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  • Ask eAIR
  • 07.12.19

Using Self-service Data to Inform Decision Making

  • by Ron Severtis, Director, Office of Institutional Effectiveness, Indiana University Southeast

RonSDear Ron: We are implementing efforts to better push self-service data to our users. Do you have tips or advice on how they might use the data to inform decision making?

I’m glad you asked! That is a question that most campuses are struggling to answer as they face public funding declines and seemingly unavoidable enrollment declines. For these and many other reasons, colleges are asked to make timely, insightful decisions with less staff support. That necessitates the production of self-service data tools especially for busy IR offices. But a pressing need along with the expertise of your technical architects of the visualization system is employing a data culture strategy to best ensure the proper use of data to inform decision making.

If I could, let me say a few words about the efforts to push self-service data to your campus. Always start with informing your users about the purpose and benefits of a particular data source. Without linking that data to the types of questions that can be explored or analyzed, the user may just see yet another email containing a vague set of numbers and never get a look at the data. So, if you are connecting users to historic section counts and FTE per instructor type, be sure to emphasize the importance of units monitoring load by instructor type, and distribution of instructor type on class level, or across online sections. Also, add a bit of campus context to any data you are asking users to access. If a retention analysis view is featured, provide a corresponding campus retention number and ask users to reflect on why their retention numbers are better, worse, or similar than the campus mark. This can lead to some beneficial department- , school-, or campus-level discussions on student success. Savvy data users should be asking their IR teams “So what?,” and the answers need to show how the data can be relevant to these users. And without providing examples of how to use data that you’ve deemed valuable, your attempts at making users data-literate is less likely to occur.

You also want to be mindful of both scope and timing of your correspondences that promote new visualizations, most likely these days sent via email to a broad list of users. A nugget regarding effective reporting found in Bers and Seybert (1999) and highlighted by Sanders and Filkins asks IR professionals to pose the question, “What does the audience need to know?” (2012, p. 596). Providing one or two clear data uses per email is plenty for data-averse constituents to digest. Focus on the purpose of the data, how to access and manipulate the data tables, how often the views are refreshed (daily, weekly, term), and the kinds of answers the data can provide. And while we are far from a saturation point with data usage, we also want to avoid too aggressive of a data schedule that leads to user fatigue. Plan around holidays accordingly.

Now, once your users have a new data source, they should first try to link it to their strategic plans. Units - or service offices preferably - should develop a plan that links to their mission and contains goals and measurable outcomes. Most data that I’ve seen developed by Indiana University and our own office at IU Southeast are easily associated with at least one unit’s plan. For instance, enrollment data serves academic affairs and enrollment management, recruitment data aids both admissions and faculty senate, and retention data serves academic units, student success programming, and student affairs.

For some units, data can be analyzed for operational efficiencies. Student affairs professionals including those in athletics and campus life can utilize card swipe metrics at sporting events, facilities, and events for ties to budgeting and student interest, for instance. Or, administrative affairs can use survey data visualizations to reveal trends in dining satisfaction. If this data does not yet exist in your self-service, it should be a priority in an effort to execute continuous improvement. And lastly, some data ages out—if data is found to no longer be useful to a campus, it could be revealed via an annual audit of view totals or discussions with primary stakeholders. That should also produce conversations about what data would be useful to start exploring.

All of these efforts taken together can begin to democratize data and drive a data-informed culture.

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