When EDUCAUSE members identified their top 10 priorities for 2017, it was clear that data analytics is expected to play a big role. Data-informed decision-making is No. 3 on the list, and data management and governance is No. 6. Other initiatives, such as student success and completion (No. 2) and strategic leadership (No. 4), also are leaning more heavily on data than ever before.
Analytics is establishing itself as one of the most powerful tools available to higher education leaders, in part because of its breadth of application: information security, student performance, financial management, business operations and infrastructure support. Experts keep finding new ways to leverage information, and educational technology companies are developing robust tools that can deliver impressive insights at an amazing speed.
It occurs to me, however, that these capabilities aren’t evenly distributed. Some colleges have the resources to hire chief data officers, create analytics teams and put the latest technology at their fingertips. Other colleges are still figuring out what kind of analysis they can conduct with limited staff and software.
This disparity runs the risk of furthering a “data divide,” a corollary to the digital divide that too often separates institutions with ample IT resources from those without. For example, if some students have access to data-driven interventions that keep them on track to graduate, while others lack these benefits, we risk creating data haves and have-nots. And some of the most common analytics applications are closely tied to the bottom line — financial operations, enrollment management and student retention — which means they have the power to help institutions stretch budget dollars further.
A discrepancy between institutions’ analytics capabilities is important, because this area represents a fundamental shift in the way leaders make decisions. Integrated analytics programs let leaders move from hunches and intuition to facts and data-driven insights, and from mere efficiency to true optimization. And rather than taking months or years to glean insight into patterns, leaders can do so in hours or even minutes. In fact, improved decision-making is one of the top benefits of an analytics program.
In a study from the EDUCAUSE Center for Applied Research (ECAR), almost half of the respondents said the cost of analytics tools, staff and training was a major concern. However, such efforts need not be expensive to be effective. For example, Austin Peay State University’s course recommendation program, Degree Compass, began as a Microsoft Excel spreadsheet.
In fact, ECAR recommends that institutions invest in “expertise, process, and policies” before spending on new tools or expanding data collection. Successful analytics programs are supported by a wide range of factors; technology solutions and expertise are a major piece of the puzzle, but they aren’t the only piece. Culture, process, reporting and governance are equally important in moving such programs from information to action, and they don’t have to cost a cent.
Another strategy to minimize the data divide is to share, among institutions, best practices and insights that emerge from analytics programs. Institutions that succeed in identifying effective academic interventions, for example, can pass these along to peers, who may be able to apply them to their own student populations.
That said, analytics solutions can be viewed as an investment, rather than simply an expense. Purchasing a ready-made solution may, in the long run, be more cost-effective than hiring a consultant to build a solution or creating one internally. A study from Nucleus Research found that every dollar that organizations invested in analytics paid off at a value of $13. When Arizona State University implemented a predictive analytics program to target student retention, the graduation rate jumped 20 percent — preserving the investment in those students that ASU would have lost if they had dropped out.
As the EDUCAUSE 2017 priorities suggest, data analytics is quickly becoming a must-have tool for institutions seeking to maximize resources and do everything they can to put students on the path to academic success. Such programs don’t replace experience, dedication and wisdom, but they can help institutions make the most of those qualities. As the field of data analytics continues to mature, let’s make sure that we extend those benefits to everyone.
This article is part of EdTech: Focus on Higher Education’s UniversITy blog series.