Data-Driven Decision-Making: It’s a Catch-Up Game

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Data-Driven Decision-Making: It’s a Catch-Up Game

7/23/2006

By Linda L. Briggs

Feeling the pressing need for sophisticated business intelligence solutions and processes, higher ed looks for models—wherever they exist.

Good data is powerful. At Rensselaer Polytechnic Institute in upstate New York, Data Warehouse Program Manager Ora Fish was astounded when her data warehousing team was roundly applauded for presenting data on graduate admissions—data derived from the data warehouse—to top-level officials. “The cabinet had never had [solid] numbers before,” Fish realized. Suddenly, she says, “they didn’t have to argue about whose numbers were right. They could talk about the issues: how we’re doing in graduate admissions.”

Having an abundance of data residing in individual silos across campus, but little decision-ready information, is a typical scenario at many institutions. “We’ve always said the campus was ‘data-rich,’ even when we had manual collection of that data. But we couldn’t get access to it,” explains Michael Zastrocky, a VP with research firm Gartner. Zastrocky has more than 30 years of experience in higher education, and has followed the campus data situation for decades. “Then we moved to relational databases, and people said, ‘We’re still having trouble getting access to the right information.’ That’s been a major issue on campus.”

One problem: The terms data warehousing (DW) and business intelligence (BI) refer to very different things, although the two often go hand-in-hand. Data warehousing describes an architecture for storing data; business intelligence involves analytics run against that data in order to discover patterns and glean information to analyze past performance and predict future events. Typically, a data warehouse is constructed first, in itself a complex process that requires significant planning and institution-wide coordination. BI tools are then used on the warehoused data to produce reports, dashboard displays, and other windows into the data.

While many higher ed institutions now have extensive data residing in enterprise resource planning (ERP) solutions, the typical US university owns what only amounts to “an infant data warehouse,” says David Wells, director of education with The Data Warehousing Institute. While ERP solutions can offer detailed reports, and ERP vendors are moving to include more analytics solutions with their products, they can’t offer the kinds of nuanced ways to slice, dice, and analyze data that a data-warehouse- and-BI solution can. Yet higher ed lags behind private industry in its adoption of BI. “A few of the leaders in higher ed have decent data warehouses,” Wells says, but points out that most schools are still focused simply on maturing their data warehouse and data integration capabilities, “with analytics farther out on the horizon.” There are exceptions, however.

RPI and UI: Institutions Leading the Charge

Rensselaer Polytechnic Institute, for one, began to roll out a data warehousing solution in 2001, when it decided that the school’s new ERP solution couldn’t provide all the analytics and reporting needed. The warehouse was constructed across a three-year timeline; RPI also selected a series of BI tools from Brio Software (later acquired by Hyperion Solutions; www.hyperion.com) for analytics. RPI’s DW and BI solution is one of the most advanced in US higher ed, and Fish often speaks about it at conferences.

Several years ago at the University of Illinois (which, along with RPI, TDWI’s Wells cites as a leader in data warehousing), administrators decided to build an enterprise-wide data warehouse. At the same time, the university moved to a new ERP system, replacing a number of legacy data systems across UI’s three campuses. The new, institution-wide system raised the question: How to get meaningful data back out of the ERP system?

To meet this need, over a several-year process UI has constructed a mature data warehouse that includes all the core business data from the ERP. In addition, the university uses enterprise decision support tools from Business Objects to access and analyze warehoused data.