Data Analytics

Data Governance in Higher Ed is Critical. Here’s How to Achieve and Sustain It.

As data proliferates across the higher education landscape, colleges and universities find themselves in need of data governance policies that help them protect and effectively use the metrics they gather. Here’s where to start.

Lauren Glenn Manfuso

Lauren Glenn Manfuso is a journalist and editor in the Washington D.C. metro area. Her work has appeared in Prevention magazine online, the Miami Herald and USA Today.

If college applicants and potential teachers have anything in common with current students and tenured professors, it’s this: They’re one more piece of data in an ever-growing mountain of it.

There was a time when higher education data was largely limited to things like enrollment numbers, demographic information and revenue. But with the increasing digitalization of institutional metrics — academic performance, tuition revenue, student health, diversity and inclusion, and more — has come a level of data proliferation that many colleges and universities are struggling to make sense of and manage.

As a result, more universities are embracing the concept of data governance, the practice of creating standards for incoming data to analyze it more effectively and accurately. Once typically considered a corporate practice and largely stereotyped as an IT function, data governance has gained a higher profile in higher education as schools work to take the barrage of data they’re constantly collecting and interpret it in meaningful ways.

“We often say the that colleges and universities are data-rich and information-poor,” says Betsy Reinitz, director of the CIO and Senior Technology Leaders program at EDUCAUSE. “They’ve got this staggering amount of data, and yet it’s hard to make good decisions and do good planning with it unless you take a holistic view of it. And that’s where data governance comes in.”

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Build a Collaborative Data Governance Culture by Breaking Down Silos

In many cases, Reinitz says, certain groups might feel a degree of ownership or territoriality over certain sets of data because of its relevance to their own departments or their role in aggregating it. “It’s important to remember, however, that data is an institutional asset,” she says.

Divided as institutions are by different schools and academic departments — not to mention professional departments like IT, enrollment or student life — silos are often unavoidable in higher education.

Those silos often are one of the biggest barriers to developing and implementing an effective data governance strategy across an institution. That’s because data governance works best as a Venn diagram than in silos, says Matthew Hagerty, a consultant who specializes in IT, efficiency and analytics, and faculty engagement at EAB, a Washington D.C.-based education consulting firm.

“Make sure the right people are in the room to craft that policy,” Hagerty says. He says that many times during initial data governance meetings, “maybe halfway through, someone will raise their hand and ask, “‘Wait a second. Why isn’t Bob from finance here? Who’s representing human resources in this committee?’”

“So, the first step is to make sure that we have the right people in the room to set that policy,” he says.

LEARN MORE: What is CEDS and how can universities use it?

The Risks of Not Establishing Data Governance in Higher Ed

When it comes to creating an institutional culture that supports data governance and stakeholder buy-in, it’s critical that institutions educate stakeholders about the risks associated with falling short. From privacy violations to revenue loss, colleges and universities have much to lose from mismanaged or poorly utilized data.

Between 2020 and 2021, cyberattacks on colleges and universities increased 75 percent. The risk of an attack succeeding significantly increases without a reliable, comprehensive data governance strategy, says Brian Kelly, formerly director of the cybersecurity program at EDUCAUSE and now virtual CISO at Compass IT Compliance.

“Without governance, the whole lifecycle of the data — how it’s being collected and stored, who’s collecting it, how they’re using it, and how it’s disposed of — is vulnerable to risk,” says Kelly. Data governance, he explains, allows institutions to put into place controls and processes to ensure that only the right people have access to the right data at the right time. It also helps schools to achieve another crucial best practice: transparency.

You have to be very transparent with your community about what you’re doing, what problem you’re solving, what data you’re collecting, and how you’ll protect that data.”

Brian Kelly Virtual Chief Information Security Officer, Compass IT Compliance

“We always say that the worst data breach is the one in which you lose data you shouldn’t have had to begin with,” says Kelly. Today’s users, particularly students, are much more conscious of how their data is being gathered and used, and also more skeptical. To avoid mishaps and lost trust, Kelly says universities must be transparent and upfront about how they’re collecting, retaining and using student data, and it needs to happen before a breach occurs.

“You have to be very transparent with your community about what you’re doing, what problem you’re solving, what data you’re collecting, and how you’ll protect that data from both a privacy and a security standpoint,” Kelly says.

DIG DEEPER: See why zero trust is higher ed’s best defense for valuable research assets.

What Data Governance Looks Like in Higher Ed and Where to Start

When developing a data governance strategy, Hagerty says, the first step is to define what data governance looks like at your institution and what you want to accomplish with it.

“Without those really clear boundaries, you start to have a bit of mission creep, where suddenly everyone’s pet project could be connected to data governance,” he says. “And that might lead to a lot of really great ideas, but not a lot of results.”

Next, Hagerty says, you have to identify who should be in the room as you’re developing a strategy. That group should include executive leadership who genuinely believe in the project and are willing to evangelize it. It’s also critical to establish a baseline of data literacy, along with a path for continued growth and learning.

“This is something that is going to require sustained attention and interest from a wide variety of folks on campus,” Hagerty says. “You have to make sure that, as employees turn over and things evolve, there’s a program in place to make sure that new data users get the training they need to become more data literate in the work that is pertinent to them.”

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