A Single Version of the Truth: Using Business Intelligence to Inform Policy and Decision-Making

1. A Single Version of the Truth: Using Business Intelligence to Inform Policy and Decision-Making Presented to TAIR March 2010 by Kristi D. Fisher Associate Vice Provost and Director, Office of Information Management & Analysis The University of Texas at Austin

2. Overview • Information Management at UT Austin • “Project IQ” • Demo Specific Academic Cubes and Reports • Course Enrollments • Teaching Activities • Student Demographics • Faculty Demographics • Faculty Workload • Formula Funding • Graduation and Retention Rates

3. The University of Texas at Austin • 51,000+ students • 12,000 degrees awarded annually • 17 colleges • 2,500 faculty, 14,000 staff • $2+ billion budget • $460+ million research funding

4. Information Management & Analysis (IMA) • Statutory / Required Reporting • Texas Higher Education Coordinating Board (THECB) • IPEDS • Legislative Budget Board • NCAA • Accountability Systems • THECB • UT System • NASULGC/VSA • Data Sharing Consortia (AAU Data Exchange) for Comparison / Benchmarking Data

5. Information Management & Analysis (IMA) • Institutional Task Force / Committee Support • Formula Funding Task Force • First Year Support Programs Working Group • Gender Equity Task Force • Transfer Student Working Group • Task Force on Enrollment Strategy • Ad-hoc Data Support to Executive Officers (white papers, speeches, legislative issues) • Ad-hoc Requests for Information from Media, General Public, Researchers, etc. • Response to Surveys and Rankings • USN&WR, NRC Doctoral Programs

6. Information Management & Analysis (IMA) • Online Information Systems: • FaSET 12th Class Day System • ISFACL – Facilities Reporting System • Faculty Prior Approval Request Document • HRMS Faculty Positions • Faculty Rosters / Separations / Elections / Credentialing • Faculty Workload • Faculty Database and Processes • *** Extensive Batch Processing and Reporting *** • New Web Site (for more self-service information delivery)

7. Information Management & Analysis (IMA) • Enterprise Data Warehouse Support: “IQ/PBIS” – stewardship, business requirements, data sourcing, validation, analysis • Course Enrollments Cube • Student Demographics Cube • Teaching Activities Cube • Faculty Demographics Cube • Formula Funding Cube • Faculty Workload Cube • FTIC Retention and Graduation Rates Cube • Faculty Instructional Summary Report • Simultaneous Majors Report • Student Flow / Progression Reports • and much, much more….

8. Office of Information Management and AnalysisOrganizational Chart – February 2, 2010 Assoc. Vice Provost and Director, Information Management & Analysis Associate Director for Reporting Associate Vice President Senior Admin. Associate Assistant Directorfor Research Assistant Director for IT Services Assistant Director Faculty Information Business Analyst Business Analyst (IQ) Research Analyst Research Analyst Senior Systems Analyst Senior Systems Analyst Office Assistant Research Analyst Systems Analyst Systems Analyst B.I. Developer Research Analyst Information Analyst Information Analyst

9. IQ - Information Quest is… …a business intelligence initiative that provides accurate and flexible analytical tools and management information to support University leaders in data-driven decision making. Initiative was started by our VP for Financial Affairs. Phase I = Financial Information

10. Why UT Austin Began IQ • We are data rich, but information-starved • We have reliable transaction systems but weak reporting • The information we need to analyze is in transactional databases, which are not usable for analysis • Coded data requires interpretation • Programmers required to extract and format information • Process to retrieve information can be time-intensive

11. IQ … Gives University leaders the information they need in the way they want it … • Tools for reporting and analysis • Quick extraction of data without custom programming • Systematically updated data • Flexible formatting of data • Appropriate security

12. Financial Info Student Info Alumni/Donor Info Facilities Human Resources Info What Information Goes into IQ? Research Info Faculty & PBIS info

13. Benefits for Decision-Makers • Easily access trend information • Evaluate outcomes for specific populations – vary the characteristics (criteria) that define the population • Efficiently answer strategic questions without programmer intervention • “Single version of the truth” – consistent definitions across campus facilitate comparison to other colleges • Monitor and manage strategic performance initiatives • Investigate data to identify trends that have meaning in light of college initiatives

14. What is Cognos? Cognos Business Intelligence software runs on a series of servers that you access with you internet browser. Cognos lets you: Analyze your data in many different ways, at many different levels, and create charts and graphs quickly and easily… …with the click of a mouse!

15. IQ Uses Cognos to Turn Transactional Data Into Management Information

16. How Does IQ Work? The products of IQ are “cubes” and reports.

17. Project Process • Requirements Determination – Circle Diagram Session • Load all related data • Validate • Cleanse • Develop cubes and reports • Validate and cleanse • User acceptance testing • Develop training curriculum

18. IQ Data Integrity Legacy Systems (original) • Four – way data validation: • Mainframe to Mainframe • Mainframe to Oracle • Oracle to Cubes • Cubes to Mainframe Legacy Systems (revised) COGNOS Course Cube Student Cube ORACLE (warehouse) Faculty Cube Enrollment Report

19. Information Quest (IQ) Tools • ETL tools: IBM Data Stage; Treehouse tRelational / DPS • RDBMS: Oracle 9i/10g, SQL-Server • O/S: Sun Solaris RAC, IBM Z/OS, Windows 2003 • BI tools: Cognos Powerplay 7.4, Impromptu 7.4, Cognos 8.2/8.3 (new) • Named User Accounts: 1,250

20. IQ / PBIS ProcessCircle Diagram

21. IQ / PBIS ProcessTranslate to Cube

22. IQ / PBIS ProcessBusiness Rules • Example of Business Rules (give handout)

23. IQ / PBIS ProcessTraining Materials

24. Project Approach • Focus on business questions to answer • Collaboration between IQ team, data stewards and college deans/VP’s • Business not IT project • Proof of concept must capture essential business questions with actual business data • Shorten time-to-market for analytical needs • Under-promise and over-deliver

25. Project IQ Structure Phase 1 Subcommittee Phase II Subcommittee

26. Roles of the B.I. Data Steward • “Owns” the data • Maintains source systems & databases • Drives /determines business requirements • Identifies / developss data sources • Determine data definitions, joins • Validates data transfer, cubes, reports • Develops reports • Creates and maintains business rules, FAQ’s, training materials, etc.

27. IMA, IQ, and Cognos

28. Phase II = “IQ/PBIS” Information to Support the Performance Based Instruction Systemand… • Course and Instruction Planning • Enrollment Management • Strategic Discussions with EVPP/Pres • Accountability Systems

29. IQ / PBIS ProcessBusiness Questions • What percent of our undergraduate courses are taught by professional faculty? By senior lecturers, visiting or clinical faculty, lecturers and specialists? • How many TA’s are needed? How are they being used? How many faculty do I have in each department that need TA support? • What programs does course “GOV 310" draw students from? What majors is this course serving? • How can we best utilize the space we have to offer enough classes? What percent of seats were taken for each course? Were room sizes commiserate with enrollment? • How much formula funding is potentially foregone due to class/student level mismatches? Due to repeatability? Excess hours?

30. IQ / PBIS ProcessBusiness Questions (cont.) • How do we effectively evaluate classes? Is there some correlation between evaluation results and class size, the use of technology, faculty rank, etc…? • What are our 4-year graduation rates? How do they change if we exclude special classes of students (such as those in 5-year programs)? • How can we best manage enrollment? What is the impact of readmissions? SCH in excess of requirements? Admissions under CAP? • What is our student/faculty ratio by student level? • What are the indicators/predictors of success for students from specific subpopulations? To what extent are our first-year support programs effective in improving student success? etc…

31. IQ/PBIS Subject Areas • Course Enrollments • Teaching Activities • Faculty Workload • Faculty Demographics • Student Demographics • Graduation and Retention Rates • Instructional Cost / Budgeting • Affordability • Formula Funding • Course Completions / Output / Evaluations • Progress to Degree / Degrees Awarded • Facilities Utilization / Planning • Admissions

32. Cubes and Reports Under Development Cubes: • Transfer Graduation & Retention Rate • Graduate Graduation & Retention Rate • Affordability • Faculty Tenure-Track Progression • Degrees Awarded Reports: • Student Success by Sub-Population (First Gen, etc.) • Time to Degree • DFW Rates for STEM Courses

33. Access and Security • Authorizations and training are requested by the IQ/PBIS Dean’s Office Contact for each college. • Must have a Cognos account. • Each account is put into a user class,and the user class is authorized for reports and cubes. • All authorizations are “Institutional” view • Must attend training for subject areas to have access • Must acknowledge Statement of Appropriate Use to have access…

34. Statement of Appropriate Usehttps://utdirect.utexas.edu/iq/aboutiq.WBX • Purpose of IQ/PBIS is to provide academic management information to university administrators • Not to be used for personal knowledge or gain • Authority to grant access rests with Dean or VP • Every user must attend training and acknowledge this Statement of Appropriate Use • IMA provides “official” University info to THECB, Legislature, etc. • Refer responses to external requests follow university policy (Public Info. Act, FERPA, etc.) • Responses to internal requests are at Dean or VP discretion • Remember the sensitive nature of individually identifiable data

35. Deployment • On-site and/or individualized training • College information sessions • Established dean’s office contacts • Incorporating project into established academic performance initiatives (Provost’s and President’s Offices)

36. Analyze & Interpret Consider Options Data Gathering BEFORE Information Gathering Analyze Consider Options AFTER More Time For Decisions

37. Pulse Check • Is anyone using them? • Are you addressing the correct business questions and business questions correctly? • Can you show ROI? • What is the Single Version of Truth? • How is the quality of data ensured?

38. DEMO

39. Questions? Kristi D. Fisher University of Texas at Austin Office of Information Management and Analysis kfisher@austin.utexas.edu (512)471-3833 http://www.utexas.edu/academic/ima/

41. 12th Day Course Enrollments

42. Question #1

43. Answer: Seats Taken by Major

44. Question #2

45. Answer: Trend for ACC 311

46. Question #3

47. Answer: % Taught by TN/TT

48. Answer: % Taught by TN/TT

49. Analyze a Specific Class

50. Class Profile Report