Data Governance and Student Success —

I just attended the Higher Ed Data Warehouse (HEDW) conference, which this year was hosted at the University of Arizona in Tucson.   This is our second year attending (as a sponsor).    U of A is a sizeable institution with an excellent facility to accommodate the 300+ attendees.  And Tucson makes for a pleasant destination for this time of year.

The conference was professional and well run, complete with phone app agenda.  The topics and scheduling were well constructed, everything was recorded.  And the stuff that people really care about – the food and the excursion – were super. Kudos to the organizers.

The conference has adroitly attracted both technical people, from the IT/BI/Analytics offices, as well as people from the Institutional Research office who represent the “business” side of the equation.  It is refreshing for a technology conference to have this equal level of participation from the “user side” which makes the experience that much more valuable.

Taking a step back from the many individual topics, the big themes were (1) Data Governance and (2) Student Success.   The former reflects irrefutability that analytics is sabotaged if you cannot agree on what the data means.  Our work in higher-Ed has shown this can be challenging – the definition of a seemingly simple metric “full time enrolled student” can be complex with multiple conditions (business rules) that govern what constitutes full time enrollment.  Indeed, sometimes metrics in industry (e.g. “total customers”) is simpler to establish.

The later theme, Student Success, aims to understand the causal factors that lead students to quit, fail or transfer out.  In my straw poll, student retention ranges from a worrying 60% at some schools, to 85% or so at others and aligns well with this statistic from the NSCRC published in 2015.  Leading indicators (e.g. frequency of use and completion of LMS course modules) that together create a holistic view of an at-risk student can serve as a powerful target for intervention initiatives to change the direction of these students.  Many institutions consider anything less than 85% retention unacceptable and boards are mandating their institutional leadership show improvement.

This last point, board level objectives that necessitate robust analytic programs is driving the investment, and a sea change of efficiency and effectiveness is brewing across the higher-Ed landscape.  University leadership is becoming more businesslike, and in my last blog I identified the following targets that have huge potential:

• Improving student recruitment and enrollment
• Improving student success
• Improving alumni engagement and fundraising
• Improving facilities operations and efficiency
• Improving financial aid and grant management
• Improving faculty planning and learning management
• Improving University financial administration and HR administration
• Improving the intensive process of LCME accreditation (for medical campuses)

Now I will get to the point, and title, of this blog.   What was striking about HEDW were 3 things:

• The commitment, investment and smart people working to create powerful analytical resources for their institution
• The “common denominator problems” everyone is wrestling with (and struggling with)
• The lack of a simple product or framework for people to borrow and bootstrap their efforts

Big stuff.  In my next blog in this series I will establish what these “common denominator” problems are, and how to approach them.

Until then… please feel free to ping me here or on LinkedIn with any thoughts and items to share

Kurt