Business Intelligence Need in Higher Education

“A community college in the State of Ohio realized an additional $1.1 million in tuition/state subsidy for the 2007 academic year, the first year after its data warehouse implementation, by identifying credit students who were registered and not paid on the 15th day of the term and would have been simply forgotten in years past….all on an investment of $725,000 in a business intelligence solution.”

Value Proposition

Comprehensive, campus-wide analytics – commonly referred to as “one source of the truth” – provide the foundation for strategic revenue and expense management strategies. This article touches on four highlights of a higher education business intelligence (BI) initiative: 1) getting to “institutional intelligence,” 2) application challenges for a typical business intelligence solution, 3) scoping business intelligence deliverables, timeframes and cost, and 4) sample dashboards for revenue and expense management.

Institutional Intelligence – “One Source of the Truth” from Disparate Data Sources

The concept of institutional intelligence is rooted in the academic analytics that show up on standard transactional reports, metrics, graphs and projections. A single topic, such as enrollment data, has the opportunity to inform the institution about student profiles (race/gender), institutional profiles (class/college/department) or revenue potential (credits/residency/term). Because the decision-making data is frequently stored in multiple source systems, many institutions face a huge barrier when making financial and operational decisions on the same strategic goal. Hence, the trek to the “single version of the truth” is dependent not only upon having a single authoritative source with standardized calculations but also on making this view into the institution widely available to the academic and support community.

Figure 1

Higher Education BI Process Challenges

A comprehensive business intelligence solution involves people, process, technology and data. Institutional research analysts, financial analysts and IT report writers are the leading actors in developing the culture of analytics supporting your institutional intelligence. Working together, they govern the process of storing data in business terms, creating a reliable update process and providing a unified view into multiple source systems. With a process mind-set, these folks will collaborate on a data model that can accommodate the unique challenges of higher education. Several are listed here to illustrate the challenges for a typical BI application:

• Non-cumulative measures, such as GPA or completion rate %, which must be calculated at the presentation layer rather than stored in the database.
  
  
• Slowly changing dimensions which need to preserve historical values such as academic major change.
  
  
• Unbalanced and ragged hierarchical structures, commonly seen in different departments and campus organizations.
  
  
• Need to integrate external data sources frequently used to complement marketing initiatives and compliance reporting.

Business Intelligence Expectations for Deliverables, Timeframes and Cost

Few institutions have experience in BI implementations and can articulate their deliverables, expected timeframes and projected costs. With the goal of providing “take-action analytics” for the institution’s urgent and emerging issues, a typical deliverable may need to integrate student, employee, financial, and external data. The number of datasets – commonly referred to as “stars” in best practice design – will drive the timing and costs. While the design phase and initial star creation is time and resource intensive, additional stars take less than half the start-up time and are easily multi-threaded, as in the sample timeline illustration in Figure 2.

Figure 2

The best news may be that the BI solution is easily “projectized” into multiple pieces, creating a more digestible and affordable project. A high value pilot project allows the institution to address urgent needs while minimizing costs and risks to the project due dates. After a successful pilot phase, the institution can address emerging and strategic issues with additional data “stars” as time and budgets permit.

Finally, many institutions have no idea what a business intelligence solution will cost. Well, there’s good news on that front! The bulk of business intelligence costs have traditionally been in “tool” acquisition, with costs ranging from a few thousand to over one million dollars. With the consolidation in the market, that model is changing and higher education institutions would be best served to worry more about back-end design rather than which tool houses or accesses their data. Best practice leverages the use of star schema design as the foundation for any “institutional intelligence” initiative. With the right foundation, your tool options and price points are virtually unlimited:

• Microsoft Excel – Generally available at no incremental cost, useful for initial rollout to power users; not generally recommended for widespread rollout and user self-service.
  
  
• Microsoft BI products – Microsoft’s bundled BI tools (i.e., SQL Server, Integration Services, Analysis Services, and Reporting Services) makes the incremental cost of implementing a BI solution with Microsoft especially low. These products are intended to service the power users as well as the novice and executive users, with special emphasis on user self-service, ease of maintenance and enabling a campus-wide culture of analytics.
  
  
• Vendor Hardware/Software Integrated platforms – Due to the 2007 market consolidation, these are the IBM/Cognos, Oracle/Hyperion, and SAP/Business Objects vendors. Comparatively, their price points range from medium-high 6 figures for the additional BI applications which have been integrated with their hardware platforms. Again, these products are intended to service the power users as well as the novice and executive users, with special emphasis on user self-service, ease of maintenance and enabling a campus-wide culture of analytics. MicroStrategy remains the only pure play BI tool vendor offering the business user tool and not the database and back office BI tools.

Not to beat too hard on the point, here, but all higher education institutions in search of “one source of the truth” can realistically set their sights on “take-action analytics” and grow into true institutional intelligence!

Dashboards for Revenue and Expense Management

Institutions deserve comprehensive, campus-wide analytics that improve institutional performance and accountability. With applications throughout the unified digital campus, business intelligence can enable your institution to:

• Know your student (and faculty) customer,
  
  
• Maximize student retention,
  
  
• Capitalize on alumni loyalty,
  
  
• Quickly respond to enrollment changes,
  
  
• Manage curricula to market demand,
  
  
• Improve admission, registration and other process efficiencies,
  
  
• Seek additional grants via better measurable objectives, and
  
  
• Minimize time and effort involved in compliance reporting.

For revenue and expense management, BI deliverables commonly include dashboards and mobile alerts. What do these look like? Some examples of actual dashboards used in the educational arena are shown in Figure 3.

Figure 3

Let’s discuss a final word on business intelligence deliverables and dashboards for the higher education community. Just as in the business world, higher education business intelligence solutions should be focused on “take-action analytics” based on a combination of history and forecasts. A simple data mart of historical information is no substitute for true institutional intelligence. With best practice “star schema” design to create the single version of the truth and a capable and user-friendly tool to interrogate historical, benchmark and forecast information, higher education institutions can create a foundation for strategic revenue and expense management strategies.

Recent articles by Janet Kuster, MBA, PMP, Christina Rouse, Ph.D.

• Business Intelligence: Identifying Profitable Niches
• Improve Top Line Revenue with the Right Customer Risk Analysis: Rethinking Customer Profiling after the Recession
• Why Stars Work
• Canary Metrics – A New Thought Process