Why Data Is the Most Important Tool for a Higher Education Leader
Let's assume that an institution has figured all that out. They have a mature data system, they have wide-scale culture of adoption. Then the burden really shifts from the data provider to the data consumer. And it's hard to get a leader or a decision-maker to move from what I like to call "me-search," which is what they think and believe and perceive, versus research, which is actual data-informed decision-making. The other challenge is, does the institution have the right level of analytic maturity to look beyond basic descriptive statistics and reporting?
Much of the work being done by AIR, Educause, and NACUBO, first with the Joint Statement on Analytics, and now with the Bill and Melinda Gates Foundation grant that they recently received, is driven at trying to provide tools for institutions of higher education — all the way from two-year to four-year, public, private, doesn't matter — on how to actually move the needle in getting a more mature data ecosystem.
CT: You mentioned many institutions have not performed a data audit. What does that entail, and what's keeping institutions from doing it?
Simon: Most of the time it's not for any nefarious reason. It's just because the requests that data provisioners are fielding are at such a high volume that they don't have the luxury of time or prioritization or someone guiding them to do it.
Most modern data provisioning shops in higher education right now are consumed by federal reporting, state reporting, ad hoc requests — and they lose sight of the opportunities that analytics can provide them in terms of self-service data. For us at the University of North Texas, before we could even get to a data audit, we first had to really understand who are our data partners.
The first step is to develop a RACI matrix by data typology across the campus. RACI is who's Responsible, who's Accountable, who needs to be Consulted, and who needs to be Informed. It's a common practice in a lot of IT areas, but in terms of a data audit, it's vital because it sets the stage on understanding who you're going partner with across the campus on what type of data, be it financial aid, human resources, finance, student accounting. It also serves as a necessary first step for data governance. In essence, you're identifying key data governance partners, both functional and technical. And lastly, that RACI process helps the data leader or chief data officer pinpoint who they need to build strategic relationships with and how to maximize those relationships.
Once you know who your partners are, it's about understanding your institution's data landscape. There are several ways to do that. One is to bring together all those people and have a very honest and transparent conversation on what's working with our data and what's not, where are areas of opportunity, where are areas of weakness, and what's going to be the plan to address those. It could also be a series of focus groups between the data shop on campus and key executive stakeholders. Ask very direct questions: not just how do you feel about data, but when's the last time you leveraged data to make an informed decision? When is the last time you really needed data and the institution wasn't able to provide it? If you could wave a magic wand, what data would you like to see arrive in your inbox every day? It's also important to engage with folks who are "data-adjacent": your IT staffs, your information security teams, your key people who are in the trenches with their hands on the data on a daily basis, in key higher education systems like enrollment, finance, human resources. All of that leads organizations and institutions to identify pretty quickly where their pain points are, and then hopefully with a good culture of leadership, determine how to begin to address those.