARREN, NC 1 0.05% 1 0.12% $560 0.00% 88.64% CABARRUS, NC 1 0.05% 1 0.12% $475 0.00% 88.64% LEE, NC 1 0.05% 1 0.12% $450 0.00% 88.64% VANCE, NC 1 0.05% 1 0.12% $400 0.00% 88.65% STOKES, NC 1 0.05% 1 0.12% $350 0.00% 88.65% MOORE, NC 1 0.05% 1 0.12% $150 0.00% 88.65% 2

NEW HANOVER, NC 14 0.64% 5 0.58% $61,055 0.23% 88.87% CUMBERLAND, NC 4 0.18% 4 0.46% $12,965 0.05% 88.92% CATAWBA, NC 7 0.32% 4 0.46% $8,530 0.03% 88.95% WATAUGA, NC 3 0.14% 3 0.35% $12,243 0.05% 89.00% IREDELL, NC 2 0.09% 2 0.23% $18,957 0.07% 89.07% LENOIR, NC 3 0.14% 2 0.23% $12,350 0.05% 89.12% JACKSON, NC 6 0.28% 2 0.23% $3,700 0.01% 89.13% HARNETT, NC 2 0.09% 2 0.23% $2,300 0.01% 89.14% GASTON, NC 2 0.09% 2 0.23% $1,713 0.01% 89.14% RUTHERFORD, NC 1 0.05% 1 0.12% $7,050 0.03% 89.17% CLEVELAND, NC 2 0.09% 1 0.12% $6,204 0.02% 89.19% BEAUFORT, NC 1 0.05% 1 0.12% $3,608 0.01% 89.21% DARE, NC 2 0.09% 1 0.12% $1,805 0.01% 89.21% PITT, NC 1 0.05% 1 0.12% $1,200 0.00% 89.22% SAMPSON, NC 1 0.05% 1 0.12% $772 0.00% 89.22% CALDWELL, NC 2 0.09% 1 0.12% $146 0.00% 89.22%




P A G E 6


MARKET AREA ANALYSIS PROFESSIONAL SERVICES

FY 2010-2014

County, State # of

Contracts % of


% of Firms

Dollars

% of Dollars

Cum%1

NEW YORK, NY 15 0.69% 14 1.62% $33,387 0.12% 89.35% FAIRFAX, VA 40 1.84% 8 0.93% $59,846 0.22% 89.57% FULTON, GA 8 0.37% 6 0.70% $82,323 0.31% 89.87% LANE, OR 15 0.69% 6 0.70% $5,072 0.02% 89.89% MONTGOMERY, MD 9 0.41% 5 0.58% $31,331 0.12% 90.01% BALTIMORE CITY, MD 28 1.28% 5 0.58% $13,711 0.05% 90.06% COOK, IL 6 0.28% 5 0.58% $5,503 0.02% 90.08% OAKLAND, MI 8 0.37% 4 0.46% $288,491 1.07% 91.15% HENNEPIN, MN 11 0.50% 4 0.46% $60,076 0.22% 91.37% ROCKINGHAM, NH 6 0.28% 4 0.46% $34,688 0.13% 91.50% DEKALB, GA 12 0.55% 4 0.46% $20,226 0.08% 91.58% SANTA CLARA, CA 4 0.18% 4 0.46% $11,363 0.04% 91.62% HARRIS, TX 5 0.23% 4 0.46% $10,095 0.04% 91.66% ALAMEDA, CA 5 0.23% 4 0.46% $8,825 0.03% 91.69% MIDDLESEX, MA 4 0.18% 4 0.46% $4,941 0.02% 91.71% ALEXANDRIA CITY, VA 7 0.32% 4 0.46% $1,710 0.01% 91.71% WESTCHESTER, NY 8 0.37% 3 0.35% $60,737 0.23% 91.94% SAN FRANCISCO, CA 7 0.32% 3 0.35% $53,547 0.20% 92.14% DOUGLAS, NE 10 0.46% 3 0.35% $32,988 0.12% 92.26% SAN DIEGO, CA 3 0.14% 3 0.35% $27,485 0.10% 92.36% HILLSBOROUGH, NH 11 0.50% 3 0.35% $27,120 0.10% 92.46% DALLAS, TX 6 0.28% 3 0.35% $23,653 0.09% 92.55% MARICOPA, AZ 3 0.14% 3 0.35% $19,760 0.07% 92.62% ORANGE, CA 7 0.32% 3 0.35% $17,834 0.07% 92.69% FRANKLIN, OH 5 0.23% 3 0.35% $12,426 0.05% 92.74% LOS ANGELES, CA 3 0.14% 3 0.35% $10,629 0.04% 92.78% DISTRICT OF COLUMBIA, DC 3 0.14% 3 0.35% $6,771 0.03% 92.80% BEXAR, TX 4 0.18% 3 0.35% $6,099 0.02% 92.82% YORK, SC 7 0.32% 3 0.35% $4,218 0.02% 92.84% NASSAU, NY 3 0.14% 3 0.35% $1,606 0.01% 92.85% JOHNSON, KS 6 0.28% 3 0.35% $837 0.00% 92.85% SUFFOLK, MA 3 0.14% 2 0.23% $291,123 1.08% 93.93% STAUNTON CITY, VA 12 0.55% 2 0.23% $215,169 0.80% 94.73% ARAPAHOE, CO 8 0.37% 2 0.23% $158,293 0.59% 95.31% DENTON, TX 4 0.18% 2 0.23% $140,291 0.52% 95.84% CUMBERLAND, ME 3 0.14% 2 0.23% $89,902 0.33% 96.17% NEW CASTLE, DE 6 0.28% 2 0.23% $52,745 0.20% 96.36% CANADA 4 0.18% 2 0.23% $51,444 0.19% 96.56% PALM BEACH, FL 8 0.37% 2 0.23% $45,796 0.17% 96.73% PINELLAS, FL 5 0.23% 2 0.23% $42,425 0.16% 96.88% TRAVIS, TX 3 0.14% 2 0.23% $39,098 0.15% 97.03% WOOD, WI 11 0.50% 2 0.23% $25,804 0.10% 97.12%




P A G E 7


MARKET AREA ANALYSIS PROFESSIONAL SERVICES

FY 2010-2014

County, State

# of Contracts

% of Contracts

# of Firms

% of Firms

Dollars

% of Dollars

Cum%1

WORCESTER, MA 2 0.09% 2 0.23% $24,857 0.09% 97.22% SAINT LOUIS, MO 35 1.61% 2 0.23% $11,636 0.04% 97.26% BROWARD, FL 4 0.18% 2 0.23% $9,222 0.03% 97.29% FRESNO, CA 2 0.09% 2 0.23% $7,990 0.03% 97.32% MONROE, IN 2 0.09% 2 0.23% $7,745 0.03% 97.35% JOHNSON, IA 5 0.23% 2 0.23% $6,520 0.02% 97.38% ORANGE, FL 2 0.09% 2 0.23% $5,256 0.02% 97.40% ALLEGHENY, PA 2 0.09% 2 0.23% $4,137 0.02% 97.41% OTHER 201 9.22% 101 11.72% $697,688 2.59% 100.00%

Total 2,179 100.00% 862 100.00% $26,947,380 100.00% Source: Guilford County Schools Master Encumbrance Database 1 Cumulative total of percent of dollars in market area. 2 Counties above the line are included in the relevant market area. *MSA Counties **CSA Counties




P A G E 8


MARKET AREA ANALYSIS OTHER SERVICES

FY 2010-2014

County, State # of

Contracts % of


% of Firms

Dollars

% of Dollars

Cum%1

GUILFORD, NC* 1,922 43.75% 512 43.50% $26,236,536 53.89% 53.89% MECKLENBURG, NC 136 3.10% 56 4.76% $5,424,719 11.14% 65.03% FORSYTH, NC** 389 8.85% 76 6.46% $2,135,304 4.39% 69.41% RICHMOND, NC 10 0.23% 1 0.08% $1,700,114 3.49% 72.91% DURHAM, NC 37 0.84% 17 1.44% $1,552,223 3.19% 76.09% WAKE, NC 202 4.60% 47 3.99% $1,213,572 2.49% 78.59% DAVIDSON, NC** 24 0.55% 9 0.76% $1,169,518 2.40% 80.99% RANDOLPH, NC* 109 2.48% 33 2.80% $644,198 1.32% 82.31% ALAMANCE, NC** 100 2.28% 25 2.12% $309,094 0.63% 82.95% MONTGOMERY, NC 2 0.05% 1 0.08% $171,947 0.35% 83.30% CABARRUS, NC 19 0.43% 6 0.51% $119,605 0.25% 83.55% ORANGE, NC 9 0.20% 8 0.68% $90,263 0.19% 83.73% ROCKINGHAM, NC* 20 0.46% 12 1.02% $89,322 0.18% 83.91% YADKIN, NC** 5 0.11% 1 0.08% $22,421 0.05% 83.96% UNION, NC 6 0.14% 3 0.25% $21,532 0.04% 84.00% DAVIE, NC** 3 0.07% 3 0.25% $30,842 0.06% 84.07% VANCE, NC 1 0.02% 1 0.08% $19,900 0.04% 84.11% SURRY, NC** 4 0.09% 2 0.17% $8,221 0.02% 84.13% STANLY, NC 1 0.02% 1 0.08% $1,050 0.00% 84.13% ROWAN, NC 2 0.05% 2 0.17% $759 0.00% 84.13% STOKES, NC 1 0.02% 1 0.08% $420 0.00% 84.13% WARREN, NC 1 0.02% 1 0.08% $160 0.00% 84.13% 2

NEW HANOVER, NC 22 0.50% 8 0.68% $376,837 0.77% 84.90% CATAWBA, NC 2 0.05% 1 0.08% $291,447 0.60% 85.50% WAYNE, NC 1 0.02% 1 0.08% $194,617 0.40% 85.90% LENOIR, NC 6 0.14% 2 0.17% $69,589 0.14% 86.05% NASH, NC 1 0.02% 1 0.08% $50,764 0.10% 86.15% IREDELL, NC 22 0.50% 7 0.59% $47,913 0.10% 86.25% WILSON, NC 3 0.07% 1 0.08% $47,083 0.10% 86.35% EDGECOMBE, NC 3 0.07% 1 0.08% $34,063 0.07% 86.42% HENDERSON, NC 1 0.02% 1 0.08% $29,875 0.06% 86.48% CUMBERLAND, NC 17 0.39% 4 0.34% $13,867 0.03% 86.50% GASTON, NC 3 0.07% 3 0.25% $8,010 0.02% 86.52% HERTFORD, NC 1 0.02% 1 0.08% $8,000 0.02% 86.54% JONES, NC 8 0.18% 1 0.08% $6,804 0.01% 86.55% LINCOLN, NC 5 0.11% 3 0.25% $3,560 0.01% 86.56% CARTERET, NC 2 0.05% 1 0.08% $3,500 0.01% 86.57% CLEVELAND, NC 1 0.02% 1 0.08% $3,410 0.01% 86.57% COLUMBUS, NC 1 0.02% 1 0.08% $2,912 0.01% 86.58% BRUNSWICK, NC 4 0.09% 3 0.25% $2,836 0.01% 86.59%




P A G E 9


MARKET AREA ANALYSIS OTHER SERVICES FY 2010-2014

County, State

# of Contracts

% of Contracts

# of Firms

% of Firms

Dollars

% of Dollars

Cum% 1

BUNCOMBE, NC 2 0.05% 2 0.17% $1,860 0.00% 86.59% DARE, NC 1 0.02% 1 0.08% $629 0.00% 86.59% ROBESON, NC 1 0.02% 1 0.08% $200 0.00% 86.59% BUCKS, PA 11 0.25% 3 0.25% $630,623 1.30% 87.89% WORCESTER, MA 12 0.27% 2 0.17% $619,984 1.27% 89.16% BALTIMORE, MD 4 0.09% 4 0.34% $366,727 0.75% 89.91% KANE, IL 6 0.14% 4 0.34% $326,668 0.67% 90.58% STAUNTON CITY, VA 13 0.30% 2 0.17% $300,130 0.62% 91.20% FULTON, GA 353 8.04% 9 0.76% $299,351 0.61% 91.81% MONTGOMERY, MD 6 0.14% 5 0.42% $289,734 0.60% 92.41% CANADA 4 0.09% 1 0.08% $256,566 0.53% 92.94% ROCKLAND, NY 19 0.43% 2 0.17% $223,991 0.46% 93.40% MORGAN, IL 58 1.32% 1 0.08% $184,887 0.38% 93.78% FRANKLIN, OH 31 0.71% 5 0.42% $141,649 0.29% 94.07% MIDDLESEX, MA 49 1.12% 9 0.76% $138,622 0.28% 94.35% ALAMEDA, CA 1 0.02% 1 0.08% $137,600 0.28% 94.63% BALTIMORE CITY, MD 1 0.02% 1 0.08% $136,506 0.28% 94.92% ROCKINGHAM, NH 4 0.09% 1 0.08% $134,759 0.28% 95.19% CHARLESTON, SC 5 0.11% 1 0.08% $133,973 0.28% 95.47% COOK, IL 48 1.09% 10 0.85% $127,667 0.26% 95.73% PINELLAS, FL 2 0.05% 2 0.17% $122,549 0.25% 95.98% ORANGE, FL 12 0.27% 6 0.51% $110,792 0.23% 96.21% ARAPAHOE, CO 3 0.07% 3 0.25% $104,223 0.21% 96.42% WOOD, WI 32 0.73% 2 0.17% $101,104 0.21% 96.63% LOS ANGELES, CA 103 2.34% 2 0.17% $90,430 0.19% 96.82% TRAVIS, TX 2 0.05% 2 0.17% $83,429 0.17% 96.99% CHESTERFIELD, VA 8 0.18% 1 0.08% $83,167 0.17% 97.16% MARION, IN 3 0.07% 2 0.17% $65,706 0.13% 97.29% BEXAR, TX 3 0.07% 3 0.25% $63,393 0.13% 97.42% DALLAS, TX 7 0.16% 5 0.42% $59,697 0.12% 97.55% ALLEGHENY, PA 20 0.46% 3 0.25% $56,305 0.12% 97.66% PALM BEACH, FL 1 0.02% 1 0.08% $48,195 0.10% 97.76% JEFFERSON, AL 7 0.16% 4 0.34% $38,944 0.08% 97.84% WESTCHESTER, NY 1 0.02% 1 0.08% $35,000 0.07% 97.91% MACOMB, MI 1 0.02% 1 0.08% $33,076 0.07% 97.98% CHESTERFIELD, SC 4 0.09% 2 0.17% $32,918 0.07% 98.05% SAN FRANCISCO, CA 1 0.02% 1 0.08% $30,000 0.06% 98.11% SUFFOLK, MA 1 0.02% 1 0.08% $30,000 0.06% 98.17% FAIRFAX, VA 6 0.14% 3 0.25% $28,279 0.06% 98.23% PICKENS, SC 1 0.02% 1 0.08% $27,400 0.06% 98.29% DOUGLAS, NE 23 0.52% 5 0.42% $26,711 0.05% 98.34% BIBB, GA 1 0.02% 1 0.08% $26,414 0.05% 98.39%




P A G E 10


MARKET AREA ANALYSIS OTHER SERVICES

FY 2010-2014

County, State

# of Contracts

% of Contracts

# of Firms

% of Firms

Dollars

% of Dollars

Cum% 1

NICOLLET, MN 11 0.25% 1 0.08% $26,184 0.05% 98.45% MADISON, MS 1 0.02% 1 0.08% $25,327 0.05% 98.50% HARRISON, IA 9 0.20% 1 0.08% $25,096 0.05% 98.55% ROANOKE, VA 3 0.07% 1 0.08% $25,066 0.05% 98.60% CHESTER, PA 2 0.05% 2 0.17% $24,933 0.05% 98.65% OTHER 390 8.88% 195 16.57% $655,063 1.35% 100.00%

Total 4,393 100.00% 1,177 100.00% $48,688,333 100.00% Source: Guilford County Schools Master Encumbrance Database 1 Cumulative total of percent of dollars in market area. 2 Counties above the line are included in the relevant market area. *MSA Counties **CSA Counties




P A G E 11

TABLE K-5

GUILFORD COUNTY SCHOOLS GOODS AND SUPPLIES

MARKET AREA ANALYSIS FISCAL YEARS 2010-2014

County, State

# of Contracts

% of Contracts

# of Firms

% of Firms

% of Dollars

Dollars Cum% 1

MECKLENBURG, NC 66,072 52.89% 94 3.12% $58,935,760 28.68% 28.68% GUILFORD, NC* 31,678 25.36% 901 29.87% $42,306,255 20.59% 49.27% ROCKINGHAM, NC** 63 0.05% 14 0.46% $25,367,001 12.35% 61.62% WAKE, NC 3,258 2.61% 107 3.55% $16,789,514 8.17% 69.79% FORSYTH, NC** 2,475 1.98% 106 3.51% $12,967,468 6.31% 76.10% ALAMANCE, NC** 1,968 1.58% 44 1.46% $3,805,633 1.85% 77.95% DURHAM, NC 380 0.30% 34 1.13% $2,890,706 1.41% 79.36% RANDOLPH, NC* 442 0.35% 52 1.72% $1,542,884 0.75% 80.11% STANLY, NC 1,388 1.11% 2 0.07% $728,542 0.35% 80.47% UNION, NC 7 0.01% 4 0.13% $718,901 0.35% 80.82% CHATHAM, NC 89 0.07% 5 0.17% $363,561 0.18% 80.99% ORANGE, NC 32 0.03% 13 0.43% $359,352 0.17% 81.17% LEE, NC 3 0.00% 2 0.07% $253,238 0.12% 81.29% YADKIN, NC 14 0.01% 3 0.10% $146,359 0.07% 81.36% CABARRUS, NC 24 0.02% 9 0.30% $134,691 0.07% 81.43% DAVIE, NC** 3 0.00% 3 0.10% $116,522 0.06% 81.49% DAVIDSON, NC** 64 0.05% 19 0.63% $69,846 0.03% 81.52% ROWAN, NC 45 0.04% 10 0.33% $56,834 0.03% 81.55% SURRY, NC** 16 0.01% 4 0.13% $24,477 0.01% 81.56% MONTGOMERY, NC 6 0.00% 4 0.13% $22,611 0.01% 81.57% FRANKLIN, NC 22 0.02% 1 0.03% $6,822 0.00% 81.57% VANCE, NC 1 0.00% 1 0.03% $6,800 0.00% 81.58% MOORE, NC 7 0.01% 1 0.03% $6,500 0.00% 81.58% GRANVILLE, NC 2 0.00% 1 0.03% $5,990 0.00% 81.58% RICHMOND, NC 4 0.00% 1 0.03% $1,945 0.00% 81.58% WARREN, NC 7 0.01% 1 0.03% $1,370 0.00% 81.58% STOKES, NC** 1 0.00% 1 0.03% $393 0.00% 81.58% CUMBERLAND, NC 445 0.36% 8 0.27% $1,562,241 0.76% 82.35% WAYNE, NC 17 0.01% 6 0.20% $988,252 0.48% 82.83% NEW HANOVER, NC 59 0.05% 15 0.50% $543,614 0.26% 83.09% WILSON, NC 10 0.01% 2 0.07% $351,239 0.17% 83.26% IREDELL, NC 180 0.14% 10 0.33% $348,739 0.17% 83.43% BUNCOMBE, NC 168 0.13% 7 0.23% $310,844 0.15% 83.58% NASH, NC 1,363 1.09% 5 0.17% $297,902 0.14% 83.73% CATAWBA, NC 31 0.02% 7 0.23% $291,468 0.14% 83.87% CRAVEN, NC 371 0.30% 1 0.03% $264,648 0.13% 84.00% WILKES, NC 59 0.05% 3 0.10% $206,284 0.10% 84.10% LENOIR, NC 12 0.01% 3 0.10% $131,219 0.06% 84.16% CARTERET, NC 8 0.01% 2 0.07% $97,222 0.05% 84.21% GASTON, NC 34 0.03% 7 0.23% $85,845 0.04% 84.25%




P A G E 12


MARKET AREA ANALYSIS GOODS AND SUPPLIES

FY 2010-2014 # of

Contracts % of

Contracts # of

Firms % of

Firms % of

Dollars

County, State Dollars Cum% 2 JOHNSTON, NC 2 0.00% 2 0.07% $42,013 0.02% 84.27% ROBESON, NC 2 0.00% 1 0.03% $39,440 0.02% 84.29% BRUNSWICK, NC 39 0.03% 4 0.13% $36,652 0.02% 84.31% HENDERSON, NC 29 0.02% 2 0.07% $26,160 0.01% 84.32% TRANSYLVANIA, NC 3 0.00% 2 0.07% $20,002 0.01% 84.33% EDGECOMBE, NC 5 0.00% 1 0.03% $16,475 0.01% 84.34% BURKE, NC 9 0.01% 1 0.03% $13,738 0.01% 84.35% WATAUGA, NC 8 0.01% 3 0.10% $13,475 0.01% 84.35% ASHE, NC 2 0.00% 1 0.03% $13,200 0.01% 84.36% MCDOWELL, NC 1 0.00% 1 0.03% $10,000 0.00% 84.36% CALDWELL, NC 3 0.00% 2 0.07% $3,758 0.00% 84.37% CLEVELAND, NC 3 0.00% 2 0.07% $3,655 0.00% 84.37% HARNETT, NC 1 0.00% 1 0.03% $3,000 0.00% 84.37% JONES, NC 11 0.01% 2 0.07% $2,597 0.00% 84.37% CHOWAN, NC 1 0.00% 1 0.03% $2,500 0.00% 84.37% LINCOLN, NC 5 0.00% 3 0.10% $1,830 0.00% 84.37% COLUMBUS, NC 1 0.00% 1 0.03% $1,387 0.00% 84.37% ALEXANDER, NC 1 0.00% 1 0.03% $550 0.00% 84.37% LAKE, IL 1,153 0.92% 15 0.50% $4,067,243 1.98% 86.35% WORCESTER, MA 93 0.07% 5 0.17% $1,502,944 0.73% 87.08% ALAMEDA, CA 74 0.06% 17 0.56% $1,161,604 0.57% 87.65% LOS ANGELES, CA 651 0.52% 24 0.80% $1,018,566 0.50% 88.15% COOK, IL 290 0.23% 45 1.49% $952,527 0.46% 88.61% KANE, IL 253 0.20% 13 0.43% $860,372 0.42% 89.03% DALLAS, TX 123 0.10% 25 0.83% $849,781 0.41% 89.44% FRANKLIN, OH 346 0.28% 25 0.83% $763,706 0.37% 89.81% DOUGLAS, NE 152 0.12% 9 0.30% $697,135 0.34% 90.15% HAMILTON, OH 19 0.02% 8 0.27% $676,841 0.33% 90.48% FULTON, GA 593 0.47% 28 0.93% $661,382 0.32% 90.80% DUPAGE, IL 1,016 0.81% 12 0.40% $627,648 0.31% 91.11% DAUPHIN, PA 262 0.21% 1 0.03% $624,842 0.30% 91.41% DEKALB, GA 154 0.12% 11 0.36% $603,777 0.29% 91.71% OUTAGAMIE, WI 926 0.74% 6 0.20% $553,880 0.27% 91.98% BOONE, IN 113 0.09% 4 0.13% $537,340 0.26% 92.24% ROCKLAND, NY 36 0.03% 1 0.03% $443,908 0.22% 92.45% DENTON, TX 136 0.11% 7 0.23% $396,608 0.19% 92.65% MIDDLESEX, MA 279 0.22% 25 0.83% $396,286 0.19% 92.84% MCLEAN, IL 8 0.01% 1 0.03% $393,766 0.19% 93.03% ORANGE, CA 100 0.08% 18 0.60% $388,172 0.19% 93.22% PICKENS, SC 23 0.02% 3 0.10% $354,084 0.17% 93.39% BEXAR, TX 105 0.08% 12 0.40% $336,457 0.16% 93.56% CHESTERFIELD, VA 20 0.02% 3 0.10% $321,118 0.16% 93.71%




P A G E 13


MARKET AREA ANALYSIS GOODS AND SUPPLIES

FY 2010-2014 # of

Contracts % of

Contracts # of

Firms % of

Firms % of

Dollars

County, State Dollars Cum% 2 SUFFOLK, MA 23 0.02% 8 0.27% $316,501 0.15% 93.87% NEW YORK, NY 131 0.10% 29 0.96% $304,643 0.15% 94.02% TRAVIS, TX 57 0.05% 12 0.40% $303,474 0.15% 94.16% HENNEPIN, MN 120 0.10% 19 0.63% $289,130 0.14% 94.30% MONTGOMERY, MD 38 0.03% 10 0.33% $285,547 0.14% 94.44% OTHER 6,673 5.34% 1,076 35.68% $11,417,670 5.56% 100.00%

Total 124,921 100.00% 3,016 100.00% $205,466,876 100.00% Source: Guilford County Schools Master Encumbrance Database 1 Cumulative total of percent of dollars in market area. 2 Counties above the line are included in the relevant market area *MSA Counties **CSA Counties