Minding the Gap: Analytics and Organizational Capacity

Analytics enjoys strong support and endorsement at most of our institutions; it’s probably harder to find a campus without an initiative today than one with it.  To those of us withbackgrounds in the field, it’s a very exciting time with lots of potential projects being envisioned.  But to recall the late Steven Covey (Covey, 1989), we create two times: once when we create a goal, and a second time in the actions we take to achieve it.  In the case of analytics in higher education, I believe that we have an organizational capacity gap between the first and second creations.

Subway image with text "Mind the Gap"

The 2012 ECAR analytics study found high expectations for analytics; 86% of respondents thought that in two years analytics would be more important for higher education’s success than it is today (Bichsel, 2012).  The study found current deployments limited, especially when considering predictive analytics or proactive use of data for decision-making.  However, these results are all-too-familiar.  In the 2005 Educause report that coined the term “Academic Analytics”, 63% of respondents (with capacity beyond transaction systems) planned to upgrade their analytics infrastructure within two years (Goldstein & Katz).  What happened? Either this capacity was created and lies unused, or the plans were not implemented.  Why do we continue to have these unfulfilled expectations when it comes to analytics in higher education?

Both of these studies report a lack of staff with the requisite knowledge and backgrounds to conduct analytics.  But just adding staff won’t create an analytics program.  If people were found and convinced to join our ranks, where would they fit in an institution?  Asked another way, whose responsibility are analytics?

At present, I don’t think that analytics neatly fits anywhere: Institutional Research is overburdened with mandated and standard reports, and frequently not accustomed to working with innovative enterprise technologies and changing requirements.  Institutional (or Academic) Technology is accustomed to innovation and technology, but doesn’t have the research methods skills.  Academic affairs often has experienced leaders in these areas, but doesn’t have the resources for campus-wide implementations.

If campuses want to break this cycle of deflated expectations, a preliminary question to answer is where to place analytics as a program and set of responsibilities.  To be successful, this will require changes to our organizations – not just in leaders using data for decision-making, but also in creating an organizational culture and responsibilities that don’t currently exist.  We’ve already created this goal once; it’s time we’re successful on the implementation.

Works Cited

Bichsel, Jacqueline. (2012). 2012 ECAR Study of Analytics in Higher Education. Educause Center for Applied Research. Boulder, CO: EDUCAUSE and Associaction for Institutional Research.

Covey, Steven. (1989). The 7 Habits of Highly Effective People. New York: Fireside (Simon and Schuster).

Goldstein, Philip J, & Katz, R.N. (2005). Academic analytics: The uses of management information and technology in higher education. Washington, DC.

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