decision matrix for functional evaluation of project management automation

UNIVERSITY OF CINCINNATI Date:___________________

I, _________________________________________________________, hereby submit this work as part of the requirements for the degree of:

in:

It is entitled:

This work and its defense approved by:

Chair: _______________________________ _______________________________ _______________________________ _______________________________ _______________________________

DECISION MATRIX FOR FUNCTIONAL EVALUATION OF

PROJECT MANAGEMENT AUTOMATION

Decision Matrix for Functional Evaluation of Project

Management Automation

A Thesis Submitted to the

Division of Research and Advanced Studies

Of the University of Cincinnati

In partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

In the Department of Civil and Environmental Engineering

Of the College of Engineering

2006

by

Sameer Mohanty

B.E. (Civil) Nagpur University, India, 2000

Thesis Committee Chairman

Dr O.M. Salem, PhD, PE, CPC

ABSTRACT

The construction industry is one of the largest and fastest growing industries in the

USA as well as in most parts of the world. The US department of commerce reported that

construction industry spending peaked all-time in the month of November 2005 with an

annual spending of over $1160 billion. It presently employs over 10 million people.

However, increasing demand for better services at lower costs resulting in greater market

share, profits and client satisfaction compel the construction industry to focus on

intangible parameters that affect its competitiveness.

As a tool to aid construction management (CM) and other project activities it

encompasses, scores of PM software applications have been written over the years.

However, with increasing availability of a broad range of such applications, organizations

are generally disoriented and uncertain with respect to which applications and tools are

best suited to their business goals. Furthermore, with project management systems

becoming more and more complex with time and encompassing sophisticated practices

for better management and control, selection of such tools has become increasingly

difficult.

Amidst all of this technology development, investments and implementation towards

CM efficiency, it is imperative that the project executives and senior management, who

are also the primary users of such applications, be facilitated a simple decision support

system that acts as a framework towards justifying investments, setup and installation,

utilization and upgrade of project management applications.

This study, through a broad preview of the past, current and futuristic CM application

functioning, its developmental history and an industry-wide survey aims to demarcate

i

current IT and software solutions trends in the US construction industry. Some of the

pertinent issues addressed include critical business areas, investments, deployment,

expenditures and work environment. Categories include computing, networking and

telecommunications hardware and software, purchase, technology transfer and

maintenance modalities, personnel, training and HR as well as preferences and

globalization issues.

Assimilated survey data has been analyzed to create a decision model that shall guide

project personnel and owners step-by-step in understanding and evaluating their priorities

and constraints, tasks and budgets, communications, networking and other stipulations in

order to formulate a strategy that allows them to center upon software applications that

functionally and financially best suit their enterprise and operations.

Conclusions and recommendations that are elicited from such data analysis and the

formulated decision matrix are based on statistical relevance of observed trends and

logical inferences thereof.

ii

iii

Acknowledgements

Faith, My Parents & God

iv

Special Thanks

I thank Dr Salem, Dr Wei & Dr Ioannides for their continued guidance and mentoring

in all of my research efforts.

I especially thank Mr. Tim J. Walsh, Senior Engineer, Turner Construction Company

for his eager enthusiasm and for the time, experience and patience that he lent to this

prolonged study. He stands out as one of the very few professionals who believe in the true

spirit of engineering and research. This work would not have been possible without him.

v

Table of Contents

CHAPTER 1 – INTRODUCTION

1.1 PROJECT MANAGEMENT............................................................................................01

1.2 PROJECT MANAGEMENT IN CONSTRUCTION............................................................02

1.3 BACKGROUND AND CONCURRENT RESEARCH..........................................................03

1.4 PROBLEM STATEMENT...............................................................................................09

1.5 OBJECTIVES................................................................................................................10

1.6 RESEARCH SCOPE......................................................................................................11

1.7 METHODOLOGY.........................................................................................................11

1.8 ORGANIZATION OF THESIS.......................................................................................13

CHAPTER 2 – LITERATURE REVIEW

2.1 CONSTRUCTION PROJECT MANAGEMENT AUTOMATION........................................15

2.1.1 Computerization of CM: Issues......................................................................17

2.1.2 CM Applications: Research Approach...........................................................20

2.2 THE SEVEN YEAR PLAN.............................................................................................21

2.2.1 Ideal Application Design…………….……......………...........................…..24

2.2.2 Advanced Computing Protocols: Database Management Systems...............26

2.2.3 Decision Support Systems…………….......…….………...............……........28

2.2.4 Modeling and Simulation Tools……………………………...........…......…30

2.2.5 Construction Process Optimization Modeling...............................................36

2.2.6 4D-CAD, BIMs and Schedule Simulators.....................................................37

2.3 CORPORATE FUNCTIONS AND PM APPLICATIONS: INFLUENCES...........................40

2.3.1 Nature and Size of Construction Firms.........................................................42

2.3.2 Hierarchical Structure and Interdepartmental Communication….….........44

2.3.3 Personnel and Training………………….……………….......………..........45

2.3.4 Control Areas and Utilization…………………………….………................47

2.3.5 Investments and Returns……………………………………………............49

2.3.6 Priorities and Future Agendas……………….………..........…….....……...51

vi

2.4 DISCUSSION................................................................................................................52

CHAPTER 3 – APPRAISAL OF CM APPLICATIONS

3.1 INTRODUCTION…… ……………………………………………………................54

3.1.1 Overview of Application Selection..................................................................55

3.1.2 Methodology and Definition of Criteria……......….…………………..........56

3.2 TURNERTALK………………………………………….....…………………...........57

3.3 CONSTRUCTWARE……………...………………………...………………...…….....62

3.4 PRIMAVERA ENTERPRISE……..………………………….…….......………...….....68

3.5 AASHTO’S TRANSPORT………...………………………………...………................72

3.6 CMIC ENTERPRISE AND PROJECT MANAGEMENT……...…………………......….78

3.7 DISCUSSION ………………………………...............................……………………82

CHAPTER 4 – IT DIAGNOSTIC AND DESCRIPTIVE STATISTICS

4.1 SURVEY INSTRUMENT DESIGN CONSIDERATIONS……….........…....….……….......87

4.1.1 Form and Dissemination………………………….……....………….……..87

4.1.2 Logical Sections and Phraseology………………………….........….…....…90

4.1.3 Compositions and Rating Scales………………….……………….....…..…92

4.1.4 Recruitment of Participants………………………………………..........…..94

4.1.5 Response Rates…………………………………………..........…....….…….96

4.2 DATA ADEQUACY…………………......…………...………………….....…...…..…97

4.2.1 Sample Size………………………….....……………………….….....….......97

4.2.2 Industry Representation…………………..……....…................….…..........98

4.2.3 Data Accuracy...............................................................................................105

4.3 DATA ANALYSIS....……………………………........................................................105

4.4 DESCRIPTIVE STATISTICS AND PM IT TRENDS.......................................................110

4.4.1 Cross-Functional and External Collaboration............................................111

4.4.2 Competitiveness and Peer Appraisal............................................................114

4.4.3 Project Management and IT work Environment.........................................118

4.4.4 Project Management Applications...............................................................122

vii

CHAPTER 5 – MATRIX DESIGN

5.1 DESIGN STRATEGY...................................................................................................127

5.1.1 Establishment of Substantive Priorities......................................................127

5.1.2 Analysis and Ranking of Influences and Attributes....................................129

5.1.3 Statistical Comparison of Parameter Means...............................................131

5.1.4 Formulation and Analysis of Top-Lists.......................................................140

5.2 STRATEGY FOR MODEL FORMULATION..................................................................150

5.2.1 Determination of Statistical Correlations....................................................151

5.2.2 Logical Inferencing and Table Notations....................................................153

5.2.3 Matrix Design................................................................................................162

5.3 USING THE MATRIX.................................................................................................165

5.4 VALIDATION OF THE MATRIX .................................................................................167

CHAPTER 6 – DISCUSSION OF RESULTS

6.1 DISCUSSION AND RECOMMENDATIONS...................................................................170

6.1.1 On General Trends.......................................................................................170

6.1.2 On Analyzed Results.....................................................................................172

6.1.3 On Case Study...............................................................................................174

6.2 FUTURE DIRECTIONS...............................................................................................176

REFERENCES

APPENDICES

viii

List of Figures

1. Construction Project Management Functions and Control Areas....................................05

2. Hypothetical Interactive Project Management Application Framework..........................25

3. Contingent Model for Network Based ORDBMS...........................................................27

4. Decision Support Inputs and Constraints.........................................................................29

5. Postulated Inter-operational M&S Framework................................................................35

6. Proposed Schematic for Integrated Optimizer.................................................................36

7. Autodesk Revit 7.0 Preview.............................................................................................38

8. Navisworks Preview.........................................................................................................39

9. Graphic Representation of Corporate Structure Effect on Selection Criteria..................41

10. Screen Shot of the TurnerTalk Dashboard.......................................................................58

11. TurnerTalk Application Toolsets.....................................................................................59

12. Screen Shot of the Constructware Dashboard..................................................................63

13. Constructware Application Toolsets................................................................................65

14. Screen Shot of Primavera Expedition Dashboard............................................................69

15. Primavera Expedition Application Features.....................................................................71

16. AASHTOs Trns•port Application Modules.....................................................................73

17. CMiC Project and Enterprise Application Tools.............................................................80

18. Questionnaire Design Methodology................................................................................88

19. Survey dissemination process and response selection statistics.......................................95

20. Percent Distribution of Responses by US Geographical Zones.......................................99

21. Industry Representation by Areas of Operation.............................................................101

22. Industry Representation by Number of Employees.......................................................102

ix

23. Industry Representation by Number of Functional Departments...................................103

24. Industry Representation by Spread of Operations..........................................................104

25. Industry Representation by Years of Experience...........................................................105

26. Industry Classification by PM Applications Approach..................................................106

27. Diagrammatic Comparison of Communication Efficiencies.........................................113

28. Comparative Mean Ratings of Project Performance based on Location........................114

29. Assessment of PM Applications in Peer and Affiliate Companies................................116

30. Impact of IT setup of Peers and Affiliates on Project Performance...............................117

31. Percentage of All Categories Having In-house IT Departments....................................119

32. Relative Plot of Deployment Durations for PM Applications.......................................120

33. IT Training Trends in Various Segments of the Construction Industry.........................121

34. Types of Software Applications Enhancements by Industry Category..........................123

35. Integration Protocols within PM Software applications by Categories.........................124

36. Preference Assessment for Commercial PM Applications............................................125

37. Corporate Concern Centric Decision Matrix Design Strategy.......................................128

38. Elimination Algorithm for Comparison of Parameter Means........................................135

39. Top Lists For Large Companies.....................................................................................146

40. Top Lists For Midsize Companies.................................................................................147

41. Top Lists For Contracting Companies...........................................................................148

42. Top Lists For Program Management Companies...........................................................149

43. Business Centric Matrix for Evaluation of PM Application Parameters.......................163

44. Application Centric Progression of Business Matrix for Prospect Identification..........164

45. Instructions for Using the Decision Matrix....................................................................166

x

List of Tables

1. Brief Review of Research Efforts in Construction Process Simulation......................32

2. Project Management Control Areas, Tools, Forms and Functions..............................48

3. AASHTO Trns•port BAMS Information Features......................................................75

4. Comparison of Aspects of PM applications affecting Selection Criteria....................85

5. Geographical Distribution of Participating Organizations..........................................99

6. Industry Representation by Top Companies..............................................................100

7. Mean Ranking of Modes of Collaboration................................................................111

8. Statistical Comparison of Means Pairwise Iterations For Corporate Concerns Towards

Allocation of Exclusive Ranks...................................................................................137

9. Categorization of Various Parameters within Corporate Concerns...........................141

10. Exclusive Rankings of Corporate Concerns for All Categories................................142

11. Exclusive Rankings of Application Features for All Categories...............................143

12. Exclusive Rankings of Application Characteristics for All Categories.....................144

13. Exclusive Rankings of Advanced Application Features for All Categories..............145

14. Exclusive Rankings of Barriers in Implementation for All Categories.....................145

15. P Values from Spearman’s Test for Correlation between Corporate Concerns and

Application Features..................................................................................................156

16. P Values from Spearman’s Test for Correlation between Corporate Concerns and

Application Characteristics........................................................................................157

17. P Values from Spearman’s Test for Correlation between Corporate concerns with

Advanced Toolsets and Deployment Barriers...........................................................158

xi

18. P Values from Spearman’s Test for Correlation between Application Features and

Application Characteristics........................................................................................159

19. P Values from Spearman’s Test for Correlation between Application Features with

Advanced Toolsets and Deployment Barriers...........................................................160

20. P Values from Spearman’s Test for Correlation between Application Characteristics

with Advanced Toolsets and Deployment Barriers...................................................161

xii

List of Symbols

H0: Null Hypothesis

HA: Alternative Hypothesis

PFn: Probability of occurrence on Factor ‘n’

χ2: Chi-Square

r: Coefficient of Correlation

rs: Spearman rank correlation coefficient

R: Coefficient of Determination

D: Difference between the ranks of corresponding values of the two variables

N: Sample Size

σ: Variance

μ: Mean

α: Probability of occurrence of Type I error in a statistical test

xiii

List of Abbreviations

AASHTO: American Association of State Highway and Transportation Officials

AEC: Architecture, Engineering and Construction

ANOVA: Analysis of Variance

ASP: Application Service Provider

BIM: Building Information Models

CAD: Computer Aided Design

CM: Construction Management

CPE: Construction Project Extranet

CPM: Critical Path Method

DBMS: Database Management Systems

EPCOMD: Engineer Procure Construct Operate Maintain Decommission

ERP: Enterprise-wide Resource Planning

FIATECH: Fully Integrated and Automated Technologies

GPS: Global Positioning Systems

GUI: Graphical User Interface

HTTP: Hypertext Transfer Protocol

HTTPS: Hypertext Transfer Protocol Secure Sockets

HVAC: Heating, Ventilation and Cooling

IPMS: Integrated Project Management System

IT: Information Technology

LLC: Limited Liability Corporation

M&S: Modeling and Simulation

xiv

MEMS: Micro Electro-Mechanical Systems

ODBC: Open Data Base Connectivity

ORDBMS: Object Relational Database Management Systems

P3: Primavera Project Planner

PCO: Potential Change Orders

PDA: Personal Digital Assistant

PERT: Program Evaluation and Review Technique

PMBOK: Project Management Body of Knowledge

PM: Project / Program Management

PRINCE: Project in Controlled Environments

RFI: Radio Frequency Identifications

RFI: Request for Information

RFQ: Request for Quotes

ROI: Return on Investments

SAS: Statistical Analysis System

SQL: Structured Query Language

SSL: Secure Sockets Layer

XML: Extensible Markup Language

xv

CHAPTER 1 INTRODUCTION

1.1 PROJECT MANAGEMENT

PM (Project management) is the application of knowledge, skills, tools and

techniques to project activities in order to meet or exceed stakeholder needs and

expectations from a project, as defined by the PMBOK® (Project Management Body of

Knowledge), the accredited standard accepted in the US. However, like most of the

aspects and agendas it encompasses, this canonical treatise has been scrutinized,

reviewed and modified several times. Other parts of the world, like the UK and other

European nations adhere to PRINCE2® (Projects in Controlled Environments), a similar

benchmark.

The earliest project managers, as believed by some, were said to be irrigators,

engineers, architects and artists, all-in-one. This was during the agricultural revolution

phase starting in parts of Iraq and Syria and spreading over to Asian and African

countries during prehistoric times. Constructions of most of the seven wonders are hailed

as historic projects. Nevertheless, these were not attributed as works of various specialists

but of a few generalists. Specialization in engineering and management is believed to be

but a few centuries old.

Genesis of project management in the US occurred with the transcontinental railroad

project in the mid-19th century. Modern project management however, seemingly started

with the works of Frederick Taylor and Henry Gantt in the early 20th century with the

application of sound scientific logic to allocate resources. An important milestone was

the development of the PERT technique by US Department of Defense’s Navy Special

1

Projects Office in 1958 as a part of the Polaris project in response to Russia’s Sputnik

program. Around the same time, DuPont Corporation created the CPM technique to

identify dependencies along terminal activities. The industrial revolution followed next

and pressed the manufacturing and infrastructure sectors to conform, more than ever

before, to sound management and administrative protocols based on scientific techniques.

The resulting progression led to almost all industries and business areas taking up some

or the other form of project management practices.

1.2 PROJECT MANAGEMENT IN CONSTRUCTION

Construction is probably the oldest form of project management as we see it today.

The Egyptian civilization in the Nile valley around 9000 years ago, the Sumerian

civilization along the Tigris as well as the Peruvians in the Americas about 7000 years

ago lived in citadels that were strategically located and well planned. Cases of

monumental construction, the architectures and engineering of which are unparalleled to

this day, are attributed to some of these earliest civilizations.

Modern project management, however, might be attributed more to the manufacturing

industry than to the construction industry. Two essential phases that lead to the demand

for scientific management techniques were mass production based upon the assembly line

concept and unionized labor. Owing to the works of Adam Smith of Smith & Wesson

pistol manufacturers, Frederick Taylor, also called the father of scientific management

and others like Henri Fayol, director of Comambault mines in France, administration and

management of production setups gained increasing importance in the late 18th and early

19th centuries.

2

The construction industry, though not a pioneer in these areas in the truest sense, has

always been one of the largest industrial sectors worldwide. With analogies being

developed to identify both parallels and differences between the manufacturing and

construction sectors, it has been very quick to adapt to increasing demands for quality,

productivity and variety. It is manifest in construction engineering and management

research that this industry has been able to keep up with the latest innovations, both

technological and managerial, to address it’s concerns.

Irrespective of the numerous parallels drawn between the construction and the

manufacturing sectors, it has been acknowledged that there are some characteristic

differences as well. Construction project management is one, probably the foremost, of

these.

1.3 BACKGROUND AND CONCURRENT RESEARCH

The construction industry is one of the largest and more important, the largest

growing industrial sectors in the USA, and other parts of the world. In January of 2005,

construction spending increased by 0.7 % to gross $1050 billions. It peaked in November

2005 with an annual spending of over $ 1160 billion, as reported by the US Department

of Commerce. With approximately 720,000 establishments, almost 80% of the

investments pertain to infrastructure systems like transportation, power and other

commercial sectors. It presently employs close to 10 million people (US Census Bureau,

2006).

As mentioned earlier however, there are certain aspects of the construction industry

that make it quite different from other manufacturing enterprises. Most of the products,

3

so to say, produced by the construction industry, are custom built and unique

(Chinowsky, 2000). In the sense that they are built as per pre-decided plans,

specifications, designs and costs over a decided and mutually agreed period of time, with

all stake-holders having a say in it. A critical aspect is also the fact that there are

numerous stake-holders in a construction project (Rojas, 1999), a lot more than other

manufacturing facilities, especially if it’s a public or infrastructure systems capital

project.

Another distinguishing feature of this industry is owing to the risks or changes that

are associated with any construction project. Even though most of these risks may be

forecasted and reduced, capital projects involve great amounts of finance and any change

in any aspect, be it design, schedule, legalities, logistics or weather, has an adverse

financial impact on the entire project. It has also been noted that risk analysis and

management in construction have traditionally depended mainly on intuition, judgments

and experience (Akintoye, 1997). Adding to all this is the fact that, in certain situations,

decisions need to be taken almost immediately (FIATECH, 2004).

Construction research, additionally, has seen a paradigm shift in the impetus for

higher competitiveness. Focus has increased on parameters like human factors and

productivity issues, planning and logistics as well as conceptual, scientific and computing

innovations, even take-offs from other industries. Nevertheless, the decentralized nature

of the construction industry (Macomber, 2003) and uniqueness in it’s operations make it

difficult to develop and follow any particular set of guidelines towards management of

projects.

4

As illustrated below, construction firms may include any or all project functions from

basic architecture and design, to entire EPCOMD operations. All of these include some

planning and control obligations such as supply and procurement, monitoring, change

management, updating schedules, managing and tracking materials and equipments, sub-

contracting, human resource management and ensuring quality controls and safety.

Pre- Design

Planning

Design

Engineering

Supply and

Procurement Construction

Execution

Start-Up

and Operations /

Handover

Preventive and

Routine Maintenance

Decommission / Demolition /

Salvage

Equipment Management

Human Resource

Materials Management

Quality Control

Financial Management

Sequencing and

Scheduling

Safety

Timeous Execution

Supply and Procurement

Change Management

Planning

and Control

Figure 1: Construction Project Management Functions and Control Areas

Construction projects therefore involve enormous amounts of information flow that is

generated at numerous ends (Deng, 2001). In order to track the variables and keep the

project execution under control efficiently, this information has to be captured,

transmitted or communicated, interpreted, organized, and utilized timely and accurately

(Rojas, 1999). Prevailing industry-wide communication practices reveal excessive

5

dependence on human effort and time (FIATECH, 2004), along with moderately efficient

communication systems, to collect, incorporate and analyze this information.

Despite the enormous amount of responsibilities that are involved in all of these

processes, decision making within the project planning effort, for most part, remains

instinctual with very little use of computational technology (FIATECH, 2004). With

attempts to introduce ubiquitous tracking and sensing systems thereby promoting real-

time access to information for apposite stakeholders into construction execution, and later

the operation and maintenance of facilities, it is imperative to equip project managers and

construction engineers with toolsets that allow them to access and interpret the

information pool, analyze it and adjudge optimized and sustainable decisions in accord

with concerned stakeholders.

Current industry trends also indicate that the decision-making authority mostly

resides in one person (FIATECH, 2004), who may or may not have the requisite amount

of CM experience. Use of scenario modeling or simulation capacity by decision makers is

relatively unknown. Project data of similar projects which could help in forecasting

challenges that might be posed are either unavailable or unorganized, barring quick

review and decision making. There is a need to improve documentation of lessons

learned and to communicate these efficiently (O’Connor, 1998).

Likewise, thumb rules used by experienced managers are barely documented. And in

some cases, tight project deadlines force very quick decisions. Capital projects are known

to be largely diverse and the project variables that need addressing are often weighed

differently for different projects.

6

Traditionally, detailed construction resourcing methods have not been considered at

the preliminary planning stage, but are left to contractors to decide at the construction

stage. Lessons learned during construction of a project are not effectively incorporated

into design and construction phases of other projects (Kartam, 1995). Lack of expert

systems to analyze the success or failure of alternate execution strategies and to

experiment with the project plan adds to the difficulty.

Endeavors to bring in advanced monitoring systems have not yet been validated as

substantive technology enablers because appropriate software applications that are

compatible and integrated with such hardware are yet to be fully explored. Application

enhancements for data collection, conversion and analysis to process automated sensory

or manual inputs into intelligible information are not clear to software vendors, since

such requirements are not known to them for most part.

Communication and information systems are said to be time consuming, error prone

and highly dependent on human initiative and expertise. One of the key barriers to PM

practices has been noted as limited access to information (PenaMora, 2002). Poor

communication between companies is also attributed as a leading cause of problems in

construction processes (FMI, 2004). Distributed and arbitrated decision making is known

to lag since information integration with suppliers, and also with third parties like

owners, sub-contractors, regulatory agencies, etc. is inadequate.

Large construction firms are known to be subdivided based on administrative areas

and inter-disciplinary understanding and cross-functional communication are said to be

minimal. The timelines for communication along various points in the supply chain are

long and even though information generated and needed has increased manifold, most

7

information delivery and processing has still remained paper-based. Current project

management practices are often isolated and are concerned with managing problems

related to individual stages of the projects (Alshawi, 2003).

Application of state of the art DBMS (database management systems) has not yet

penetrated the construction industry. Lack of knowledge management tools that would

qualify timely capture of information between phases, applications and stakeholders

sometimes results in creation of multiple loops of data that cause confusion. Ambiguous

data exchange methods result in inefficient communication and information flow

integration. This is further aggravated by the reticence within the construction industry to

follow an open universal data transmission protocol as this would affect the advantages

of competitiveness (FIATECH, 2004). Then again, business data security requirements,

especially after 9/11, mandate high levels of security regarding capital facilities

information. Interfaces with external databases to capture regulatory requirements, codes

and standards are not in place. Interactive limited access databases to update project

information and delivery system data is lacking.

Tools are being implemented, but are principally used for visualization and not for

mathematical process modeling towards decision support and optimization. If any

experiential knowledge and real-time data is available, it is not integrated with other

systems forcing multiple entries of data into alternate scenario planning, which might be

redundant and / or inaccurate. Optimization techniques are not implemented during

conceptual planning and design processes. With companies shifting to multi-project

centralized sourcing to benefit from economies of scale and most of the execution being

out-sourced to local subcontractors, trading-off multiple parameters and shared resources

8

to make fully optimized best-value decisions is imperative. Quantified assessment of

risks and liabilities regarding ventures, own vs. lease decisions, cost and schedule

impacts of optional execution strategies etc. are barely available and do not have a

scientific basis. Tools to capture and analyze alternate scenarios and optimize them on the

basis of constraints comprehended by real-time project status are unavailable, thereby

resulting in inefficient change management techniques.

As cited above, most of the problem areas have been identified and solutions are

being researched. Addressing most of these concerns, however, feature upon the aid of

computing tools, which would allow project teams to collaborate and plan the project

structure and controls efficiently and accurately.

1.4 PROBLEM STATEMENT

As a tool to aid construction management (CM) and other project activities it

encompasses, scores of PM software applications have been written over the years.

However, with increasing availability of a broad range of such applications, organizations

are generally disoriented and uncertain with respect to which applications and tools are

best suited to their business goals. Furthermore, with project management systems

becoming more and more complex (Ahuja, 1994) and encompassing sophisticated

practices for better management and control, selection of such tools has become

increasingly difficult.

Available applications, in essence, have attempted to scale the width and depth of

project activities and protocols and are therefore extremely varied in their architecture,

functioning, features and costs. Though penetration within the industry is reportedly not

9

much (Cutter, 1999) and the construction industry is said to be averse to computerization

and unwilling to experiment with new systems owing to uncertainness in benefits and

lack of precedents (O’Connor, 2003), such applications are gaining popularity by the day

so much so that most construction firms have dedicated IT departments to cater to such

needs.

Technology flooding, inadequate focus on implementation and sustainability issues

(Nitithamyong, 2004) as well as inadequate research elaborating “the past in this field

and the current situation of the CPE (Construction Project Extranet) market” (Becerik,

2004) have been cited as prime reasons of slow adoption of PM applications technology

by the AEC industry.

1.5 OBJECTIVES

This study targets the above mentioned problem areas through an in-depth,

sustainability-based review of the genesis, development and implementation of

computing tools in CM. Focusing on implementation, it attempts to address corporate

needs and concerns through an overview of the evolution (past) and the research agendas

(future) for such applications that allow the construction industry to better understand

possibilities as well as difficulties in this arena.

It aims to provide construction firms with a multi-faceted perspective into the

software development, marketing and implementation processes through a review of

popular commercially available and customized PM software applications.

Industry trends and preferences relevant to PM computerization and work

environment from the business and organizational management purview have also been

established based on an industry-wide survey.

10

Primarily, it provides a decision model that would lend project managers and

executives greater insight into crucial aspects of PM applications, based on industry

preferences and trends for such applications. The model will aid as a guideline for

selection of a software system that best-fits a given enterprise and will provide a

reference for project managers and construction executives to center upon applications

that would best fit their budgets, operations and requirements from such applications.

1.6 RESEARCH SCOPE

Some of the phased deliverables of this work would include:

• Review of emerging software technologies that enhance construction project

management capabilities and their evolution.

• Review of select PM applications that are currently being used for varying aspects of

project planning and management, their unique capabilities and grey areas.

• Identification of industry trends related to project management work environments as

relevant to computer-based applications.

• Survey-based assessment and recommendations for best-fit project management

application systems based on the functions, size and structure of construction firms.

• Recommendations for further studies towards evolving the setup, development and

deployment of such tools.

1.7 METHODOLOGY

In order to design a decision matrix for the purpose mentioned above, a multi-step

process has been followed.

11

A study of the developmental history, evolution and implementation of PM

applications and other areas of computing in construction was done to gain insight into

the functions, capabilities, problems, barriers and necessary future enhancements that

exist in this field.

It was also crucial to identify specific areas of focus for further exploration into the

PM IT work environment. In order to achieve this, specific applications were identified

and reviewed on the basis of popularity, usage and variations. These are as mentioned

below:

• Primavera Systems Inc.’s Expedition

• Autodesk’s Constructware

• Computer Methods Int. Corp’s Enterprise (Messer Construction Co.)

• Meridian Project Systems and Turner Corporation’s Inc. TurnerTalk

• AASHTO’s Trns•port

Studying the architecture, functioning, upgrades and features of these applications

aided not only in the development of the diagnostic but also yielded relevant information

about the construction industry’s hierarchical structure and working patterns.

Simultaneously, studies of PM methods, techniques and processes were taken up in

order to design an online survey to better gauge the IT trends with respect to PM

applications and the various factors affecting it, as explained in greater detail in the

literature review chapter.

Depending upon availability, personal and telephonic interviews with project

managers and executives from top firms were conducted to determine feasibility of use,

implementation as well as other issues that they deemed as relevant in this context.

12

Critical areas that have been addressed in the survey and interviews have been explained

in detail in Chapter 4. Information and ratings obtained from the survey have been

categorized and analyzed in order to statistically establish or negate associations between

various parameters.

All of the information collected from the above mentioned phases has been used to

develop the decision matrix.

1.8 ORGANIZATION OF THESIS

The thesis constitutes six chapters. The first chapter introduces the entire concept

underlying the study. It attempts to encapsulate, as briefly as possible, the necessary

information that led to the formulation of the objective of this work. Brief descriptions of

the various steps and methods adopted have been explained to highlight later chapters.

The second chapter dwells into the preliminary studies and literature research that has

been conducted in order to understand the precedents and concurrents of this study. It

also focuses on future research agendas that are being considered worldwide within the

arena of construction automation and integration. It additionally presents a subsection on

advanced software technologies that are being researched in several academic fraternities

towards construction IT. Also included is information on how the nature and corporate

structure of a firm largely influence the PM software applications that best fits them. The

third chapter pertains to selection criteria and review of software applications as well as

discussion of inferences obtained from the review. The fourth chapter deals with

important aspects and design considerations of the diagnostic survey, data analysis,

descriptive statistics, and the discussion of established trends. The fifth chapter utilizes

13

rankings pertaining to various categorized aspects of PM applications and PM IT work

environments obtained through the survey to formulate the decision matrix. It also

explains the working of the matrix and its advantages and presents a case study that has

been conducted to validate the decision tool. The sixth chapter presents some conclusions

inferred through various observations in this study and discusses the results obtained

thereof.

14

CHAPTER 2 LITERATURE REVIEW

2.1 CONSTRUCTION PROJECT MANAGEMENT AUTOMATION

Corporates of varying sizes and operations within the construction industry acclaim

the contribution of PM applications that assist in business and operational practices, as

reflected by the rapidly growing number of software vendors in this area. An integrated

intelligent construction management application that enables process modeling and

scientific or algorithmic analysis of construction process planning, interacts with a

mainframe-based automated relational database system and drives the project sequencing,

scheduling, decision making and change management processes can introduce dramatic

speed, simplicity and accuracy into existing project planning practices. Such applications

empower project managers and construction engineers to make quick decisions based on

accurate information that can be visualized, studied, optimized and quantified with far

greater accuracy than seen in current construction industry norms.

Several research organizations and academic fraternities in concert with industry

participation are studying the needs for development, feasibility and implementation of

such futuristic tools as described above. Some of these include:

• Construction Industry Institute (CII)

• National Institute of Standards and Technology (NIST)

• Center for Integrated Lifecycle Facility (CIFE) at the Stanford University

• National Research Council (NRC), Canada

• Center for Construction Industry Studies (CCIS) at The University of Texas at Austin

• Project Management Institute (PMI), and

15

• Fully Integrated and Automated Technologies (FIATECH).

Research efforts worldwide to introduce technological innovations into the

construction industry, like those listed below, might enable making the entire project

planning, control and management process highly automated, timely and reliable.

• Process simulations

• ORDBMS (object relational database management systems)

• 4D or timebound-3D CAD (computer aided design)

• Wireless networks and data migration

• Software applications integration, and

• Advanced information technologies

These technologies offer the potential to significantly enhance information sharing,

decision making and process optimization in construction planning and execution.

Concurrent research efforts are also being directed to introduce ubiquitous tracking

and sensing systems that will enable pertinent stakeholders to visualize the status,

location and other significant information concerning project parameters like resources,

equipments, supplies, execution progress, etc. Attempts are also being made to improve

the timeliness, accuracy and reliability of involved communication systems.

The need for accord between all stakeholders, expedited determination, interpretation

and judicious scoping of changes and variations and speedy decision making is also well

acknowledged, eminently for capital facilities and global construction projects. However,

few tools are available or in widespread use that empowers authorities with most of the

benefits mentioned above.

16

2.1.1 Computerization of CM: Issues

Computing, electronic and communication tools have been experimented and used

extensively by the construction industry in the last few decades. For the most part,

however, such tools were used for the conceptual drawing, design and preconstruction

planning aspects of the project. The use of such applications to plan, schedule, manage

and optimize construction projects is also believed to be minimal (Ding, 2002). Initiatives

to computationally develop scheduling networks like CPM and PERT, risk analysis and

optimization of cyclical operations were also taken up. In the last two decades many new

software applications have been developed to aid planning and control of projects and are

also being implemented. The capability of these applications to be compliant with latest

research innovations is however, either lacking or unknown. A number or reasons have

been cited by researchers and industry professionals for this. These include, but are not

limited to, those mentioned below:

• Commercially available off-the-shelf project management softwares are very

expensive and can be afforded only by large PM (project management) and

construction firms.

• Smaller softwares are definitely cheaper but are unable to address important aspects

of project controls that are demanded by specific companies and are also not

amenable to customization (Gidado, 1996).

• It is cumbersome and costly to procure a software and experiment with it in order to

optimize and test it for a given firm or project (Becerik, 2005).

• Introducing a new technology is cited as being more difficult in the construction

industry than in other industries (Allmon, 2000).

17

• Off-the-shelf software tools cannot be a source of competitive edge as others can

procure it as well resulting in project managers relying on information and experience

to make decisions (FIATECH, 2004).

• The fragmented nature of structure and operations of firms within the construction

industry make it difficult for software vendors to gauge a common set of features or

tools to incorporate in their existing software applications (Molenaar, 2002).

• “Most researches seem to have ignored the fact that technology push is not the only

critical success factor for effective implementation of a new technology”

(Nitithamyong, 2004).

• There is a preference for established conventional methods and the industry seems

disinterested in research and development. Surveys of IT expenditures in US

companies have highlighted that construction is the lowest spender among major

industries (Cutter, 1999).

• “Relatively little work has been done related to what had happened in the past in this

field, the current situation of the CPE market and the reasons of slow adoption of

CPE technology by the AEC industry” (Becerik, 2004).

Despite extensive research activities within this area, there are several limitations in

project management softwares that are not yet addressed. Some areas of intuitive

planning that remained lacking, and are, for most part, still unfulfilled, include the fact

that construction projects need collaborative planning amongst all the stake-holders,

which means that people and parties seated in distinct geographical locations need to pool

in their inputs towards the holistic plan.

18

Another includes the fact that all of this information exchange had to be relayed

across all parties concerned, the decisions made and again relayed across all, and then

implemented on-site, which could be in another geographical location. Need for tools to

streamline the job of managing information for construction professionals has been

acknowledged since long (Shahid, 1998).

FIATECH (Fully Integrated and Automated Technologies) through its CPTR (Capital

Projects Technology Roadmap) initiative forayed into the above mentioned problem. It

outlines certain targets (within the scope of this work) that such applications need to

possess and asserts that the tools of the future should be able to:

• Support accurate and complete planning and analysis of all important aspects of the

project.

• Analyze activities, recognize and evaluate conflicts, analyze risks and recommend

actions based on situational analysis.

• Learn and continually build the enterprise knowledge base.

• Adapt to needs of individual companies.

• Ensure seamless data access that is available through reliable and secure search

mechanisms.

• Enable information sharing and online capabilities.

• Inter-operate with all systems related to construction project management and

services.

• Automatically extract and interpret data.

• Optimize across the enterprise, considering interaction between and among projects

for highest business value.

19

For current PM applications to achieve the goals listed above, it is imperative to first

understand the genesis, development and functionality of these tools. It is essential to

delineate what the current tools can and cannot process and why, their limitations as well

as the concerns and problem areas that seem to be a barrier in their implementation,

before steps to make them more capable are taken up.

2.1.2 CM Applications: Research Approach

A primal phase in establishing the needs or functional deliverables of PM applications

is to identify various construction and project management activities that are involved in

different types of project scenarios, companies, operations, different hierarchical and

departmental structures, and so on. This includes works detailed to construction firms

from site selection and pre-design planning, resource allocation, project control and

construction execution, to maintenance and decommissioning of the facilities. Analysis of

parties, tasks, resources, information flows and causes and consequences of changes

involved is needed in order to make a preliminary sketch of how the PM application

needs to function ideally.

Most CM or generic PM applications which are commercially available are used for

business, documentation and control aspects of project management. Futuristic

capabilities as mentioned above are largely unknown insofar as these tools are concerned.

However, major players within the software industry catering to such applications are

attempting to enhance their systems and software architectures in order to incorporate

more features into their existing applications.

20

There is no absolute method that may be employed in order to center upon the

limitations of such softwares as what could be a limitation for one firm might be an

advantage of another. It depends upon the perspective of the user and the particular task

that is to executed, which is known to vary. Then again, there are certain generic features

that all softwares possess, like purchase, setup, licensing, technical support and many

more, which need consideration.

It was therefore deemed imperative, in order to design the survey questionnaire and to

be able to form an unbiased opinion, to study some of the software application research

agendas as well as literature on current PM IT trends in the construction industry.

2.2 THE SEVEN YEAR PLAN

FIATECH (Fully Integrated and Automated Technologies), amongst many other

research bodies, through their CPTR (Capital Projects Technology Roadmap) initiative in

2004, identified numerous elements or areas within the capital projects construction

industry wherein research can be undertaken to develop and deploy innovative tools and

technologies for the future. Some of these elements, as pertaining to the scope of this

work and related to generic construction project management and not capital projects

alone have been described as under:

The Scenario Based Project Planning concept (Element 1, Oct. 2004) aims to provide

a comprehensive, collaborative project planning system that will enable interactive

evaluation of project alternatives and creation of conceptual designs and project plans

that best meets the needs of all the stakeholders. This collaborative planning environment

will provide full awareness of the impacts of decisions on costs, schedules and lifecycle

21

performance. Options will be evaluated using a suite of M&S (modeling and simulation)

tools that enable rapid real-time exploration of different scenarios to arrive at an optimum

decision, both within the context of the project and the facility lifecycle. Scenarios may

be evaluated at project milestones or at critical decision junctures to validate and / or

modify the planning for subsequent stages. The suite of tools will also interface with

external databases to capture regulatory requirements, codes and standards and to co-

relate them to the design requirements. It will automatically generate an initial work

breakdown structure and other key elements of the project management toolset to provide

a framework for the costing, scheduling and workflow tasking.

The Automated Design concept, (Element 2, Oct. 2004) in its vision for the future,

again iterates that emerging capabilities in intelligent IS (information systems) offer the

opportunity to create a truly integrated and automated project design environment. In this

environment, all tools will work together as an interconnected system that provides all of

the functionality needed to develop and validate detailed designs for every aspect of a

project based on the design criteria. This integrated design environment will dramatically

reduce the time and cost in moving from concept to construction execution through

automation of complex design engineering tasks. It will also greatly reduce errors and

liability through comprehensive design optimization and verification. Optimization

would include a variety of options including total installed cost, total lifecycle cost, and

plant output.

The Intelligent And Automated Construction Job Site brief, (Element 4, Oct 2004)

describes an M&S driven automated time bound 3D (or 4D) design and modeling system

that will enable project managers to communicate project information across all

22

disciplines and phases of the project to increase productivity and reduce project rework.

The visualization of the project sequence will help identify potential conflicts in project

schedules.

The Real Time Project Management and Control function, (Element 6, Oct. 2004)

envisions that management tools and systems of the future will empower integrated

control of project and facility processes, and will provide continuous visibility to all plans

and tasks throughout the planning, design, construction and facility lifecycle. The result

will be a well-orchestrated series of interrelated tasks and activities optimized for

efficiency and results by coordinating resources and plans in an error-free fashion which

will radically reduce the time and cost required to move from planning to design to

construction to the operation stages.

A study of the report confirms that there are numerous capabilities and qualities that

are desirable in a project management application. Notwithstanding the fact that CPM

(construction project management) is a widely researched field, there are still diverse

features and limitations that need to be considered. Some of these, as defined by the

FIATECH report, include the following:

• Tools for visualization and fit are quite widespread in the industry but mathematical

or statistical based toolsets for process optimization and selection lag.

• Uncertainty in cost / benefit ratios pertaining to acquisition and implementation of

softwares and their use (FIATECH, Oct 2004, Becerik, 2005).

• Resistance to change from deeply rooted traditions (FIATECH, Oct. 2004, Moselhi,

1991). Project managers need informed decision making, especially with many

changes happening simultaneously (FIATECH, Oct. 2004).

23

• The fact that the goal of a comprehensive tool, as an aid to project managers, should

not be acquisition of data but the interpretation and processing of such data so as to

enable them to make decisions in tandem with all stakeholders (FIATECH, Oct.

2004).

• Lack of integration of knowledge and information management systems with

intelligent control systems (FIATECH, Oct. 2004).

Considering the issues cited above, this work focuses on the functional capabilities of

such advanced tools and their deliverables while keeping the compatibility and

implementation perspectives of current construction management applications in mind.

2.2.1 Ideal Application Design

With advances in IT and communication systems research, the options of initiating

new programming constructs into existing applications in order to incorporate

intelligence and automation has increased. It is quite manifest that enabling these

applications to integrate or interact with each other would have significant bearings for

the construction industry.

As depicted in the figure 2 on the following page, empowering an advanced toolset

with intelligence to update relevant variables, once the data has been appropriately fed

into the database, will allow extremely rapid simulation of various options.

The alternate scenarios, of course, have to be created by making alterations in the pre-

designed simulated model for the project master plan, in coordination with the decision

authority after negotiating with pertinent stakeholders. The toolset should have the

24

capability to explore the changes in the database, thereby relating to other operations and

processes within the master schedule.

Informed Collaborative Decision Making

Compartmentalized

Limited Access Object Relational DBMS

Information Retrieval,

Interpretation and Data

Pre-designed Process Simulation Model

Process Analysis and Creation of

Options

Negotiated Scenario Specific Constraint Based Optimization

Sequencing Scheduling Delivery Systems Materials Management Equipment Management Human Resource Quality Control Safety

In order to derive the best total value results over the enterprise, the system should be

able to analyze and compare these scenarios. Optimization may be done against different

variables, as deemed important at the given project stage. The selection of the most

favorable scenario, along with quantified results, should be communicated to pertinent

stakeholders and then should drive the sequencing and scheduling toolset to generate the

Finance and Cash Flows Delays Changes

STAKEHOLDERS

Suppliers Regulatory Agencies Architects Design Engineers Project Engineers Owner Operators Service Providers Sub-contractors Insurers Financers

GPS Systems Tracking Systems 3D Laser Scanners RF Identification Tags Wireless Networks Smart Chips

PHASES

Conception Pre-Design Planning Construction Execution Supply and Procurement Resource Allocation Risk Assessment Operation Maintenance Financial Management Change Management Business Management

Figure 2: Hypothetical Interactive Project Management Application Framework

PROCESSES

UBIQUITOUS COMPUTING

SYSTEMS

Automated Updating of Project Schedule

PROJECT INFORMATION FLOWS

25

revised schedule. Such a system will also allow the participants to capture and review the

changes, decisions and other affected variables. It should be capable of efficiently

tackling all or most of the afore-mentioned problem areas.

2.2.2 Advanced Computing Protocols: Database Management Systems

The opportunity for improving construction project planning through real-time

access, relay and interpretation of latest information, thereby augmenting construction

systems productivity and project execution efficiency, is impressive.

Efforts are being made to improve this arrangement owing to the fact that most sub-

contractors, field managers and construction firms work off the job site and rely on

locally available resources.

Former researches indicate that systematic collection, sorting and storing of data has

not yet been established in the construction industry. In order to make the entire project

information system more efficient, it is vital that along with data collection and

transmission technologies, construction firms have the application toolsets that automate

the interpretation, sorting and storing of such data.

Figure 3 on the following page outlines a suggested model for a relational database,

with the shaded portions depicting areas of further research and beyond the scope of this

work. Implementing the said model would act as a repository for all information

reception across the entire lifecycle of the project.

It shall be based on an enterprise model on grounds of best business value and not be

applicable to specific projects alone. Stored data shall be sorted and compartmentalized,

with controlled access to relevant participants that will allow online updating and review

of project information, decisions and changes.

26

SUBCONTRACTORS JOB STATUS

INFORMATION

SUPPLIER DELIVERY STATUS

INFORMATION

ACCIDENTS, SAFETY ISSUES,

WEATHER DELAYS

CONSTUCTABILITY ISSUES

RESOURCE ASSET DATABASE

EQUIPEMENT ASSET DATABASE

DOCUMENT MANAGEMENT

SYSTEMS

SUBCONTRACTORS INFORMATION

DATABASE

SUPPLIER INFORMATION

DATABASE

RESOURCE ALLOCATION

DATABASE

HISTORICAL PROJECT

LIFECYCLE DATA

BUILDING CODES, STANDARDS,

DESIGN CODE S

UBIQUITOUS PROJECT TRACKING SYSTEMS

GPS SYSTEMS 3D LASER SCANNERS RFIs EQUIPMENT TRACKING SYSTEMS LABOR TRACKING SYSTEMS PROGRESS TRACKING SYSTEMS SMART CHIPS and MEMS

PROJECT PROGRESS TRACKING SYSTEMS

FACILITY OPERATION and MAINTAINENCE

STATE and GOVERNMENTAL

REGULATIONS

Stakeholders

Ubiquitous Computing

Systems

Job Site Information

FUTURE RESEAR

MAINFRAME

Figure 3: Contingent Model for Network Based ORDBMS

CH

This shall capacitate project managers and other participants to positively use gainful

project control and decision making data. It shall also facilitate the review of information

from previous projects to allow for judicious creation of alternate scenarios towards

change management. Most importantly, it will provide rapid relay of current status of

various project phases as well as operations and maintenance data of facilities which in

turn would capacitate fast identification and scoping of changes and variations.

27

2.2.3 Decision Support Systems

The need for a benchmarked or standardized decision support system, which could be

tweaked to merge with the administrative structure of different firms, has been widely

recognized by the construction industry and associated academia. The central cause being

that decision authority resides mostly with one person within the project administration

hierarchy who is flooded with information from all quarters and is, at times, compelled to

make very quick decisions. Figure 4 on the next page attempts to encapsulate the parties

and the phases of project controls wherein the information is received.

Development of an integrated project management tool will have the capability to

overcome this problem. It will automatically enable tracing of changes and information

that has been added to the data repository, intelligently identify dependencies related to

the alterations in order to simulate, optimize and quantify the outcomes of the changes.

An advanced decision support system shall endow various participants to review the

project planning options, execution strategies and scenarios quickly and accurately. The

database thus construed shall allow project managers to review similar information from

previous projects and develop alternate scenarios in accordance with concerned

participants.

Nevertheless, the fact that the decision liability will still be the onus of one person

who does not have real-time knowledge of all the project bearings is undesirable.

In order to develop a model for distributed collaborative decision making, it is

essential that the decision support system be benchmarked and industry-wide best

practices be identified. It is manifest in current industry trends that different firms prefer

different tools and methods to achieve similar objectives. Clients and external agencies

28

are also known to have preferences in this regard. A standardized decision making

protocol shall preclude such deviations and promote uniformity and concord over the

enterprise. This shall also aid in the development of the system architecture of an

integrated application environment.

Regulatory Agencies

Suppliers

Design Engineers

Construction Engineers

Owners / Operators

Sub-contractors

Insurers / Financers

Service Providers

Financial Management

Change Management

Operation and

Maintenance

Risk Assessment

Resource Allocation

Supply and Procurement

Construction Execution

Pre-Design Planning

DECISION SUPPORT SYSTEM

CONSTRAINTS

Lack of Time Lack of Experience Inadequate Information Inaccurate Information Redundant Data Inefficient Communication Rules of Thumb Centralized Decision Making Uninformed Decision Making Traditional Business Practices Lack of tools to Quantify Impacts Lack of Archived Project Data

Figure 4: Decision Support Inputs and Constraints

Essentially, this will allow all stakeholders to contribute to the decision making

process through seamless integration across organizational and inter-departmental

boundaries, thereby reducing the burden on one person and will impart a mathematical

basis to the chosen option. It would also benefit the owners or operators by reducing

uncertainties and liabilities that are normally clubbed with experiential off-the-cuff

decisions that rely on personal enterprise.

29

2.2.4 Modeling and Simulation Tools

The arena of construction process simulation has an eloquent history. The earliest

records of such attempts date back to the early 1960’s with efforts to use random number

techniques to resolve stochastic problems encountered in construction project

management like range estimating, evaluation of project time duration (PERT

simulation), expected productivity of construction processes etc. This led to gaming

concept innovations, some configurations of which are still used at several universities

for teaching purposes (Au et al, 1969, Abourizk, 1992).

This was followed by application of the link node method into construction process

simulation. Another pioneering work was the development of CYCLONE (Cyclic

Operations Network) by Halpin at the University of Illinois (Halpin, 1999). With the

advent of desktop computers and faster processing speeds and programming constructs,

intricate computing tools became more accessible, and led to multitudinous efforts to

introduce various innovative computing protocols into the project planning environment.

Table 1 on following pages lists some of these efforts.

However, almost all of the applications in either of the above mentioned spheres

remain mostly confined to the academic and research fraternities and evidence of their

deployment in the industry is lacking. Current state of the art process simulation tools

have the capability to analyze a variety of processes from production measurement, risk

analysis, resource allocation, site planning (Sawhney, 2003) and process optimization and

review.

Almost all of these initiatives can be classified into certain major segments. The first

of these dealt with incorporation of desired capabilities to make the simulation modeling

30

process easier, faster and more compatible with theoretical project planning concepts.

The second involved introducing different scientific approaches from other areas of

engineering into the construction simulation models. The third led to lending of

intelligent capabilities into the system so as to enable automated decision making and the

fourth addressed the issue of shared real-time access to project information.

In order to enhance the entire functional system, and not only the communication

system, it is imperative to device software packages that can automatically read data from

a centralized repository or database. Having read the data, the softwares should be

capable of intelligently identifying the dependencies within the project plan that shall be

affected. They should also possess the capability of importing and exporting data to other

software packages that will allow simultaneous updating of information thereby making

the change management uniform, accurate and faster.

Another impediment to best business value decision making dwells within the

enterprise-wide resource planning (ERP) system. An integrated or inter-operable

construction management application, as depicted on the previous page, shall also enable

comparison and quantification of ERP systems.

Project planning is also profuse with variables and complicated inter-relationships,

which are furthermore, unique to different projects. Construction managers are,

conventionally, believed to be uncomfortable with mastering the techniques of modeling

such systems. This is aggravated by programs comprising multitudinous modeling

constructs that need to be clearly understood and dispensed.

31

Design Tool Designer Features / Enhancements Category

Link Node Method

Teicholz, Stanford University, 1963

Chain like or linked graphical representation of the model for construction networking concepts.

Primarily for construction bidding, extended to SUPERBID by Abourizk at University of Alberta Canada in 1992.

Gaming Concepts

Au, Parti, and Bostleman, 1969 Germinal Tools

Modeling repetitive / cyclic construction processes like excavation, ground water removal and other common construction processes.

Halpin, University of Illinois, 1973 Cyclone

Table 1: Brief Review of Research Efforts in Construction Process Simulation

CONSTRUCTO Halpin, University of Illinois, 1976

Integration of the effects of weather and labor productivity into project management using network format.

Insight Paulson, Stanford University, 1978 Enhanced interactive user interface.

Insight Touran, Stanford University, 1981 Integration with real time data acquisition.

UM - Cyclone Ioannou, University of Michigan, 1989 Advanced construction process modeling

PICASSO Halpin, Purdue University, 1988

Project Integrated Cyclic Analysis of Serial System Operations, integrated CPM with process simulation to bridge CPM and simulation incompatibility.

MicroCyclone Luch and Halpin, Georgia Tech, 1981. PC based version of Cyclone

Cyclone Abourizk and Dozzi, 1993

Predicting lost man-hours due and added complexities like weather changes, labor skill and site conditions etc. to aid in settling construction disputes.

Cyclone Based Tools

Catering to users with different levels of simulation skills to view and understand the processes based on the level of sophistication of the user

Halpin, Jen and Kin, Purdue University,

2003 WebCyclone

Model for Uncertainty Determination, Enabled cyclone-based simulation modeling to provide sampling of unbalanced estimate of durations and criticalities.

Carr, University of Michigan, 1979 Cyclone - MUD

Chang, University of Michigan, 1986

Encapsulated advanced resource handling capabilities. Resque

Dynamic Interface System for Construction, Allowed more customization by allowing the user to create cyclone models graphically and view the simulation results.

Huang, DISCO Grigoriadis and

Halpin, 1994

32


Cheng, Chaoyang University,

Taiwan, 2003

Genetic Algorithms with Construction Operation Simulation Tool Incorporated the fundamentals of genetic algorithms for resource optimization and selection, with a spread sheet input format.

GACOST

Dept of CEM, Purdue

University.

Improving construction productivity by analyzing resource utilization and cycle times. Prosidyc

State and Resource Based Simulation of Construction Operations, Introduced three-phase activity scanning concept without process interaction and made it easier to model complex resource in cyclic operations.

Martinez, University of

Michigan, 1996 STROBOSCOPE Cyclone Based

Tools

Tommelein and Odeh, University

of Michigan, 1994

Construction Integrated Project and Process Planning Simulation System Introduced object-oriented concept allowing user to relate project specifications and designs to construction plan

CIPROS

Animated Construction Process Simulation System, Introduced 3-D animated display of construction sequences facilitates non-ambiguous evaluation of schedules.

Liu, University of Illinois, 1996 ACPSS

Abourizk, University of

Alberta, Canada, 1999

Special Purpose Simulation, Allowed simulators to design customized operation templates to create operation models and implement it.

Simphony - SPS

Borcherding, University of

Texas at Austin, 1977

Cost Control Simulation, modeled analysis of financial aspects of construction projects by simulating uncertainties at construction site.

CCS

Liu and Ioannou, University of

Michigan, 1992

Construction object-oriented process simulation, allowed advanced resource definition and tracking capabilities and linked with other systems

COOPS

Hajjar and Abourizk,

University of Alberta, Canada,

2002

Unified Modeling Methodology encapsulated a comprehensive approach to improve appeal of simulation tools and elicit acceptance in the construction industry.


UMM Research

Enhancements with Standalone

Tools

Resource Interacted Simulation, Made modeling process easier and less time consuming by dividing the model into the resource level and the process level models.

Chua and Li, NUS, Singapore,

2002 RI-SIM

McCabe, University of

Toronto, Canada, 1998

Provided diagnostic analysis of different process decisions to determine the effect that changes in resource configurations would have on the performance.

Belief Networks

Interactive Simulation System, Allowed a user unfamiliar with simulation concepts to evaluate construction process productivity.

Kim, Purdue University, 2000 ISS

33


Agent Based Modeling and Simulation, Modeled subsystems as a collection of autonomous decision making entities which stochastically respond to a situation based on a set of pre-defined rules or conditions

Sawhney, Arizona State University 2003 ABMS

Hierarchical Simulation Modeling, Combined UMM and CIPROS to conceptualized the break between project-level and process-level simulation models, allowing addition of elements to manipulate resources, interlink processes and establish inter-process constraints

Sawhney and Abourizk, 1995 HSM


ANN Hajjar, Abourizk and Mather, University of Alberta, Canada,1998

Artificial Neural Networks, Incorporated intelligence by ascertaining and controlling variability in project processes, the simulation could automatically analyze inter-relationships and aid in faster decision making

Research Enhancements

with Standalone

Tools

Incorporated Java to access a web browser interface, it has the capabilities of object-oriented language that can be used to design hierarchical, modular and reusable simulation models.

Sawhney, Arizona State University, 2000 JavaSim

Coding based program for discrete event simulation, involved drawing block diagrams and typing character-based representations of blocks.

Geoffrey Gorden, IBM, 1961 GPSS

Simulation Language for Alternate Modeling, FORTRAN based and PC based discrete event language, included network and continuous features.

Pritsker Corp. Indianapolis, 1988 SlamSystem

Halpin, Learning Systems Inc. Indiana,

1990

Microcomputer based commercial version of Cyclone. MicroCyclone

Simscript Markowitz et al., Rand Corporation, 1962

A high level language for discrete-event and hybrid modeling, evolved to Simscript II by CACI products Co. LaJolla, California.

Commercial Programs

Systems Thinking in an Experimental Learning Lab with Animation, GUI based program for modeling dynamic systems and processes.

High Performance Systems, Hanover, 1987 Stella II

General-purpose simulation analysis program for modeling discrete-continuous systems, the framework allows component models based on three distinct orientations to be combined in a single system model.

Pegdan, Systems Modeling Corp,

Sewickley, 1980s

SIMAN

34

35

Definition of System and Dependencies

Systems Analysis

Accord

Creation and Collaborative Validation of Alternate

Models

YES

NO

Model Formulation and Translation

Data Preparation and Entry for Simulation input

Experimental Design for Information Generation and

Execution

Quantified Analysis of Impacts

Simulation Run and Process Analysis for Alternate

Models and Constraints

Interpretation and Distributed Decision

Making

Implementation

Document

Model Formulation and Development

Optimization, Collaborative Negotiation and Validation

of Initial Plan

Data Interpretation, Arbitration, Problem

Definition

Stakeholders

Ubiquitous

Computing Systems

NO

Y

ES

Job Site Information

Figure 5: Postulated Inter-operational M&S Framework

MAINFRAME

Consolidation of these gaps into a framework design will not only endow managers

and engineers with a decision making expert system, but also add visibility to the

enterprise’ project portfolio, thereby allowing various business function experts to share

their perspectives and expertise and contribute to the change management process. It

would allow them to exactly scrutinize the decisions that have been made, why they were

deemed necessary, and identify the gaps to adjudge what needs to be done or improved.

2.2.5 Construction Process Optimization

Applied optimization refers to the technique of allocation of resources to effect

maximum business value. It lends a statistical basis to decision making and allows most

efficient use of enterpreneual assets.

INTELLIGENT OPTIMIZATION PROCESSOR

Resource Based Constraint

Legal Constraint

Time Based Constraint

Business Value Constraint

Activity Based Constraint

Finance Based Constraint

Supply Based Constraint

Design Constraint

Sequence Based Constraint

Simulation Processor

Alternate Scenarios

Smart Database

Recognition of Dependencies

IMPLEMENTATION

Figure 6: Proposed Schematic for Integrated Optimizer

Process Analyzer

Quantified Results

Concerted Planning

Final Decision

36

Figure 6 on the previous page presents a hypothetical framework for such an

optimality processor. This system shall be capable of automatically interacting with the

simulation processor, upon manual initiation, and present quantified data, analyze

contrasts for various scenarios and present graphical output for easy interpretation and

dissemination.

Nevertheless, substantive information regarding use of such techniques in current

industry practices is wanting. Phases of construction projects, traditionally, have been

viewed as unique, as pertaining to optimization and scheduling. In cases where

optimization is exercised, it is done against one major variable at a time, in most cases

finance, or some other scarce resource. The concept of holistic optimization against all

known constraints and other corporate resources is believed to be lacking. Consequently,

allocation and utilization of labor, materials, equipment, finance, supply chains and time

do not yield utmost possible benefits.

2.2.6 4D-CAD, BIMs and Schedule Simulators

Some of the other advanced technologies that seem to be penetrating the construction

industry are 4D-CAD (Computer Aided Drawing), BIMs (Building Information Models)

and project and schedule simulators.

4D-CAD is seen as an adept scheduling tool and its utilization is being researched in

various universities worldwide. This tool was evolved in order to overcome the areas or

aberrations that standard tools like Gantt charts and network diagrams do not address. In

order to understand the various impacts of actual spatial or four-dimensional aspects of

construction execution on project schedules, it was found necessary to view the design,

37

planning and progress of works as live models. This facilitates project managers to

clearly demarcate problem areas and develop alternative solutions to determine best-

suited execution strategies at any given project stage. In combination with generic

planning tools, these models associate 3D designs with project execution activities and

are capable of generating visual construction progress scenarios over time. Some

software applications that primarily cater to the construction industry include Bentley

Schedule Simulator and Balfour Technologies Visual Project Manager.

Another futuristic tool that is being widely explored is BIM (Building Information

Model) which was primarily initiated keeping in mind the maintenance, repair and

operations of facilities, as well as security concerns of complicated building designs.

Source: aecbytes.com

Figure 7: Autodesk Revit 7.0 Preview

38

In order to bypass issues created due to lack or absence of design information on

paper based renderings combined with construction documents, 3D layered designs are

created with linked information organizing drawing sets with CAD layers, schedules,

symbols, conventions, graphs and plots. These designs include detailed information and

specifications on building components ranging from very basic phases like woodwork

and dry walling to construction steps involved in complicated designs.

Though there is lack of evidence of widespread use of this technology, it has been

implemented by some companies who have chosen to shift from regular 3D modeling

applications such as Rhino, 3D Studio and AutoCAD. This aided development of 3D

models that permit capturing tangible design, material, process, phases and property

information towards more efficient project planning, especially when modular and

fabrication technologies are being used for construction.

Figure 8: Navisworks Preview

Source: aecbytes.com

39

These systems also offer greater control on planning by visually simulating conflicts

in design and installation as well as the work breakdown structures beforehand. Some of

the applications that have been implemented include Autodesk Revit Building and

Bentley's MicroStation Triforma. Here it must be mentioned that this technology is by far

for architectural and design purposes but has definite benefits for overall project planning

and control if implemented at early stages.

The third radical tool that is also being scrutinized by research fraternities is schedule

simulators. These applications allow a probabilistic study of construction schedules for a

project. Preparation of an initial schedule for a construction project requires the design to

be interpreted and translated into execution steps with the primary aid being the

knowledge, experience and information the planner has about the design. In addition, it is

entirely manual and paper based, at least initially. However, schedules generated with

inadequate or uninformed construction-execution strategies pose barriers to revision since

causes underlying a particular sequence of activities are not clear.

In such case, a schedule simulator allows creation of various alternate work

breakdown structures and is capable of presenting a probabilistic time bound simulation

for different project execution paths along with detailed execution information. Some of

the available softwares that possess such capabilities include Bentley Schedule Simulator

and NavisWorks TimeLiner JS.

2.3 CORPORATE FUNCTIONS AND PM APPLICATIONS: INFLUENCES

As noted earlier, construction project management software applications have seen a

great amount of maturation in the last couple of years and gauging by the extensive

40

research being conducted both in academic and industrial bodies, more is yet to come.

Primary amongst the causes is the diverse structures, operations and variety of services

that the construction industry renders.

It is understandable that the requirements of a large construction conglomerate with

global operations cannot be the same as that of a mid-size firm providing design,

architecture or consultancy services. The basic necessity of information management,

collaboration and communication however, needs to be fulfilled even for these firms,

since they work as affiliates to major players in the industry and are therefore participants

in the project.

NUMBER OF

FUNCTIONAL DEPARTMENTS

Figure 9: Graphical Representation of Corporate Structure’s Effect on Selection Criteria

INTER-DEPARTMENTAL COLLABORATION AND

COMMUNICATION

BUSINESS STRATEGIES

VENDOR PREFERENCE

PROJECT MANAGEMENT

ACTIVITIES

SIZE OF THE COMPANY

FINANCIAL VOLUME OF

PROJECTS

PERCENTAGE OF PM FUNCTIONS

ANDPERSONNEL

NUMBEMP

ER OF LOYEES

NUMBER OF BRANCHES and

DIVISIONS

EXISITNG PM APPLICATION

SETUP

PROJECT MANAGEMENT POLICIES AND PROTOCOLS

PM AGENDAS and

PRIORITIES

INVESTMENT

CONTROL AREAS

DESIRED PM APPLICATION ENHANCEMENTS

DEFINITION OF

APPLICATION SELECTION CRITERIA

TYPE OF COMPANY

COMPANY STRUCTURE and

HIERARCHY

SPREAD OF OPERATIONS

CATEGORY OF

WORKS

NATURE OF WORKS (PUBLIC,

PRIVATE, ETC)

PERSONNEL TRAINING

SERVICES PROVIDED

COSTS

TIME

41

In order to avoid a biased opinion and ambiguous extrapolation of data, studies

pertaining to company structures, sizes, operations, PM work environments, applications,

opinions and demands were essential.

The focus was to enable distinction of requirements of PM applications on the basis

of different types of firms that form an integral part of the construction industry and play

an active role in project processes. Even though it is difficult to canvas the entire range of

such firms, efforts have been made to study as many distinct segments as possible.

2.3.1 Nature and Size of Construction Firms

The construction industry is known to be extremely fragmented, in the sense that it

reflects a wide array of occupations, types and nature of works. Different kinds of

organizational configurations exist with many firms working together in a project and

affiliated to each other through various contractual bindings. Then again, many large

construction corporations for example, have worldwide or country wide operations with

branches in several locations. Though it has been observed that in addition to general

contracting, such companies offer a variety of services ranging from AEC or design-build

consultancy and exclusive PM services to client litigation and homeland security services

through distinct divisions, it would not be fair to assume that a company undertaking a

project in one location acts exclusively and would not consult or collaborate with its other

branches of divisions if need arises.

All the same, it has also been noted that branches of major construction companies

often use PM applications that are not being implemented by their co-divisions and do

undertake exclusive contracts.

42

The type of projects being contracted is also a consideration as design requirements,

specifications, legalities and stringency are known to vary with different projects and

clients.

The size of the company is another decisive factor where PM applications are

concerned. Large to midsize companies with hundreds of employees are known to have

many functional sub-divisions in individual branches each working exclusively in their

specialized areas. A company might, for instance, have a distinct legal, financial, and

planning department each working independently yet playing a particular but crucial role

in the project planning, execution and control. Levels of existing and desired

communication between such functional areas are also definitive criteria impacting

implementation of PM collaboration tools. In the same league is the levels of

communication with subcontractors, vendors, clients, design firms, etc. that are also

known to vary in number as well as in scope with the type of size of projects a company

contracts.

Another important factor is the spread of operations that a company displays in

relation to its ERP targets. For example, certain company headquarters might choose not

to get too involved in the projects that their branches, subsidiaries or sister firms are

executing but might want to keep a strict watch on their individual cost control measures.

In order to adjudge appropriate tools for different priorities, an insight into how the

company functions or goes about its holistic project management is important. The costs

of software applications are known to vary greatly with the number of users and the

degree of collaboration and restricted access facilities being provided, and costs are an

extremely important factor influencing such selection of applications.

43

2.3.2 Hierarchy and Interdepartmental Communication

While some of the functional aspects described above pertain to communication

within different branches and third parties, cross functional communication protocols

followed within company departments at a single location also have a marked influence

on the software tools being employed. The timing, substance and implications of such

collaboration upon a project plan depend on the organizational hierarchy which decides

which department has priorities to any given information. Human resources and

organizational behavior scientists have studied, classified and benchmarked different

kinds of organizational structures, like functional (grouped by functions), divisional

(grouped by location or clients), hybrid (a mix of both), organic (lesser formalization of

functions and delegated decision making), mechanistic or military (pyramid-type with

complex and centralized decision making), and many more. Notwithstanding these, it is

quite erroneous to categorically state that company structures in construction firms follow

a certain benchmark or fall into a certain league even though they are functionally

similar.

Interdepartmental communication protocols have a far-reaching consequence on

construction projects and the information flow pattern is crucial in obviating avoidable

operational issues like delays, claims and changes. Project personnel are known to rely on

timely access to a large amount of project information and the recording, processing, and

further dissemination of such information is critical. For instance, quite a few companies

while maintaining most or all cross-functional communications like logs, memos,

submittals, change orders, RFIs and RFQs, etc. in electronic format still follow a policy

based practice of retaining paper based formats. This makes it important to gauge the

44

amount of reliability a company attributes to its IT systems as it affects the features that

the desirable application may possess in terms of data storage, retrieval, accuracy,

security and vulnerability to bugs and viruses. Complexity or the lack of such features

creates major differences in the costs and maintenance procedures of PM applications.

2.3.3 Personnel and Training

With implementation of PM applications over the enterprise, an important

consideration that comes up is the adequacy of current staff to use the application

effectively and accurately. As explained in the later chapters, all such applications are

GUI (Graphical User Interface) based and none of these applications involve any form of

coding that necessitates programming skills. However, most of these tools have many

modules and sub-modules and it is crucial that all users be familiar with what goes where.

Then again, since these tools are designed with project personnel as the primary users,

most users are expected to be familiar with the terms and notations used in the

applications. It has also been noted that companies like to use specific nomenclature

schemes to name various details being entered into the digital logs. For example, upon

implementation of such an application, a company might want to name change orders

using a specific scheme which clearly outlines the project, initiating party, date, phase,

etc. pertaining to it. This is practiced since it allows easy sorting, storing and retrieval of

the data. Owing to a large number of such minor specifics, the fact that critical project

information is generated at various ends, and all data entry cannot be assigned to certain

individuals, it is mandatory that all users be trained.

45

Different companies adhere to different practices in this regard. Large companies

with spending (or investment) power have their own IT departments that, amongst other

functions, train and update their staff in the use of such applications. Turner Construction

Company, for instance, provides online courses teaching the use of TurnerTalk (its

customized version of Prolog Manager) though its Turner University initiative as one of

the few measures to train its employees. Companies are also known to hire certified

training professionals working with the application vendors to come and instruct their

staff. Some companies, on the other hand, choose to get their staff trained by disbursing

allowances to take instructional courses from external agencies. Other companies have

application knowledge as a hiring criterion and might not be providing training at all.

Since all of these efforts involve costs, they form a primary factor in deciding which kind

of application the company deems to be most suitable.

The implementation of such applications, besides the training aspect, also involves

time, which translates into costs for all business enterprises. The time taken to implement

such applications primarily depends on the way the company chooses to go about it. Most

companies prefer a phased implementation in order to avoid any adverse effect on

ongoing projects. This could take anywhere from a couple of weeks to a few months

depending on a lot of other influences like the complexity of the application architecture,

legacy data transfer, standardizing features and practices, training, etc. Another time

bound aspect is the customization of the software as demanded by the company which, in

some cases, could take even more than a year. The amount of time construction firms

want to invest and the agendas they want to pursue in implementation of the software

imposes considerable limitations of what kind of PM tools and architectural attributes

46

(like data storage and updating, backups, online restricted access, etc.) the application

may or may not have.

2.3.4 Control Areas and Utilization

Construction project planning, management, control and execution strategies typically

involve numerous processes, phases and activities. These differ largely by way of the

departments or people that initiate and / or execute them, the included / effected parties,

the phases and aspects of project they pertain to, and so on.

However, it cannot be assumed that all (or most) construction companies follow these

procedures in all their projects. Project activities and controls that are practiced vary from

company to company and also within companies based on the type of project, client

demand, contingent situations, area of operations, etc. Such protocols form a definitive

criterion for selection and / or customization on PM applications. An increase in the

number of functional capabilities or features that companies prefer their PM tools to

possess leads to higher costs and greater implementation time and also increases the

complexity of application architecture, thus forming a vicious cycle leading to demands

of continuous maintenance and upgrade.

It is imperative for a firm to not only decide what deliverables they desire form their

applications but also to strategize their project processes in synchronization with what the

application can and cannot do.

Table 2 (abridged) on the following page enlists some of the essential activities that

have been observed during a pilot study survey on PM practices by the School of

Business Administration, University of Quebec at Montreal, Canada.

47

The 70 PM Tools in Alphabetical Order Activity list Parametric estimating Baseline plan Pareto diagram Bid documents PM software for cost estimating Bid/seller evaluation PM software for monitoring of cost Bidders conferences PM software for monitoring of schedule Bottom-up estimating Software for multi-project scheduling/leveling Cause and effect diagram PM software for resource leveling Change request PM software for resource scheduling Client acceptance form PM software for simulation Communication plan PM software for task scheduling Configuration review Probabilistic duration estimate Contingency plans Product Breakdown Structure Control charts Progress report Cost/benefit analysis Project charter Critical chain method and analysis Project communication room Critical path method and analysis Project Web site Customer satisfaction surveys Quality function deployment Database for cost estimating Quality inspection Database of historical data Quality plan Database of lessons learned Ranking of risks Database of risks Re-baselining Database of contractual commitment Requirements analysis Decision tree Responsibility assignment matrix Earned value Risk management documents Feasibility study Scope statement Financial measurement tools Self directed work teams Gantt chart Stakeholders analysis Graphic presentation of risk information Statement of work Kick-off meeting Team building event Learning curve Team member performance appraisal Lesson learned/post-mortem Top-down estimating Life Cycle Cost (LCC") " Trend chart or S-Curve Milestone planning Value analysis Monte-Carlo analysis Work authorization Network diagram Work Breakdown Structure Besner, C. and Hobbs, B. (2004). “An Empirical Investigation of Project Management Practice: In reality, which

tools do practitioners use?” Proceedings of the 3rd PMI Research Conference, London, UK.

Table 2: Project Management Control Areas, Tools, Forms and Functions

48

Another far reaching influence that a company’s project-related activities have with

respect to PM tools is the amount of utilization of included features and the practical

significance that this feature deliverable has.

For example, most companies would choose generic features like task scheduling,

cost control and monitoring of progress as these are critical to effective project

management. A process or cash flow simulation tool, however, might not be favored by

many since it is not an integral part of contemporary project management practices. The

underlying drivers or company objectives thereby define the choices a company makes

regarding the PM tools and features it needs. The array of such features that different

companies opt for impacts the time, cost and training aspects of these applications

thereby influencing the selection criteria.

2.3.5 Investments and Returns

Purchase and use of PM applications, like any other enterpreneual activity, is targeted

towards making the company setup more efficient, involves major expenditures and

therefore qualifies as a business venture that should yield returns. This aspect forms one

of the most significant issues while selecting a PM application. Two major influences

effect this phase. One is the corporate concern, as mentioned in the previous section. This

characterizes the reason, at the very basic level, as to why such investment should be

made and whether or not these investments can be justified in light of objectives that the

enterprise seeks to achieve.

And the second is to assess the costs that shall be incurred and the amount of returns

this investment would yield. To assess the costs in such an endeavor is a complex task.

49

Though it is relatively easier to estimate the expenditures towards initial and recurring

expenses, hardware installations (if any), costs for training, allocations towards IT

division etc., it is quite difficult to quantify intangible costs like that of time lost during

implementation and user training. Being able to assess the costs of risks like data loss or

theft, downtime occurrences owing to network breakdowns and user errors is all the more

intricate.

In the midst of all this, it is arduous to determine at the outset if such an endeavor

shall produce anticipated returns or not, especially in the long run. One method that

companies adopt to assess returns is to scrutinize parallel industry precedents of the

application through the vendor’s client profiles. The other is to empirically determine the

share of returns owing to faster information cycle times, reduced overheads like meeting

allowances towards collaboration, and so on. A measure of how significantly this aspect

effects the investment decision can be made from the fact that Constructware, one of the

most widely used PM applications, in addition to its many PM modules, also has an ROI

(Return on Investment) analyzer which determines the percent return on any PM

applications that is being used. Autodesk, after its acquisition of Constructware,

announced that its ROI has peaked as high as 500%.

2.3.6 Priorities and Future Agendas

Major investment decisions towards better management practices are made not only

to improve existing systems but also to gain a competitive edge in the long run. This is

probably one of the reasons why large construction companies in the US seem to be more

inclined to use either their in-house PM applications or regular softwares that have been

50

customized to suit their business and operational systems. This customization may be of

two types:

• Contracting the vendor’s software development team to tweak the software in certain

areas that better suit your firm.

• Employing in-house IT departments to do the customization.

Another method that may be adopted at times is to buy commercially available

softwares that are specifically developed by vendors to communicate between two or

more given softwares. Such applications, understandably, have very limited use as they

do not have any functionality by themselves. They only aid data migration and obviate

data re-entry. Owing to this, these packages are known to be very expensive.

Another critical aspect of PM application selection from the business practices

perspective lies in the fact that once a firm decides on a particular software (or vendor), it

understands that they have to work in close consort with this firm over a period of time in

order to institute a continuous improvement process. This is primarily because it is the

vendor’s team that performs application administration. In other words, since an in-house

IT department does not have the legal rights to alter or modify copyrighted material, to

customize the application, its essential that the application users and vendors design team

work together to correlate what is desirable, what can and cannot be achieved and how to

achieve it.

Owing to this consideration, construction companies (by nature) are known to prefer

vendors that they have earlier employed and have some work history with. They are also

known to prefer vendors who are willing to allow some sort of a control structure for the

client within their firm. For example, a construction company might prefer a software

51

application provider if they have some stake in the providers firm. It is difficult to

definitively state what good this does or does not do or whether the entire application

provision would have worked with similar efficiency without the construction company

holding the vendor company’s stakes or not. It does however lend a sense of security for

the construction company and may create an environment of camaraderie that promotes

working together as a team.

Companies are also known to prefer vendors that provide other software applications

that the company may be using, since business ties already exist and a new system might

be procured with some concessions or extra features for an old ally.

2.4 DISCUSSION

As observed above, various processes and phases in construction project planning and

execution are being abundantly scrutinized and researched in order to cover all grey areas

that might capacitate better project planning, execution and delivery. Notwithstanding

these, the fact that such advanced protocols have not yet penetrated the industry is well

acknowledged.

Keeping the deliverables of this work in mind, these studies were conducted to

understand the genesis or reasons that necessitated the use of computing tools, their

ramifications, and how they have evolved and have been implemented over time.

Analysis of this information when combined with knowledge of applications that are

prevalent today as well as current industry practices will enable focusing on specific

areas having significant practical implications while attempting to enlist the functional

requirements of PM applications.

52

A generic review of project management applications and the desired features that

may be incorporated into existing tools is also necessitated because it is imperative, in the

midst of all of this research, to identify whether or not these shall be utilized and how the

industry feels about them.

53

CHAPTER 3 APPRAISAL OF PM APPLICATIONS

3.1 INTRODUCTION

In order to perceive whether or not advanced technologies and complex programming

constructs effect the deployment of PM applications in the industry and to understand

current PM demands, practices, priorities, available software resources as well as needs

for the future, it is necessary to observe and evaluate prevalent applications and toolsets.

It has been noted that top management demand that investments in PM tools and systems

be justified financially (Kwak, 2000). Consequently, it is best to have a balance between

the amount being invested and the advanced technologies desired to meet both ends.

However, an optimal solution such as this is unavailable and compromises have to be

made between the costs involved and tools acquired.

Nevertheless, purchase or upgrade of PM / CM applications involves much more than

simply the above mentioned. It is difficult to quantify the benefits achieved, especially in

large companies, and also to forecast the expenses to be incurred over time. An appraisal

of such applications was therefore taken up to allow greater insight into the following:

• Core qualities and functionalities of PM applications.

• Technological upgrades that are demanded by the patrons in order to increase

efficiency and convenience.

• Identification and interpretation of processes and areas of project management that

these upgrades enhance and how they may or may not be extended to other areas.

• Issues and barriers that effect such deployment, the underlying causes and concerns,

and analysis of how these barriers may be overcome.

54

Specific software applications that are either being extensively used by the industry or

have been exclusively developed by certain construction companies were therefore

selected for scrutiny. The review did not include extremely detailed aspects of the

softwares but attempted to focus on criteria that make them so popular or necessary.

3.1.1 Overview of Application Selection

Oftentimes, generic office management software applications, like Microsoft Axapta,

are confused with PM applications since they cover some vital features that most PM

applications have, for example, collaboration and logs. Another confounding area is ERP

(Enterprise-wide Resource Planning) solutions applications like Oracle’s JD Edwards

that also possess to a great degree most features that are required of PM applications.

Despite this, at least a few hundred applications are available commercially for PM

purposes. These softwares are distinct in the toolsets and capabilities they provide, costs,

and the segment of industry they address.

A trend that has also been observed in recent years is companies purchasing regular

off the shelf applications and then having their own IT departments or external agencies

tweak it to suit their individual needs. Better still, firms having the financial resources to

do so are known to contract major software vendors directly and have them customize

existing applications to which they have proprietary rights, and provide upgrades and

technical support as well.

It was therefore thought appropriate to cover all of these varying architectures than to

simply examine regular applications alone. This allows investigation of several facets and

approaches of PM applications, particular preferences, etc subsequently leading to easy

55

assignment of what is important and what is not so important. Five software applications

were studied towards this end, as listed below:

• Primavera Systems Inc. Expedition

• Constructware

• Computer Methods Int. Corp. Enterprise (Messer Construction Co.)

• Meridian Project Systems Inc. TurnerTalk

• AASHTO Site Manager and Trns•port

Of these, Expedition, Enterprise and Constructware are regular commercially

available PM / CM tools. TurnerTalk is a customized application, developed and

maintained by the vendors for Turner Construction Company. AASHTO’s (American

Association of State Highway and Transportation Officials) Trns•port is another such tool

but caters specifically to the transportation segment of the construction industry.

3.1.2 Methodology and Definition of Criteria

This review does not address the marketing aspect but has been strictly conducted

from a technical and implementation process perspective to assess current industry

inclinations. To achieve this end, certain criteria for the study were defined so as to

examine what made these tools popular or more efficient than their contemporaries,

including:

• Various costs associated with implementation of said applications

• Essential features, modules and sub-modules of the application

• Functioning and architecture of the application

• Problem areas and implementation aspects.

56

It must be mentioned here that no specific benchmarked methods has been used to

review these applications. The guiding logic was to find answers to certain queries that

would enable us to establish why companies are investing in such tools, what they desire

of it and how they go about achieving it.

3.2 TURNERTALK

TurnerTalk, the proprietary customized version of MPS Project Talk from the Prolog

Manager suite of applications, was established through collaboration between Meridian

Project Systems and the Turner Corporation in late 2002. This was a multi-year multi-

million dollar agreement. Around 2000, the Turner construction company developed a

charter to standardize its PM activities and delivery methods across all of its

approximately 40 offices across USA. They wanted a shift from their in-house MS

Access based IPMS (Integrated Project Management System) being used in some of their

offices along with quite a few other tools like Prolog Manager to one standardized,

sophisticated collaboration and management tool in order to align software application

usage for various CM purposes.

Similar to Project Talk, which they were using in several offices at the time,

TurnerTalk is also an online PM application tweaked to suit Turner’s requirements that is

deployed in an ASP (Application Service Provider) environment and was designed by

Meridian Project Systems. There are however a number of partners in this initiative

including AEC Management Solutions, the Cram Group and Qwest Communications. It

has most of the functionalities and features of Prolog Manager with the primary

advantage being that the application is not installed or run from the company’s own

57

servers. It is hosted through two Qwest data centers using highly secured 128 bit SSL

(Secure Sockets Layer) data transfer with Citrix RC5 encryption for added security, one

of which is located in Chicago.

Figure 10: Screen Shot of the TurnerTalk Dashboard

The core focus underlying use of this application was that most of the PM tools

would now be accessible over the internet to all licensed users. Turner also encouraged

liaising subcontractors and partners to avail these tools in order to affect an enterprise

wide PM information network. Various types of licenses are available for different

purposes on a per-user cost basis. Over a period of time, this application has evolved

greatly and its current version 7.5 includes quite a few feature-rich capabilities. The

essential modules of TurnerTalk have been graphically depicted in Figure 11.

58

Company Setup (For Jobsite)

Advanced Company Setup

Cost Period (Accounting)

DCR Crew Setup

Distribution Lists

Building Setup

Employee Setup

Expenditure Authorizations

Owner Funding Assignments

Lookup Groups Maintenance

Miscellaneous Links Portfolio Manager

Punch Lists Areas Maintenance

Schedule Tasks Contract Types Currency Codes

Metric Packages

Turner Custom Reports

Secure (Visible to Logon)

Cost

Engineering

Field

Miscellaneous

Purchasing

THE TURNERTALK DASHBOARD

PURCHASING COST ENGINEERING FIELD REPORTS TURNER APPS ADMIN

Addendum Setup

Contract Attachments

Buyout Items

Buyout Groups

Bid Packages

Applications For Payment

Budget

Budget Control

Change Order Request

Contract Invoices

Contracts

General Invoices

Potential Change Orders

Turner Change Orders

Revenue Codes

Subcontract Change Orders

Closeout Log

Conversation Log

Drawing Packages

Drawings and Specifications

Hotlist

Issues

Meeting Minutes

Requests For Information

Submittal Packages

Submittal Items

Submittal Transmittals

Transmittals and Correspondence

DCR Daily Details

Daily Construction Report

DCR Daily Events

Not Used

Inspections and Tests

Material Inventory

DCR Comply Notices

Punch Lists

DCR Safety Notices

ORM Reports

Closeout Matrix

IOR Administration

CMiC Queue Interface

GC Monitor

Figure 11: TurnerTalk Application Toolsets

59

In order to overcome minor irregularities during the implementation, for example,

lack of broadband connections in its jobsites, Turner planned a phased implementation

spanning close to 2 years to allow all of its setups to come up to the level.

It does not have any specific hardware or software requirements, takes very little time

to install (mostly the license purchase procedure and basic setup formalities) and does not

need any formal training in software use assuming that the user has basic awareness of

generic PM tools.

TurnerTalk empowers all parties in a construction project team to collaborate from

wherever they are located. The collaboration is entirely real-time which allows greater

visibility and thus provides all members of the project team with latest information. The

system also promotes cross functional communication between various internal Turner

departments. Since different parties have distinct restrictions on their licenses, it offers

greater control on information access.

Some of the salient features of TurnerTalk include the following:

• The fundamental strength of TurnerTalk lies in its flexibility, the software

requirements, its deployment and vast array of toolsets allow it to be quickly and

easily applied to different types and sizes of projects.

• Another unique advantage is the customizability, it can be tweaked to suit different

companies and business enterprises with little time, effort or investment.

• It is backed up with an excellent service network that allows continuous update of

data and round the clock monitoring of project information.

• It affords a centralized recommendation committee that has been especially

established so that all users can express their opinions in a common forum that meets

60

quarterly leading to further enhancement of its features and capabilities. Also, there is

also a 12 hours a day helpline that can be contacted by phone or internet for any help.

• Most of the key features found in other standalone PM software applications can be

found in TurnerTalk in addition to the advanced features inbuilt to manage projects

the Turner Way, like Potential Change Order Tracking and exhaustive cost

monitoring and cost control tools and logs.

• The Turner Corporation, through its internet based training initiative called Turner

University, conducts courses that train users on the use of various tools in

TurnerTalk.

• It has good integration features with most standard office solutions packages like

Microsoft products, Primavera P3 etc. and further integration with other products like

CMiC tools and Timberline estimating is said to be in the pipeline.

It is said that the most important thing for a construction company is to always have

the awareness that it is making money. TurnerTalk, with its suites of PM tools and the

core ideals of continuous improvement is empowered to achieve this. The only major

issue that this package faces is the risk of an internet breakdown which could render it

useless, but known instances of such occurrences are very few and have been overcome

quickly. Owing to phased deployment procedures, little or no downtime has been

experienced and continued training programs are offered by MPS to update all

professionals using it.

Unlike contrary beliefs regarding its usage, TurnerTalk is open for purchase and use

to firms and its partner firms like MPS and AEC management systems offer

61

customization and training services for all buyers at a price. A sample pricing chart for

TurnerTalk can be seen in Appendix I.

As mentioned earlier, it has a robust cost control module that allows real-time cost

management visibility and facilitates timely forecasting of project costs. It has inbuilt

tools to automatically update project budgets by tracking change order parameters and

also allows to foresee future changes by determining the cost impacts of potential change

orders.

Featuring advanced document management, reports and log generation capabilities as

can be seen in the module chart, it can prepare customized change requests, purchase

orders and the like. It facilitates logging and tracking of all specifications, submittals,

meeting minutes, and other project-related information. All of this information can be

sorted, filtered and grouped for preparing different types of reports on project progress. It

also provides a sophisticated site management tool for recording daily work progress,

crew information, inspections related information, safety logs etc.

The TurnerTalk official website claims that it has over 2500 users managing over $4

billion worth of projects all across the United States.

3.3 CONSTRUCTWARE

Constructware was developed by a mid-size privately held ASP called Emerging

Solutions Incorporated (later changed to Constructw@re) based in Alpharetta, Georgia as

an online project management tool in 1994. Probably the first of its kind, it provided

internet based collaborative solutions specifically for CM activities. This setup was

62

recently acquired by Autodesk for $46 million and there is news that it shall be integrated

with Autodesk owned premier web-based PM application, Buzzsaw.

One of the pioneers in web-based project management systems, Constructware

currently boasts more than 28000 licensed users and more than 50000 users through these

licenses including more than 20% of ENR top 400 general contractors executing projects

across USA and Canada worth over $6 billions. It has seen a 70% increase in its sales

over 2004 of which includes 250% growth owing to new clientele.

This is a web-server based application developed using Microsoft's Active Server

Pages technology and contains embedded SQL (Structured Query Language) statements

with its functional logic written in VBScript.

Figure 12: Screen Shot of the Constructware Dashboard

63

These statements communicate with the centralized database using ODBC (Open

Data Base Connectivity) to invoke the scripts and create web pages based on the

information recalled by the user depending upon user license restrictions and availability

of information. It runs on a 32-bit Windows NT 4.0 Server with Internet Information

Server (IIS) 4.0.

With close to 100 modules under 12 heads, it includes most functions and capabilities

that enable tasks for various types, scales and delivery methods encountered in CM. Like

all other web based systems, this is also controlled, administered and maintained through

a centralized database. Access to the users is restricted on the basis of user license types

and is allocated by the administrators.

The key to Constructwares success has also been an institutionalized continuous

improvement process. Its recent development inclusions comprise a cost control tool and

a design collaboration module. The cost control tools enables monitoring and comparison

of several budget control aspects, changes and associated costs. It is also capable of

generating various finance related documents like invoices, purchase orders, RFQs etc.

The design collaboration module was added in order to enhance its initial toolset

designed specifically for construction companies, subcontractors and owners which

allows greater collaboration with designers and architects. It has an array of tools that

archive, recall and permit easy access for various drawings and are also capable of

tracking and recording design alteration data.

Its most exhaustive functionality lies in the document management module. All

documents that are entered, altered or updated are automatically time stamped to allow

64

easy tracking of changes and allow easy tracking of RFIs, submittals, drawings,

documents, emails, logs, transmittals, punch lists and meeting minutes.

Attachments

Design Review

Daily Reports

Custom Forms

ASIs

Distribution

Documents

Drawing Logs

Meetings

Owners

Punch Lists

RFIs

Submittals

Transmittals

Correspondence

Employee Info

Confidential Info

Benefits

Wages

Dependents

Education

Evaluation

Attendance Batch Updates Assign Companies

Today

Messaging Inbox

THE CONSTRUCTWARE EXECUTIVE DASHBOARD

Messaging Outbox

Task List

Notices

Call Log

User Info

Dashboard

Documents Sent

Emails

Approves Documents

Project Details

Competition

Project Proposal

PreBid Checklist

Project Summary

Bid Packages

Bid Invitations

Bid CSI Codes

Call Sheets

Split Call Sheets

Sub Bid Templates

Subcontractor Bids

Reports

Outstanding Events

Project Details

Project Calendar

Project Team Contract / Bond

Project Defaults

Phones

Project CSI Codes

Discussion Forum

Web Cam

PERSONAL ORGANIZER

RTINGREPO

BUSINESS DEVELOPEMENT

BID MANAGEMENT

COST MANAGEMENT

PROJECT INFORMATION

DOCUMENT MANAGEMENT

HUMAN URCES RESO

DESIGN DEVELOPMENT

RISK MANAGEMENT

PROJECT WEBSITE

MAINTAINENECE and HELP

Budget Owner RFP

Cost Events Invoices

SOV SetupCost Items

PayAppsRFQs

RCOs Bonds

OCOs Insurance

Insurance DefaultsSubcontracts

Addl Insured DefaultsSCOs

POs Markup Formulas

POCOs Sub Change Request

Figure 13: Constructware Application Toolsets

65

In addition to those shown, it also includes modules for risk management,

subcontractors, a project web site and a maintenance module.

The concept of an executive dashboard was probably started by Constructware. This

allows project executives to focus on issues that need immediate attention (much like

primavera expedition) like pending RFIs, PCOs and submittals etc. that could have a cost

impact on the project.

It also provides a tiered visualization of sensitive information on an enterprise wide

basis for multiple projects. In addition to this, there is a personal organizer that is setup

uniquely for every user and allows the user to maintain records, memos, meeting minutes,

personal information, appointments and so on.

The Project Information module allows users to record detailed information for

monitoring of projects. It also contains relevant information pertaining to the project

primaries, contractual agreements and company codes for the project as well as a project

schedule. One unique capability is the Web Cam module that allows executives to view

the job site in real time and also maintains logs of status and previous images.

Another feature that makes Constructware versatile is the inbuilt toolset for generic

office management that obviates the need for installing other applications. This module

facilitates maintaining records of various sales and purchases, business documentations,

bid details, rosters and payrolls etc.

The centralized database communication allows access to project information from

any computer that is connected to the internet. The exchange of data using XML

(Extensible Markup Language) enhances integration of multiple project information and

66

provides better control by automating the generic PM activities like RFIs, change orders

and transmittals.

Another advantage that is offered by Constructware is the reduced legal liability that

is afforded by delegating accountability. Since all records are maintained in a single

location that has advanced search capabilities, discovery costs are greatly reduced.

Despite these, there are certain known drawbacks that have been acknowledged by

the industry. Since the data setup is administered through a centralized location,

individual users are not allowed to allocate specific attributes to various documents in

order to restrict unauthorized access or editing. It is however allowed for certain

categories. Therefore if an attribute is to be assigned to a certain document, it has to be

done to all the documents in that category. This could sometimes result in users not

circulating the documents they would like to since they cannot protect it from violations.

There are also reported issues regarding the incapability of Constructware to inter-

operate with more generic PM applications like P3 and MS Project. It is also believed

that Constructware is not designed to the details that it should be to enable efficient

construction management and that it does not fully accommodate all the areas that a

construction management process needs. These forces maintaining paper documents

which cannot be done partially since it would be very tedious to have some data on paper

and the rest in digital format.

Nonetheless, the increasing popularity and market share that Constructware enjoys is

a significant indicator that its benefits outweigh any minor issues that have not yet been

addressed.

67

3.4 PRIMAVERA EXPEDITION

Expedition was developed as a project and portfolio management software

application by Pennsylvania based Primavera Systems, Inc. Established in 1983, they are

probably the pioneers in providing software applications for project management

solutions worldwide. With over 20 years of experience in this field and various

applications designed by Primavera like P3 (Primavera Project Planner), Suretrak,

Enterprise and Expedition being used world-wide in most industrial sectors, they are also

the most reliable PM application providers.

Expedition, currently in its 10.X version was developed both with a single machine

standalone and a server-based local client configuration. In order to improve its

performance and probably to keep up with increasing competition, it is available in server

based distributed client as well as web-based (separate) servers with distributed clients. In

summary, it is available in all the four forms possible and can therefore cater to the needs

of a variety of clientele ranging from large corporates to small businesses.

Understandably, the pricing, functional and implementation aspects for different

architectures shall be different.

One of the reasons behind the huge market share that Primavera tools like Expedition

enjoy could be in the fact that they are not designed as industry specific applications and

have a generic applicability. Another good reason is that their PM applications are

designed to automatically inter-operate with all of the other segments of applications they

provide, like Suretrak and P3 schedulers (which are widely used) and also generic office

solutions tools like Microsoft and Adobe Products.

68

Figure 14: Screen Shot of Primavera Expedition Dashboard

Primavera official website claims that over $5 trillion worth of projects have been

managed using their tools, so much that they actually have a calculator

(http://www.primavera.com/about/trillion.asp) that gives the real time figure as this

amount increases. And this value increases at close to $1000 per second.

The core architecture of all of the configurations mentioned above is quite the same.

Version 10.0 of Expedition Professional Edition is based on an Oracle or Sybase database

server, an integrated Tomcat web server, a JBoss application server with an Expedition

Administration and Application package. Both the servers have to be installed in one

machine since they run in the same JVM (Java Virtual machine). Primavera itself

69

http://www.primavera.com/about/trillion.asp

recommends the separate servers with distributed client configuration as the most

optimum solution amongst the four options, primarily from the cost efficiency, speed and

system administration perspective. Communication with other systems is established

using an HTTP (default) or HTTPS protocol. The HTTPS protocol may be enabled if the

communications being made between the server and the client machine needs to be

encrypted for added security. The package does not include an inbuilt firewall and leaves

it on the client to make the choice.

Hardware requirements vary with the configuration and depend upon the needs and

budget of the client. Since the “separate servers with distributed clients” is by far the

most advanced configuration, its requirements are the highest. However, these shall also

depend on how many clients use the application and the number of projects being

managed concurrently. The installation and setup is not complicated but definitely needs

basic skill levels of a network administrator.

Expedition comprises PM tools that cater to the needs of most generic projects as

seen below but does not have as advanced capabilities as seen in other web based

customized PM applications. Though it may be customized at very basic levels (to some

extent) in order to suit individual businesses, extra features cannot be designed into it.

However, interoperability with other tools fills this gap to some extent.

Custom profiles (called role-based project control setup) can be developed for all

project members and the type of profile the member has defines the nature and extent of

access he or she has to project information. This allows added visibility with necessary

security restrictions. Systematized Action lists and turnaround graphs help various parties

identify areas that immediately need attention and might hold up project progress.

70

Safety

Telephone Records

THE EXPEDITION DASHBOARD

PROJECT INFORMATION

CONTRACT INFORMATION

CO

LOMMUNICATION GS

It also features an automated report generating facility using Sybase Infomaker that

enables all contract information like submittals, change orders, financial data, etc. to be

compiled into a summary report at various points of project execution. All these

documents are stored in one location which obviates the need to search for information.

It also features an automated report generating facility using Sybase Infomaker that

enables all contract information like submittals, change orders, financial data, etc. to be

compiled into a summary report at various points of project execution. All these

documents are stored in one location which obviates the need to search for information.

Another aspect that allows readily available access to project data is Expedition’s

ability to import data to MS Excel worksheets. Such information may be filtered and

sorted as the user desires and a report can be generated using an excel log format. This

facility also enables tracking of project costs, proposals and bids down to the base level.

Another aspect that allows readily available access to project data is Expedition’s

ability to import data to MS Excel worksheets. Such information may be filtered and

sorted as the user desires and a report can be generated using an excel log format. This

facility also enables tracking of project costs, proposals and bids down to the base level.

Schedules

Contracts

Issues

Cost Worksheet

Contracts - Budgeted

Contracts - Committed

Purchase Orders

RFP

Payment Requisitions

Change Management

Proposals

Change Orders / CIR

Drawing SetsTransmittals

Request For Information Drawings

Non Compliance Notices Submittal Packages

Work Change Directives Submittals

Letters Materials

Correspondence Sent Daily Reports

Correspondence Received Insurance

Meeting Minutes Punch Lists

Notepads

Figure 15: Primavera Expedition Application Features

71

Integration options with other cost accounting and office management applications offer

easy cross-functional data exchange like scheduling, finance and so on.

Besides these, Expedition offers all the other general advantages that are

characteristic of web-based PM applications like centralized information database,

tracking and monitoring of project progress, contract information, change orders, RFIs,

cost monitoring and control, generic collaboration tools, office organizers etc.

Directly available through Primavera, it also features a round the clock technical

support team. Routine maintenance and upgrades are available for little or no cost

depending on the type of maintenance contract for its users. Primavera also provides

several modular training courses for the industry and on-site training for client firms at a

fee.

3.5 AASHTO TRNS•PORT

AASHTO (American Association of State Highway and Transportation Officials), a

non-profit organization representing members of the highway and transportation

departments of the 50 united states, the District of Columbia and Puerto Rico developed

the Cooperative Computer Software Development Program (also called AASHTO Joint

Development Program) through an administrative resolution for two primary reasons.

First among these was that as opposed to purchase of a software product from a vendor, if

they were to develop and regulate their own tool, it would lead to significant savings

through the lifecycle of the application. They would also benefit from economies of

scale. The second aspect was the attempt to benchmark and to standardize various

72

processes revolving around relevant best-practices involved in the design, construction

and maintenance of highways and bridges through such universal tool.

Figure 16: AASHTOs Trns•port Application Modules

Courtesy: www.aashtoware.org

For this purpose, AASHTO contracted InfoTech, a Florida based software design

firm to develop a comprehensive suite of software applications, together called Trns•port.

Trns•port, as compared to its contemporaries, is unique is many ways. The foremost is

that even though the entire transport suite comprises 14 distinct components, all these its

tools can be purchased and used individually based on the clients needs. It is not

mandatory to but the complete suite.

Owing to this, the software architecture, hardware requirements and functionality of

these components vary. There are different types of client server, database server and

application server configurations for different toolsets. The functioning also varies

depending upon the type of configuration the user desires and there are options ranging

73

from standalone to client server to web server architectures. The hardware and software

environments are, however, standard and require Microsoft, Oracle, IBM and other

universal softwares and database applications.

BAMS/DSS, CES, PES, LAS, CAS, Field Manager Suite, Site Manager, SitePad and

SiteXchange are client server modules. BAMS/DSS, for example, uses at least MS

Windows 2000 with SAS/ACC-ODBC, SAS/CONNECT, SAS/GRAPH, SAS/STAT

versions 9.1.3 software environments for its application server. For its database server,

one can choose form an array of DB2, MySQL, Oracle or Sybase server applications with

specified configurations. SiteXchange, Expedite and Estimator modules can run on PCs

and SitePad can run oh handheld PCs. FieldManager and its sub-modules can operate in

standalone, client server or web server environments. The software contractor Infotech

does assist in this process and aid transfer of existing project data into the newly

configured servers. In case the process is complex, they also offer a preliminary study to

center upon various modifications, conversions and data migration issues that might be

necessary and present a proposal including forecasted plans, costs and schedules.

Though all of this adds more complexity in the application selection decision-making,

the effort to develop these modules using three-tiered architecture was undertaken in

order to increase the scalability of this application. It is this configuration that enables it

to support a wide array of users from small companies using single machines to large

companies with operations spread in various geographical locations.

The one major consideration that arises with these advanced scalability issues is the

cost of these tools. At close to $300,000 for the entire suite per year per license per

person, this application does seem to be quite expensive. Another major consideration is

74

that it has specifically been designed for managing transportation projects and its utility

in managing other kinds of capital construction projects does not have industry

precedents so far. Some of the features of various Trns•port modules are as follows.

CAS, or the Construction Administration System, is the main knowledge

management database for contract information. This module contains records pertaining

to funds allocation, approvals, contractor payments, change orders, status reports, etc.

Intranet was introduced into the Trns•port suite especially for client/server versions of

various Trns•port modules. This obviates the need for a special client application and

allows various web-based functions by facilitating access of Trns•port on the web.

The Trns•port BAMS decision support is a relational database that contains historical

data towards to aid decision making in contractual issues. This feature was not provided

to non-member organizations initially but a reduced version (called the standard analysis

version) was later developed to cater to non-members demands. Some of the specific

information it provides includes (source: www.aashtoware.org):

• Cost Data Book • Item Rank Analysis

• Combine Bid History Files • Line Item Profiles

• Contract Profiles • Price Estimation Methods

• Cost Variance Profile • Item Price Analysis

• Historical Item Price Regression • Quantity Variance Analysis

• Historical Statistics • Contract Selection

• Cost Data Book • Item Rank Analysis

Table 3: AASHTO Trns•port BAMS Information Features

75

http://www.aashtoware.org/

Trns•port’s Cost Estimation System (CES) provides parametric estimates ranging

from conceptual to final estimates for award of the contract. It is inter-operable with other

modules of Trns•port and includes standard cost groups for estimation existing labor,

equipment, material, and crew data. It allows sorting and migration of data sets so that

estimators may split and combine estimates as demanded.

The Field Manager suite combines sub-modules like fieldbook, fieldbuilder and

fieldpad and forms the core construction management component of Trns•port. It

contains systems for managing, tracking and documenting construction progress, real-

time updating of contract information and sharing of data, managing contractors as well

as recording on-site construction information regarding site conditions, various work

items, materials, etc. The field pad module allows managers and inspectors to record such

information using a hand-held device while maintaining the security and functionality of

Fieldbook.

The Site Manager module addresses recording information pertaining to personnel,

daily reports, permits, correspondence, disputes and claims, meeting minutes, checklists,

etc. It has sub-modules inclusive of contract records, administration and payments. The

materials management tools contains comprehensive lists for reference and validation of

information regarding materials, testing and qualifications, approvals, suppliers and

equipments.

The PES (Proposal and Estimates system) aids management of the pre-letting phase

of construction. This module enables the user to use an interactive online system to enter

project data and prepare standard reports like detailed estimates, proposal estimates and

76

proposals towards a bid package. It also includes a client-server configuration that allows

data entry into spreadsheets with automated data retrieval from design systems.

The LAS or Letting and Awards system aids management personnel in advertising

and tracking proposals, processing bid information and making award decisions. It

functions in consort with Trns•port Expedite to process the incoming information and

provides notice to contractors, bid tabulation and bid summary reports.

The Expedite module was expressly developed to work together with the PES and

LAS and allows qualified bidders to obtain proposal information and documentation in

electronic format, enter data towards the said proposal and then submit it electronically,

wherein it may be read by the PES and LAS modules for further processing.

Almost all of the modules of Trns•port are constantly being improved, upgraded and

tested as can be observed through their different versions. AASHTO provides phased

reports with respect to such enhancements and their functionality and other issues

(though they are not accessible to the public). NY State DOT is said to have successfully

implemented some of these modules towards project lifecycle analysis and management

though additional information is unavailable. AASHTO uses its own website called

Cloverleaf to provide up-to-date information, product testing, releases and support

contracts, pricing charts, hardware and software requirements, etc pertaining to Trns•port

and its AASHTOware software products. Information about implementation of this tool

in the construction industry is unavailable. These and other related issues shall be

addressed in the discussion section.

77

3.6 CMiC ENTERPRISE AND PROJECT MANAGEMENT

CMiC (Computer Methods International Corporation) is a Canada based software

solutions provider and has been in business for more than 30 years now. Its products cater

to the integrated project and enterprise management segment of the software

development community and are aimed primarily at construction or construction

affiliated business management.

The firm started making news in the USA with the Cincinnati based Messer

Construction Company and Manhattan based Hunter Roberts Construction Group opting

for its enterprise management packages sometime in late 2004. However, the fact that the

company claims to own 25% of all the at-risk construction per ENR’s top 100 list

establishes its credibility in the US construction industry.

CMiC’s product line includes three main packages, namely Project Management,

Enterprise and Integration. All three are interoperable and may be purchased as a package

or individually. Nonetheless, they are continually upgrading these applications in order to

provide better tools. In the Technology for Construction executive forum in Las Vegas in

January 2006, CMiC featured three unique advanced technologies in their products. “Self

Service”, a toolset from the Enterprise suite allows the client to customize its views and

panes tailored to their particular requirement for information all by themselves.

Dashboard was another featured tool which displays pooled company or project data. IO

capacitates mobile collaboration by letting users transmit emails into the central project

database from any e-mail enabled mobile hand-held or pocket device.

The Messer Construction Company, after its successful completion of $393 million

worth of projects in 2002 (The Enquirer, 01/2003) and anticipating further growth, was

78

looking to streamline its operations and management practices in several offices and job

sites by implementing a holistic application instead of various distinct applications that

were being used at that time. They selected CMiC’s Enterprise and Project Management

applications with the purview of enabling internet based access and personalized toolsets

towards better project management of complex projects from and at different

geographical locations. Moreover, CMiC’s application was found to be capable of fully

integrating with their existing accounting system. This enabled greater control over their

holistic budget and change items and reduced manual data entry. As compared to MPS

ProjectTalk and JD Edwards, this was found to be a cheaper solution in their case and

also less cumbersome to implement. It also addressed their organizational management

concerns in addition to core project management through effective integration between

the two modules. The complete setup was spread over a one year selection phase

followed by 3 months of planning and 8 months of complete data migration from legacy

systems. The new application was tested on 5 pilot projects for a period of one year

before completely integrating it over the entire enterprise. The various modules present in

this application are shown on the following page.

Enterprise is designed to support varying cross functional aspects of an organization

as well as different kinds of businesses. Its Financial Management module handles both

internal and external transactions. It is capable of making automated recurring payments,

auditing, performing statistical analyses and comparisons and integrates with all billing

systems over the organization. It also manager vendor payments and balances, maintains

historical data and can generate periodic financial reports.

79

The Projects module handles all the costing, billing, invoicing, tracking, estimating

and cost control aspects of projects. It is the main subcontractor and change order

management tool and records all contracts, bids, revenues and agreements. It enables

running cross-company project related queries regarding work-in-progress, payments,

percent complete, etc. and generates custom reports.

Figure 17: CMiC Project Management and Enterprise Application Toolsets

Cost and Budget Management

Bid and Procurement

Document Management

Site Management

Collaboration Manager

THE CMiC INTEGRATED TOOLSET

PROJECT MANAGEMENT ENTERPRISE

General Ledger

Fixed Assets

Accounts

Accounts Payable

FINANCIALS

PROJECTS

HUMAN CAPITAL

ASSETS

CRM

Time and Expense

Self Services

Human Resource

Payroll

Procurement Management

Preventive Maintenance

Equipment Costing

Inventory Management

Service

Marketing

Subcontractor Qualification

Proposal Generation

Sales Force Automation

Costing and Billing

Change Management

Subcontractor Management

80

The Human Capital module maintains all employee information, payrolls and

personnel management aspects of the company. It primarily handles and tracks all of the

financial and employment information pertaining to employees. The assets module caters

to the procurement records of the company or project. It also maintains the inventory

records with real-time updating of information and is also the main equipment

management component.

CRM is the customer relations toolset that tracks and records various marketing and

sales activities. It creates, approves and generally maintains vendor information, creates

project reports and proposals and handles generic contract management and resource

planning. It also manages the bid processes, performance management, document

management and forecasting areas of projects as well as the organizations other efforts.

In addition to Enterprise, Messer also implemented Project Management application

that additionally manages all information pertaining to their projects. All aspects of the

project costing, site management, collaboration, documentation, bids, contracts etc. are

handled by this application. It can detect project anomalies and highlight them by

recording and tracking various bid packages, establishing compliances at the vendor,

subcontractor or invoice levels and monitor various bonds, insurances, liens and special

contractual agreements.

At close to $200,000 or higher (depending upon the modules purchased and the

number of users), Enterprise features an Oracle based application server with an open-

standard relational database architecture. This allows configuration of the entire system

depending upon the clients needs, be it standalone or distributed client and is globally

accessible through networks. It also allows development of customized extensions to

81

CMiC applications to gel with the clients requirements. It supports common network

protocols like TCP/IP, ISDN and Microsoft NT server as well as most operating systems

barring Apple Macintosh which add to its compatibility and customization capabilities.

CMiC provides all clients with installation and training services. There are various

choices available for the client to choose from depending upon his needs and budget.

Training from CMiC, however is necessary as they practice the T3 (train the trainer)

policy. It may be on-site or at the clients location. Their preference of this practice can

probably be attributed to the fact that it brings into direct interaction the designers and

end-users, thus making the training and feedback process simultaneous. Consultation

services are also provided at a fee in addition to the regular web-based or telephonic

technical help.

3.7 DISCUSSION

The primary objective underlying this phase of the study is threefold. The foremost is

to understand the features or toolsets and architectural functioning of these applications

that allow us to identify relevant queries while developing the questionnaire for further

investigation. The second is to analyze various business related aspects of these

applications that influence the selection of PM applications in a given case. The third

objective was to develop an insight into how various aspects of the software application

from the software vendors and designers disposition affect the tool selection criteria.

Some of the general observations that have been made in this phase are as follows:

PM software applications, irrespective of the architecture or purpose that they are

designed for, are for most part extremely sophisticated databases with elaborate front-end

82

tools. Most tools do not have any data processing capabilities beyond regular arithmetic

programming like adding, multiplying and so on.

A study of the deployment of some of these tools in the industry makes it evident that

the reputation of delivering and having precedents of implementation and returns on

investment by similar companies contribute largely towards the application selection

criteria.

Applications that are relatively generic with lesser features as compared to large

customizable tools are favored by the smaller companies. The foremost reason can safely

be attributed to limited budgets. Another reason behind this could be that these

applications are capable enough to fulfill most requirements demanded by their clients.

What these cannot achieve can be done by using in-house software departments or

hundreds of small software vendors who create packages to add inter-operability between

softwares.

Marketing strategies and business development practices employed by software

vendors seems to play a decisive role in the considerations towards such selection. These

range from maintaining fancy websites and providing high quality technical support to

being very participative in industry activities.

The lack of processing power of these tools and the recent upgrades that have been or

are being done is indicative of the industry’s inclination towards more convenient tools.

None of these software applications seem to be adding advanced scientific protocols like

optimization or simulation capabilities. An underlying cause for this could be that these

tools are designed for versatility and it is quite difficult to program algorithms that would

suit a wide array of projects or company practices.

83

84

Even though all of these applications are networked databases and applications, none

of the applications interact with external databases, as proposed by FIATECH, for any

reason (like regulatory compliances or vendor lists). One reason could be that there is

very limited knowledge of such databases that are regulated by authorized agencies. Also,

security concerns associated with establishing communication with external sources of

data might be barring such initiatives.

In cases of process improvement measures within an enterprise, it is the company’s

corporate concerns that dictate the investments. Likewise, in decisions pertaining to the

financial corpus that should be dispensed towards IT and software applications, the

business needs and goals of the company seem to be the primary movers. Other factors

follow and may or may not be related to such business targets.

The table in the following page presents some generic information pertaining to these

software applications. The “number of modules” refers to the core functional areas, for

example “Contracts”, “Meeting Minutes”, etc. Number of Toolsets measures the total

number of features available under all these modules.

Cited price ranges are quite tentative since the pricing of these tools varies with the

number of licensed users (one user per machine), concurrent users (multiple users per

license, one at a time access or concurrent access over the internet), size of the projects,

architecture of the system, installation, customization, training, services and maintenance

facilities availed. The prices indicated are based on a mid-size company (around 30

users), mid-sized project volume (approx 150 million dollars) with regular installation

service charges and licenses for one year.

Interoperability / Offered Lacking Offered Offered Information Unavailable

12

85

APPLICATIONS

FEATURES TURNER and MPS

TURNERTALK AUTODESK

CONSTRUCTWARE PRIMAVERA EXPEDITION

CMiC ENTERPRISE and PROJECT MANAGEMENT AASHTO TRANSPORT

Number of Modules* 7 12 4 10

Number of Tools* 60 (approx) 100 (approx.) 30 (approx) 60 (approx) Over 100 (approx)

Price Range $ 150,000 + Services ((midsize approx. avg.)

$ 30,000 + Services (midsize approx. avg.)

$ 30,000 + Services (midsize approx. avg.)

$200, 000 + Services (midsize approx. avg.)

$200,000 + Services (midsize approx. avg.)

Relative Order Higher Order Higher Order Middle Order Higher Order Higher Order

Ownership Multiple Partners Single Single Single Multiple Partners

Applicability by Industry**

• Construction Specific • Large – Midsize General Contracting Companies • Most Parties and Capital Projects

• Construction Specific • Large – Small General Contracting and PM Companies • Most Parties and Projects

• Most midsize – small Industries • Most Parties and Projects • Primarily Contract Management and Project Controls

• Most Industries • Large – Midsize Companies • Most Parties and Projects • Both ERP and project management

• Large – Midsize Companies • Transportation Centric • Most Parties and Projects

Market Capture • Over 2500 Users (2004).

• Approx 50 % of all User Firms (2002) • Over 28000 Users (2005).

• Approx 14% (2003) • Over 100,000 User Licenses

• 25% of all at risk construction based on ENR's top 100 list

Information Unavailable

Market Capture by Project Volume > $4 Billion (2004) > $6 Billion (2004) > $5 Trillion Order of billions Information Unavailable

Top Establishments as Clients

• Turner Corporation and Affiliates

• Bovis Lend Lease Inc. Heery International • Vanir CM •

• California DOT • Indiana DOA

• Black and Veatch Haliburton/KBR • Parsons •

• Caterpillar • SC DOT

• Messer Construction Co. DeSilva Gates • Construction Hunter Robert• s • Macomber Builders • Summit Builders

• NYS DOT • State DOTs and Federal Transportation Agencies across US and Canada.

Customization * Th is based on the versions of these applications studied and later versions might have additional modules or toolsets.

t state that it is not feasible beyond those mentioned. is information

** This section observes the core areas by function, size and project volume for which the said tools is most feasible. It does no This tabulated information is meant to provide a relative comparison of these tools with each other and is based on approximations. This information is not absolute.

Table 4: Relative Comparison of Various Aspects of PM applications affecting Selection Criteria

The data tabulated above has been formulated on the basis of individual pricing

information available for various categories and services in the application websites.

Costs to companies might vary greatly depending upon their individual needs.

Furthermore, all pricing is subject to negotiation and concessions are also available to

qualified buyers.

Order refers to the magnitude of detailed features that these applications possess. For

example, CMiC’s Enterprise + Project Management and TurnerTalk are very high-end

solutions with much more capabilities as compared to Expedition.

Ownerships refer to the type of proprietorship pertaining to these applications, as in

whether they are owned and operated by a single party, like Autodesk or multiple parties,

like TurnerTalk.

The information provided above allows a quick preview of some of the core aspects

of these applications that affect their prices and purchase and are based upon news

articles and other information available from company sites or other internet resources.

The various lessons learned through the review of these applications and analysis of

various cause and effect scenarios have been used to guide the questionnaire. Some of

these observations have been discussed further after the data obtained from the survey

was analyzed for studying descriptive statistics.

86

CHAPTER 4 IT DIAGNOSTIC AND DESCRIPTIVE STATISTICS

4.1 SURVEY INSTRUMENT DESIGN CONSIDERATIONS

One of the aims of the studies conducted until this stage was to develop an insight

into the entire PM IT and applications system that would enable the design of a fitting

questionnaire. The questionnaire itself was designed in order to quantitatively assess

some of the primary influences on such systems and then analyze these influences. An

attempt has also been made to collect information that could help us describe some

generic trends with the CM IT area.

The first step in developing a survey instrument that aims to quantitatively analyze

certain factors or study some cause and effects or preferences is to design the experiment

strategically so that the data obtained can be easily analyzed using standard statistical

methods to make necessary inferences. This aspect defines how and what kind of the

critical questions shall be asked has been explained in detail in the following sections.

However, there are many more components like costs, time, methods, etc, which have

to be taken into consideration keeping the ultimate goal (the number of responses) in

mind before it is sent out to the respondents. These have been explained in the following

sections.

4.1.1 Form and Dissemination

Surveys may be conducted using regular paper-based formats, template forms, and

personal interviews and / or may be designed online. The key determinant here is

87

twofold. The first is the ease involved in responding to the survey and the second is the

ease in survey dissemination, collection and compilation of data.

DEFINING THE NEEDS AND AIMS OF THE QUESTIONNAIRE

FORMULATION OF STATISTICAL DATA ANALYSIS STRATEGY

CHARTING LAYOUT OF THE SURVEY, LOGICAL SECTIONS,

QUESTIONS, SCALES AND WORDS

DECIDING HOW THE SURVEY SHALL BE DISSEMINATED and NECESSARY INFORMATION

SELECTION OF SERVICE PROVIDER

ONLINE DESIGN OF SURVEY

QUESTIONNAIRE

DISSEMINATION

DESIGN and REVISION OF THE

PRELIMINARY QUESTIONNAIRE

SELECTION OF RESPONDENTS and

AVAILABLE INFORMATION

REVISION FOR GAUGING SURVEY PAREMETERS LIKE LENGTH, TIME ETC

SELECTION OF APT FORM OF

SURVEY

PAPER BASED

TEMPLATE

ONLINE

Figure 18: Questionnaire Design Methodology

88

In case of paper based methods, the questionnaire is printed out and sent by mail to

the appropriate respondent. He / she then fills it out and mails it back in a pre-stamped,

preaddressed envelope that has been provided with the questionnaire. This is the easiest

method from the designer’s perspective. However, it is relatively cumbersome for the

participant and the designer needs to have the participant’s complete mailing address.

Costs are also criteria here. Since the questionnaire was quite lengthy, it was thought best

to not choose this method as it be too rigorous and elicit few responses.

For the template design, a form bearing the survey questions is designed with the

standard text boxes, radio buttons and check boxes. These allow the respondent to answer

queries by typing using the keyboard and mouse-clicking on answer options. This is

relatively easier as only the email ID of prospective participants is needed and no writing

or mailing is involved. It is also easier to answer for the respondent. The form is

circulated through email as an attachment. Upon receipt, the participant downloads the

form file onto his computer, fills it and clicks on a “submit” button provided. If

connected to the internet, the designer receives the responses (not the form) immediately

and then has to make sense of them and enter the data into a worksheet. This method was

also considered but was decided against later. A sample of this form can be found in

Appendix H.

Online surveys are by far the easiest form of conducting a survey. Here, a survey is

designed using one of the many software packages for this purpose downloadable from

the internet for little or no money. They may also be designed using internet

programming languages like HTML, Java, JSP (Java Server Pages) and so on. The design

and data export features are mostly inbuilt using applets in websites that host such

89

surveys for a fee. Disseminated through emails, the participant is provided with a link

that he clicks to enter the survey, fills it out and simply exits the program. The responses

are stored in the host’s server and can be accessed by the designer at any time. There are

automated features that allow exporting the responses into standard worksheets like

Excel.

This form was chosen for two primary reasons. Ease of use to the participant, which

would ultimately yield more responses, as well as ease in dissemination and data

collection. In this case however, the data export feature was not used since the export

format was found to be too rigorous for properly arranging and deciphering the data. The

entire survey can be perused in Appendix A. A complete preview of all the web pages of

the online questionnaire can be found in Appendix B.

4.1.2 Logical Sections and Phraseology

Once the form of the survey has been decided, it is important to determine which

questions to ask, how to phrase the questions and divide them into logical sections. The

most critical task is to keep the respondent interested and the only way this can be

achieved is through an interesting design. If at any occasion the participant loses interest

or has to strain his / her mental faculties, they might decide to quit, or worse, give inexact

responses.

The wording of the questions is also a very important aspect. The questions should

not be too wordy and express what they want by using simple vocabulary and technical

terms in as less words as necessary. They should not produce any kind of bias effect

wherein the respondent is implicitly goaded to select a particular response. The options

90

and words used should be explicit and clear with no grounds for ambiguity. Any rating or

ranking schemes that are being used should be clearly defined for the respondent and not

left to individual participant’s discretion.

It is also crucial that the questions be divided into coherent logical sections. This

makes it easier on the respondent to comprehend the question as well as to select the

appropriate response. Keeping the transitions between the questions and the sections

smooth results in increasing enthusiasm in the participant and they are more likely to

complete the survey with accurate responses.

The questionnaire for this study was divided into the following four logical sections:

• Personal Information

• General Information

• Project Management Work Environment

• Project Management Applications

The personal information section contains questions about the company that the

participant works for and his position in the firm. Since the responses would be fruitless

without this, these were designed such that they could not be omitted. Other questions

contained in this section were generic and included to build user interest. A deliberate

attempt was made to include as less personal information queries as possible in order to

qualify expedited approval by the review board and not be too impersonal as well.

The general information section includes questions pertaining to the respondent and

his firm. Once again, some queries were conducted to develop further interest and also to

establish major and minor trends in the CM IT industry.

91

The third section outlines the start of the critical queries that were primal to the

formulation of the decision matrix. Addressed areas here included the participant’s

opinion on various PM functions like collaboration and communication, PM IT training

and deployment issues and generic information about their existing project management

application setup. The last question in this section pertains to corporate concerns that

define the many criteria related to PM applications initiative in his company and the

importance that the participant attributes to these factors.

The fourth section includes questions regarding the opinions of the respondent with

respect to the functionality of their PM applications. It has ratings that allow the

participant to rate the importance of the features (existing and desired), the architecture

and compatibility characters of such applications and the barriers that exist in the

procurement, implementation and exercise of such systems.

4.1.3 Composition and Rating Scales

A variety of compositions have been used to arrange different types of queries while

framing the questions. Such features in a survey are not only necessitated in certain cases

but also known to accrue user enthusiasm. Also, having exactly the same type of

questions one after another could lead to the user losing interest in the questionnaire.

What software/s or line of softwares does your firm currently use towards as a PM

application? (Check All Applicable)

Microsoft Products (MS Project, MS Dynamics, MS Axapta etc.)

Primavera Systems Products (Project Planner, Enterprise, Expedition, Suretrak

92

Check boxes have been used in queries where it was deemed to provide the user the

option to select more than one option. A sample has been shown in the previous page.

The second type of question is where the user is expected to respond by typing it in

the provided text box, like for example his company’s name or any generic comments

that he would like to convey about PM applications or the questionnaire.

Some questions require that the user select only one response and should not be able

to select more than one as that could render the response useless. Use of option buttons

(also called radio buttons) has been made to design these, as shown in the sample below.

51 – 250 employees

251 – 1000 employees

Above 1000 employees

What is the number of employees in your firm?

Less than 20 employees

21 - 50 employees

The fourth and the most critical questions included the opinions of the participants in

terms of ranking of factors on a Likert scale of 1 to 4. Essential questions in this area

address the four conclusive categories of various factors that influence the entire PM

application system. These are as mentioned below:

• Corporate Concerns

• Application features

• Application architecture and functioning

• Barriers in deployment

93

3: Significant issues, but not in all cases

Lack of precedents of application usage in the industry 1 2

Major investment without guarantee of success and/or returns 1 2 3

3

How would you rate some of the following aspects as generic obstacles to procurement

and implementation of advanced project management software applications in

construction firms? [On a scale of 1 to 4 where;]

1: Not an obstacle at all

2: Minor problem that may be addressed and overcome

A 4 point Likert scale was opted for instead of a complicated one as the number of

alternatives being used is open to manipulation. The underlying concept is that the user

should fully understand the scale and that there should not be differences in the way the

user and the designer interpret the ratings.

Once again, though these responses were integral to the study, they were not designed

as mandatory. Primary reason for this was the fact that it is quite possible that a

participant may skip a query by mistake and this single error would not have a major

effect the response set. However, if the respondent is pushed to answer all questions by

repeated prompting, he or she might lose interest and quit the survey altogether.

4.1.4 Recruitment of Participants

Questionnaire for this study could aptly be answered only by select industry

professionals, namely senior construction engineers, project executives and managers

who are the primary users of such tools. Senior or top management also use such

applications and are involved in the IT system decision making process. Then again,

94

since this study focuses on the construction industry, it was required that the participants

also represent construction firms.

The initial strategy for distribution of the survey was to post messages in pertinent

online discussion forums. Select members of such forums that had provided a personal

profile which enabled checking their fitness as prospective participants to some extent

were also sent individual mails.

109 TOTAL RESPONSES

DEFINE RESPONDEDNT SELECTION CRITERIA

MESSAGE POST ON ONLINE DISCUSSION FORUMS

REQUESTING PARTICIPATION

SEEK CONTACT INFORMATION FROM COMPANY AND

ASSOCIATION / INSTITUION WEBSITE

SENDING INDIVIDUALLY CUSTOMIZED EMAILS

INTRODUCING THE STUDY and REQUESTING PARTICIPATION

372 EMAILS SENT (EXCLUDING 185

FOLLOW UPS)

22 EMAILS BOUCNED

69 RESPONSES

ACCEPTABLE

26 PARTIAL RESPONSES

14 NO

RESPONSES

65 RESPONSES ANALYZED FOR FINAL RESULTS

04 DEEMED

INAPT

Figure 19: Survey dissemination process and response selection statistics

95

This process was, however, abandoned in the early stages of the study. Foremost

amongst the reasons was that there was no access control on the survey and quite a few of

the responses were mere blanks, incomplete or rendered meaningless owing to inadequate

respondent information. There was also no categorical check to determine if the

respondent qualified to take the survey as well as to gauge the veracity of the responses. 4

responses were deemed inapt for this reason.

Switching to the second method of sending personal emails ensured the reliability of

the respondents as well as the responses because basic information about the respondent

was reviewed before an email was sent to request participation. This was done by

collecting contact and business information of prospective participants from various

member lists provided by esteemed institutes like the Project Management Institute

(PMI), the Construction Management Association of America (CMAA), FIATECH, etc.

An email was sent only when the respondent was found competent enough to take the

survey.

4.1.5 Response Rates

The response rate for the questionnaire was close to 18%. Of the total of 372 mails

that were sent, only 109 people responded. Of these, 14 were completely empty records,

10 had barely completed the first section and 16 had completed little more than the first

section. All of these could not be included in the data analysis since it would affect the

classification of record sets later. Any response set where the participant had skipped an

entire section was not considered. Another observation was that of participants who had

switched jobs and were now working elsewhere and therefore, quite a few e-mails

96

bounced. In four cases as mentioned earlier, complete response sets had to be omitted on

grounds that the participant was a project executive belonging to an alternate industry or

profession and therefore his or her responses would not be representative of current

practices in the construction industry. The remaining 65 responses were considered for

the final data analysis.

4.2 DATA ADEQUACY

In order to generalize conclusions obtained from the inferential or descriptive analysis

of data collected from surveys, it is imperative that the data have two essential

qualifications. The foremost is that the data sample be representative of the population.

Pertinent to this study, this includes various segments of the US construction industry that

use PM software applications for their day to day business and operations management

practices and tend to benefit from such use.

The other qualification is that the sample size be sufficient enough to lend credibility

to the results obtained from statistical or any other acceptable form of data analysis.

Depending upon the results that are being anticipated or desired, a variety of statistical

tests may be performed on the data. This would in turn depend upon the probabilistic

distribution of the data which ultimately, amongst a number of factors, is also based on

the sample size.

4.2.1 Sample Size

The sample size achieved was deemed adequate considering the scope of the study

and the limitations for respondent recruitment. The size was impeded owing to the fact

97

that participants were required to belong to the US construction industry only and were to

be essentially aware of the PM applications and trends in their professions. Another

factor affecting the number of responses could be attributed to the fact that the

questionnaire was lengthy comprising close to 30 questions with several subsets which

caused many participants to omit critical sections. It would, however, be extremely

demanding to arrive at conclusions without most of the queries made.

It was also found to be adequate from the statistical testing objectives. It must be

mentioned here that the sample size obtained was much higher than anticipated during

the initial stages of the study.

Various statistical tests were considered, as explained in later sections, and select tests

were performed on the data in consultation with qualified researchers based on the

distribution, type of the data and the sample size obtained. Moreover, the prolific

representation that was achieved by virtue of variety overcomes the lacks, if any,

resulting from sample size issues. This has been elaborated further in subsequent

sections.

4.2.2 Industry Representation

As mentioned earlier, online design of the survey questionnaire was chosen

specifically for the reason that the target audience could be attracted easily and also for

ease of use from the participant’s perspective.

In order to penetrate the lengths and widths of the construction industry, selection of

respondents was done keeping in mind that the array of responses that would be

necessitated to infer conclusively. Emails were sent to professionals belonging to

98

companies which varied in sizes, geographical locations, areas of operations and the type

of projects they cater to. This resulted in an unexpected set of data that achieved almost

all agendas that the dissemination process had targeted.

GEOGRAPHICAL SPREAD OF QUESTIONNAIRE PARTICIPATION

• Ohio • North Dakota • Michigan • Indiana • Illinois

• Tennessee • Florida • Georgia • Virginia • Oklahoma

• New Jersey • New York • Massachusetts • Pennsylvania • Rhode Island

Table 5: Geographical Distribution of Participating Organizations

MID-WEST US SOUTHERN US WESTERN US NORTHEAST US

• Texas • California • Montana • Oregon • Washington

Industry participation in this study was very diverse and represented all cross-sections

of the construction industry. Responses were received from more than 20 states covering

the spread across North America. Some of these are listed above. A chart showing the

percent distribution of survey responses from across the United States based on the US

Census Bureau classification has been presented below.

33.84

32.30

20.00

13.84MID-WEST US

SOUTHERN US

WESTERN US

NORTH-EAST US

Geographical Distribution based upon US Census Bureau Classification. Source www.wikipedia.org

Figure 20: Percent Distribution of Responses by US Geographical Zones

99

Considering the scope of this study, representing companies were categorized on the

basis of their primary area of operations as contracting firms and program management /

CM firms since these two segments reflect a difference in their needs from PM

application toolsets purview. There are other known sectors of the construction industry

including AEC and design firms but all or most of their requirements of PM tools parallel

that of program management companies. This aspect shall be discussed in detail in

following sections. Some of the respondents belonging to top companies in the United

States and also worldwide included those given below:

SELECT COMPANY PARTICIPATION IN SURVEY QUESTIONNAIRE

• Bechtel, CA • Skanska USA Incorporated, NY • The Turner Corporation, TX • The Whiting-Turner Company, MD • Jacobs, CA • The Walsh Group, IL • Swinerton Incorporated, CA • Gilbane Building Company, RI • Manhattan Construction Company, OK • Parsons, CA • Messer Construction Company, OH

• CH2M Hill Companies, CO • Parsons Brinckerhoff, NY • Heery International, GA • PBS&J, FL • URS, CA • 3D/I, TX • Hill International Incorporated, NJ • Carter and Burgess Incorporated, TX • HDR, NB • Vanir Construction Management, CA • PinnacleOne, AZ

TOP 100 CONTRACTING FIRMS TOP 100 PROGRAM MANAGERS

Source: The ENR Top 400 Construction Firms

Table 6: Industry Representation by Top Companies

A factor that also impacts the project management protocols followed in a company,

thus apparently creating a difference in their observations and demands of PM

applications is the nature of works that the company conducts. There are various

categories from this viewpoint in the industry. The chart on the following page depicts

the percentage response distribution achieved from this prospect.

100

It can be noted that the sum total of the percentages exceeds 100 and also that the

representation of companies like utilities contractors, maintenance and repairs, land

development, etc. is very low. Both of these are because in many instances, respondents

belonged to companies that are involved in more than one of these categories. For

example, the one person responding to the demolition and salvage category belonged to

the URS Corporation which is involved in many facets of the holistic construction

process like design build, AEC consultancy, infrastructure development etc, but is

primarily a CM firm.

Architecture and Engineering

Design Build Firms

Building and Residential Construction

Infrastructure and Heavy Construction

Specialized Industrial Construction

Real Estate and Land Development

Utilities Contractor

Demolition, Salvage, Renovation Services

General Contractor

Operations and Maintenance, Repairs

AEC Consultancy

Project Management and Planning

41.

30.

15.

20

12.3

4.61

1.53

1.53

26.1

1.53

13.

73.

53 76 38

84 84

NATURE OF OPERATIONS PERCENT RESPONSE

** The percent responses add up to over 100% as quite a few responses were from construction companies that operate in a number of domains.

Figure 21: Industry Representation by Areas of Operation

Another important aspect that needs consideration in so far as covering or prototyping

the industry is concerned is to encompass different sizes and organizational structures or

hierarchies of firms within the industry. It is understood that companies like Bechtel or

Hill International that operate in international arenas will not have similar requirements

pertaining to PM applications with that of a small firm with less than 50 employees

working from 2 departments with localized operations as a corporate affiliate.

101

In order to achieve this, in addition to deliberately targeting companies with different

sizes and operations, relevant questions were also included in the “general information”

section of the survey to enable categorizing the responses. The following charts delineate

the breadth of industry coverage.

Less Than 50 Employees

51 – 500

Employees

Above 500 Employees

10.78

30.76

58.46

PERCENT RESPONSE NUMBER OF EMPLOYEES

IN THE FIRM

Figure 22: Industry Representation by Number of Employees

It is seen that responses from companies with less than 50 employees was much lesser

than that of others. Reasons for this are two fold. Owing to lack of information of these

companies from generic sources like yellow pages or online resources, the targeted

number of such companies was relatively less. Another reason underlying this figure is

that in several cases the responses were actually filled out and received. However, since

small companies do not cater to holistic project management but function mostly as

support or specialty services, the respondent could not or did not complete several

sections of the questionnaire and quite a few responses were recorded as “not applicable”.

Such records were therefore not considered for the study. This however does not affect

the inferences since small companies do not stand out as major players in the PM

applications scenario and are mostly known to use generic office management or PM

tools.

102

Another factor affecting the PM environment and thus influencing the selection and

utility of PM tools in construction companies is the number of branches, divisions or

cross-functional departments that the said companies have. Since efficient

interdepartmental communication is vital to timely response and distributed decision

making processes, the organizational structure is considered a major criterion. The chart

below shows the distribution of such companies as observed in the survey responses.

1 - 5

5 – 20

Above 20

26.98

47.61

25.41

NUMBER OF FUNCTIONAL DEPARTMENTS

PERCENT RESPONSE

Figure 23: Industry Representation by Number of Functional Departments

It can be seen here that close to half the responses belonged to companies having

anywhere from 5 – 20 functional departments. These include both large and midsize

companies involved in contracting and / or construction management. Companies with

over 20 departments are those that operate in a global arena and undertake a variety of

projects, sometimes with distinct project delivery systems based on client’s demands.

Responses from small companies are again found to be relatively less owing to

aforementioned reasons.

The distribution observed for this factor was considered above par from the

descriptive data analysis perspective based on grounds mentioned earlier. Since the

categorization for inferential statistical analysis does not consider this aspect as a

103

primary, this and other factors mentioned above do not influence the decision model.

These aspects have only been studied to substantiate industry representation.

A correlated aspect of the number of cross-functional divisions that a company may

have is the geographical spread of operations. The chart below shows the percentage

responses of different categories.

Localized

Across USA

Global

40.00

41.53

18.47

GEOGRAPHICAL SPREAD OF OPERATIONS

PERCENT RESPONSE

Figure 24: Industry Representation by Spread of Operations

The response distribution of companies with operations localized in one or a few

locations is as much as that of companies operating throughout the United States. The

percentage rates described in this sub-section should be examined independent of each

other since most companies would simultaneously be in many different categories for

distinct factors while at the same time forming only one data record. For example,

companies operating worldwide include only 18.47% of the respondents. Considering the

figures shown in the previous chart, these would include most of the 25.41% of

companies with over 20 departments some of the 47.61% of companies with 5 – 20

functional sections. In other words, all of the 25.41% companies noted as having more

than 20 departments earlier do not all have global businesses, but some or most do.

104

4.2.3 Data Accuracy

. All respondents are either PM professional like projects managers, project control

specialists, senior construction managers etc. or hold top management positions like Vice

President or Director of projects or operations. The chart below shows percentage

responses based on the years of experience the participants had in project positions. Most

respondents have over 10 years of experience in their respective fields and are believed to

have used PM applications of various types during their professional career.

Less Than 1 Year

1 – 5 Years

5 – 10 Years

10 – 20 Years

Above 20 Years

1.53 4.61 15.38 27.71

50.77

YEARS OF PROFESSIONAL EXPERIENCE

PERCENT RESPONSE

Figure 25: Industry Representation by Years of Experience

An insight into their involvement in and with such applications can also be gained

from some of the comments that participants added along with their responses listed in

Appendix D.

4.3 DATA ANALYSIS

In order to design the decision matrix such that it could be applied universally to

various segments of the industry that need such decision support systems, it was pertinent

105

that the record sets be categorized on the basis of differences in approaches and

influencing factors as related to PM applications.

CONSTRUCTION INDUSTRY BY PM APPLICATION UTILITY

SIZE OPERATIONS

LARGE COMPANIES (41%)

SMALL COMPANIES (24%)

PROGRAM MANAGEMENT / CM FIRMS (55%)

MIDSIZE COMPANIES (35%)

CONTRACTING FIRMS (45%)

Figure 26: Industry Classification by PM Applications Approach

Initial observation of datasets coupled with common knowledge revealed certain

differences in the company reflections towards such applications in two areas:

• Size and spread of the firm

• Primary operational functions

It was accordingly decided that the data records be divided into 2 broad categories on

the basis of size and functions as shown above.

Large Companies contained the body of responses from firms having over 500

employees and over 10 cross functional departments catering to management areas like

operations, finance, procurements etc. They operated or had branches, partners and / or

clients at a global or at least at a nationwide level. It was also discerned from response

records that such companies were involved in various aspects of construction from AEC

106

consultancy to general contracting, facilities maintenance and repair, program

management / CM and more. Such companies constituted approximately 41% of all

participating firms and included firms like Bechtel, Skanska, CH2M Hill, Parsons

Brinckerhoff etc.

Midsized companies typically employed more than 250 people and the number of

cross-functional divisions ranged between 5- 10. Their operations, clientele, branches and

/ or business affiliates were contained yet well spread within the USA and in some cases

localized to a few states. Most of these firms, like large companies, were also active in

several areas of construction ranging from contracting and consultancy to construction

management. Some of these also catered to specialized services like dispute avoidance

and resolution, land development, homeland security, etc. Such firms made up close to

35% all respondents and included firms like Archer Western Constructions, Messer

Construction Company, Dick Corporation and Paragon Project Resources Inc.

Small companies exhibited a marked deviation from large and midsize companies and

constituted anywhere from 20 to approximately 200 employees. They had very few (1-5)

or no cross functional departments and functioned as affiliates, support services (like

HVAC or plumbing services), or special contracting firms in tandem with larger firms.

Some of the firms in this category were independent contracting firms too. Their

operations are totally localized with branches or business partners in a few cities at most.

These are in most cases sole proprietorships or LLCs (Limited Liability Corporations)

involved in activities like AEC consultancy, structural and transportation design, minor

construction contracting and maintenance works, etc. These comprised around 24% of

the respondents and included firms like Coma Consultants Inc., CA, NC Monroe

107

Construction Company, NC, Touchstone CPM, GA, Construction Controls Group, OR

and many more.

Having grouped all participating firms on the basis of size, it was also necessary that

the classification be done again, for all the firms, on the basis of their operations.

Principal reason behind such break down can be attributed to the fact that companies

providing distinct services cannot be expected to have similar requirements or concerns

from the organizational practices or project management context, which would reproduce

differences in their attitudes towards PM protocols and applications.

Even though enlisting all such distinct operational areas within the construction

industry is a confounding an extremely burdensome task, it was relatively easier in this

case since categorization was not being done from a generic viewpoint but only from the

PM applications and IT trends outlook. Another factor that added to the ease, and to the

confusion as well, was the fact that most large and midsize companies forming a major

portion of respondents, were involved in a number of operational activities. It was

therefore thought apt to categorize on the basis of their primary occupations.

Contracting firms were classified as those that invested their own manpower,

equipments and other resources in the construction execution process. In addition to

these, such firms may or may not be the sole parties are responsible for various other

phases of construction projects like design, planning, monitoring and control,

procurements, finance, legalities etc. In other words, their primary function was that of

general contracting on projects of various scales and all the other aspects might be

controlled by the firms themselves or delegated to its affiliates or partners. Most of the

responses collected from such firms reveal that such firms are active in various different

108

aspects of construction projects as well, including construction and program

management. Such firms amount to approximately 45% of the respondents and include

Turner Corporation, the Whiting-Turner Contracting Company, Skanska, Tishman

Construction Corporation of DC, Gilbane Building Company and many more.

The other category from the operational standpoint included companies whose

primary area of activity embraced program or construction management. These are firms

that principally cater to the project and / or construction engineering and management

needs as affiliates of contracting companies. Their services range from, for example,

exclusively design and architectural services to financial management and move on to

encompass everything but actual construction execution. Such firms do not deploy their

own resources towards the execution. These firms include close to 55% of all respondents

and include companies like Parsons Brinckerhoff, Carter and Burgess, Johnson Mirmiran

and Thompson, PinnacleOne, Hill International and so on.

It is noticeable that the classification process adopted in this study is not

unequivocally definitive owing to extremely diverse operational characteristics of various

members of the construction industry, and its fragmented nature as well. Quite a few

feature-based overlaps can be observed for many of the participating firms. It must be

mentioned here that company information obtained through the survey questionnaire was

not the only parameter used for the above classification. In case of most companies,

further insight was necessitated owing to the overlaps mentioned above. Generic

established sources of information like the company websites and construction industry

research compendiums like ENR (Engineering News Record), Reed Construction Data,

McGraw-Hill Construction Online etc. were delved into in order to gain qualified

109

information about respective company’s operations, branches and affiliates, project

histories, turnovers and so on. All of the collective information was used to group the

participating firms.

Then again, such classification was conceived on the basis of differences perceived

from their initial responses with the primal objective being to study whether or not such

distinctions actually exist from the PM practices and applications viewpoint. If

subsequent statistical analysis revealed that the differences did exist and were significant,

then the approach adopted for designing the decision tree would have to be unique for

each end user category. In the sense that the decision tool design criterion for a large

contracting firm would differ from that of a mid size CM firm or a midsize contracting

firm and so on.

4.4 DESCRIPTIVE STATISTICS AND PM IT TRENDS

Descriptive statistics were studied to elicit initial guidelines before formally

establishing whether the differences mentioned above existed or not. Data obtained from

the first two sections of the questionnaire were used towards this end. Queries in the

survey had been designed to specifically address certain areas of organizational practices

and to compare and analyze issues within. Some of these included:

• Internal communications, associated preferences and barriers

• Competitiveness and peer evaluation

• Project management IT environment

• PM applications, implementation and preferences

110

Having sorted the data based on the classification described above, charts were

created to display aggregate results from all categories. Inferences were then drawn on

the basis of various observations derived from these charts. These have been explained in

detail in the following subsections.

4.4.1 Cross-Functional and External Collaboration

Inter-departmental communication and collaboration with various stakeholders and

partners is one of the key precursors for the recent spate in development and

implementation of PM applications. Recent technologies in such applications are known

to enable collaboration in all of its forms ranging from simple emails and telephonic

conferences to real time video conferencing as well as automated site level audio and

video capturing using hand held or pre-installed electronic devices. This is also one of the

main functional aspects, along with data transfer and storage that drive the industry to

invest in such applications. Studying this aspect, at least at a basic level, was necessary to

examine how project personnel belonging to different setups feel about it.

COMMUNICATION LARGE MID-SIZE SMALL CONTRACTING PROGRAM

MODES and DEVICES COMPANIES COMPANIES COMPANIES COMPANIES MANAGERS

2 2 2 2 2 TELEPHONES, FAX

4 4 3 4 4 MEMOS, DOCUMENTS

1 1 1 1 1 EMAILS

5 5 5 5 5 PDAs, INTERCOMs

3 3 4 3 3 SOFTWARE TOOLS

Table 7: Mean Ranking of Modes of Collaboration

111

Asked to rate various modes of communications within their organizational and

project network, respondents assigned the rankings shown below in terms of means.

Emails are the foremost means of communication followed by telephones and faxes.

PDAs and intercoms are the least rated and collaborative software applications are mid-

ranked. Only one deviation is observed in the ratings allocated by different categories.

This was the assignment of computer based collaboration as one of the least preferred

modes by small companies.

All the same, it must be noted that preferences still remain with time-tested

conventional methods and the shift to other courses is lacking. Reasons for this as cited

by research bodies like FIATECH is that project personnel prefer tools that have been

used through the years and are commonly accepted forms of communications. Large

companies that are known to have invested exorbitant funds on PM applications also do

not seem to rely on them for communication but only for data storage and centralized

information access.

Unanticipated results in the midst of such analysis is that even though conventional

tools are preferred and have been used through the years, communications have been

rated as efficient and timely by an average 35% of the respondents only. As can be easily

noted, between 30% – 40% respondents from all 5 categories have described their

communications as highly efficient. On the other hand, close to 58% reflect that

communications are redundant and inaccurate on occasions with moderate efficiency and

that there is a need for improvement. 2% of respondents (averaging a holistic 6%

representation from small companies and 3% from contracting firms) believe that it is

lacking and cumbersome.

112

0

10

20

30

40

50

60 Large Companies Mid-Size Companies Small Companies Contractors and Builders P M

HIGHLY

EFFICIENT AND TIMELY

REDUNDANT / INACCURATE

ON OCCASIONS

MODERATE EFFICIENCY

LACKING AND CUMBERSOME

NOT APPLICABLE

Figure 27: Diagrammatic Comparison of Communication Efficiencies

There are another two noticeable aspects here. The first is the ratings from small

companies. Generally compared with large and midsized companies, communications in

small firms are more efficient and less redundant and inaccurate. This could logically be

attributed to the lesser strength and departmentalization in small companies as compared

to bigger firms which justifies their inhibitions from investing in expensive collaborative

tools.

Another aspect is the marked deviation of midsize companies in the moderate

efficiency category. This could be because midsize companies, while undertaking high

volume construction projects, affiliate with a lot more agencies towards integrated project

control as compared to large companies that are well equipped to absorb most task

delegations within their parent firms. Comparative evaluation of other parameters in

following sections allows us to better explain such discrepancies.

113

4.4.2 Competitiveness and Peer Appraisal

A critical factor that features in justifying the investments on PM applications and

various other related issues like data security is the ambition to stay competitive in the

market. This is totally from the business share perspective and has supreme importance

for construction companies since it is the largest growing industry worldwide.

An associated aspect is also the implicit demand to match up to the tools, applications

and technologies that are being used by partner firms and affiliates. This is significant

from the composite performance efficiency and compliance side of project planning,

execution and monitoring. When asked to rate their performance on projects being

executed in various different locations relative to those being executed on home sites,

most respondents from all categories rated these as equally successful.

0

10

20

30

40

50

60

70

80

90

100

SIGNIFICANTLY

LESS SUCCESSFUL

LESS SUCCESSFUL

EQUALLY SUCCESSFUL

MRE SUCCESSFUL

SIGNIFICANTLY MRE

SUCCESSFUL

NOT APPLICABLE

Large Companies Mid-Size Companies Small Companies Contractors and Builders Program Managers

Figure 28: Comparative Mean Ratings of Project Performance based on Location

114

Close to 20% of midsize contracting firms, however, rated projects being undertaken

at external locations as more successful. This aberration could be attributed to the fact

that in cases of projects being executed at job sites away from the company home cities,

monitoring and control tasks are delegated to resident project executives and foremen

who work from the job site itself and are quite cut off from the organizations

headquarters. This is believed to result in better efficiencies in terms of execution and

construction productivity owing to the shielding of situational decision making processes

from the top management authorities. This obviates the need of communicating with the

headquarters for every decision being made resulting in lesser downtimes and differences

in opinions and interpretations.

This concept, called “production shielding” (Ballard, 1988) is still being explored and

there is some conclusive evidence of success due to such shielding within the lean project

delivery systems arena. This feature however is beyond the scope of this study.

A notable deviation is also seen in close to 40% of small companies rating as not

applicable which is reflective of their operations being completely localized in one place.

Then again, in cases of project work undertaken in different locations is concerned, the

volume of work might be such that the difference in location does not seem to be

affecting their performance efficiencies.

Efficiency assessments from the level and nature of collaboration were also

necessitated. Consider a large contracting company that is using certain applications

which can receive, sort, process and then re-transmit information or data to their

affiliates, for example, located on the jobsite towards a given decision.

115

0

10

20

30

40

50

60

70

80

90

Large Companies Mid-Size Companies Small Companies Contractors and Builders

100

P M

NOT AS ADVANCED AS

OURS

SIMILAR AND EQUALLY

GOOD

MORE ADVANCED THAN OURS

NOT APPLICABLE

Figure 29: Assessment of PM Applications in Peer and Affiliate Companies

The affiliates computing setup however, is unable to receive or compile this

information and present it in comprehensible forms. This would result in a bottleneck

leading to loss of time and project progress. It is therefore mandated or at least

recommended by top companies that their affiliates use applications that are compliant

with other applications being used towards integrated management.

This shows that more than 80% of respondents from all categories rate the

applications being used by their other branches and affiliates as being equally good and

compliant with their current computing and IT setups. This is indicative of the fact that

penetration of PM applications, though unidirectional, is yielding uniform growth within

the construction IT area.

116

Once again, the slight deviation that is noted in the case of small firms is because they

mostly do not undertake projects that have continued responsibilities at different

locations. Most tasks delegated to such firms are during the pre-construction phase and

are contractually completed upon delivery. In a lot of cases again, these companies work

the entire project single-handedly without any collaborating parties since the projects are

small scale construction works.

Similar observations were also made when the respondents were asked to comment

upon how the PM IT setups of their peers or partner firms affected their performance on

projects, as shown on the following page.

Close to 75% of large contracting firms seem to agree that PM applications and

computing tools employed by their peers have a positive effect on project performance.

Similar trends are noted for around 55% of midsized CM firm.

0 5

10 15 20 25 30 35 40 45 50

NEGATIVE EFFECT ON

PERFORMANCE

DOES NOT EFFECT

PERFORMANCE

POSITIVE EFFECT ON

PERFORMANCE

SIGNIFICANTLY ENHANCES

PERFORMANCE

NOT APPLICABLE

Large Companies Mid-Size Companies Small Companies Contractors and Builders

Figure 30: Impact of IT setup of Peers and Affiliates on Project Performance

117

Approximately 34% of small companies again do not feel affected by their peer’s PM

tools with another 40% responding to “not applicable”. Only one sector, that of 5%

midsize program management / CM firms or affiliates, feel that PM applications

employed by their partners seem to have a negative effect on their performance.

However, this does not stand out as a trend as the said observation has too low an

occurrence and is very specific. No other category responded similarly. In general, the

trends are indicative of positive affects on project performance.

4.4.3 Project Management and IT Work Environment

The PM and IT work environment encompass many variables that pertain to project

management IT enablers in a company’s organizational and functional establishment. Its

study is necessitated since these factors are indicators of a company’s approach towards

enhancements in project management practices through computing and technology

implementation. It also helps assess the degree of readiness of a company for easy

upgrades or enhancements to their computing and IT infrastructure.

Very favorable responses were elicited when queries regarding the presence of an in-

house IT department were made, as shown on the following page. Excepting small

companies, an average of 89% of all firms reported having their own IT divisions. 53%

of small companies also reported as having IT setups. A caveat must be mentioned here.

Not all IT departments have qualified professionals that can develop software

applications.

It is quite possible that in many of the above cases, the IT departments that the

participants refer to are mostly a team of computer installation and maintenance people.

118

0 20 40 60 80 100

LARGE COMPANIES

MIDSIZE COMPANIES

SMALL COMPANIES

CONTRACTORS

PROGRAM MANAGERS

96.15 %

91.30 %

53.33 %

85.71 %

85.71 %

Figure 31: Percentage of All Categories Having In-house IT Departments

It can be noted from the questionnaire records that many companies do have IT

divisions that create customized software applications for exclusive use by the company.

In some cases, they may also be making small packages whose only functional value lies

in creating communication protocols between different software packages. Altering a

proprietary application cannot be done since its illegal. And very few companies have the

financial resources or the inclination to have customized applications developed for them.

Another critical factor that affects the PM application implementation is the time

taken for such deployment, shown graphically below. It can be stated with reasonable

assurance that the average duration ranges from a couple of months to more than a year.

As mentioned before, some companies take more than 2 years for total deployment over

their entire enterprise. This is because companies opt for a phased deployment process so

that it does not affect their on-going project or operations. The is also true for companies

that take a few weeks or days for such implementation, the only difference lying in the

fact that the applications being installed are much smaller and simpler and therefore take

119

lesser deployment time as compared to highly complex web-based custom solutions

being used by some large companies.

0

10

20

30

40

50

60

MORE THAN A YEAR

COUPLE OF MONTHS

FEW WEEKS LESS THAN A WEEK

NOT APPLICABLE

Large Companies Midsize Companies Small Companies Contractors Program Managers

Figure 32: Relative Plot of Deployment Durations for PM Applications

This is clearly reflected in the fact that 50% of large and midsize contracting

companies take around a year towards such efforts since deployment is slow and in parts.

Another observation here is the close to 30% companies responding to “not

applicable”. This does not indicate that such deployment did not occur in their respective

organizations but that the participant in question did not experience such implementation

since questions in the survey had been carefully worded to elicit a response only if the

participant had personally experienced such an occurrence.

120

Another crucial aspect of PM applications deployment and effective utilization arises

from the executive training and development programs that companies practice. Purchase

or implementation of such tool is futile if company professionals do not know how to use

such applications or are ill-at-ease with them. The IT training trends of a company are

therefore indicative of its advancement in this direction.

Responding to the training codes followed by their firms, approximately 30% of

respondents reported being up-to-date and well trained. Close to another 40% reported

moderate and need based training, which is also good.

0

5

10

15

20

25

30

35

40

45

50

VERY WELL TRAINED and UPTO

DATE

MODERATE and NEED

BASED

TRAINED INITIALLY

and EXPECTED TO COPE

DELEGATED TO EXTERNAL AGENCIES AT

PERSONAL EXPENSE

NOT TRAINED and HIRED ON

BASIS OF KNOWLEDGE

NOT APPLICABLE


Figure 33: IT Training Trends in Various Segments of the Construction Industry

Responding to another query inquiring if they felt that such applications make PM

tasks more agile and easy to perform, more than 50% felt positive about it. Varieties of

121

comments were also received towards this query and have been listed in Appendix C.

These are reflective of the mixed feelings that the industry evinces towards advanced

computing protocols and IT technologies in general, PM applications being an integral

part of these.

However, it is also noted that close to 30% of all firms imparted training initially and

then expected the employees to cope with further enhancements. Very few firms reported

training being delegated to external agencies at personal expense or not being imparted

by the hirer at all. Even though in extremely few cases, this does indicate that the benefits

of such applications are yet to be fully understood or appreciated by the industry and

efforts need to be taken up to disseminate more about such enhancements in industry

wide forums.

4.4.4 Project Management Applications

Investigation of PM software applications currently being used by the industry was

done to assess preferences and inclinations for different software architectures and

functionalities as well as to study industry trends relevant to these. Foremost amongst

such queries was to determine the suitability of commercially available applications for

various firms. Responses to this query have been depicted below.

It is manifest that in most cases the industry deems regular applications inadequate to

address their PM concerns and demands of computing tools, Close to 85% of all

respondent’s firms are noted to have opted for customization, even though the modes

have been different. Approximately 50% of small companies are using off-the-shelf

122

applications, the main cause for which can be attributed to lack of financial resources

towards customizing the applications to meet their individual needs.

0

10

20

30

40

50

60

CUSTOMIZED BY EXTERNAL AGENCIES

CUSTOMIZED BY IN HOUSE IT

DEPARTMENT

CUSTOMIZED BY VENDORS

DESIGN TEAM

COMMERCIAL OFF-THE-SHELF APPLICATIONS

OTHERS OR A COMBINATION

OF THESE


Figure 34: Types of Software Applications Enhancements by Industry Category

Almost half of all customizations are being carried out by the software vendors

design team itself, which indicates that vendors are aware of the general preference of the

industry towards customized tools. Moreover, this also forms a lucrative prospect for the

vendors since such modifications are done for a fee and are proprietary as well. This

makes the vendor a very important participant in the entire computerization process and

also yields consistent profits for them since they contractually bind the construction

companies for future upgrades and maintenance of data and hardware.

Noting that most firms opt for customized tools, it was imperative to understand and

analyze reasons as to why such customization was done, especially since from the

construction company’s viewpoint, it is quite an expensive endeavor.

123

0ONE PACKAGE WITH

INTEGRATED CORRELATED

MODULES

DIFFERENT APPLICATIONS WITH

AUTOMATED IMPORT / EXPORT OF DATA

DIFFERENT APPLICATIONS WHERE

DATA IS ENTERED MANUALLY EACH TIME

NOT APPLICABLE


10

20

30

40

50

60

Figure 35: Integration Protocols within PM Software applications by Categories

Queried about the levels of automation such tools posses, close to 50% of all

participants reported that their tools were capable of automated data transfer and updating

facilities. This sheds light on the fact that customization is done with the objective of

minimizing data entry and re-entry into for various ends.

This does not go to say that automated data transfer or centralized updating and

access is the only or primary reason for such customization but that it does seem to be a

highly demanded feature. A 20% average response for single package integrated modular

architecture for such applications is also indicative of the fact that construction

companies are acknowledging the need for greater integration in their applications and

realizing that it is an effective tool towards avoidance of typographical errors, redundant

information, increasing efficiency, timeliness and accuracy.

124

However, as mentioned earlier, this does not stand true for the entire industry since

close to 30% of such applications still necessitate manual data entry and updating and

tracking of information. A near uniform distribution in this category also reflects that the

problem areas does not exist for a particular sector of the industry but is quite applicable

to all sections.

Another area that was examined as a follow up to the conclusions arrived at during

the software review phase of this study was the preferences for various commercially

available PM tools. In order to understand corporate concerns from the construction

company’s standpoint and also the business efforts from the software vendor’s side,

inquiry was made into the generic applications that most companies favor.

MICROSOFT PRODUCTS

PRIMAVERA PRODUCTS

MERIDIAN SYSTEMS PRODUCTS

SAGE TIMBERLINE PRODUCTS

CMiC PRODUCTS

OTHER APPLICATIONS

26.14 %

32.03 %

16.34 %

10.45 %

3.26 %

11.78 %

Figure 36: Preference Assessment for Commercial PM Applications

It is observed here that most companies prefer PM tools from established vendors like

Microsoft, Primavera and Meridian systems. Even though the applications designed by

CMiC, for example, are as capable if not more as some of these tools, they are not in

much use. Probable cause for such statistics could be twofold. The first is that companies,

125

after investing in the purchase and customization of regular applications, and then again

for procuring generic tools to address other areas of project management, do not want to

invest further towards such expensive tools.

Another reason is founded on the fact that CMiC is a Canadian firm and has therefore

not been competing very well with US based firms like Microsoft and MPS towards

capturing a larger market share. This does not reflect that CMiC’s products are not

popular but merely indicate that they are not as well accepted as cheaper tools from

established US based vendors.

The low percentage utilization of Sage Timberline line of products is observed as it

mostly caters to the estimation process and its product line of PM tools includes few

applications like “Office”. Constructware and Oracle’s JD Edwards form a large part of

the “other” application category.

Various insights gained through all of these statistics have been used to guide further

inferential statistical analysis of data towards development of the decision tool.

126

CHAPTER 5

MATRIX DESIGN

5.1 DESIGN STRATEGY

A preliminary strategy was formulated before designing the survey questionnaire to

construct the decision matrix. This concept was modified as certain aspects related to the

application features and selection process came into light.

The core methodology of the matrix design has been explained below:

• Identification of priorities of construction business as well as operational functions.

• Establishing logical links between such priorities and other aspects of PM software

applications like their functional features, architectural or hardware qualities and

demands for advanced toolsets in the future.

• Establishing associations between above mentioned priorities as well as software

characteristics with known barriers in such deployment processes.

• Selection of upward sloping associations between each of these subsets, if any, based

on statistical inferences.

• Design a chart or diagram that allows negotiating through the entire decision support

process to center upon desired aspects.

5.1.1 Establishment of Substantive Priorities

Substantive priorities, in this case, refer to the primary reasons underlying a

company’s plans to initiate an IT or computing investment. Relevant to the scope of this

study, these would form the cardinal reasons for investing in PM applications. During the

initial phases of the study, it was believed that such priorities had two essential facets, the

127

chief corporate concerns and software application features. However, as more and more

information was collected and examined, it became evident that there was only one

primary in the entire PM computerization initiative. This included the very many

corporate concerns that not only create a thrust but also aid in financial case justification

for such investments.

All other aspects of such software selection processes revolve around this set of

corporate concerns. It was also inferred that in case of all categories, these concerns are

based on common grounds with very few differences and did actually follow a generic

trend.

Additionally, it was also observed that very few differences existed in the approaches

adopted by various different segments of the industry studied, namely large and midsize

companies performing contracting or program management / CM functions, towards the

application itself.

CORPORATE CONCERNS

APPLICATION FEATURES and

TOOLSETS

APPLICATION ARCHITECTURE

and FUNCTIONING

ADVANCED INTEGRATED

FEATURES

BARRIERS IN IMPLEMENTATION

Figure 37: Corporate Concern Centric Decision Matrix Design Strategy

128

Small companies, though initially included in this study, were not exclusively

considered while designing the model since most of them were found to be using generic

applications and PM tools and the shift towards web-based customized solutions was

quite incidental.

5.1.2 Analysis and Ranking of Influences and Attributes

Identification of various essential factors and application attributes that influence the

selection processes was done through literature and software reviews. These were listed

and then categorized as:

Corporate Concerns

Barriers

• Influencing Factors

Application’s Features or Modules

Application’s Functional Characters

Desirable Advanced Toolsets

• Application Attributes

A total of 74 items comprising 18 corporate concerns, 9 barriers to implementation,

20 feature set aspects, 18 functional characteristics and 9 advanced toolsets were listed in

the above mentioned categories in the survey questionnaire to be ranked by the

respondents. Ratings for these items were averaged over the entire pool of respondents

and then compared with each other and arranged in a ranked descending order within

respective categories. The same process was adopted after splitting the pool into large,

midsize and small companies; contracting firms and program management / CM firms.

129

All of this yielded 6 sets of results for the groups listed below and were tabulated as

shown later in this section in Tables 10 through Table 14.

• All responses

• Large Companies

• Midsized Companies

• Small Companies

• Contracting Companies

• Program Management / CM Companies

In order to avoid any likelihoods of user error while manually assigning ranks by

visual comparison of means, the MS Excel Rank function was used to computationally

assign ranks to various items in each category. It was noted that in many cases, the mean

ratings were same and therefore such items were ranked equally since the rank function is

in-built and uses a pre-defined algorithm. Enabling the function to assign exclusive ranks

to all items necessitated the use of a custom formula that was appended to the in-built

rank formula as shown below.

=RANK(C332,C$332:C$340)+COUNTIF(C$332:C332,C332)-1

DEAFULT RANK FUNCTION APPENDED FORMULA

Here, C332 denotes the cell corresponding to column C and row 332. C332:C340

indicates the range of the comparison, that is, the mean in C332 is to be compared with

all items from cell C332 to cell C340. The appended portion of the formula works by

adding to the rank of the number in cell C332 another number that equals the number of

times the mean in question gets repeated minus 1.

130

Appraising the rankings of all 74 items was not necessary considering the ultimate

aim of this study, which is to design the decision matrix. Nonetheless, since the matrix is

founded mostly on the top established priorities, i.e. the corporate concerns, in order to

facilitate users with itemized rankings that might be important to them while not being

generally top-ranked, it was decided to tabulate all features in all categories.

Another crucial concern that needed attention was to determine if the means were

truly different from each other, since they seem to have very insignificant numeric

differences. Statistical comparison of means was done to verify whether the differences

were significant or not.

5.1.3 Statistical Comparison of Parameter Means

Statistical comparison of sample means under differing treatments is a commonly

used procedure to determine whether or not the difference in means exists and also to

determine if the difference, if present, is significant as compared to another mean or any

given number. There are several standardized tests that are used towards this end. Some

of the common ones include the ANOVA, the chi-square contingency analysis, the

Wilcoxon test and many more. All these follow the basic hypothesis testing procedures.

All tests can be applied to all types of data and will yield results as well, but these

results may or may not reflect the statistical inferences accurately depending on three

essential aspects. These include the type of data, its probabilistic distribution and the

sample size being studied.

ANOVA was deemed inappropriate to compare the means since it is based on the t-

distribution. This assumes that the data being analyzed is continuous and is also normally

131

distributed. Though the CL (central limit) approximation could be used for our study

since the sample size is more than 30 (believed by some to be a reasonable sample size

for using the CL theorem) in all cases, another pertinent issue was that the data in this

study was not continuous but ordinal.

2 The χ (chi-square) contingency (or frequency) analysis, from the above mentioned

aspects, seemed to be appropriate for our data. Nonetheless, the hypothesis that is tested

was not satisfactory to conclusively infer difference in the means of various parameters.

Say, for example, we are testing the means of Factor 22 and Factor 23, which have the

following frequency tables based on Likert ratings from 1 - 4.

Factor 22 7 3 11 21

2 13 5 12

1 2 3 4

Factor 23

RATING SCALE

Factor 22 has received 7 1-pointers, 3 2-pointers, 11 3-pointers and 21 4-pointers; and

likewise for Factor 23. The hypotheses that the χ2 analysis tests are based upon for

comparison of the proportions of different ratings that have been received between the

two factors is shown below.

H0: PF221 1 2 = PF23 , PF22 = PF23

2 3, PF22 = PF233 4 4, P = PF22 F23

1 1 2HA: PF22 ≠ PF23 , PF22 ≠ PF232 3, PF22 ≠ PF23

3 4 4, P ≠ PF22 F23

If any of the four proportions reflect a difference, the results of the tests show a

statistically significant difference. Moreover, these do not actually test the differences in

means but the ratio between frequencies of 1-pointers, 2-pointers, 3-pointers and 4-

pointers for the two factors in question. Another grey area with this test is that even

132

though it is designed for frequency analysis, it needs that the number of counts (1-4 in

our case) be greater than or equal to 5.

The Wilcoxon test is a non-parametric test, i.e. it is able to accept or reject a null

hypothesis without any knowledge or assumptions of the underlying population or

parameters. It is considered excellent for making conclusions of small to mid-size

samples when the underlying population distribution is not known or is known to be non-

normal (Blank, 1980).

The two-tailed Wilcoxon test was therefore selected for a pairwise comparison of

means between various items in each of the 5 categories described above. The hypothesis

tested in this case, for example, is shown on the following page.

H : μ0 F22 = μF23

HA: μ ≠ μF22 F23

SAS, a statistical analysis package, was used to compare the means pairwise. The

program (Appendix F) yields the one-tailed and two-tailed P-Values at the α = 0.05

significance level. P values of lesser than 0.05 indicate that a statistically significant

difference exists between the two means being compared.

Analysis of the data using this procedure revealed disparate patterns. The comparison

was initiated starting with the two factors that had top initial (also called ground)

rankings based on their mean values. Consider, for example, that they did reflect a

difference. In such case, the 3rd ranked factor was considered and the comparison was

done with the 2nd ranked factor. Assuming that they did not reflect a difference, the next

ranked factor was taken up with the 3rd ranked factor. The same trend was observed for

the 5th th and 4 , 6th th and 5 , 7th th and 6 and so on. Since differences were not being observed

133

from the 2nd ranked factor onwards, all following factors has been assigned the 2nd rank

with the top ranked factor being 1st. At this stage, a check was done to compare the mean

of the 7th ranked factor with the 2nd and it reflected a difference.

The anomaly was that if 3rd was same as 2nd, 4th as 3rd th, 5 as 4 , and so on then the

difference between the 7th and 2nd ranked factor needed an explanation. One very simple

reason to this anomaly was that this occurrence was observed owing to the fact that the

questionnaire used a 4-point scale and therefore all the mean ratings were very close to

each other.

In order to overcome this anomaly however, an elimination algorithm was developed.

The underlying concept was to keep comparing the means of parameters based on the

descending order of initial rankings till a pool or group of factors with the same statistical

ranking were observed.

Then the comparisons are started again between the two parameters farthest within

the pool to see if a difference exists between the highest and the lowest ranked items from

within the pool. If a difference is observed, the highest ranked item is eliminated from the

pool and maintains its statistical rank, and the statistical rank for the other parameters is

increased by one.

This process was followed till the very end of the parameter list was reached and has

been expressed in a flow chart form in the preceding page. Table 7 on the following page

shows an example of the iterative steps that were followed for parameters belonging to

the “corporate concern” category for “all” responses. This table is an example of the

process followed based on actual values and does not contribute to the actual design of

the decision tool.

134

YES

YES

NO

YES

NO

NO

START

SR (FGR = 1) = 1

i = 2

j = ( i – 1 )

Are the means significantly

different?

Compare means of FGR = i and FGR = j

SR (FGR = i) = SR (FGR = j) + 1

Store Value

of j

SR (FGR = i) = SR (FGR = j)

j = j - 1 j > 0

i = i + 1

Get SR ( FGR = i ) AND

SR ( FGR = i ) = SR ( FGR = j )

i = i + 1 i ≤ N ?

STOP

SR = Statistical Rank FGR = Ground Rank of Factor i = Rank Variable j = Rank Variable

Figure 38: Elimination Algorithm for Comparison of Parameter Means

135

136

The sole objective of this formulation was to enable assignment of exclusive ranks to

various parameters. The unanticipated part in this analysis was that when one set of

parameters had been ranked till the end of the list, most items with initial top ranks

(referred to as ground rank in the flow diagram) had been eliminated from equal ranked

pools and had been assigned exclusive ranks, a comparison between the statistical ranks

and the ground ranks did not exhibit any difference at all, as can be observed in the table.

This process was then applied to other categories as well to see if difference in sample

sizes caused any deviation and no difference was observed in these cases either.

It was therefore concluded that the exclusive ranks that had been allocated to various

parameters using the Excel based modified rank function were accurate enough to safely

assume that differences did exist between the means. The iteration tables mentioned

above are presented in the following three pages.

137

ITERATIONS 1 2 3 4 5 6 7 8 9

1 - 2 2 - 3 3 - 4 4 -5 5 - 2 5 - 6 6 - 2 7 - 6 8 - 7 CORPORATE CONCERNS

ME

AN

GR

OU

ND

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

A specific project warrants the use of the application 3.22 2 0.002 2 2 2 2 2 2 2 2 2

Generic drive for better business process practices 2.85 7 0.75 3 3

Necessitated due to competitiveness in the industry 2.97 4 0.58 2 2 2 2 3 3 3

Strategic management and business expansion decisions 2.86 6 0.56 2 0.02 3 3 3

Availability of better technologies at lower costs 2.59 13

Clients expectations / demands / preferences 3.50 1 1 1 1 1 1 1 1 1 1

Legal compliance for a particular task 2.92 5 0.84 2 0.08 2 2 3 3 3

Compliance with latest / new quality assurance programs 2.67 10

Drive for greater integration in PM functions 2.71 9

Return on Investments and Financial case justification 2.71 9

Application purchase, licensing, renewal and service costs 2.55 15

Proficiency of current staff in using advanced applications 2.61 12

Need to hire experts or train existing employees etc. 2.43 17

Staff multi-tasking and flexible work distribution 2.53 16

Staff expectations / demand for easier / better softwares 2.58 14

Industry Trends and Anticipated Changes or Developments 2.65 11

Feedback from Clients / Partners / Subcontractors 3.03 3 0.13 2 2 2 2 2 3 3 3

Prior experience with computerization had excellent results 2.78 8 0.48 3

Table 8: Statistical Comparison of Means Pairwise Iterations for Corporate Concerns towards Allocation of Exclusive Ranks

138

ITERATIONS 10 11 12 13 14 15 16 17

8 - 3 8 - 9 9 - 4 10 - 9 10 - 11 11 - 5 12 - 11 12 - 6 CORPORATE CONCERNS

ME

AN

GL

OB

AL

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

A specific project warrants the use of the application 3.22 2 2 2 2 2 2 2 2 2

Generic drive for better business process practices 2.85 7 4 4 5 6 5 6 7 7

Necessitated due to competitiveness in the industry 2.97 4 4 4 4 4 4 4 4 4

Strategic management and business expansion decisions 2.86 6 4 4 5 6 5 6 6 6

Availability of better technologies at lower costs 2.59 13 4 4 5 6 5 6 8 8

Clients expectations / demands / preferences 3.50 1 1 1 1 1 1 1 1 1

Legal compliance for a particular task 2.92 5 4 4 5 5 5 5 5 5

Compliance with latest / new quality assurance programs 2.67 10 5 6 5 6 8 8

Drive for greater integration in PM functions 2.71 9 0.6 4 5 6 5 6 8 8

Return on Investments and Financial case justification 2.71 9 0.6 4 5 6 5 6 8 8

Application purchase, licensing, renewal and service costs 2.55 15 0.89 8

Proficiency of current staff in using advanced applications 2.61 12 8 8

Need to hire experts or train existing employees etc. 2.43 17

Staff multi-tasking and flexible work distribution 2.53 16

Staff expectations / demand for easier / better softwares 2.58 14 0.01 8 8

Industry Trends and Anticipated Changes or Developments 2.65 11 0.75 5 0.03 6 0.75 5 0.03 6 8 8

Feedback from Clients / Partners / Subcontractors 3.03 3 3 3 3 3 3 3 3 3

Prior experience with computerization had excellent results 2.78 8 0.04 4 4 5 6 5 6 8 8

Table 8: Statistical Comparison of Means Pairwise Iterations for Corporate Concerns towards Allocation of Exclusive Ranks (Contd.)

139

ITERATIONS 18 19 20 21 22 23 24 25

13 - 12 14 - 13 14 - 7 15 - 14 16 - 15 16 - 8 16 - 17 17 - 9 CORPORATE CONCERNS

ME

AN

GL

OB

AL

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

P V

AL

UE

RA

NK

A specific project warrants the use of the application 3.22 2 2 2 2 2 2 2 2 2

Generic drive for better business process practices 2.85 7 7 7 7 7 7 7 7 7

Necessitated due to competitiveness in the industry 2.97 4 4 4 4 4 4 4 4 4

Strategic management and business expansion decisions 2.86 6 6 6 6 6 6 6 6 6

Availability of better technologies at lower costs 2.59 13 0.96 7 7 8 8 8 9 9 10

Clients expectations / demands / preferences 3.50 1 1 1 1 1 1 1 1 1

Legal compliance for a particular task 2.92 5 5 5 5 5 5 5 5 5

Compliance with latest / new quality assurance programs 2.67 10 7 7 8 8 8 9 9 10

Drive for greater integration in PM functions 2.71 9 7 7 8 8 8 9 9 9

Return on Investments and Financial case justification 2.71 9 7 7 8 8 8 9 9 9

Application purchase, licensing, renewal and service costs 2.55 15 0.89 8 8 9 9 10

Proficiency of current staff in using advanced applications 2.61 12 7 7 8 8 8 9 9 10

Need to hire experts or train existing employees etc. 2.43 17 0.37 9 0.02 10

Staff multi-tasking and flexible work distribution 2.53 16 0.82 8 0.04 9 9 10

Staff expectations / demand for easier / better softwares 2.58 14 0.82 7 0.01 8 8 8 9 9 10

Industry Trends and Anticipated Changes or Developments 2.65 11 7 7 8 8 8 9 9 10

Feedback from Clients / Partners / Subcontractors 3.03 3 3 3 3 3 3 3 3 3

Prior experience with computerization had excellent results 2.78 8 7 7 8 8 8 8 8 8

Table 8: Statistical Comparison of Means Pairwise Iterations for Corporate Concerns towards Allocation of Exclusive Ranks (Contd.)

5.1.4 Formulation and Analysis of Top Lists

The rankings for the two influencing factors, namely corporate concerns and

implementation barriers; and the three application aspects, namely features, characters and

advances toolsets were then tabulated for all 6 data groups mentioned earlier. This was not

necessitated from the matrix design viewpoint since the matrix design only needs to rate the

priority aspect that is “corporate concerns”, for all data groups.

Tabulated results for all 5 aspects can be seen in Tables 10 through 13 immediately

following Table 9. These also include a column for global rankings which displays the

aggregate ranks for all 74 items as a comparative tool.

These rankings were then used to formulate top-lists for 4 categories, namely large,

midsize, and contracting and program management / CM companies. These top lists are only

guidelines as configured using the data collected through the survey and do not imply that

these are the only criteria that are considered by the industry while considering PM

application enhancements. These top-lists have been presented in figures 39 through 42

immediately following the rating charts.

It can be noticed that the category of “small companies” has been omitted while

preparation of the top-lists. Primal amongst the reasons for this omission was that incidences

of small companies using web-based custom PM applications are very rare. It is also

difficult for such companies to justify huge investments towards such applications since the

use of such advanced tools are neither necessary nor will guarantee returns understanding

that the volume of projects or responsibilities undertaken by such companies is not very

high. In order to develop a design strategy for the decision matrix, both the ratings of

various parameters and the top-lists were done. The top-lists however, are not as important

140

Another critical observation that was made from a review of the top lists as well as the

rating charts was that most of the top rated parameters within the “corporate concerns”

section pertained to corporate functions of the industry and not towards enhancement of PM

process efficiencies. Consider the 12 parameters from the “corporate concerns” area listed

below and categorized as corporate aspects and application aspects. Corporate aspects relate

to various issues that address the corporate concerns of the organization. Application based

aspects are more related to PM efficiencies and issues relating to PM software applications

under consideration.

It was noted here that very few differences existed between the top items in the 5 areas

and 4 categories. For example, if the top ten items from the global rankings for all 5 aspects

were being considered, they encompassed most or all of the top ten items when selected

category-wise. This meant that various trends for software application purchase,

implementation, desirable features and functional aspects, etc were quite universally

applicable and were not unique for the various categories studied.

as the rating charts since they exhibit only the top seven parameters within the “corporate

concerns” and “application features” aspect of software selection and are a representation of

the results obtained thus far. A thorough study of the rating charts from all aspects was

mandated.

141

A specific project warrants the use of the application

Generic drive for better business process practices

Necessitated due to competitiveness in the industry

Client’s expectations / demands / preferences

Feedback from Clients / Partners / Subcontractors

Drive for greater integration in PM functions

CORPORATE ASPECTS

Staff multi-tasking and flexible work distribution

Staff expectations / demand for easier / better softwares

Prior experience with computerization had excellent results

Availabilit

Proficiency of current staff in using advanced applications

Return on Investments and Financial case

y of better technologies at lower costs

justification

APPLICATION BASED ASPECTS

Table 9: Categorization of Various Parameters within Corporate Concerns

GLOBAL LARGE MID-SIZE SMALL CONTRACTORS AFFILIATES

CORPORATE CONCERNS MEAN RANK MEAN RANK MEAN RANK MEAN RANK MEAN RANK MEAN RANK

A specific project warrants the use of the application 3.220 2 3.417 2 2.952 6 3.214 2 3.038 2 3.364 2

Generic drive for better business process practices 2.850 7 2.750 8 2.955 4 2.857 5 2.926 6 2.788 7

Necessitated due to competitiveness in the industry 2.967 4 3.000 4 3.000 3 2.714 8 3.037 3 2.909 5

Strategic management and business expansion decisions 2.864 6 2.696 11 3.136 2 2.786 7 2.963 4 2.781 8

Availability of better technologies at lower costs 2.593 14 2.826 7 2.500 16 2.357 18 2.630 13 2.563 12

Clients expectations / demands / preferences 3.500 1 3.667 1 3.500 1 3.357 1 3.333 1 3.636 1

Legal compliance for a particular task 2.917 5 3.000 5 2.955 5 2.929 4 2.852 8 2.970 4

Compliance with latest / new quality assurance programs 2.667 11 2.917 6 2.591 13 2.500 12 2.630 14 2.697 10

Drive for greater integration in PM functions 2.712 9 2.667 14 2.864 7 2.615 10 2.889 7 2.563 13

Return on Investments and Financial case justification 2.712 10 2.739 10 2.818 10 2.643 9 2.963 5 2.500 15

Application purchase, licensing, renewal and service costs 2.550 16 2.667 15 2.500 17 2.500 13 2.481 17 2.606 11

Proficiency of current staff in using advanced applications 2.610 13 2.652 17 2.682 11 2.571 11 2.667 12 2.563 14

Need to hire experts or train existing employees etc. 2.433 18 2.458 18 2.545 14 2.429 16 2.481 18 2.394 18

Staff multi-tasking and flexible work distribution 2.525 17 2.696 12 2.409 18 2.500 14 2.593 15 2.469 16

Staff expectations / demand for easier / better softwares 2.583 15 2.667 16 2.545 15 2.429 17 2.778 10 2.424 17

Industry Trends and Anticipated Changes or Developments 2.650 12 2.750 9 2.636 12 2.500 15 2.556 16 2.727 9

Feedback from Clients / Partners / Subcontractors 3.033 3 3.208 3 2.864 8 3.143 3 2.815 9 3.212 3

Prior experience with computerization had excellent results 2.780 8 2.696 13 2.864 9 2.857 6 2.704 11 2.844 6

Table 10: Exclusive Rankings of Corporate Concerns for All Categories

142

143

GLOBAL LARGE MID-SIZE SMALL CONTRACTORS AFFILIATES APPLICATION FEATURES

MEAN RANK MEAN RANK MEAN RANK MEAN RANK MEAN RANK MEAN RANK

Executive Collaboration and Decision Support Dashboards 2.571 18 2.565 19 2.636 14 2.250 19 2.667 16 2.500 18

Proposals, Contracts and Bid Management, Details and Status 3.161 9 3.217 10 3.227 7 2.917 10 3.125 10 3.188 9

Contract Administration, Finance, Insurance and Records 3.375 5 3.348 8 3.455 2 3.417 2 3.333 7 3.406 4

Work Breakdown, Planning, Scheduling and Monitoring 3.464 4 3.739 1 3.227 8 3.333 6 3.333 8 3.563 1

Vendor databases, Management, Procurements, Tracking 3.000 11 3.130 12 2.955 10 2.750 13 3.208 9 2.844 12

Subcontractor Collaboration, Work Allocation, Payments, RFIs 3.357 6 3.478 5 3.136 9 3.417 3 3.500 3 3.250 8

Purchase Orders, Tracking and Related Documentation 3.321 8 3.391 7 3.455 3 2.917 11 3.375 5 3.281 6

Change Orders, Managing, Documenting and Collaboration. 3.589 1 3.609 2 3.545 1 3.667 1 3.708 1 3.500 3

Submittals, Management, Approval and Review Cycles 3.482 2 3.522 4 3.409 5 3.417 4 3.583 2 3.406 5

Project Budgets, Financial Analysis, Monitoring and Cash Flows 3.482 3 3.565 3 3.455 4 3.417 5 3.375 6 3.563 2

Equipment Management, Allocation, Tracking and Expenses 2.545 19 2.783 17 2.524 17 2.333 17 2.667 17 2.452 19

Resource Management, Forecasting, Availability and Utilization 2.768 14 3.000 14 2.636 15 2.583 14 2.750 15 2.781 14

Risk Management, Identification, Planning, Mitigation 2.786 13 2.739 18 2.773 12 2.917 12 2.917 12 2.688 16

Material Management, Inventory Control, Usage and Insurance 2.643 16 2.913 15 2.591 16 2.333 18 2.792 14 2.531 17

Operations Management and Workflow Analysis 2.636 17 2.913 16 2.524 18 2.500 16 2.542 19 2.710 15

Partner Management, Investments, Portfolios and Collaboration 2.179 20 2.522 20 1.909 20 2.083 20 2.125 20 2.219 20

Enterprise wide assessment of schedule and budget impacts 2.750 15 3.174 11 2.409 19 2.583 15 2.625 18 2.844 13

Daily Logs, Rosters, Meeting Minutes, Letters and Reports 3.339 7 3.435 6 3.273 6 3.333 7 3.417 4 3.281 7

Periodic Reporting Cycles, Statistics, Timelines, Progress Rates 3.036 10 3.304 9 2.773 13 3.000 8 3.000 11 3.063 10

Reports, Notices, Memos, Invoices and Other Documentation 2.982 12 3.043 13 2.909 11 3.000 9 2.875 13 3.063 11

Table 11: Exclusive Rankings of Application Features for All Categories

GLOBAL LARGE MID-SIZE SMALL CONTRACTORS AFFILIATES APPLICATION CHARACTERS


3.400 5 3.650 3 3.409 3 3.000 10 3.458 3 3.379 5 Backward Compatibility with Legacy Systems

3.309 8 3.545 6 3.182 8 2.917 12 3.250 8 3.355 6 Scalability and Customization for individual business needs

3.018 16 3.318 13 2.909 18 2.750 16 2.958 14 3.065 15 Hardware Resource Requirements of the Application

3.000 17 3.045 18 3.182 9 2.833 13 2.958 15 3.032 16 Initial Cost of the Software Application

3.036 15 3.136 17 3.045 13 3.083 9 3.125 10 2.968 18 Costs for License renewal, Extension and Upgrades

3.164 11 3.227 15 3.045 14 3.417 1 3.042 13 3.258 10 Toolsets and Functional Features of the Application

3.545 1 3.727 1 3.409 4 3.417 2 3.542 2 3.548 1 Communication and Networking Capabilities

3.091 13 3.409 9 3.000 17 2.833 14 2.917 17 3.226 11 Compatibility with Generic Devices like PDAs and Laptops

3.327 7 3.500 7 3.318 5 3.000 11 3.333 7 3.323 9 Business data security concerns

3.491 2 3.591 4 3.500 1 3.250 4 3.625 1 3.387 3 Vulnerability of Application to viruses and system bugs

3.418 4 3.500 8 3.318 6 3.417 3 3.458 4 3.387 4 Data storage, interpretation, access and visibility aspects

3.200 10 3.318 14 3.091 11 3.167 7 3.167 9 3.226 12 Data Entry Protocols and Output Report Formats

3.236 9 3.409 10 3.045 15 3.167 8 3.083 11 3.355 7 Data Transfer to/from Other Computers and Devices.

3.491 3 3.682 2 3.500 2 3.250 5 3.458 5 3.516 2 Ease-of-Use and User Friendly Interfaces

3.091 14 3.364 11 3.091 12 2.667 17 2.917 18 3.226 13 Compatibility with other Office Solutions Applications

3.000 18 3.227 16 3.045 16 2.500 18 2.958 16 3.032 17 Projected Life, in terms of Utility, of Software Application

3.164 12 3.364 12 3.182 10 2.833 15 3.083 12 3.226 14 Easy to procure, Install, Customize and Upgrade

3.364 6 3.591 5 3.273 7 3.250 6 3.375 6 3.355 8 Strong Customer and Technical Support / Documentations

Table 12: Exclusive Rankings of Application Functional Characteristics for All Categories

144

GLOBAL LARGE MID-SIZE SMALL CONTRACTORS AFFILIATES ADVANCED TOOLSETS


3.327 1 3.545 1 3.273 1 3.000 1 3.200 1 3.433 1 Integrated estimating, scheduling and project monitoring tools 2.509 5 2.727 4 2.455 5 2.167 6 2.440 7 2.567 4 4D (time-bound 3D) process visualization and simulation 2.236 8 2.591 5 2.136 8 1.833 9 2.480 5 2.033 9 Global or continental vendor / subcontractor databases 2.582 4 2.500 8 2.591 4 2.750 4 2.640 4 2.533 5 Onsite wireless technologies with automated data acquisition 3.055 2 3.136 2 3.091 2 2.750 5 3.040 2 3.067 2 Lessons learned and prior project execution / experience databases 2.111 9 2.238 9 2.091 9 2.000 8 2.080 9 2.138 8 Automated algorithm-based optimized resource allocation 2.296 7 2.571 6 2.182 7 2.083 7 2.320 8 2.276 7 Central regulatory and compliances databases 2.426 6 2.524 7 2.227 6 2.833 3 2.480 6 2.379 6 Automated simulations for change management decision-making 2.759 3 2.857 3 2.636 3 3.000 2 2.720 3 2.793 3 Centralized network-based limited-access monitoring for all parties

Table 13: Exclusive Rankings of Advanced Application Features for All Categories

GLOBAL LARGE MID-SIZE SMALL CONTRACTORS AFFILIATES BARRIERS


2.852 5 2.864 6 2.857 3 2.833 4 2.958 4 2.767 5 Lack of precedents of application usage in the industry

3.321 1 3.429 1 3.286 1 3.250 1 3.292 1 3.345 1 Major investment without guarantee of success and/or returns

2.574 7 2.818 7 2.333 8 2.583 7 2.500 8 2.633 7 Necessity of high computing proficiency levels in senior management

2.887 4 3.182 4 2.810 5 2.727 6 2.917 6 2.862 4 Apprehension regarding start-up issues during critical ongoing projects

2.259 9 2.273 9 2.381 7 2.083 9 2.292 9 2.233 9 Preference for old-style paper-based / existing management protocols

2.852 6 3.182 5 2.571 6 2.750 5 2.958 5 2.767 6 Concerns regarding data security and confidential strategic business plans

3.056 3 3.227 2 2.857 4 3.083 2 3.042 3 3.067 2 Lack of applications that may rapidly be customized to suit our firm

3.057 2 3.227 3 2.900 2 3.083 3 3.250 2 2.897 3 Concerns about application bugs that may result in financial risks / losses

2.444 8 2.591 8 2.238 9 2.583 8 2.667 7 2.267 8 Downtime owing to upgrade of existing setup and existing data entry

Table 14: Exclusive Rankings of Barriers in Implementation for All Categories

145

TOP LISTS FOR LARGE COMPANIES

Clients’ expectations / demands / preferences

A sp

APPLICATION FEATURES

CORPORATE CONCERNS

Work Breakdown, Planning, Scheduling and Monitoring

ecific project warrants the use of the application Change Orders, Managing, Documenting and Collaboration

Feedback from Clients / Partners / Subcontractors Project Budgets, Financial Analysis, Monitoring and Cash Flows

Necessitated due to competitiveness in the industry Submittals, Management, Approval and Review Cycles

Legal compliance for a particular task Subcontractor Collaboration, Work Allocation, Payments, RFIs

Compliance with latest / new quality assurance programs Daily Logs, Rosters, Meeting Minutes, Letters and Reports

Availability of better technologies at lower costs Purchase Orders, Tracking and Related Documentation

Figure 39: Top Lists for Large Companies

146

TOP LISTS FOR MIDSIZE COMPANIES


CORPORATE CONCERNS

Clients’ expectations / demands / preferences Change Orders, Managing, Documenting and Collaboration

Strategic management and business expansion decisions Contract Administration, Finance, Insurance and Records

Purchase Orders, Tracking and Related Documentation Necessitated due to competitiveness in the industry

Generic drive for better business process practices Project Budgets, Financial Analysis, Monitoring and Cash Flows

Legal compliance for a particular task Submittals, Management, Approval and Review Cycles

A specific project warrants the use of the application Daily Logs, Rosters, Meeting Minutes, Letters and Reports

Drive for greater integration in PM functions Proposals, Contracts and Bid Management, Details and Status

Figure 40: Top Lists for Midsize Companies

147

TOP LISTS FOR GENERAL CONTRACTING COMPANIES




Strategic management and business expansion decisions

Return on Investments and Financial case justification


Drive for greater integration in PM functions

Change Orders, Managing, Documenting and Collaboration

Submittals, Management, Approval and Review Cycles

Purchase Orders, Tracking and Related Documentation

Daily Logs, Rosters, Meeting Minutes, Letters and Reports


Project Budgets, Financial Analysis, Monitoring and Cash Flows

Contract Administration, Finance, Insurance and Records


CORPORATE CONCERNS

Figure 41: Top Lists for Contracting Companies

148

TOP LISTS FOR PROGRAM MANAGEMENT COMPANIES



Feedback from Clients / Partners / Subcontractors

Legal compliance for a particular task


Prior experience with computerization had excellent results



Project Budgets, Financial Analysis, Monitoring and Cash Flows

Change Orders, Managing, Documenting and Collaboration

Contract Administration, Finance, Insurance and Records





CORPORATE CONCERNS

Figure 42: Top Lists for Program Management Companies

149

5.2 STRATEGY FOR MODEL FORMULATION

Since it is evident logically as well as manifest from the studies so far, aspects

associated with PM applications enhancements, as explained above, circle around the core

corporate concerns that the organization prescribes to. It is also worth a mention here that in

most situations where companies are faced with the dilemma of selecting software tools that

best fit their organization, the only parameters known to them are their corporate concerns.

All other demands, needs and desirables are initially unknown and are derived from such

concerns or drivers.

The strategy developed to design the decision matrix is founded on this logic. Since the

top parameters in each of the 5 areas were already known, compiling a simple list of all of

these was thought of as a simple solution. In such case, however, all of these parameters

would be independent of each other and no justification could be provided as to which

particular ones should be chosen. Understanding that senior management and project

professionals know their needs and also purportedly know of available computing facilities,

reproducing a set of parameters listed per their relative importance as dictated by industry

trends did not make sense.

In order to formulate a roadmap or a guide that would allow them to relate various

parameters from various categories and lead them from one point to another, or rather from

the start to the end, it was decided to establish associations between all of the essential

parameters. If a company is able to center down on its primary corporate concerns, such an

interacting structure would allow them to follow the path directed by this model and

eventually center down upon all requisites. Since the matrix is based on statistical grounds

and it is quite difficult to guarantee that a statistically designed model can replicate realities

150

exactly, missing links may or may not exist are and if present, can always be overcome

using simple knowledge based logic. This forms the essential foundation on which the

matrix is based.

5.2.1 Determination of Statistical Correlations

Keeping in mind the nature of the data and the aims of the study, it was decided that

using MS Excel’s in-built regression tool to establish associations, despite being simpler and

less tedious, would not be accurate since the distribution of data is not known. Literature

review reveals that researchers have used this tool to establish associations by testing the

correlation for all available distributions and then accepting the one that elicits the

maximum value or R2, R2 being the coefficient of correlation where,

tionTotalVariaariationExplainedVr =

Though this technique does yield valid results, its applicability by itself becomes

debatable. This is because the computed value of R, and therefore R2, measures the degree

of the relationship relative to the type of equation that is actually assumed. Therefore, if a

linear (or any other) equation is assumed and the value of R2 is found to be 0, it is only

indicative that a linear relationship does not exist, not that a correlation does not exist

(Spiegel, 1992). It has also been noted that it is possible to increase the value of R2 by

increasing the range of the regressor (dependent) variable and that a large value of R2 does

not imply that the relationship or the equation thereof is an accurate predictor (Montgomery

and Peck, 1982). Cases have been presented by statisticians where the relationships

151

between the variables were known to be non-linear but a linear regression model presented

large values of R2 (Montgomery and Peck, 1982).

Moreover, it is also possible to establish statistical regression-based relationships

between variables that are completely independent and unrelated in the practical or logical

sense. Then again, development of predictor equations that may be used to quantify

dependent variables (like features, application characteristics, etc. in this case), given the

values of regressors (like corporate concerns) or asserting causative or any other form of

relationship was beyond the scope of this study.

It was therefore decided to use simple non-parametric technique that was more apt

considering the nature of the data and to follow up the results with logical arguments. The

Spearman non-parametric test for rank correlation was found suitable in that the Spearman

R is an equivalent of the Pearson R except that the Spearman R is computed on the basis on

ranks (or ordinal data) which was the true nature in this case. The equation for Spearman’s

R is given below.

)1(6

2

2

−∑NN

Dr

Here, D is the difference between the ranks of corresponding values of the two variables

and N is the sample size. SAS programming based on PROC CORR was used to determine

whether or not a correlation existed by observing the P values for the hypothesis as shown.

H0: σ = 0

HA: σ ≠ 0

s = 1 -

152

P values lesser that 0.05 exhibit that a correlation exists at the α = 0.05 significance

level. Further analysis is explained in the following sub-sections.

Considering that only one parameter could be tested against a group at a time, the same

program with altered data sets was run over 110 times and the results transcribed on paper.

The tabulated results were then entered into an MS Excel worksheet with conditional

formatting to highlight strong correlations automatically. The entire data entry was

rechecked twice by columns and by rows to obviate any user errors while entering the data

manually. These correlations have been presented in subsequent pages extending form

Tables 15 through table 20.

5.2.2 Logical Inferencing and Table Notations

Coefficient of correlation values range from 1 to -1. A value of 1 or -1 reflects a perfect

relationship since all of the variation in the dependent variable can be explained based on

the independent variable. A value of 0 indicates no relationship and was therefore the null

hypothesis condition in this case. Positive values of correlation coefficient indicate a direct

proportionality and negative values indicate indirect relationships between the variables.

The default significance level used by PROC CORR (and most other procedures) in SAS

is 0.05. There are several different interpretations of this significance value in various annals

of statistics. One meaning of achieving a result at a 0.05 level means that if the sample sizes

were unlimited (or tended to infinity) then there is 95% likelihood that the similar results

shall be obtained. The SAS Institutes way of saying this is that there is a less than 0.05%

probability that the results obtained have been arrived at by chance (Schlotzhauer, 1991).

153

The design of the decision matrix aimed to enable users to configure, given their

priorities, the other essential aspects of web-based or other PM applications that would gain

importance. Towards this end, it was decided that only positive upward sloping associations

should be used. Since the aim of the matrix is to inform users on what accessories shall

accompany their primal requirements and not those that shall not, negatively correlated

parameters were excluded from the matrix design. The ‘r’ or the ‘p’ values do not however

indicate the type of relationships that exist between the variables. In order to determine this,

another SAS program was created to develop plots of the variable correlations.

Only established correlations pertaining to parameters that were being used towards the

matrix design were studied. The tables shown on the following pages include p values

collected from the results of the Spearman Rank Correlation test. Cells shaded in pink

indicate those associations that reflected p values of less than 0.05. P values displayed as

0.000 are ones that reflected values lesser than 0.001. Cells shaded light golden indicate p

values between 0.1 and 0.05, which are also established associations with a lesser

confidence level. This was done during the initial stages of the analysis to allow an insight

into other aspects that might be important, but was not used at all since it was deemed

unnecessary.

Of these, a total of 52 parameters including top 12 corporate concerns (6 omitted), 15

application features (5 omitted), 15 application characteristics (3 omitted) and 5 each of

advanced tools and deployment barriers (4 in each omitted) were tested. The program was

run 145 times with different sets of data. Of these, 9 were found to be downward sloping

(inversely related) and one was a horizontal relationship. Upward sloping ones that indicated

154

155

increase in the dependent variable with increase in the independent variable were used for

plotting the relationships and subsequent design of the decision matrix.

Certain remarkable observations were made during the process of plotting the said

associations and the matrix design. It was seen that quite a few parameters that have been

attributed top ranks based on the survey questionnaire do not truly seem to be correlated

with most other top factors from other areas. It was also noticed that the associations with

barriers in implementation had extremely rare. These are discussed further in later sections.

156

SPEARMANS CORRELATION BETWEEN CORPORATE CONCERNS AND


Exec

utiv

e C

olla

bora

tion

and

Dec

isio

n Su

ppor

tD

ashb

oard

s

Prop

osal

s, C

ontra

cts a

nd B

id M

anag

emen

t, D

etai

ls a

nd S

tatu

s

Con

tract

Adm

inis

tratio

n, F

inan

ce, I

nsur

ance

an

d R

ecor

ds

Wor

k B

reak

dow

n, P

lann

ing,

Sch

edul

ing

and

Mon

itorin

g

Ven

dor d

atab

ases

, Man

agem

ent,

Proc

urem

ents

, Tra

ckin

g

Subc

ontra

ctor

Col

labo

ratio

n, W

ork

Allo

catio

n, P

aym

ents

, RFI

s

Purc

hase

Ord

ers,

Trac

king

and

Rel

ated

D

ocum

enta

tion

Man

agem

ent

Cha

nge

Ord

ers,

Man

agin

g, D

ocum

entin

g an

d C

olla

bora

tion.

Subm

ittal

s, M

anag

emen

t, A

ppro

val a

nd

Rev

iew

Cyc

les

Proj

ect B

udge

ts, F

inan

cial

Ana

lysi

s, M

onito

ring

and

Cas

h Fl

ows

Equi

pmen

t Man

agem

ent,

Allo

catio

n,

Trac

king

and

Exp

ense

s

Res

ourc

e M

anag

emen

t, Fo

reca

stin

g,

Ava

ilabi

lity

and

Util

izat

ion

Ris

k M

anag

emen

t, Id

entif

icat

ion,

Pla

nnin

g,

Miti

gatio

n

Mat

eria

l Man

agem

ent,

Inve

ntor

y C

ontro

l, U

sage

and

Insu

ranc

e

Ope

ratio

ns M

anag

emen

t and

Wor

kflo

w

Ana

lysi

s

Partn

er M

anag

emen

t, In

vest

men

ts, P

ortfo

lios

and

Col

labo

ratio

n

Ente

rpris

e w

ide

asse

ssm

ent o

f sch

edul

e an

d bu

dget

impa

cts

Dai

ly L

ogs,

Ros

ters

, Mee

ting

Min

utes

, Let

ters

an

d R

epor

ts

Perio

dic

Rep

ortin

g C

ycle

s, St

atis

tics,

Tim

elin

es, P

rogr

ess R

ates

Rep

orts

, Not

ices

, Mem

os, I

nvoi

ces a

nd O

ther

D

ocum

enta

tion

A specific project warrants the use of the application 0.569 0.281 0.363 0.751 0.011 0.008 0.270 0.075 0.114 0.809 0.224 0.667 0.503 0.584 0.649 0.627 0.390 0.658 0.156 0.755

Generic drive for better business process practices 0.218 0.638 0.206 0.570 0.452 0.466 0.718 0.034 0.084 0.064 0.037 0.556 0.007 0.213 0.913 0.393 0.821 0.118 0.338 0.068

Necessitated due to competitiveness in the industry 0.885 0.679 0.143 0.679 0.461 0.064 0.057 0.042 0.200 0.483 0.324 0.002 0.007 0.024 0.075 0.291 0.291 0.660 0.602 0.067

Strategic management and business expansion decisions 0.000 0.514 0.305 0.159 0.711 0.411 0.326 0.037 0.116 0.127 0.429 0.409 0.399 0.273 0.161 0.443 0.423 0.232 0.183 0.441

Availability of better technologies at lower costs 0.007 0.816 0.532 0.086 0.693 0.589 0.705 0.514 0.225 0.286 0.912 0.770 0.734 0.469 0.110 0.349 0.425 0.905 0.513 0.852

Clients expectations / demands / preferences 0.379 0.216 0.752 0.665 0.125 0.483 0.230 0.672 0.570 0.756 0.834 0.387 0.667 0.447 0.837 0.105 0.253 0.681 0.337 0.687

Legal compliance for a particular task 0.757 0.695 0.045 0.472 0.791 0.710 0.929 0.811 0.080 0.284 0.432 0.472 0.164 0.090 0.631 0.069 0.870 0.481 0.302 0.651

Compliance with latest / new quality assurance programs 0.320 0.321 0.132 0.052 0.122 0.146 0.253 0.166 0.859 0.002 0.109 0.000 0.003 0.003 0.196 0.019 0.004 0.545 0.008 0.312

Drive for greater integration in PM functions 0.009 0.406 0.035 0.027 0.121 0.027 0.036 0.019 0.023 0.039 0.077 0.102 0.307 0.559 0.084 0.324 0.102 0.193 0.804 0.615

Return on Investments and Financial case justification 0.001 0.716 0.097 0.265 0.417 0.167 0.209 0.194 0.021 0.118 0.267 0.345 0.117 0.911 0.330 0.603 0.952 0.049 0.297 0.124

Application purchase, licensing, renewal and service costs 0.792 0.931 0.304 0.471 0.444 0.063 0.615 0.216 0.811 0.531 0.218 0.726 0.552 0.054 0.664 0.048 0.304 0.836 0.364 0.441

Proficiency of current staff in using advanced applications 0.009 0.332 0.197 0.455 0.226 0.064 0.840 0.042 0.254 0.507 0.496 0.228 0.024 0.027 0.237 0.009 0.375 0.697 0.615 0.670

Need to hire experts or train existing employees etc. 0.704 0.706 0.947 0.568 0.357 0.729 0.367 0.596 0.634 0.968 0.946 0.681 0.928 0.515 0.424 0.911 0.489 0.894 0.509 0.781

Staff multi-tasking and flexible work distribution 0.000 0.243 0.188 0.007 0.110 0.224 0.508 0.159 0.017 0.049 0.591 0.201 0.302 0.894 0.065 0.051 0.080 0.363 0.030 0.753

Staff expectations / demand for easier / better softwares 0.920 0.443 0.614 0.160 0.332 0.297 0.097 0.352 0.487 0.827 0.224 0.132 0.985 0.039 0.022 0.173 0.037 0.247 0.935 0.387

Industry Trends and Anticipated Changes or Developments 0.896 0.342 0.685 0.012 0.446 0.179 0.636 0.184 0.087 0.297 0.266 0.109 0.051 0.535 0.046 0.885 0.033 0.127 0.090 0.001

Feedback from Clients / Partners / Subcontractors 0.773 0.785 0.438 0.270 0.922 0.578 0.818 0.279 0.519 0.630 0.573 0.268 0.267 0.694 0.431 0.015 0.013 0.326 0.003 0.549

Prior Experience with computerization had excellent results 0.001 0.306 0.010 0.014 0.202 0.193 0.181 0.013 0.286 0.241 0.579 0.128 0.040 0.950 0.794 0.042 0.299 0.181 0.155 0.399

Table 15: P Values from Spearman’s Test for Correlation between Corporate Concerns and Application Features

157

SPEARMANS CORRELATION BETWEEN

CORPORATE CONCERNS AND APPLICATION CHARACTERISTICS

Bac

kwar

d C

ompa

tibili

ty w

ith

Lega

cy S

yste

ms

Scal

abili

ty a

nd C

usto

miz

atio

n fo

r in

divi

dual

bus

ines

s nee

ds

Har

dwar

e R

esou

rce

Req

uire

men

ts

of th

e A

pplic

atio

n

Initi

al C

ost o

f the

Sof

twar

e A

pplic

atio

n

Cos

ts fo

r Lic

ense

rene

wal

, Ex

tens

ion

and

Upg

rade

s

Tool

sets

and

Fun

ctio

nal F

eatu

res

of th

e A

pplic

atio

n

Com

mun

icat

ion

and

Net

wor

king

C

apab

ilitie

s

Com

patib

ility

with

Gen

eric

D

evic

es li

ke P

DA

s and

Lap

tops

Bus

ines

s dat

a se

curit

y co

ncer

ns

Vul

nera

bilit

y of

App

licat

ion

to

viru

ses a

nd sy

stem

bug

s

Dat

a st

orag

e, in

terp

reta

tion,

acc

ess

and

visi

bilit

y as

pect

s

Dat

a En

try P

roto

cols

and

Out

put

Rep

ort F

orm

ats

Dat

a Tr

ansf

er to

/from

Oth

er

Com

pute

rs a

nd D

evic

es.

Ease

-of-

Use

and

Use

r Frie

ndly

In

terf

aces

Com

patib

ility

with

oth

er O

ffic

e So

lutio

ns A

pplic

atio

ns

Proj

ecte

d Li

fe, i

n te

rms o

f Util

ity,

of S

oftw

are

App

licat

ion

Easy

to p

rocu

re, I

nsta

ll, C

usto

miz

e an

d U

pgra

de

Stro

ng C

usto

mer

and

Tec

hnic

al

Supp

ort

/ Doc

umen

tatio

ns

A specific project warrants the use of the application 0.202 0.421 0.186 0.820 0.280 0.105 0.405 0.168 0.170 0.387 0.412 0.815 0.316 0.750 0.642 0.404 0.585 0.151

Generic drive for better business process practices 0.797 0.714 0.799 0.466 0.374 0.960 0.768 0.898 0.414 0.575 0.841 0.596 0.968 0.483 0.763 0.986 0.325 0.515

Necessitated due to competitiveness in the industry 0.070 0.089 0.528 0.923 0.402 0.420 0.780 0.141 0.151 0.086 0.957 0.565 0.840 0.006 0.024 0.043 0.039 0.806

Strategic management and business expansion decisions 0.466 0.925 0.573 0.180 0.092 0.881 0.568 0.493 0.061 0.096 0.775 0.776 0.752 0.052 0.190 0.432 0.189 0.299

Availability of better technologies at lower costs 0.010 0.625 0.027 0.014 0.062 0.344 0.948 0.095 0.264 0.941 0.763 0.215 0.109 0.081 0.000 0.008 0.856 0.398

Clients expectations / demands / preferences 0.044 0.085 0.193 0.137 0.290 0.155 0.070 0.783 0.061 0.574 0.285 0.393 0.138 0.150 0.378 0.768 0.001 0.050

Legal compliance for a particular task 0.244 0.181 0.107 0.257 0.012 0.209 0.250 0.141 0.004 0.049 0.603 0.884 0.553 0.044 0.796 0.171 0.004 0.576

Compliance with latest / new quality assurance programs 0.253 0.201 0.251 0.897 0.127 0.055 0.741 0.316 0.011 0.357 0.205 0.670 0.801 0.027 0.187 0.057 0.086 0.605

Drive for greater integration in PM functions 0.095 0.923 0.510 0.071 0.176 0.119 0.725 0.078 0.119 0.469 0.460 0.019 0.055 0.160 0.000 0.004 0.563 0.400

Return on Investments and Financial case justification 0.853 0.995 0.252 0.900 0.094 0.797 0.874 0.649 0.031 0.026 0.758 0.288 0.809 0.220 0.310 0.134 0.030 0.806

Application purchase, licensing, renewal and service costs 0.582 0.145 0.544 0.618 0.008 0.871 0.629 0.219 0.063 0.085 0.868 0.687 0.906 0.019 0.269 0.090 0.038 0.216

Proficiency of current staff in using advanced applications 0.485 0.615 0.411 0.022 0.551 0.853 0.864 0.822 0.405 0.340 0.776 0.652 0.988 0.058 0.588 0.705 0.009 0.665

Need to hire experts or train existing employees etc. 0.346 0.550 0.357 0.878 0.127 0.918 0.873 0.173 0.053 0.229 0.989 0.679 0.732 0.428 0.348 0.626 0.022 0.818

Staff multi-tasking and flexible work distribution 0.072 0.261 0.182 0.677 0.053 0.192 0.829 0.056 0.421 0.922 0.586 0.392 0.879 0.239 0.451 0.049 0.023 0.258

Staff expectations / demand for easier / better softwares 0.071 0.198 0.467 0.972 0.045 0.994 0.173 0.278 0.195 0.572 0.970 0.328 0.936 0.005 0.271 0.081 0.295 0.041

Industry Trends and Anticipated Changes or Developments 0.173 0.066 0.543 0.792 0.013 0.344 0.282 0.133 0.215 0.660 0.945 0.216 0.500 0.111 0.232 0.006 0.273 0.062

Feedback from Clients / Partners / Subcontractors 0.540 0.814 0.103 0.730 0.647 0.202 0.207 0.358 0.938 0.131 0.875 0.184 0.217 0.496 0.858 0.306 0.073 0.159

Prior Experience with computerization had excellent results 0.677 0.919 0.571 0.012 0.115 0.103 0.830 0.954 0.049 0.676 0.554 0.368 0.169 0.553 0.551 0..723 0.155 0.389

Table 16: P Values from Spearman’s Test for Correlation between Corporate Concerns and Application Characteristics

158

ADVANCED FEATURES BARRIERS

SPEARMANS CORRELATION BETWEEN CORPORATE

CONCERNS, ADVANCED FEATURES AND BARRIERS

Inte

grat

ed e

stim

atin

g, sc

hedu

ling

and

proj

ect m

onito

ring

tool

s

4D (t

ime-

boun

d 3D

) pro

cess

vis

ualiz

atio

n an

d si

mul

atio

n

Glo

bal o

r con

tinen

tal v

endo

r /

subc

ontra

ctor

dat

abas

es

Ons

ite w

irele

ss te

chno

logi

es w

ith

auto

mat

ed d

ata

acqu

isiti

on

Less

ons l

earn

ed a

nd p

rior p

roje

ct e

xecu

tion

/ exp

erie

nce

data

base

s

Aut

omat

ed a

lgor

ithm

-bas

ed o

ptim

ized

re

sour

ce a

lloca

tion

Cen

tral r

egul

ator

y an

d co

mpl

ianc

es

data

base

s

Aut

omat

ed si

mul

atio

ns fo

r cha

nge

man

agem

ent d

ecis

ion-

mak

ing

Cen

traliz

ed n

etw

ork-

base

d lim

ited-

acce

ss

mon

itorin

g fo

r all

parti

es

Lack

of p

rece

dent

s of a

pplic

atio

n us

age

in

the

indu

stry

Maj

or in

vest

men

t with

out g

uara

ntee

of

succ

ess a

nd/o

r ret

urns

Nec

essi

ty o

f hig

h co

mpu

ting

prof

icie

ncy

leve

ls in

seni

or m

anag

emen

t

App

rehe

nsio

n re

gard

ing

star

t-up

issu

es

durin

g cr

itica

l ong

oing

pro

ject

s

Pref

eren

ce fo

r old

-sty

le p

aper

-bas

ed /

exis

ting

man

agem

ent p

roto

cols

Con

cern

s reg

ardi

ng d

ata

secu

rity

and

conf

iden

tial s

trate

gic

busi

ness

pla

ns

Lack

of a

pplic

atio

ns th

at m

ay ra

pidl

y be

cu

stom

ized

to su

it ou

r firm

Con

cern

s abo

ut a

pplic

atio

n bu

gs th

at m

ay

resu

lt in

fina

ncia

l ris

ks /

loss

es

Dow

ntim

e ow

ing

to u

pgra

de o

f exi

stin

g se

tup

and

exis

ting

data

ent

ry

A specific project warrants the use of the application 0.614 0.124 0.613 0.659 0.174 0.709 0.985 0.636 0.699 0.655 0.877 0.431 0.742 0.428 0.127 0.157 0.375 0.279

Generic drive for better business process practices 0.110 0.123 0.967 0.686 0.648 0.240 0.635 0.424 0.865 0.460 0.876 0.622 0.823 0.532 0.675 0.835 0.258 0.938

Necessitated due to competitiveness in the industry 0.639 0.494 0.476 0.306 0.000 0.509 0.381 0.067 0.307 0.233 0.676 0.817 0.175 0.119 0.806 0.282 0.792 0.706

Strategic management and business expansion decisions 0.779 0.657 0.692 0.691 0.656 0.878 0.307 0.837 0.512 0.204 0.655 0.203 0.587 0.019 0.912 0.310 0.877 0.166

Availability of better technologies at lower costs 0.996 0.648 0.007 0.142 0.284 0.060 0.266 0.900 0.595 0.022 0.127 0.375 0.929 0.604 0.063 0.203 0.266 0.977

Clients expectations / demands / preferences 0.265 0.030 0.634 0.155 0.751 0.410 0.069 0.052 0.016 0.403 0.522 0.243 0.903 0.064 0.346 0.875 0.414 0.383

Legal compliance for a particular task 0.927 0.990 0.060 0.927 0.914 0.697 0.188 0.202 0.989 0.192 0.772 0.978 0.597 0.222 0.363 0.904 0.240 0.084

Compliance with latest / new quality assurance programs 0.246 0.721 0.060 0.961 0.209 0.236 0.003 0.046 0.046 0.375 0.242 0.271 0.639 0.002 0.981 0.945 0.814 0.341

Drive for greater integration in PM functions 0.955 0.897 0.058 0.435 0.024 0.378 0.014 0.695 0.090 0.656 0.135 0.563 0.699 0.166 0.939 0.640 0.879 0.463

Return on Investments and Financial case justification 0.974 0.606 0.001 0.554 0.263 0.608 0.020 0.050 0.039 0.144 0.523 0.152 0.712 0.545 0.205 0.748 0.287 0.465

Application purchase, licensing, renewal and service costs 0.324 0.269 0.150 0.174 0.460 0.363 0.531 0.574 0.579 0.788 0.484 0.734 0.111 0.995 0.429 0.443 0.928 0.168

Proficiency of current staff in using advanced applications 0.592 0.751 0.094 0.630 0.796 0.240 0.080 0.024 0.082 0.399 0.855 0.811 0.637 0.669 0.229 0.206 0.873 0.443

Need to hire experts or train existing employees etc. 0.971 0.632 0.303 0.101 0.361 0.084 0.465 0.629 0.859 0.071 0.066 0.404 0.437 0.616 0.774 0.174 0.691 0.113

Staff multi-tasking and flexible work distribution 0.953 0.312 0.117 0.823 0.129 0.084 0.433 0.030 0.207 0.783 0.237 0.825 0.119 0.183 0.498 0.949 0.331 0.941

Staff expectations / demand for easier / better softwares 0.906 0.359 0.187 0.251 0.388 0.407 0.676 0.651 0.940 0.310 0.991 0.464 0.876 0.351 0.603 0.753 0.949 0.175

Industry Trends and Anticipated Changes or Developments 0.929 0.703 0.782 0.949 0.100 0.724 0.807 0.820 0.936 0.447 0.415 0.995 0.897 0.296 0.330 0.689 0.197 0.610

Feedback from Clients / Partners / Subcontractors 0.087 0.155 0.184 0.167 0.075 0.058 0.071 0.023 0.004 0.819 0.914 0.823 0.737 0.131 0.808 0.636 0.538 0.515

Prior Experience with computerization had excellent results 0.487 0.681 0.318 0.538 0.099 0.078 0.114 0.060 0.188 0.026 0.848 0.061 0.337 0.289 0.236 0.007 0.203 0.118

Table 17: P Values from Spearman’s Test for Correlation between Corporate Concerns with Advanced Toolsets and Deployment Barriers

159

SPEARMANS CORRELATION APPLICATION FEATURES AND

CHARACTERISTICS

Bac

kwar

d C

ompa

tibili

ty w

ith

Lega

cy S

yste

ms

Scal

abili

ty a

nd C

usto

miz

atio

n fo

r in

divi

dual

bus

ines

s nee

ds

Har

dwar

e R

esou

rce

Req

uire

men

ts o

f th

e A

pplic

atio

n

Initi

al C

ost o

f the

Sof

twar

e A

pplic

atio

n

Cos

ts fo

r Lic

ense

rene

wal

, Ex

tens

ion

and

Upg

rade

s

Tool

sets

and

Fun

ctio

nal F

eatu

res o

f th

e A

pplic

atio

n

Com

mun

icat

ion

and

Net

wor

king

C

apab

ilitie

s

Com

patib

ility

with

Gen

eric

Dev

ices

lik

e PD

As a

nd L

apto

ps

Bus

ines

s dat

a se

curit

y co

ncer

ns

Vul

nera

bilit

y of

App

licat

ion

to

viru

ses a

nd sy

stem

bug

s

Dat

a st

orag

e, in

terp

reta

tion,

acc

ess

and

visi

bilit

y as

pect

s

Dat

a En

try P

roto

cols

and

Out

put

Rep

ort F

orm

ats

Dat

a Tr

ansf

er to

/from

Oth

er

Com

pute

rs a

nd D

evic

es.

Ease

-of-

Use

and

Use

r Frie

ndly

In

terf

aces

Com

patib

ility

with

oth

er O

ffic

e So

lutio

ns A

pplic

atio

ns

Proj

ecte

d Li

fe, i

n te

rms o

f Util

ity o

f So

ftwar

e A

pplic

atio

n

Easy

to p

rocu

re, I

nsta

ll, C

usto

miz

e an

d U

pgra

de

Stro

ng C

usto

mer

and

Tec

hnic

al

Supp

ort

/ Doc

umen

tatio

ns

Executive Collaboration and Decision Support Dashboards 0.762 0.429 0.835 0.687 0.281 0.199 0.038 0.214 0.647 0.615 0.217 0.280 0.897 0.869 0.457 0.639 0.746 0.704

Proposals, Contracts and Bid Management, Details and Status 0.975 0.889 0.914 0.837 0.360 0.776 0.047 0.400 0.336 0.729 0.765 0.696 0.663 0.810 0.403 0.357 0.747 0.978

Contract Administration, Finance, Insurance and Records 0.849 0.875 0.900 0.022 0.064 0.259 0.411 0.359 0.048 0.093 0.012 0.001 0.022 0.091 0.006 0.017 0.393 0.023

Work Breakdown, Planning, Scheduling and Monitoring 0.205 0.180 0.742 0.246 0.214 0.031 0.184 0.025 0.121 0.751 0.022 0.033 0.095 0.598 0.054 0.050 0.736 0.614

Vendor databases, Management, Procurements, Tracking 0.809 0.327 0.083 0.331 0.447 0.313 0.790 0.792 0.060 0.562 0.073 0.089 0.376 0.203 0.075 0.031 0.419 0.110

Subcontractor Collaboration, Work Allocation, Payments, RFIs 0.586 0.129 0.362 0.696 0.880 0.218 0.336 0.917 0.006 0.032 0.011 0.012 0.090 0.343 0.442 0.321 0.707 0.561

Purchase Orders, Tracking and Related Documentation Management 0.487 0.450 0.720 0.223 0.549 0.855 0.460 0.289 0.035 0.042 0.021 0.007 0.528 0.422 0.016 0.024 0.669 0.945

Change Orders, Managing, Documenting and Collaboration. 0.155 0.920 0.367 0.884 0.593 0.407 0.476 0.777 0.315 0.429 0.199 0.002 0.388 0.121 0.512 0.928 0.767 0.351

Submittals, Management, Approval and Review Cycles 0.526 0.114 0.862 0.029 0.228 0.888 0.410 0.539 0.710 0.873 0.013 0.007 0.187 0.648 0.864 0.751 0.180 0.936

Project Budgets, Financial Analysis, Monitoring and Cash Flows 0.677 0.544 0.707 0.348 0.345 0.240 0.014 0.016 0.098 0.286 0.023 0.044 0.105 0.388 0.338 0.078 0.603 0.311

Equipment Management, Allocation, Tracking and Expenses 0.895 0.126 0.113 0.024 0.023 0.925 0.176 0.282 0.194 0.112 0.466 0.220 0.174 0.043 0.249 0.254 0.690 0.751

Resource Management, Forecasting, Availability and Utilization 0.510 0.258 0.623 0.246 0.470 0.076 0.029 0.497 0.006 0.071 0.135 0.059 0.001 0.034 0.022 0.067 0.768 0.416

Risk Management, Identification, Planning, Mitigation 0.967 0.617 0.276 0.410 0.417 0.131 0.050 0.456 0.086 0.159 0.182 0.102 0.042 0.304 0.392 0.379 0.504 0.340

Material Management, Inventory Control, Usage and Insurance 0.611 0.940 0.118 0.273 0.078 0.619 0.331 0.180 0.192 0.372 0.886 0.526 0.490 0.009 0.545 0.132 0.099 0.328

Operations Management and Workflow Analysis 0.410 0.118 0.185 0.221 0.053 0.120 0.147 0.001 0.634 0.235 0.181 0.000 0.003 0.000 0.003 0.002 0.400 0.085

Partner Management, Investments, Portfolios and Collaboration 0.575 0.831 0.030 0.078 0.106 0.400 0.127 0.366 0.248 0.627 0.575 0.079 0.031 0.016 0.115 0.206 0.143 0.092

Enterprise wide assessment of schedule and budget impacts 0.723 0.022 0.798 0.372 0.237 0.077 0.013 0.084 0.663 0.895 0.073 0.000 0.000 0.042 0.029 0.022 0.405 0.100

Daily Logs, Rosters, Meeting Minutes, Letters and Reports 0.367 0.786 0.885 0.956 0.340 0.115 0.031 0.504 0.394 0.728 0.256 0.000 0.172 0.995 0.519 0.477 0.107 0.502

Periodic Reporting Cycles, Statistics, Timelines, Progress Rates 0.513 0.810 0.027 0.379 0.300 0.024 0.013 0.146 0.214 0.794 0.046 0.001 0.010 0.360 0.170 0.607 0.235 0.252

Reports, Notices, Memos, Invoices and Other Documentation 0.545 0.143 0.025 0.341 0.767 0.180 0.894 0.524 0.179 0.658 0.004 0.000 0.002 0.895 0.094 0.119 0.588 0.282

Table 18: P Values from Spearman’s Test for Correlation between Application Features and Application Characteristics

160


SPEARMANS CORRELATION BETWEEN APPLICATIONS FEATURES, ADVANCED

FEATURES AND BARRIERS

Inte

grat

ed e

stim

atin

g, sc

hedu

ling

and

proj

ect m

onito

ring

tool

s

4D (t

ime-

boun

d 3D

) pro

cess

vi

sual

izat

ion

and

sim

ulat

ion

Glo

bal o

r con

tinen

tal v

endo

r /

subc

ontra

ctor

dat

abas

es

Ons

ite w

irele

ss te

chno

logi

es w

ith

auto

mat

ed d

ata

acqu

isiti

on

Less

ons l

earn

ed a

nd p

rior p

roje

ct

exec

utio

n / e

xper

ienc

e da

taba

ses

Aut

omat

ed a

lgor

ithm

-bas

ed o

ptim

ized

re

sour

ce a

lloca

tion

Cen

tral r

egul

ator

y an

d co

mpl

ianc

es

data

base

s

Aut

omat

ed si

mul

atio

ns fo

r cha

nge

man

agem

ent d

ecis

ion-

mak

ing

Cen

traliz

ed n

etw

ork-

base

d lim

ited-

acce

ss m

onito

ring

for a

ll pa

rties

Lack

of p

rece

dent

s of a

pplic

atio

n us

age

in th

e in

dust

ry

Maj

or in

vest

men

t with

out g

uara

ntee

of

succ

ess a

nd/o

r ret

urns

Nec

essi

ty o

f hig

h co

mpu

ting

prof

icie

ncy

leve

ls in

seni

or m

anag

emen

t

App

rehe

nsio

n re

gard

ing

star

t-up

issu

es

durin

g cr

itica

l ong

oing

pro

ject

s

Pref

eren

ce fo

r old

-sty

le p

aper

-bas

ed /

exis

ting

man

agem

ent p

roto

cols

Con

cern

s reg

ardi

ng d

ata

secu

rity

and

conf

iden

tial s

trate

gic

busi

ness

pla

ns

Lack

of a

pplic

atio

ns th

at m

ay ra

pidl

y be

cu

stom

ized

to su

it ou

r firm

Con

cern

s abo

ut a

pplic

atio

n bu

gs th

at

may

resu

lt in

fina

ncia

l ris

ks /

loss

es

Dow

ntim

e ow

ing

to u

pgra

de o

f exi

stin

g se

tup

and

exis

ting

data

ent

ry

Executive Collaboration and Decision Support Dashboards 0.274 0.629 0.227 0.643 0.099 0.347 0.051 0.851 0.266 0.353 0.009 0.221 0.362 0.343 0.085 0.020 0.102 0.077

Proposals, Contracts and Bid Management, Details and Status 0.211 0.633 0.037 0.375 0.110 0.436 0.004 0.899 0.206 0.509 0.158 0.528 0.918 0.852 0.008 0.023 0.226 0.229

Contract Administration, Finance, Insurance and Records 0.578 0.136 0.289 0.083 0.122 0.371 0.012 0.125 0.016 0.033 0.589 0.814 0.855 0.814 0.653 0.661 0.419 0.835

Work Breakdown, Planning, Scheduling and Monitoring 0.070 0.728 0.114 0.542 0.074 0.926 0.242 0.851 0.606 0.543 0.814 0.517 0.867 0.099 0.574 0.977 0.361 0.340

Vendor databases, Management, Procurements, Tracking 0.812 0.015 0.015 0.675 0.030 0.932 0.009 0.543 0.946 0.663 0.281 0.727 0.826 0.055 0.130 0.363 0.584 0.686

Subcontractor Collaboration, Work Allocation, Payments, RFIs 0.678 0.083 0.246 0.613 0.001 0.975 0.170 0.487 0.213 0.822 0.139 0.931 0.570 0.833 0.956 0.681 0.930 0.778

Purchase Orders, Tracking and Related Documentation 0.543 0.949 0.107 0.130 0.036 0.258 0.007 0.986 0.271 0.562 0.186 0.114 0.866 0.718 0.413 0.128 0.928 0.546

Change Orders, Managing, Documenting and Collaboration. 0.678 0.619 0.501 0.374 0.039 0.227 0.478 0.202 0.025 0.301 0.577 0.621 0.787 0.398 0.132 0.157 0.480 0.698

Submittals, Management, Approval and Review Cycles 0.553 0.060 0.460 0.830 0.087 0.198 0.512 0.426 0.404 0.958 0.173 0.950 0.181 0.207 0.658 0.274 0.291 0.406

Project Budgets, Financial Analysis, Monitoring and Cash Flows 0.167 0.541 0.125 0.989 0.395 0.665 0.095 0.746 0.545 0.622 0.753 0.172 0.472 0.046 0.780 0.741 0.950 0.669

Equipment Management, Allocation, Tracking and Expenses 0.355 0.087 0.005 0.381 0.285 0.907 0.081 0.409 0.516 0.803 0.166 0.513 0.237 0.955 0.302 0.663 0.237 0.273

Resource Management, Forecasting, Availability and Utilization 0.026 0.838 0.004 0.287 0.007 0.096 0.000 0.001 0.027 0.425 0.214 0.288 0.978 0.006 0.763 0.777 0.253 0.315

Risk Management, Identification, Planning, Mitigation 0.272 0.047 0.060 0.048 0.001 0.776 0.087 0.002 0.101 0.817 0.117 0.289 0.205 0.053 0.616 0.665 0.291 0.181

Material Management, Inventory Control, Usage and Insurance 0.448 0.937 0.010 0.931 0.884 0.890 0.029 0.319 0.770 0.289 0.499 0.485 0.516 0.181 0.406 0.503 0.109 0.736

Operations Management and Workflow Analysis 0.091 0.323 0.013 0.036 0.102 0.185 0.008 0.113 0.047 0.462 0.858 0.061 0.332 0.782 0.844 0.617 0.085 0.487

Partner Management, Investments, Portfolios and Collaboration 0.072 0.510 0.000 0.097 0.018 0.025 0.002 0.010 0.003 0.625 0.668 0.865 0.271 0.892 0.952 0.521 0.041 0.613

Enterprise wide assessment of schedule and budget impacts 0.000 0.985 0.004 0.152 0.071 0.104 0.001 0.011 0.000 0.267 0.814 0.968 0.417 0.133 0.175 0.853 0.803 0.738

Daily Logs, Rosters, Meeting Minutes, Letters and Reports 0.111 0.448 0.435 0.427 0.438 0.665 0.217 0.693 0.078 0.718 0.239 0.806 0.855 0.376 0.264 0.444 0.698 0.102

Periodic Reporting Cycles, Statistics, Timelines, Progress Rates 0.087 0.029 0.106 0.725 0.059 0.105 0.017 0.049 0.000 0.906 0.465 0.101 0.783 0.305 0.839 0.309 0.097 0.558

Reports, Notices, Memos, Invoices and Other Documentation 0.681 0.012 0.755 0.292 0.067 0.605 0.037 0.351 0.038 0.966 0.658 0.598 0.892 0.737 0.299 0.935 0.836 0.432

Table 19: P Values from Spearman’s Test for Correlation between Application Features with Advanced Toolsets and Deployment Barriers

161


SPEARMANS CORRELATION BETWEEN APPLICATION

CHARACTERISTICS, ADVANCED FEATURES AND BARRIERS

Inte

grat

ed e

stim

atin

g, sc

hedu

ling

and

proj

ect m

onito

ring

tool

s

4D (t

ime-

boun

d 3D

) pro

cess

vis

ualiz

atio

n an

d si

mul

atio

n

Glo

bal o

r con

tinen

tal v

endo

r /

subc

ontra

ctor

dat

abas

es

Ons

ite w

irele

ss te

chno

logi

es w

ith

auto

mat

ed d

ata

acqu

isiti

on

Less

ons l

earn

ed a

nd p

rior p

roje

ct

exec

utio

n / e

xper

ienc

e da

taba

ses

Aut

omat

ed a

lgor

ithm

-bas

ed o

ptim

ized

re

sour

ce a

lloca

tion

Cen

tral r

egul

ator

y an

d co

mpl

ianc

es

data

base

s

Aut

omat

ed si

mul

atio

ns fo

r cha

nge

man

agem

ent d

ecis

ion-

mak

ing

Cen

traliz

ed n

etw

ork-

base

d lim

ited-

acce

ss

mon

itorin

g fo

r all

parti

es

Lack

of p

rece

dent

s of a

pplic

atio

n us

age

in

the

indu

stry

Maj

or in

vest

men

t with

out g

uara

ntee

of

succ

ess a

nd/o

r ret

urns

Nec

essi

ty o

f hig

h co

mpu

ting

prof

icie

ncy

leve

ls in

seni

or m

anag

emen

t

App

rehe

nsio

n re

gard

ing

star

t-up

issu

es

durin

g cr

itica

l ong

oing

pro

ject

s

Pref

eren

ce fo

r old

-sty

le p

aper

-bas

ed /

exis

ting

man

agem

ent p

roto

cols

Con

cern

s reg

ardi

ng d

ata

secu

rity

and

conf

iden

tial s

trate

gic

busi

ness

pla

ns

Lack

of a

pplic

atio

ns th

at m

ay ra

pidl

y be

cu

stom

ized

to su

it ou

r firm

Con

cern

s abo

ut a

pplic

atio

n bu

gs th

at m

ay

resu

lt in

fina

ncia

l ris

ks /

loss

es

Dow

ntim

e ow

ing

to u

pgra

de o

f exi

stin

g se

tup

and

exis

ting

data

ent

ry

Backward Compatibility with Legacy Systems 0.338 0.298 0.141 0.642 0.316 0.487 0.011 0.436 0.652 0.663 0.968 0.716 0.966 0.781 0.446 0.296 0.904 0.768

Scalability and Customization for individual business needs 0.065 0.010 0.301 0.722 0.126 0.280 0.045 0.330 0.427 0.518 0.681 0.051 0.427 0.436 0.381 0.587 0.163 0.376

Hardware Resource Requirements of the Application 0.697 0.240 0.013 0.414 0.172 0.910 0.028 0.366 0.519 0.729 0.658 0.083 0.104 0.058 0.151 0.984 0.070 0.802

Initial Cost of the Software Application 0.592 0.447 0.036 0.488 0.551 0.242 0.820 0.708 0.760 0.029 0.035 0.399 0.055 0.093 0.591 0.982 0.309 0.477

Costs for License renewal, Extension and Upgrades 0.961 0.294 0.022 0.710 0.974 0.506 0.732 0.896 0.996 0.070 0.025 0.615 0.013 0.404 0.025 0.056 0.030 0.820

Toolsets and Functional Features of the Application 0.317 0.600 0.184 0.957 0.217 0.297 0.136 0.109 0.083 0.996 0.833 0.893 0.562 0.316 0.695 0.106 0.671 0.613

Communication and Networking Capabilities 0.065 0.074 0.151 0.594 0.094 0.667 0.180 0.032 0.008 0.988 0.602 0.337 0.551 0.026 0.552 0.710 0.308 0.787

Compatibility with Generic Devices like PDAs and Laptops 0.012 0.795 0.016 0.654 0.165 0.394 0.084 0.934 0.913 0.263 0.209 0.638 0.278 0.389 0.627 0.855 0.659 0.407

Business data security concerns 0.597 0.597 0.009 0.792 0.078 0.746 0.065 0.405 0.825 0.079 0.703 0.165 0.980 0.536 0.088 0.505 0.267 0.820

Vulnerability of Application to viruses and system bugs 0.385 0.281 0.058 0.849 0.055 0.623 0.549 0.269 0.812 0.653 0.668 0.600 0.737 0.874 0.000 0.228 0.042 0.207

Data storage, interpretation, access and visibility aspects 0.590 0.506 0.090 0.586 0.023 0.930 0.056 0.025 0.041 0.942 0.879 0.926 0.392 0.457 0.159 0.357 0.525 0.235

Data Entry Protocols and Output Report Formats 0.115 0.372 0.123 0.269 0.219 0.065 0.070 0.009 0.000 0.438 0.971 0.987 0.561 0.997 0.615 0.960 0.435 0.438

Data Transfer to/from Other Computers and Devices. 0.001 0.171 0.114 0.163 0.047 0.405 0.020 0.030 0.001 0.731 0.642 0.737 0.550 0.192 0.577 0.266 0.473 0.062

Ease-of-Use and User Friendly Interfaces 0.048 0.168 0.111 0.942 0.164 0.274 0.619 0.289 0.185 0.444 0.609 0.169 0.036 0.978 0.592 0.329 0.206 0.549

Compatibility with other Office Solutions Applications 0.156 0.343 0.060 0.198 0.076 0.197 0.005 0.240 0.170 0.786 0.615 0.545 0.016 0.301 0.862 0.718 0.287 0.315

Projected Life, in terms of Utility, of Software Application 0.271 0.136 0.002 0.528 0.091 0.202 0.012 0.523 0.706 0.537 0.072 0.236 0.156 0.470 0.900 0.982 0.273 0.941

Easy to procure, Install, Customize and Upgrade 0.078 0.508 0.283 0.841 0.428 0.502 0.080 0.255 0.162 0.036 0.049 0.237 0.400 0.963 0.680 0.663 0.700 0.036

Strong Customer and Technical Support / Documentations 0.106 0.310 0.096 0.577 0.460 0.634 0.014 0.030 0.048 0.532 0.184 0.179 0.038 0.787 0.339 0.267 0.075 0.306

Table 20: P Values from Spearman’s Test for Correlation between Application Characteristics with Advanced Toolsets and Barriers

162

5.2.3 The Matrix Design

It was found to be quite cumbersome to design the decision matrix such that all of the

associations could be displayed on one page. Therefore, a computer aided tool was used to

design it in two parts. The initial conception of developing a 3D model was not followed

since though visually appealing, it would be very difficult to use as the user would lose the

sequence with time.

The first part of the model presents the business centric associations. Here, top 12

corporate concerns have been considered and their associations, as established from the

analysis thus far, with the other four parameter areas have been presented. This phase would

allow the user to use his/her business priorities (for most part) and configure other aspects of

the application, and the implementation barriers as well, that he/she would need to consider.

Having gained an initial insight into the entire application setup process, the user may

want to explore further into the application aspects. The second part of the matrix centers

upon the application features as the dependent variable and presents its associations with

other aspects. Thereafter, the application characteristics have been used as the dependent

variable to identify its associations with advanced tools and barriers.

A backwards approach (like trying to relate the application features to the corporate

concerns) has not been adopted since even though they might be statistically feasible, they

do not make logical sense. The matrix has been presented in the following two pages. Color

coded arrows have been used to provide as much clarity as possible. The dependent

parameter is like colored same with all the arrows that elicit from it to facilitate easier

tracking. The entire design has been done using a scaled down graphical tools as can be

enlarged up to five times and printed on plotter sheets for easy viewing.

163

164

5.3 USING THE MATRIX

A flowchart explaining step-by-step the procedures for using the matrix is presented

on the following page. The first step towards such application selection would be to

identify the emergent needs of the company in question. These should then be compared

to the various concerns enumerated in earlier sections to check if any factor needs

consideration.

It must be noted here that the matrix is based completely on mathematical results

obtained through the survey data and presents associations and considerations that need

to be addressed and looked into in the process of software application acquisition.

Starting with the corporate concerns, it configures all the other aspects like application

features, functional characteristics, advanced tools and barriers to deployment that need

to be considered. These associations do not reflect that any particular feature is or is not a

must have.

Having established all such associations, they should be studied and discussed to

countercheck if any essential parameter has been missed. There are a few features and

characters that are mandatory to all such tools and can be expressly taken for granted. For

example “Contracts and Bid Management” or “Networking” or “Data Migration”, etc. are

aspects that must be there for effective application solutions to manifest. Such aspects

should be considered whether or not the matrix identifies it (which it does for most part).

In order to avoid complexity in the matrix representation, associations were not

established between the categories, for example, it is quite possible that one feature might

be related to another, but depicting these would render the design incomprehensible.

165

166

Figure 45: Instructions for Using the Decision Matrix

Furthermore, these were noted as very basic aspects that can easily be figured out by

users familiar with such tools.

Certain notables regarding critical aspects of these results that were observed during

the formulation of the matrix have been presented in the conclusions section on analyzed

results.

5.4 VALIDATION OF THE MATRIX

In order to validate the matrix and to cite an example of its usage, a select project

executive from the construction industry was chosen. This person was provided with a

list of the various corporate concerns that have been identified and requested to rank any

six of the top concerns, from 1 – 6, as pertained to his company. Six here does not have

any specific significance, what was needed was a few of the top concerns. His selections

have been listed below in descending order of importance.

• Drive for greater integration in PM functions

• Generic drive for better business process practices

• Feedback from Clients / Partners / Subcontractors

• Client’s expectations / demands / preferences

• Industry Trends and Anticipated Changes or Developments

• Proficiency of current staff in using applications

On the basis of these concerns, associations were identified from the matrix from all

the four categories and have been listed in the following pages, by category, in

descending order of importance.

167

Application Toolsets and Features:

• Change Orders, Management, Documentation and Collaboration

• Submittals, Management, Approvals, Reviews

• Project Budgets, Financial Analysis, Monitoring and Cash Flows

• Work Breakdown, Planning, Scheduling and Monitoring

• Contracts Administration, Finance, Insurance, Records

• Subcontractor Collaboration, Work Allocation, Payments, RFIs, RFQs

• Purchase Orders, Tracking, Documentation and Management

• Periodic Reporting Cycles, Statistics, Timelines and Progress Rates

• Reports, Notices, Memos, Invoices and Other Document Templates

• Risk Management, Identification, Planning and Mitigation

• Enterprise-wide assessment of Schedule and Budget Impacts

Application Functional Characteristics:

• Communication and Networking Capabilities

• Ease of Use and User Friendly Interfaces

• Data Storage, Interpretation, Access and Visibility Issues

• Backward Compatibility with Legacy Systems

• Scalability and Customization for Individual Needs

• Data Entry Protocols and Output Report Formats

• Toolsets and Functional Features of the Applications

168

Advanced Tools:

• Lessons Learned and Prior Project Execution Experiences Databases

• Centralized network-based limited access monitoring for all parties

• 4D ( Time Bound 3D ) Process Visualization and Simulation

Barriers to Deployment:

• Lack of Precedents of Application Usage in the Industry

Some of the logical inferences that were drawn after scrutinizing the above mentioned

aspects pertaining to the project management application system have been discussed in

the next chapter.

169

CHAPTER 6

DISCUSSION OF RESULTS

6.1 DISCUSSION AND RECOMMENDATIONS

This study, through its various phases of probing into the IT and PM applications

scenario in the US construction industry, manifests various observations that demand

attention and / or further investigation. It must be mentioned here that all of these

conclusions have been arrived at on the basis of data analysis and various results reflected

by this study. Some of these have been discussed below.

6.1.1 On General Trends

Certain notable observations were made about the IT and computing penetration into

the construction industry as a whole and its related problem areas. These are as follows.

• The construction industry, like any other profit making enterprise, looks upon the

entire computerization process as it perceives any other advanced technology. It

should be sustainable and should yield returns. Various human aspects like not

wanting to shift from paper-based methods or issues pertaining to senior management

not being proficient enough to use such applications were found to be extremely rare

based on the results reflected by this study.

• The approach of the industry does not seem to vary much with the company in

question, its size, operations, etc. It is more an issue about whether or not the

company can afford the PM application setup or not. The fact that such applications

do enhance the entire organizational management and project control systems is quite

well acknowledged. One probable reason could be that of the hundreds of such

170

available applications, very few are from reliable vendors and of these few, most are

extremely expensive to procure and maintain.

• As mentioned earlier, most of these applications are high-end relational database

management systems and do not have much data processing capabilities. With this

view, certain futuristic toolsets (that were incidentally extremely low rated as

observed through the survey) that are based on database features like equipment

management and materials flow and management could be incorporated without

much difficulty. However, it is difficult to gauge the complexity of incorporating

tools based on algorithmic data processing capabilities like simulations and

optimization. It shall be all the more difficult to customize such tools, thereby making

it very expensive. Before moving into the developmental phases of such modules, it is

imperative to understand whether or not these tools shall be sustainable from the

business point of view or not. The industry on its part does not seem to doubt the

capabilities of these modules at all.

• Considering another aspect of futuristic toolsets for PM applications like centrally

regulated vendor or subcontractor databases, it was observed that most companies

prefer to work with parties that they already have a successful work history with and

shift to another party solely for commercial purposes does not reflect the business

ethics the construction industry practices. If need be, the companies might try to

improve their existing project management protocols with all concerned parties and

attempt to bring subsidiaries and affiliates to their performance levels. Such

facilitations or information databases might be helpful to new companies that are in

the process of finding project affiliates or business partners but the likelihoods of

171

their affecting the way most established companies do business is quite low.

Established companies, at best, might use it to gauge the competition in the industry.

• The above mentioned observations make it necessary to look into the business aspects

of technological innovations that are being planned. Creating IT environments that

are extremely advanced but are not synchronized with the currency of the situation

might not be accepted very well by the industry. Technological enhancements that

pertain to various industrial sectors should first cater to what is most needed rather

than attempting to realize futuristic computing solutions.

• A critical role in the entire application selection, customization, implementation and

maintenance process is played by the software vendor. As noted in the software

review section, much of the application selection also depends upon how well the

vendor is marketing its products. Unlike other softwares, web based PM applications

used by the construction industry generate not only the sales (one time) revenues but

also routine maintenance and upgrade (continued) revenues for the vendor. The

software development business aspect was one area that was found to be lacking in

the researches towards identifying issues in construction PM IT.

6.1.2 On Analyzed Results

The arena of IT and software applications in the construction industry (or any other

industry) includes various complex aspects that cannot be absorbed in researches by

studying construction firms and their activities and practices generally. In-depth insight

into these can only be gained by focusing on case studies of specific companies that have

172

experienced using such tools. Some of the observations that made it essential to include

this brief are given below.

• It was observed that top rated parameters under various application based areas like

features and characteristics are not related to any other parameters. This does not

essentially mean that such a parameter is unimportant or unrelated. As stated earlier,

mathematical or statistical modeling may or may not reflect ground realities

accurately. It is therefore left to the user’s discretion to use the rating charts along

with the matrix and his or her common knowledge to center upon the applications that

best suit their requirements. The matrix is meant to be used as a guideline from the

practical perspective and not as an absolute definitive tool.

• Amongst the advanced toolsets, “Lessons Learnt and Project History Databases” even

though third ranked, were found to be related to quite a few features and

characteristics, as compared to a feature like “4D Scheduling, Process Visualization

and Simulation”. It must be noted here that the former is easier to incorporate, has

undoubted benefits and is also easy to use. The latter, in comparison, is much more

difficult to develop, especially in a web-based application with varying information

sources and its benefits are relatively unknown. This again brings into focus the

suggestion that technological advances need to be weighed from their applicability

and business sustenance perspective.

• Except for 8 cases of the associations established amongst 52 parameters (which is

close to 2600 tests), none of the parameters seem to be related to many barriers. Even

assuming that the matrix is statistical and not purely logical or a combination of both,

this figure is believed to be too low to infer that all of the said barriers mentioned in

173

the literature review section and elsewhere exist. Such barriers will certainly vary

with the company and application in question and generalizing these to encompass

the industry is debatable.

• Of the 9 negative or inverse associations observed, 7 were found to be associated with

advanced toolsets and barriers. Of the 18 parameters in these two areas, focus

remained on “4D Scheduling, Process Visualization and Simulation” and “Lack of

applications that may rapidly be customized to suit our firm”. This could be indicative

of the fact that the industry realizes the importance of advanced customized tools

while understanding that such tools cannot be procured and implemented easily.

In closure, it must be mentioned that new technologies like Building Information

Modeling, remote sensing and tracking, etc. are largely being encouraged by the industry

which proves that the construction industry is open to innovation. However, integrated

computing environments along with their many advantages also bring in complexities.

Current researches addressing such negative or grey areas of integrated computing are

lacking. Further studies need to be taken up to investigate into what causes these issues

and how they can be overcome. Believing that the industry is not ready for such advanced

tools might be correct but examining only the industry related issues and not the

application issues by itself might not be justified.

6.1.3 On Case Study

The following include some of the inferences that were drawn on the basis of the

identified PM application aspects during the validation of the matrix. These inferences

174

have been drawn keeping in mind the size and operations of the specific construction firm

that the respondent belonged to as well as their current PM and IT applications setup.

• A study of identified application features and characteristics reveal that the impetus

seems to be more on collaboration and project cost control aspects. Issues, for

example, subcontractor collaboration, management of change orders, focus on

submittals, etc. underscore the idea that a greater level of control is desired on phases

of projects where third parties are involved.

• Aspects like monitoring project budgets and cash flows, controlling and managing

change orders and submittals, tracking and documentation of purchase orders,

enterprise wide schedule and budget impacts are indicative of the company’s focus on

project cost control.

• Stress is also manifest on almost all aspects of documentation and greater visibility

and access to project information from all quarters.

• The costs of application procurement, its implementation, training and support,

licenses, maintenance, etc. do not seem to be extremely important in this case since

almost no parameter from either the “toolsets” or the “characteristics” categories that

are relevant to above mentioned aspects have been identified.

• The identified application features or toolsets, its functional characteristics and other

aspects, barriers to deployment that might be faced and desirable advanced toolsets

(some of which are still being researched) attempt to create a framework for

deliberations towards acquisition or upgrade and implementation of the PM

application in the said firm.

175

• It is quite possible that other aspects that are not present in the list above might also

have significant implications. The above mentioned merely form a set of guidelines

that help the said firm center upon essential requisites of the application they want to

acquire.

6.2 FUTURE DIRECTIONS

Construction IT is a fast developing sector within the construction industry and its

capabilities are widely acknowledged by the academia and the industry. Though this

work was primarily aimed at developing the decision support tool, various notable

observations were made during the entire process that demonstrate various areas within

this field that need to be addressed. One such direction, for example, would be to

examine the practical feasibility of the various advanced computing protocols mentioned

in the literature review chapter from the financial case justification outlook. Another very

important area, as brought into focus through interviews with senior management towards

this study, was the business liaisons (not as a customer but as a partner) that construction

companies are known to be developing with software vendors to share their expertise of

construction with the vendors expertise in computing to develop advanced computing

solutions. These aspects are believed to be much more significant to the penetration of IT

and application tools in the industry than is attributed to them.

176

REFERENCES

Abourizk, S. M., and Mohamed, Y. (2000). "Simphony - An Integrated Environment for Construction Simulation." Proc., 2000 Winter Simulation Conference., 1907 - 1914. Abourizk, S.M., Halpin, D.W., and Lutz, J.D. (1992). “State Of The Art In Construction Simulation.” Proc., 1992 Winter Simulation Conference. 1271 – 1277. “A Collection of Modeling and Simulation Resources on the Internet.” World Wide Web html document, (http://www.idsia.ch/~andrea/simtools.html#agent). Ahmad, T.U., Russel, J.S., Abou-Zeid, A. (1995). “IT and Integration in the Construction Industry”, Journal of Construction Management and Economics, Vol. 13, 163-171. Ahuja, H.N., Abourizk, S.M. et al. (1994). “Project Management: Techniques in Planning and Controlling Construction Projects” 2nd Edition, John Wiley and Sons, Inc. New York, NY. Akintoye, A.S. and MacLeod, M.J. (1997) “Risk Analysis and Management in Construction.” International Journal of Project Management, Feb 97, 15(1), 31-38. Allmon, E. et al. (2000). “US Construction Labor Productivity Trends: 1970 -1998.” Journal of Construction Engineering and Management, ASCE, 126(2), 97-104. Alshawi, M. and Ingirige, B. (2003). “Web-enabled Project Management: An Emerging Paradigm in Construction.” Automation in Construction, ELSEVIER, 12 (2003), 349-364. Ballard, G., Howell, G. (1994). “Implementing Lean Construction: Stabilizing Work Flow.” II Annual Conference on Lean Construction, September 1994, Santiago, Chile. Ballard, G., Howell, G. (1988). “Shielding Production: An Essential Step in Production Control.” Journal of Construction Engineering and Management, ASCE, 124(1), 18-24. Becerik, B. (2004). “Review of Past, Present and Future of Web-based PM and Online Collaboration Tools and Their Adoption in AEC Industry.” International Journal of IT in AEC, 12/2004, 2(4). Becerik, B. (2005). “Critical Enhancements for Improving Adoption of OPM Technologies”. Harvard Graduate School of Design, Barrie Award Winning Reports, PMI Educational Foundation Funded. Blank, L., (1980). “Statistical Procedures for Engineering, Management and Science” McGraw-Hill, Inc., New York, NY. Caldas, C.H., Soibelman, L. and Han, J. (2002). “Automated Classification of Construction Project Documents” Journal of Computing in Civil Engineering, ASCE, 16(4), 234-243. Capano, C., Stahl, D. and McGreen, M. (2000). “Educating Future Constructors in Utilizing a Project Specific Website”, Proc. VI Construction Congress, ASCE, Orlando, 234-243.

I

Cheng, M., and Ko, C. (2003). “Object-Oriented Evolutionary Neural Inference System For Construction Management.” J. Construction Engineering and Management, ASCE, 129(4), 461 – 469. Chinowsky, P.S. and Meredith, J.E. (2000). “Strategic Management in Construction.” Journal of Construction Engineering and management, ASCE, 126(1), 1-9. Chua, D.K.H., and Li, G.M. (2002). “RISim : Resource-Interacted Simulation Modeling In Construction.” J. Construction Engineering and Management, ASCE, 128(3), 195 – 202. “Construction Spending Grows.” (2005).World Wide Web html document, Milwaukee Journal Sentinel, 02 March 2005. Cutter (1999) “US Trends in IT Finance and Business Performance.” IT Metrics Strategies, The 1999 Worldwide Benchmark Report, 05 May 1999. Deng, Z.M., et al. (2001). “An Application of the Internet-based Project Management System.” Automation in Construction, ELSEVIER, 10(2001), 239-246. Ding, S. (2002). “Digitization of Professional Management of Projects” NNSF China Funded Project Report, Research Center for Construction Economics, Honk Kong Polytechnic University. FIATECH (2004). Capital Projects Technology Roadmapping Initiative. FIATECH (www.fiatech.org) FMI Consultants and CMAA. (2004). “Report on Fifth Annual Survey of Owners”. Construction Management Association of America. Froese, T. et al. (1997). “Project Management Models and Computer-Assisted Construction Planning." International Journal of Construction Information Technology, 5(1), 39-62 Garret Jr., J.H. et al. (2004). “IT in Civil Engineering – Future Trends” Editorial, Journal of Computing in Civil Engineering, ASCE, July 2004, 185-186. Gidado, K.I. (1996). “Project Complexity: The Focal Point of Construction Production Planning”. Construction Management and Economics, Vol. 14, 213-225. Gil, N., and Tommelein, I.D. (2001). “Comparison Of Simulation Modeling Techniques That Use Preemption To Capture Design Uncertainty.” Proc., 2001 Winter Simulation Conference., 1504 – 1511. Hajjar, D., and Abourizk, S.M. (2000). “Application Framework For Development Of Simulation Tools.” J. Computing In Civil Engineering, ASCE, 14(3), 160 – 167. Hajjar, D. and Abourizk, S.M. (2000). “Integrating Document Management with Project and Company Data” Journal of Computing in Civil Engineering, ASCE, 14(1), 70-77. Hajjar, D., and Abourizk, S.M. (2000). “Unified Modeling Methodology For Construction Simulation.” J. Construction Engineering and Management, ASCE, 128(2), 174 – 185.

II

http://www.fiatech.org/

Hajjar, D., Abourizk, S.M., and Mather, K. (1998). “Integrating Neural Networks With Special Purpose Simulation.” Proc., 1998 Winter Simulation Conference., 1325 – 1332. Haldar, A., and Mahadevan, S. (2000). Probability, Reliability and Statistical Methods in Engineering Design, John Wiley and Sons, Inc., New York, NY. Halpin, D.W., Jen, H., and Kim, J. (2003). “A Construction Process Simulation Web Service.” Proc., 2003 Winter Simulation Conference., 1503 -1509. Halpin, D. W., and Martinez, L. (1999). “Real World Applications of Construction Process Simulation.” Proc., 1999 Winter Simulation Conference, 956 – 962. Hunt, M.A. (1995) “Strategic Implementation of Information Technology within the Construction Industry.” MS Dissertation, Department of Surveying, University of Salford, UK. Kagioglou, M. et al. (2001). “Performance Management in Construction: A Conceptual Framework”. Construction Management and Economics, Taylor and Francis, Vol. 19, 85-95. Kamat, V.R., and Martinez, J.C. (2002). “Comparison Of Simulation Driven Construction Operations Visualization And 4D CAD.” Proc., 2002 Winter Simulation Conference, 1765 – 1770. Kanji, G.K. and Wong, A. (1998). “Quality Culture in the Construction Industry”. Total Quality Management, CARFAX, 9(4-5), 133-140. Kartam, N.A. (1995). “Making Effective Use of Construction Lessons Learned in Project Life Cycle.” Journal of Construction Engineering and Management, ASCE, 122(1), 14-21. Kwak, Y.H., and Ibbs, C.W. (2000). “Calculating Project Management’s Return on Investment.” Project Management Journal, Project Management Institute, 31(2), 38 – 47. Liberatore, M.J. and Pollack-Johnson, B. (2000). “PM in Construction: Software Use and Research Directions.” Journal of Construction Engineering and Management, ASCE, 127(2), 101-107. Low, S.P. and Omar, H.F. (1997). “The Effective Maintenance of Quality Management Systems in the Construction Industry.” International Journal of Quality and Reliability Management, MCB University Press, 14(8), 768-790. Macomber, J.D. (2003). “IT Strategy for Construction Companies: A Pragmatists Vision” Journal of Leadership and Management in Engineering, ASCE, April 2003, 94-99. Martinez, J.C., and Ioannou, P.G. (1999). “General-Propose Systems For Effective Construction Simulation.” J. Construction Engineering and Management, ASCE, 125(4), 265 – 276. McCabe, B. (1998). “Belief Networks In Construction Simulation.” Proc., 1998 Winter Simulation Conference, 1279 – 1286. Molenaar, K.R. and Songer, A.D. (2002). “Web-based Decision Support Systems: Case Study in Project Delivery.” Journal of Computing in Civil Engineering, ASCE, 15(4), 259-267. Montgomery, D.C., and Peck, E.A. (1982). Introduction to Linear Regression Analysis, John Wiley and Sons, Inc., New York, NY.

III

Montgomery, D.C., and Runger, G.C., (1994). Applied Statistics and Probability for Engineers, John Wiley and Sons, Inc., New York, NY. Moselhi, O., Hegazy, T. and Fazio, P. (1991). “Neural Networks as Tools in Construction.” Journal of Construction Engineering and Management, ASCE, 117(4), 606-625. Nikoukaran, J., Hlupic, V., and Paul, R.J. (1998). “Criteria For Simulation Software Evaluation.” Proc., 1998 Winter Simulation Conference, 399 – 406. Nitithamyong, P. et al. (2004). “Web-based construction PM systems: How to Make Them Successful?” Automation in Construction, ELSEVIER, 13(2004), 491-506. O’Connor, J.T. and Davis, V.S. (1988). “Constructability Improvement during Field Operations.” Report of the Construction Industry Institute, University of Texas at Austin, Austin, TX. O’Connor, J.T. and Yang, L. (2003). “Understanding How Technology May Impact Project Success.” Executive Summary, Report # 30, CCIS, University of Texas at Austin, Austin, TX. PenaMora, F. and Dwivedi, G.H. (2002). “Multiple Device Collaborative and Real Time Analysis for PM in Civil Engineering.” Journal of Computing in Civil Engineering, ASCE, 16(1), 23-38. Paulson, B.C. (1995). Computer Applications In Construction, McGraw-Hill, Inc., New York, NY. Peters, G. (1981). ” Project Management and Construction Control.” Construction Press, London, UK. Porter, M. and Millar, V. (1985). “How Information Gives You Competitive Advantage.” Harvard Business Review, May 1985. Pristker, A.A.B. (1986). Introduction to Simulation and SLAM-II, John Wiley and Sons, Inc., New York, NY. Rojas, E.M. and Songer, A, D. (1999). “Web Centrics Systems: A new Paradigm for Collaborative Engineering”. Journal of Management in Engineering, 15(1), 39-45. Sawhney, A., Deshpande, H., and Mund, A. (2000). “Javabeans-Based Framework for Construction Simulation.” Proc., 2000 Winter Simulation Conference. 1919 -1925. Sawhney, A., Manickam, J., Mund, A., and Marble J. (1999). “Java-Based Simulation of Construction Process Using Silk.” Proc., 1999 Winter Simulation Conference. 985 – 991. Sawhney, A., and Abourizk, S.M. (1995). “HSM – Simulation-Based Planning Methods For Construction Projects.” J. Construction Engineering and Management, ASCE, 121(3), 297 – 303. Sawhney, A., Bashford, H., and Walsh, K. (2003). “Agent-Based Modeling And Simulation In Construction.” Proc., 2003 Winter Simulation Conference. 1541 – 1547. Schlotzhauer, S.D., and Littell, R.C. (1991). SAS System for Elementary Statistical Analysis, SAS Institute Inc., Cary, NC.

IV

Senior, B.A., and Halpin, D.W. (1998). “Simplified Simulation System For Construction Projects.” J. Construction Engineering and Management, ASCE, 124(1), 72 – 81. Shahid, S. and Froese, T. (1998). “Project Management Information Control Systems”, Canadian Journal of Civil Engineering, 25(4), 735-754. Shenhar A.J., Levy O. and Dvir, D. (1997). “Mapping the dimensions of Project Success.” Project Management Journal, 28(2), 5-15. Spiegel, M.R. (1992). Theory and Problems of Statistics, McGraw-Hill, Inc., New York, NY. Stewart, R.A. and Mohamed, S. (2004). “Evaluating Web-based Project Information Management in Construction.” Automation in Construction, ELSEVIER, 13(2004), 469-479. Stiroh, K.J. (2002). “Information Technology and US Productivity Revival: What do Industry Data Say?” The American Economic Review, December 2002, 92(5), 1559-1576. Sun, M. and Aouad, G. (2000). “IT to Support Organizational Changes in Construction.” 7th ISPE International Conference on Concurrent Engineering, July 2000, Lyon, France, 596-604. Tucker, R.L. (1997). “Emerging Global Opportunities in Construction.” Proceedings of the IV Construction Congress, ASCE, June 1997, Philadelphia, PA, 1-8. US Census Bureau. (2006). “Statistical Abstract of the United States”, 125 Edition. Zhi, H. (1995). “Risk Management for Overseas Construction Projects” International Journal of Project Management, 13(4), 231-237.

V

APPENDICES

A. Survey questionnaire

B. Screenshots of online survey

C. Verbatim comments of respondents on if advanced computing solutions are effective

as a PM tool

D. Verbatim comments of respondents on pm applications and the study

E. Sample SAS code for Spearman rank correlation test

F. Sample SAS code for Wilcoxon comparison of means test

G. Survey based journal papers and respective sample sizes

H. Web based template form of questionnaire design

I. TurnerTalk pricing chart

VI

APPENDIX A

Maturity Diagnostic for Collaborative Computing In Construction Project Management Department Of Construction Engineering and Management, University Of Cincinnati

Personal Information

Company / Agency: _______________________________________________________

Title / Position: ___________________________________________________________

Work Experience in this position (in years): ____________________________________

Email ID: (optional): ______________________________________________________

May we contact you with follow-up questions? Yes No Efforts to introduce “projectization” of operations and business process management are being viewed as a key strategy to achieve greater efficiencies and turnovers with increasing competitiveness in most industrial settings today. This is especially true of the construction industry owing to the innate nature of their operations. This questionnaire forms part of a research study being conducted at the University of Cincinnati to examine essential considerations towards the selection of optimal project management applications and prevalent trends pertaining to project management computing environments in the construction industry. Appertaining to this work, this survey intends to collate information in order to device an expert system which can be used as a guideline or modality to select Project Management (PM) software tools that best suit individual business needs and budgets. Furthermore, it will also contribute as a benchmark to weigh criteria and considerations during such selection. This survey should take approximately 20 minutes of your time and your participation is completely voluntary. You can quit at any point of time. All responses you provide are completely confidential. Raw data from this survey shall not be published or made public in any form through any media. Should you have any questions or comments, please feel free to contact the author at the address given below. Please contact UC Institutional Review Board at 513 - 558 - 5784 regarding your rights to participate in this study. Additional comments are truly appreciated and can be added on the space overleaf. We thank you for participating and contributing to this research work.

Sameer Mohanty Sam Salem, PhD, PE, CPC Graduate Student Department of Civil Engineering Department of Civil Engineering University of Cincinnati University of Cincinnati 513 – 556 – 3759 513 - 886 - 3516 513 – 556 – 2599 [email protected] [email protected]

By completing this survey I indicate my consent to participate in this study.

VII

Section 1: General Information

1. What is the primary area of activity of your firm? (Check All Applicable)

Architecture and Engineering Design Build Firms

Building and Residential Construction Infrastructure and Heavy Construction

Specialized Industrial Construction Real Estate and Land Development

Utilities Contractor Demolition, Salvage, Renovation Services

General Contractor Operations and Maintenance, Repairs

AEC Consultancy Project Management and Planning Services

Other (Please Specify)_______________________________________________________

2. How many years of work experience do you have in the project management / administration / executive or

engineering positions?

Less than 1 year

1 - 5 years

5 - 10 years

10 - 20 years

Above 20 years

3. What is the number of employees in your firm?

Less than 20 employees

21 - 50 employees

51 - 100 employees

101 - 250 employees

251 - 500 employees

Above 500 employees

VIII

4. How many functional departments like planning, legal, purchasing, etc. exist in your company?

1

1-5

5-10

10-20

Above 20

5. How would you define the presence of your firm in terms of geographical spread of operations, vendors,

subcontracting, consultancy, clientele, etc.?

Global Operations

The Americas

North America

Limited to a few states in the USA

Most operations within one locale.

6. If your firm has business operations in different locations, how would you compare the performance levels

in terms of project planning, communications, monitoring and control of local projects against projects in

other locations?

Significantly Less Successful

Less Successful

Equally Successful

More Successful

Significantly More Successful

Not Applicable

IX

7. If your firm has business partners, branches or operations in different locations, how would you rate their

project management computing tools, IT and communications setup?

Not as advanced as ours

Similar and equally good

More advanced than ours

Not Applicable

8. If your firm has business partners, branches or operations in different locations, how, in your opinion, does

their existing computing tools, IT and communications setup effect the success or performance of project

management practices in partnered projects?

Negative effect on performance

Does not effect at all

Positive effect of project performance

Significantly enhances project performance

Not Applicable Section 2: Project Management (PM) Environment 9. How would you rate the internal communication and co-ordination between various departments/sections in

your firm in terms of information flow and collaboration towards project management?

Highly efficient with very timely and accurate sharing and cycling of information.

Efficient and timely, but inaccurate and / or redundant on occasions.

Moderate efficiency with room for improvement.

Lacking and Cumbersome.

Not Applicable

X

10. How would you rate on a scale of 1 to 4, 4 being the best, the following systems as a management and

communications tool in terms of usage and importance towards internal and external information flow and

collaboration in your firm?

Telephones, Fax 1 2 3 4

Fax 1 2 3 4

E-Mail 1 2 3 4

Electronic messaging (PDAs, Intercoms etc.) 1 2 3 4

Automated Collaborative Software Tools 1 2 3 4

Others (Please Specify)________________________________ 1 2 3 4

11. What percentage of activities in your company involves Project Management functions? (Round to higher

side)

10 20 30 40 50 60 70 80 90 100

12. What, in your opinion, is the percentage of employees utilizing project management (PM) software

applications in your company? (Round to higher side)

10 20 30 40 50 60 70 80 90 100

13. How would you rate training of executives in PM applications or IT enablers in your firm?

Very well trained and Up-to-date

Moderate and Need-based Training

Trained Initially and Expected to Cope

Training delegated to external agencies at personal expense

Not trained at all

Not Applicable

XI

14. Does your firm have its own IT and / or software application development or customization

department?

Yes

No

Not Applicable

15. Which kind of PM software application/s does your firm currently employ?

Custom made software applications developed by external agencies.

Custom made software applications developed by internal IT and software department.

Commercial off-the-shelf software applications.

Not Applicable

16. If your firm uses software applications that were purchased commercially and then tweaked to best fit

your organizational setup or were developed specifically for your firm, how much initial planning in your opinion, was experienced while this upgrade / implementation occurred?

More than a year, but with / without major adverse effect on ongoing operations.

A couple of months, with / without major adverse effect on ongoing operations.

A few weeks with / without minor problems and modifications in ongoing operations.

Not Applicable

17. If your firm uses software application/s towards PM functions like scheduling, tracking and monitoring,

document management, collaboration, etc, which one of the following best describes the architecture or functioning of the said application/s?

One software package with integrated correlated modules for various PM functions.

Different softwares for various functions and automatic import / export / updating of data.

Different softwares for various functions where changes have to be made manually.

Not Applicable

XII

18. How would you rate the following factors, in terms of importance, as drivers towards investment and/or

enhancement in PM software applications in your firm? [On a scale of 1 to 4 where;]

1: Last priority; Negligible or no consideration.

2: Low priority; Minimal impact on investment decision.

3: High Priority; Major considerations influencing the investment decision.

4: Very High Priority; Primal cause for investment and business case development.

A specific project warrants the use of the application 1 2 3 4

Generic drive for better business process practices 1 2 3 4

Necessitated due to competitiveness in the industry 1 2 3 4

Strategic management and business expansion decisions 1 2 3 4

Availability of better technologies at lower costs 1 2 3 4

Clients expectations / demands / preferences 1 2 3 4

Legal compliance for a particular task 1 2 3 4

Compliance with latest / new quality assurance programs 1 2 3 4

Drive for greater integration in PM functions 1 2 3 4

Return on Investments and Financial case justification 1 2 3 4

Application purchase, licensing, renewal and service costs 1 2 3 4

Proficiency of current staff in using advanced applications 1 2 3 4

Need to hire experts or train existing employees etc. 1 2 3 4

Staff multi-tasking and flexible work distribution 1 2 3 4

Staff expectations / demand for easier / better softwares 1 2 3 4

Industry Trends and Anticipated Changes or Developments 1 2 3 4

Feedback from Clients / Partners / Subcontractors 1 2 3 4

Prior experience with computerization had excellent results 1 2 3 4

XIII

Section 3: Project Management Software Applications

19. How would you rate the following, in terms of importance, as features sets in PM software applications

that your firm currently employs or plans to employ in the near future towards enhancing business and

project management practices? [On a scale of 1 to 4 where;]

1: Not at all Important: Rarely used and hardly any significance, preferred manually.

2: Moderately Important: Not essential for most part, could be done manually.

3: Somewhat Important: Low significance but high frequency use, computing necessary.

4: Very Important: High significance and frequency of usage, computing necessary.

Executive Collaboration and Decision Support Dashboards 1 2 3 4

Proposals, Contracts and Bid Management, Details and Status 1 2 3 4

Contract Administration, Finance, Insurance and Records 1 2 3 4

Work Breakdown, Planning, Scheduling and Monitoring 1 2 3 4

Vendor databases, Management, Procurements, Tracking 1 2 3 4

Subcontractor Collaboration, Work Allocation, Payments, RFIs 1 2 3 4

Purchase Orders, Tracking and Related Documentation Management 1 2 3 4

Change Orders, Managing, Documenting and Collaboration. 1 2 3 4

Submittals, Management, Approval and Review Cycles 1 2 3 4

Project Budgets, Financial Analysis, Monitoring and Cash Flows 1 2 3 4

Equipment Management, Allocation, Tracking and Expenses 1 2 3 4

Resource Management, Forecasting, Availability and Utilization 1 2 3 4

Risk Management, Identification, Planning, Mitigation 1 2 3 4

Material Management, Inventory Control, Usage and Insurance 1 2 3 4

Operations Management and Workflow Analysis 1 2 3 4

Partner Management, Investments, Portfolios and Collaboration 1 2 3 4

Enterprise wide assessment of schedule and budget impacts 1 2 3 4

Daily Logs, Rosters, Meeting Minutes, Letters and Reports 1 2 3 4

Periodic Reporting Cycles, Statistics, Timelines, Progress Rates 1 2 3 4

Reports, Notices, Memos, Invoices and Other Documentation 1 2 3 4

XIV

20. How would you rate the following, in terms of importance, as aspects of PM software applications that

your firm currently employs or plans to employ in the near future as factors that influence the selection

of a particular application over others? [On a scale of 1 to 4 where;]

1: Not at all Important: Insignificant and not considered during business case development.

2: Moderate Importance: Does not affect PM efficiency at all and has low priority.

3: Somewhat Necessary: Not essential but preferred if application has this capability.

4: Highly Desirable: Crucial feature impacting the reasons for upgrade or purchase.

Backward Compatibility with Legacy Systems 1 2 3 4

Scalability and Customization for individual business needs 1 2 3 4

Hardware Resource Requirements of the Application 1 2 3 4

Initial Cost of the Software Application 1 2 3 4

Costs for License renewal, Extension and Upgrades 1 2 3 4

Toolsets and Functional Features of the Application 1 2 3 4

Communication and Networking Capabilities 1 2 3 4

Compatibility with Generic Devices like PDAs and Laptops 1 2 3 4

Business data security concerns 1 2 3 4

Vulnerability of Application to viruses and system bugs 1 2 3 4

Data storage, interpretation, access and visibility aspects 1 2 3 4

Data Entry Protocols and Output Report Formats 1 2 3 4

Data Transfer to/from Other Computers and Devices. 1 2 3 4

Ease-of-Use and User Friendly Interfaces 1 2 3 4

Compatibility with other Office Solutions Applications 1 2 3 4

Projected Life, in terms of Utility, of Software Application 1 2 3 4

Easy to procure, Install, Customize and Upgrade 1 2 3 4

Strong Customer and Technical Support / Documentations 1 2 3 4

XV

21. How would you rate some of the following futuristic software application toolsets, in terms of importance and helpfulness as an aid to project planning, control, administration, execution and management processes ; [On a scale of 1 to 4 where;] 1: Not at all helpful. 2: Moderate Assistance 3: Necessary 4: Highly Desirable

Integrated estimating, scheduling and project monitoring tools 1 2 3 4

4D (time-bound 3D) process visualization and simulation 1 2 3 4

Global or continental vendor / subcontractor databases 1 2 3 4

Onsite wireless technologies with automated data acquisition 1 2 3 4

Lessons learned and prior project execution / experience databases 1 2 3 4

Automated algorithm-based optimized resource allocation 1 2 3 4

Central regulatory and compliances databases 1 2 3 4

Automated simulations for change management decision-making 1 2 3 4

Centralized network-based limited-access monitoring for all parties 1 2 3 4

22. How would you rate some of the following aspects as generic obstacles to procurement and

implementation of advanced project management software applications in construction firms [On a scale of 1 to 4 where;]

1: Not an obstacle at all 2: Minor problem that may be addressed and overcome 3: Significant issues, but not in all cases 4: Major barriers

Lack of precedents of application usage in the industry 1 2 3 4

Major investment without guarantee of success and/or returns 1 2 3 4

Necessity of high computing proficiency levels in senior management 1 2 3 4

Apprehension regarding start-up issues during critical ongoing projects 1 2 3 4

Preference for old-style paper-based / existing management protocols 1 2 3 4

Concerns regarding data security and confidential strategic business plans 1 2 3 4

Lack of applications that may rapidly be customized to suit our firm 1 2 3 4

Concerns about application bugs that may result in financial risks / losses 1 2 3 4

Downtime owing to upgrade of existing setup and existing data entry 1 2 3 4

XVI

23. What software/s or line of softwares does your firm currently use towards as a PM application? (Check

All Applicable)

Microsoft Products (MS Project, MS Dynamics, MS Axapta etc.)

Primavera Systems Products (Project Planner, Enterprise, Expedition, Suretrak etc.)

Meridian Systems Products (Prolog Manager, Project Talk etc.)

Sage Timberline Products (Project Management, Integration, etc.)

CMiC Products (Integration, Enterprise etc.)

Others (Please Specify)___________________________________________________

24. What percent of your firm’s net revenues, in your opinion, is allocated to IT systems maintenance,

development and expansion, including but not limited to PM applications purchase, upgrade, extension

or acquisition of licenses? (Check One, Round to Lower Side)

10 20 30 40 50 60 70 80 90 100

25. Would you agree that highly sophisticated integrated software systems make the project management

and coordination tasks more agile and easy to perform? (Please use space below to cite any specific

reasons for your response)

Yes

No

Can’t Say

26. Who, in your firm, endorses the purchase or upgrade of PM software applications?(Check All

Applicable)

Top Management

Project Managers and Executives

Internal Software / IT Department

Other (Please Specify)___________________________________________________

XVII

APPENDIX B SCREENSHOTS OF ONLINE SURVEY

XVIII

XIX

XX

XXI

XXII

XXIII

APPENDIX C

VERBATIM COMMENTS OF RESPONDENTS ON WHETHER ADVANCED

COMPUTING SOLUTIONS ARE EFFECTIVE AS A PM TOOL

“Sophisticated integrated software allows for automatic redundant data entry (across multiple disciplines) and provides many custom reporting options. As such, tasks are inherently easier to perform.” “Sometimes yes, sometimes no.” “Yes, provided you manage the software application rather than become a slave to it.” “Software systems always lack elements of flexibility to provide necessary information that I think and want to see for field documentation. I still like to use Excel and Word for my ability to customize.” “Mostly yes, but not always.” “Yes, but cause some PM's to loose touch with the actual project and what is going on in real life.” “Depends on the use we are talking about.” “There are no programs on the market that support a large sophisticated organization in all the functions necessary to the level that companies like us need. Your internal work processes and the software need to align or one of them must change. Finding one package that either aligns or that you want to change all of your processes to or want to customize is not something large, complex companies undertake lightly. Most of the ERP implementations have produced limited success with costs and schedules far exceeding estimates.” “Yes, as long as PM staff possess equal competency levels.” “Yes, having highly integrated Enterprise software reduces redundant data entry, improves accuracy of data, and provides it real-time for project leaders during decision making.” “No. PM software is a tool and not a management organization.”” “Depending on the project size and value, many times the application of the system (in staff hours) and the costs of the system cost more than the value saved by the use of them. Keep it simple is still the best model.”

XXIV

APPENDIX D

VERBATIM COMMENTS OF RESPONDENTS ON PM APPLICATIONS AND THE

STUDY

“Major downside of most programs is that it does not focus on pre-construciton phase and pre-development work. The owner's needs are not adequately addressed in most of these packaged programs as they are targeting the larger GC market. Yet the greatest benefits for collaboration, etc. can be accrued in this phase of the work which may then dictate to GC that they must carry through with the same program during construction. The designers resist these type of solutions because they place an added burden on their staff resources when they have to deal with multiple PM software programs for their numerous projects during construction administration. If the designers are not using the same platform then the burden falls back on GC's resources to have a project engineer or admin to re-enter the data or scan in the data/faxes, etc.” “I did similar research on this subject and found that because the building industry has individuals with various backgrounds in technology, being up to par with new trends in technology would be a slow process. Once the software was utilized, it was a matter of training individuals to be able to comprehend what they were looking at. Some companies don't see the life cycle costs in how much they are saving but focus on the front end costs in terms of time and money invested. This was a challenge but was exciting to research!!!” “In general, for the type of work that we do, we have to comply with the software requirements of the contract. My personal preference is for PM Software by Primavera.” “Certainly, a single software that can "do all" sounds good, but our firm is involved in such a wide variety of projects, project sizes and project types, that no single application could ever be flexible enough to serve all of our project needs and still remain user friendly enough to be easily used without an overly burdensome investment in training.” “Good luck with your research. Been there.” “Often the software has the capability to integrate but the field staff prefers doing things the old way.” “All software usage in Construction Management should be thought of as a tool to assist in Managing the Risk. Using standard software for project controls, documentation and contract administration is a must on all construction projects. Continuous Communication is an essential part of Managing the Risk. Using a collaborative-type software for these same functions should be a must on all larger projects - say over $1,000,000 in value - to provide communications between all parties - Owner, A/E and Contractor.”

XXV

“Have not had a lot of experience with PM software personally. We can't seem to get the required participation and everyone is comfortable with how PM operations have always been done, so why change it.” “All these different systems are slowly leading back to the times when every company had its own programmer that would create coded programs to do specifically what the executives wanted. This leads to the idea that there needs to be a separate IT hierarchy for Project Management-related tools.” “Good Luck!” “Would suggest you segment the market as you continue to develop your research project. Our needs and sophistication are much different from most of the companies you will survey. Confining your survey(s) to general contractors or residential construction, etc. will help you focus and draw better conclusions, in my opinion. But obviously I am not privy to your overall research theme, so you can take my comments with a grain of salt. Good luck with your work.” “It is more common that not, most firms are usually need to adapt and utilize a system which the Client requests. More than less of the owners are not able to invest the $ required for IT and usually are forced to focus on the project cost and desire, versus the tools used to manage it.” “Typically not enough time or money is allocated for training, therefore the potential of the integrated application is never realized and return on the initial investment is minimal.” “I would like to receive the results/ analysis of this survey.” “Implementation planning of software is very important and should include: Executive Buy-in, complete process review and development, and the behavioral side of adoption of the new software.” “{Company Name Omitted} has a great IT Department and really does a good job catering to the users of the systems. They have continually provided training for the PM's, Engineers, Clerical, etc., and understand the importance of providing support and assistance. They utilize feedback and suggestions to make modifications that help improve and update the software, hardware, and at the same time use volume purchasing to get the best available pricing. They also have national deals cut with communication companies for phone systems, internet access, cell phones, licensing, etc.” “Some of the answers I have provided address our in-house software to manage company data; and some of my answers are related to the software that our clients own that we use to manage their data. Hope you can tell the difference.”

XXVI

APPENDIX E

SAMPLE SAS CODE FOR SPEARMAN RANK CORRELATION TEST

data fit; input y1-y21@@; datalines; 2 3 2 4 4 4 4 4 4 4 4 3 2 4 2 3 3 4 4 4 4 3 3 4 4 4 4 4 4 4 4 4 . 4 4 4 . 3 3 4 4 4 3 3 4 4 4 3 3 3 3 3 4 2 3 2 2 3 3 4 3 3 3 4 2 2 3 3 2 2 2 2 2 2 2 2 1 3 2 2 2 2 2 2 3 3 4 4 2 3 3 4 4 3 2 3 3 4 3 2 4 2 4 4 2 3 3 3 3 4 3 3 2 4 3 4 2 3 3 2 3 3 4 2 4 2 2 4 4 3 3 4 4 4 4 4 4 4 3 3 3 3 2 3 4 3 3 4 2 3 4 3 4 4 3 4 3 4 3 3 3 3 3 2 2 3 3 3 4 3 4 4 4 3 3 4 4 4 4 4 3 3 4 3 3 3 4 3 3 4 4 4 3 4 4 3 2 3 4 4 3 3 4 4 2 3 2 4 4 2 3 1 3 3 4 3 4 4 4 3 3 2 2 2 2 2 2 1 4 2 2 1 2 4 4 4 4 4 4 4 4 4 4 4 4 2 3 1 3 4 3 3 2 2 3 3 4 3 4 4 3 4 3 2 4 3 3 3 3 4 3 3 3 2 3 3 3 4 2 4 4 4 4 4 2 2 1 2 1 1 2 4 1 2 3 1 3 3 3 2 3 2 3 3 3 2 3 3 2 2 2 3 3 3 3 3 3 4 3 4 3 4 3 4 3 3 3 4 4 3 3 3 4 3 3 3 3 3 3 4 3 2 3 2 3 3 4 2 2 3 3 1 1 2 3 2 2 3 3 4 4 2 3 3 4 4 4 3 3 3 2 4 4 3 3 4 2 2 ; run; proc print;run; proc corr data=fit spearman; var y1-y21; run; symbol i=rl; proc gplot; plot y1*(y2-y21); run;

XXVII

APPENDIX F

SAMPLE SAS CODE FOR WILCOXON COMPARISON OF MEANS TEST

data fit; do group=1 to 18; input y@@; output; end; datalines; 2 3 3 4 4 4 4 3 3 4 3 3 4 4 4 4 4 3 3 3 4 3 1 4 4 4 3 3 3 4 3 3 3 3 4 4 3 2 3 3 3 4 3 3 3 2 2 3 2 3 4 2 3 3 4 2 3 3 3 4 4 2 2 3 3 3 3 2 2 2 3 2 3 3 4 4 2 4 4 3 2 4 3 4 2 2 3 2 3 4 3 2 3 4 3 3 3 3 2 2 3 2 2 4 2 3 4 4 2 3 3 3 1 2 3 3 3 3 2 3 3 2 3 2 2 2 4 4 3 3 4 3 4 3 3 4 3 3 4 3 3 3 3 3 4 3 3 3 3 4 4 3 3 3 3 3 3 3 3 3 3 3 4 3 2 2 3 4 4 4 2 3 1 3 4 4 2 2 4 3 3 2 2 1 2 3 3 2 2 2 3 2 2 2 2 2 3 3 3 3 3 3 3 4 3 3 4 3 3 3 3 3 3 3 3 3 3 3 3 3 2 3 2 3 3 3 2 3 2 2 2 2 2 2 2 3 3 3 2 2 2 2 3 2 3 3 2 3 2 3 2 3 2 3 3 2 3 4 2 3 3 2 3 3 2 2 3 2 4 3 3 3 3 2 3 3 1 1 2 2 2 2 2 3 3 3 2 2 4 2 3 2 2 3 3 2 2 2 2 2 2 2 3 3 3 2 ; run; proc npar1way data = fit wilcoxon; where group in(9,13); class group; var y; run;

XXVIII

APPENDIX G

SURVEY BASED JOURNAL PAPERS AND RESPECTIVE SAMPLE SIZES Liberatore, M.J., et al. (2001). “Project Management in Construction: Software Use and Research Directions.” Journal of Construction Engineering and Management, ASCE, 129(2), 101-107. {42} Assaf, S.A., et al. (1995). “Causes of Delay in Large Building Construction Projects.” Journal of Management in Engineering, ASCE, 11(2), 45-50. {48} Soares, J., et al. (1997). “Modeling Process Management in Construction.” Journal of Management in Engineering, ASCE, 13(5), 45-53. {50} Akintoye, S.A., et al. (1997). “Risk Analysis and Management in Construction.” International Journal of Project Management, ELSEVIER, 15(1), 31-38. {43} Chua, D.K.H., et al. (1999). “Critical Success Factors for Different Project Objectives.” Journal of Construction Engineering and Management, ASCE, 125(3), 142-150. {20} Alhazmi, T., et al. (2000). “Project Procurement System Selection Model.” Journal of Construction Engineering and Management, ASCE, 126(3), 176-184. {40} Archibald, D.R., et al. (2003). “Project Categories and Life Cycle Models” Proceedings of 18th IPMA Project Management World Congress, Budapest, 06/2004, IPMA {31} Doherty, J., (1997). “A Survey of Computer Use in the New Zealand Building and Construction Industry.” Study Report SR 80, Building Research Association of New Zealand, Wellington, New Zealand. {47}

XXIX

APPENDIX H

WEB BASED TEMPLATE FORM OF QUESTIONNAIRE DESIGN

XXX

Executive Collaboration & Decision Support Dashboards

Proposals, Contracts and Bid Management, Details and Status

1 2 3 4

4 3 2 1

1 2 3 4

1 2 3 4

1 2 3 4

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

4 2 1 3

3 1 2 4

4 2 1 3

3 1 2 4

Reports, Notices, Memos, Invoices & Other Documentation

Periodic Reporting Cycles, Statistics, Timelines, Progress rates


ERP based assessment of schedule & budget impacts

Partner Management, Investments, Portfolios and Collaboration

Operations Management & Workflow Analysis

Material Management, Inventory Control, Usage & Insurance

Risk Management, Identification, Planning, Mitigation

Resource Management, Forecasting, Availability & Utilization

Equipment Management, Allocation, Tracking & Expenses

Project Budgets, Financial Analysis, Monitoring & Cash Flows


Change Orders, Managing, Documenting & Collaboration.

Purchase Orders, Tracking & Related Documentation

Subcontractor Collaboration, Work Allocation, Payments, RF

Vendor databases, Management, Procurements, Tracking


Contract Administration, Finance, Insurance & Records

Section 3 : Project Management Software Applications

1 : Not at all Important : Rarely used and hardly any significance, preferred manually.

2 : Moderately Important : Not essential for most part, could be done manually

3 : Somewhat Important : Low significance but high frequency use, computing necessary.

4 : Very Important : High significance and frequency of usage, computing necessary

13. How would you rate the following, in terms of importance, as feature sets in PM software

applications that your firm currently employs or plans to employ in the near future towards

enhancing business and project management practices? [On a scale of 1 to 4 where;]

CAPABILITY BASED IMPORTANCE

LOWEST HIGHEST

APPENDIX I

TURNERTALK PRICING CHART

XXXI

AECMS Rates for 2005

Description Units Rates

TurnerTalk – Monthly RatesProject Management Account – Turner Per Month/Per User $ 125.00 Collaboration Account – Turner Per Month/Per User $ 50.00 Tier 1 Project Free OAE Accounts 10 $ - Tier 2 Project Free OAE Accounts 10 $ - Tier 3 Project Free OAE Accounts 15 $ - Tier 4 Project Free OAE Accounts 15 $ - Tier 5 Project Free OAE Accounts 15 $ - Tier 6 Project Free OAE Accounts 20 $ - Tier 7 Project Free OAE Accounts 20 $ - Additional Collaboration Account - Owner/Architect/Consultants Per Month/Per User $ 50.00 Collaboration Account - Subcontractor Per Month/Per User $ 50.00

TurnerTalk – Annual Rates**(Annual Accounts are billed in full upon setup of the account)Project Management Account Per Year/Per User $ 1,375.00 Collaboration Account - Turner Per Year/Per User $ 550.00 Collaboration Account - Subcontractor Per Year/Per User $ 550.00

Hosted Applications – Set Up Fees**(Fees are based on Construction Volume)Tier 1 Project Setup Fee [$1.5mm - $4.99mm] One-time fee per project $ 500.00 Tier 2 Project Setup Fee [$5mm - $14.99mm] One-time fee per project $ 1,000.00 Tier 3 Project Setup Fee [$15mm - $29.99mm] One-time fee per project $ 1,500.00 Tier 4 Project Setup Fee [$30mm - $49.99mm] One-time fee per project $ 2,500.00 Tier 5 Project Setup Fee [$50mm - $74.99mm] One-time fee per project $ 3,500.00 Tier 6 Project Setup Fee [$75mm - $124.99] One-time fee per project $ 5,000.00 Tier 7 Project Setup Fee [$125mm - $174.99] One-time fee per project $ 7,500.00 >/= $175mm One-time fee per project Negotiated

Professional ServicesTrainer Day $ 1,000.00 Consulting Hour $ 125.00 Senior Consultant Hour $ 150.00 Consulting (Purchasing Depts. Only for Initial Implementation) Hour $ 55.00 Custom Report Development Hour $ 125.00 Travel Time Hour $ 55.00 Travel Expenses Actual CostWorkbooks Per Unit $ 65.00 Priority Shipping Fee Per Unit $ 10.00 Shipping Fee for Software Per Shipment $ 15.00 Training Facility Set Up Per Training Class $ 250.00 Training Facility [Fee based on 12 attendees @ New Horizons] Per Day $ 995.00 WebEx Sessions (Billed in 2 hour increments) Per 2 hour increments $ 250.00

Prolog Stand Alone ApplicationProlog Manager License (Refund policy applies) Each $ 2,100.00 Prolog Manager Support Contract Per license/Per Year $ 400.00 Prolog Website Server One-time installation fee $ 2,000.00 Prolog Website Server Support Contract Per license/Per Year $ 400.00 Prolog Website Client Per concurrent user $ 450.00 Prolog Website Client Support Contract Per license/Per Year $ 100.00

Revision Date 02.09.04

NOTE: This document is intended for use by AECMS Consultants to provide the Client with a general overview of the cost involved to provide Professional Services the Client has requested or that AEC Management Solutions is recommending to the Client for the implementation of TurnerTalk, Prolog WebSite, Prolog Manager, etc. It shall in no way be used as a definitive Sales Agreement and is subject to the Terms and Conditions of the AEC Management Solutions Professional Services Sales Agreement. Rates are subject to change without notice. Sales Tax is not included in these rates and will be added to the cost for workbooks, licenses and TurnerTalk accounts. Project Setup fees are for all projects, including SPD and Interiors.

APPENDIX J

“This research document is an extremely detailed and complex analysis of project management softwares and the decision-making processes into selection and usage. The content offers well founded recommendations and criteria that need to be given serious consideration by construction management professionals in the industry.” T.J. Walsh

XXXII