Business Intelligence at the University of Minnesota

Transcription

1 Business Intelligence at the University of Minnesota Defining the need and the solution for a comprehensive decision support system for the University of Minnesota Internal Communications Network December 16, 2010 Peter M. Radcliffe Executive Director Office of Planning and Analysis

2 How do we make good decisions? Good decisions bring together Evidence and Information What does reality look like? How do the parts fit together? Expertise and Judgment How will stakeholders respond? What resources are available? What are our goals?

3 Paths to improving decision-making Attempt to improve the decision-maker s skills or enrich their context The University provides professional development and training for leaders through internal and external opportunities Business intelligence is a strategy to increase the quality, accessibility, and use of evidence

4 What is business intelligence? Many different ways of phrasing concept by different authors General concept is captured by: "BI represents an integrated set of technologies and processes that use data to analyze and understand organizational performance" Most importantly, BI is not a software package or set of tools, but a comprehensive strategy

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6 What s in a name? There are often concerns surrounding the application of ideas from the corporate or business world into academic decision-making The concerns reflect uncertainties about how decisions will be made and what information will be used to make them Business intelligence is a well studied, well articulated, widely applied concept BI has the potential to increase transparency, which has the potential to increase trust

7 Business Intelligence Initiative People and Processes Data governance common definitions and consistent practices Forum for collaboration and sharing spreading innovations and insights Training and development tools, analysis, and process improvement Tools and Technology Oracle Business Intelligence Enterprise Edition (OBIEE) Dashboards tabular and graphic reporting Analytics Ad hoc pivot table like reporting tool BI Publisher Report writer for Peoplesoft and/ or local data sources

8 What is the Need? University demand well documented more than a dozen institutional reports have investigated and reported on the need for validated data, tools and dashboards, metrics and measurements, and increased analytic capacity. PEL 2009 Academic Analytics Report

9 Consensus from University of Minnesota task force reports support BI as a priority Foster agreement and use of metrics and analytic tools Engage leadership support Develop quality assurance for each Enterprise System Create clusters of analytic staff and approaches Need for tools and dashboards Units have unique needs Need for data validation and oversight Need for analytic skills Themes Recommendations Perceptions of the Office of Institutional Research Source: PEL Academic Analytics analysis of 13 University of Minnesota task force reports

10 Why now? Our costs are escalating State appropriations are unlikely to rebound significantly Demographics will increase the competition for scarce resources As an institution we must innovate and improve efficiency and productivity

11 Higher Education and Consumer Inflation HEPI Index Value (1983=100) CPI

12 Minnesota Higher Education Expenditures per $1,000 Disposable Income $16.00 $14.00 $12.00 $10.00 $8.00 $6.00 $4.00 $2.00 $

13 Trends in Tuition & State Funds 1997 to 2011 $800.0 $700.0 $600.0 $500.0 Tuition State Funds $400.0 $300.0 $200.0 $100.0 $

14 Percentage of projected Minnesota population by age group % % 15% 10% % %

15 How can BI help? Student recruitment and retention Monitor and predict enrollment or dropout Each incremental student generates over $8,000 in tuition annually on average Course scheduling and support Optimal course offerings and timing reduce costs and increase graduation An incremental course costs about $10,000 in salary and fringe Total UofM instructional costs roughly $700 million

16 How else can BI help? Purchasing Analysis of unit spending by category/item Total UofM purchasing about $1 billion Employee satisfaction Analysis of survey results to pinpoint issues Avoid search costs and lost productivity due to turnover

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18 Collaboration and sharing Shared data a common home for institutional and unit data Shared understanding consistent data definitions and usage Shared tools a common suite of reporting tools for central, unit, or blended data Shared development units can develop and share their reports without waiting for central resources to be identified and assigned

19 Empowering faculty and staff Easier to use reporting tools empower faculty and staff to access the data they need Customizable report templates empower units to organize data to meet their specific needs Centrally supported tools empower units to develop their own reports and data-driven processes without heavy IT infrastructure investments

20 Implementation Implementation BI Implementation Committee Production BI Steering Committee BI Project Teams Data Governance U of M Analytics Collaborative

21 Organization supporting collaboration Business Intelligence Steering Committee Will provide overall direction and coordination Data governance committee Connect data custodians and other actors responsible for data integrity University of Minnesota Analytics Collaborative A virtual organization serving as a business intelligence competency center to guide and promote training, improve metadata, and facilitate innovation, sharing, and cooperation

22 Training: U of M Analytics Collaborative Source: How to Define and Run a Successful Business Intelligence Competency Center, Gartner, August 2007

23 Why use new tools? The Oracle BI toolset give us capabilities that are harder to produce otherwise, and are easier to use Improving ease of use democratizes access to data Improved sharing of innovation speeds dissemination of good ideas and best practices

24 1 Pre-built warehouse with more than 16 star-schemas designed for analysis and reporting on Financial Analytics Data: EDW & EPM 3 Pre-mapped metadata, including embedded best practice calculations and metrics for Financial, Executives & other Business Users. Presentation Layer Logical Business Model Physical Sources 2 Pre-built ETL to extract data from hundreds of operational tables and load it into the DW, sourced from Peoplesoft. 4 A best practice library of over 360 pre-built metrics, Intelligent Dashboards, 200+ Reports and alerts for CFO, Finance Controller, Financial Analyst, AR/AP Managers and Executives

25 Tools: Integrated set of Technologies in BI Continuum Strategic Dynamic Answers Dashboards Answers Dashboards Modeling Past Oriented BI Publisher PS ReporCng Answers Gateway Access PS Query Answers BI Publisher Ad-Hoc Query & Reporting Analytics Future Oriented Standardized Reporting Operational Static

26 Tools: OBIEE BI Interactive Dashboards BI Answers Ad hoc Analysis BI Delivers Microsoft Office Plug In Reporting & Publishing BI Publisher Common Enterprise Information Model Oracle BI Server OLTP & ODS Systems Data Warehouse Data Mart Oracle PeopleSoft, Siebel, Custom Apps Files Excel XML Business Process Other Local/ Enterprise Systems

27 BI Program History FY On six year strategic plan Q OIT BI initiative kick-off Q Pilot Project with Oracle BI Tool Suite completed Q Tool Purchase and Program Planning FY Initial Implementation

28 Implementation Timeline Fall 2010 Winter 2011 Spring 2011 Summer 2011 Future Planning and needs identification Analysis and design of test projects Implementation of test projects Rollout and training, establishment of governance and collaboration groups Expansion of content and distributed development

29 Key Success Factors Training and Skill Development U of M Analytics Collaborative Developer/Support Training Data Enterprise Data Warehouse (EDW) Enterprise Performance Management (EPM) Data Governance Tools Oracle BI Enterprise Edition (OBIEE)

30 Discussion and Updates We will continue to communicate with the University community through multiple venues To receive updates on the progress of the BI program, please send a request to opa@umn.edu (Office of Planning and Analysis)