Using BI to Identify Revenue and Resource Reallocation (166271280)

7/29/2019 Using BI to Identify Revenue and Resource Reallocation (166271280)

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USING BI TO IDENTIFY

REVENUE AND RESOURCEREALLOCATION

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Donna RohlferDirector Budgeting and

Business TransformationFinance and Business Services

[email protected]

Phyllis Wykoff Director,

Business Intelligence Center

IT [email protected]





•University is one of the oldest public

institutions in the country. It waschartered in 1809 and opened itsdoors to students in 1824.

• Located in Southwest Ohio

• Named for the Miami Indian Tribethat inhabited the area now knownas the Miami Valley Region of Ohio

Miami University



Total Enrollment 2012 23,390

Undergraduates

Oxford: 15,081

Hamilton: 3,615Middletown: 2,092

Masters & Doctoral

Oxford: 2,476

Voice of America Learning Center: 126

Faculty & Staff (with GA’s) 5,000Faculty & Staff (excluding GA’s) 4,198

College & Schools 6

Miami University



Recognition

Kiplingers (2012):Once again, Miami University has been

identified as a bestvalue in Kiplinger's annual list of the

"100 Best Values in Public Colleges“

Fiske Guide to Colleges (2013)The Fiske Guide to Colleges 2013 includes

Miami in its list of the nation's "best and

most interesting colleges anduniversities." Recognized for strongprograms in architecture, business, andmusic.



Recognition

• 2012 President's Higher Education Community ServiceHonor Roll

One of five recipients out of 641 eligible schools inthe nation to Miami's honor recognizes service

programs in the area of early childhood education.

Forbes 2012In the magazine's 2012 list of America's Top Colleges,

Miami ranks 35th in the nation and 1st in

Ohio among public universities



Our Environment

•Ellucian Banner ERP

•Primarily an Oracle shop

•Business Intelligence tool is

•Oracle Business Intelligence Enterprise Edition(OBIEE)



Miami’s BI History

• 2008 - Limited funding to build a BI program

• Got creative• Found and used extra SQL Server Licenses

• Found unused hardware

• Created small model and cube to show thepotential of BI

• With Miami University data

• Used Excel as presentation tool




• 2009 – Summer Profitability Project

• Create „Profit and Loss‟ statement for eachcourse section

• First production use of BI at Miami University

• Utilized „found‟ hardware and software

• Used Excel as presentation tool

• Did write some report using SQR




• 2010 Released RFP for Enterprise BI tool

• 2011 – Purchased Oracle Business IntelligenceEnterprise Edition

• Implemented in 2011

• First dashboards in late 2011

• 2013 – Still learning!



The Situation!



Financial Issues Facing Higher Education

• Price regulation

• Increasing price elasticity

• Negative demographic trends

• Increased competition

• Potential cuts in state funding

• Increased health care costs

• Rapidly rising commodity prices





Funding Sources per StudentFY1990-FY2012

(1990 Inflation Adjusted $)



Special Challenges for Miami University

• Limited revenue diversification

• Restrictive access to some high demand programs

• Slow development of new academic revenue

• Inability to measure performance of initiatives

• Cost cutting versus increased productivity

• One time versus permanent approaches tosolutions



Strategic Initiatives and Forward Thinking

“...Given the very significant changes in the economy and the competitive context of higher education, more

than ever it is critical that Miami be forward-looking

and purposeful in fulfilling our mission...”

“…prioritize and align our strategic goals with the new

economic reality and competitive higher education

context by creating a long-term sustainable baseline

budget and identifying strategic options for improving

our resource base…”



Strategic Initiative Recommendations

A. New Revenue Opportunities

B. Improve the Efficiency and Effectiveness of University Administrative and Support Functions

Included the recommendation to develop a new

budget model that will result in the generation of

new revenues, improved resource reallocation

and greater operating efficiencies



Strategic Initiative Recommendations (cont‟d)

C. Improve the Efficiency and Effectiveness of Our Core Educational Efforts

D. Improve the Efficiency and Effectiveness of Student Services and Co-Curricular Activities



Current Budget Model

• Historical budget practices at Miami

• Centralized approach

• Stand-alone worksheet based model

• Focus on unit actual to budget performance rather than institutional financial performance

• Lack of financial performance information for academic programs or support centers



Considerations in Developing a New Budget Model

• Impact of governance on planning and decision-making

• Historical clustering of academic programs

• Industry and customer (student) connections occur at the unit level

• Successful change requires strong unit supportdriven by clear incentives and rewards



New Budget Model

• More effective measure of financial performancefor every academic program

• Where are my revenues being generated?

• How are resources consumed to generate

these revenues?

• Who is enrolled in my courses?

• Decentralized system increases influence of academic divisions over financial planning andresource allocation decisions



New Budget Model (cont‟d)

• Better assures financial issues are considered inacademic program decisions

• What is capacity?

• What does this cost to offer?

• What is net revenue?

• Provides very clear incentives for improved

financial performance

• How to determine the method of revenue

allocation?



Help!

We need data!



They asked for data—

But we deliveredInformation!



Cross Functional Core Team

Cross Functional Core Team

Provost

Academic Affairs

Vice President

IT Services

Asst DirectorContinuing

Education

Assoc. VP Finance

& Business

Assoc. VP Budget &

AnalysisAsst Registrar

Controller

Budget DirectorDirector,

Institutional

Research

Sr. Director,

Enterprise

Information Systems

Director, Business

Intelligence

Business

Intelligence Team

Members and

Analysts

Director, Financial

Assistance Bursar

Vice President

Finance and Business

Services



Data Sources

•Registration data – Who is taking each course?

•Bursar data – How much was each student charged? –Undergraduate, Graduate, Campus, Residency

•Bursar data – How much did each student pay? –Waivers

•Financial Aid – Authorized Financial Aid



Registration data

•Student based data•Course data•Section data•Registration data

•Instructor •Credit hours•Headcounts

This is not an enrollment view of registration data butrather a Bursar‟s view of registration



Bursar Data

Student Based Revenue processed through Bursar

•Instructional Fee

•General Fee

•Course Specific (Equestrian courses)

•Program Specific (Architecture students)

•Lab Fees (Chemistry)

•Divisional Fee (Business Surcharge)



Financial Aid

•External Financial Aid

•Institutionally Funded Financial Aid•Expense to University

•Institutional discount rate



Reality Sets In…

•Business practices have changed•Some data was obsolete

•Some data usage changed over time

•Some data was just wrong

•Some data was missing



Reality of Source Data

• 7500+ Detail (charge) Codes used since 1999

• 1300+ Detail Codes for Tuition− No distinction between General, Out of State or

Instructional Fee

• No easy way to organize or analyze the data

• Charges by credit hour, not by course



Classification of Bursar Codes

Created a five level hierarchy for EACHdetail code.Detail Code 0106 “UG Instructional Fee – 1st Sem” • Level 1 – Revenue

• Level 2 – Tuition and Fees• Level 3 – Instructional Regular • Level 4 – UG Instructional Regular • Level 5 - blank

Detail Code C11S “Class of 2011 Scholarship”

• Level 1 – Expense• Level 2 – Tuition Aid• Level 3 – Scholarship• Level 4 – Internal• Level 5 – Instructional



Convert Fees/Waivers to be Course-based

• Miami University‟s fee structure is based on credithours attempted, not per course

• Pro-rated fees, waivers, financial aid

– Calculated per credit hour rate and applied to

course by credit hours for each student

• $10,000 in instructional fee, 10 credit hours

− Calculated per credit hour rate of $1,000 per

hour

− 3 credit hour course „price‟ $3,000



A Star is Born

• Created a dimensional model (star schema) that:• Combined the data from multiple data silos

• Added derived measures (fees/waivers

per student per class per term)

• Added derived fields (financial cohort)

• Added hierarchies for analytical capabilities

• OBIEE used to create Executive level dashboard

• And Management level reports• And Ad hoc query tool for further analysis



Derived fields = Information



Additional Project Benefits

• Model provides single version of the data• All analyses and queries provide the same

numbers• Provided the information needed to move

forward with Responsibility Center Management

• Demonstrated the power of BusinessIntelligence to address strategic needs

• Demonstrated the value of eliminating datasilos



Project issues and challenges

• Testing

• Categorizing the same data for different user needs and applications

• Merging the need for:

• Exclusive and exhaustive data granularity

• Analytics

• Executive dashboards

• Management level reportingFrom ONE data source!



Project issues and challenges

•BI requires leadership, commitment, input and work from both ITand from the business users.

•No one person understands all the data and implications

– Talk to a wide range of people to get the entire picture

•Validate, validate, validate

–New way to look at data

–Prove it ties to source data on a daily basis

•Data validation

•Immediate notification data issues

•Context is important –Data cube is both powerful and dangerous



Learnings

• Testing

• Metadata management

• Data visualization – Design and Testing

• Training – BI concepts, new tools



Best Practices

• Allow reasonable timeframe•Use project management methodology

•Have the right people at the table

− Accountability

−Everyone contributes, everyone questions

•Commitment to the project from top down

−Implies regular attendance at meetings

−The project sponsor sets the tone by showing up andparticipating

−Moves the project forward•Sub-groups address specific issues and topics

•Document, document, document



Where are we now?

• Data Warehouse developed and deployed usingOBIEE

• Learning curve – new technology, new processes

• Testing – took a huge amount of time for IT staff and for functional staff

• Training – multiple tools to learn

• Value increased communication and client/ITteamwork



Where are we now?

• Revenue model contains:

• 19 Dimensions

• 3 Fact tables

• Revenue – Over 555,000,000 rows

• Course registrations – Over 6,300,000 rows

• Updated nightly

• Capture Point in Time (PIT) Snapshots on strategicdates for historic analysis



The Original Questions

• Where are my revenues being generated?• How are resources consumed to generate

these revenues?

• Who is enrolled in my courses?

• What is capacity?• What does this cost to offer?

• What is net revenue?

• How to determine the method of revenue

allocation?



Clients view of solution

Miami University's investment in institutional analytics has provided hugedividends for our institution.

First, it has added a level of sophistication to our understanding of how our business practices are reflected in our ERP.

Second, the design work has resulted in closer alignment of our analyticalcorps across the university.

And, last but not least, it is supporting strategic conversations aroundbudgeting and finance that were not possible without this capacity. Thepromise of IA going forward is that Miami University will have stronger

management and more insight into strategic implications of our decisions.

---David Ellis, Associate Vice President, Budget and Analysis



Executive Dashboards











Questions?

Documents

Using BI to Identify Revenue and Resource Reallocation (166271280)