How Colleges Leverage Data to Retain Students as the Enrollment Cliff Looms

With funding on the line, FIU invested in a suite of analytics software, including Tableau, and held a range of training sessions to educate new users about how to benefit from the data newly at their disposal. The result was a 10 percent increase in the university’s four-year graduation rates.

“We can slice data in ways that help us determine which interventions are needed based on risk factors for individual student groups,” Perez says. “The students have benefited from having staff who can use real-time data to identify students’ challenges and devise timely interventions.”

The experience makes FIU a leader among a growing number of institutions that are seeking to leverage student lifecycle management technology to drive academic performance and retention as one way to limit the impact of the so-called enrollment cliff.

Colleges Seek Protection from the Enrollment Cliff

Projected to occur around 2025 or 2026, the enrollment cliff refers to an anticipated significant decline in higher education enrollment across the U.S., brought on by myriad factors, including decreasing birth rates, high tuition costs and an evolving job market.

As colleges and universities near the edge of the cliff, they are determined to build guardrails.

Bringing in new students, however, is only part of the solution. New students do little to help an institution’s long-term financial state unless they return every semester. That’s why institutions like FIU and Jacksonville University in Northeast Florida are increasingly focused on student retention, hoping to catch at-risk students before they fall through the academic cracks.

“We’re fortunate to have started talking about the enrollment cliff a long time ago,” says Robert Berwick, JU’s assistant vice president and registrar. “Today, as we look at enrollment or admissions data, one of the things we’re delving deeper into is where we see weaknesses. If we had 13,000 high school students interested last year, and this year we only have 11,000, where did those 2,000 students go?”

By the 2010s, JU’s student retention rate had plateaued to just under 70 percent, says Will Miller, who was the university’s executive director of institutional analytics, effectiveness and strategic planning at the time. JU’s president was determined to push that number higher.

Meanwhile, JU was trying to determine how to break down data silos and aggregate the resulting deluge of metrics into a meaningful, actionable format. Moreover, how could they democratize that data, ensuring its usefulness for everyone? To accomplish that, JU turned to Power BI from Microsoft.

While business intelligence software and customer relationship management platforms have long been staples on the corporate landscape, they are not yet ubiquitous in higher education. Even so, colleges and universities present a unique need for the data reconciliation and visualization these products offer.

With frequently siloed organizational structures, higher education institutions are particularly susceptible to data overload. A single university might boast multiple analytics platforms spread across schools and colleges.

“We had eight, nine, 10 different systems that were all best-of-breed products in their verticals, but we didn’t have a way to bring their data together,” Miller recalls. “We knew there were a lot of insights essentially being ignored or left behind because we weren’t looking at that data cohesively.”

With Power BI, Miller says, JU could aggregate analytics across platforms to provide faculty and staff with customizable, user-friendly dashboards.

“The biggest thing we wanted to do was figure out how to get more out of all of this data that we had,” explains Miller, now associate vice president for continuous improvement and institutional performance at Embry-Riddle Aeronautical University in Daytona, Fla. “We wanted to be able to democratize the data and help staff and faculty feel invested in it.”

RELATED: Can technology help community colleges avoid the enrollment cliff?

Data-Driven Solutions Can Flag At-Risk Students

Like FIU, the University of Baltimore has also embraced a data-driven predictive approach to student success, says Kathea Smith, assistant dean for enrollment, academic affairs and student services, who championed UB’s adoption of Salesforce for tracking and engaging students across the academic lifecycle.

“What we got from it was a way for advisers to see exactly where their students stand from an academic perspective and all the various red flags that exist,” Smith says.

That kind of predictive, proactive approach is one of the biggest improvements that learning management systems and student lifecycle management platforms have enabled for higher education, says Matthew Hagerty, a director and partner development executive at EAB, an education consulting firm.

“If a student isn’t logging in to the LMS, that’s a pretty big red flag that they might struggle during the term,” Hagerty adds. “We’re at a point now where we can see those flags at week one so that we can begin targeted interventions for those students early on.”