When Darren Catalano was hired as the vice president for analytics at the University of Maryland University College (UMUC), in 2011, he had one goal: to advance the college’s analytical capabilities. The college was in the middle of upgrading its student-information system, so it was the perfect time to reengineer the overall process.
“Like many universities these days, UMUC experienced some enrollment volatility over the last couple of years,” Catalano says. “We accelerated our investment in analytics to help in our efforts to stabilize enrollment.”
The case for D-I-Y software
Because there weren’t any data-warehousing packages meant for higher education that did what Catalano wanted, he decided to build his own.
“We wanted to combine data from throughout the university so that people can conduct analysis on the fly and create data sets that they can do something with,” he says. “To have an effective analytics program, you need to understand the data, make assumptions, take action, measure results and assess where you are.”
By building a data platform and leveraging data, UMUC stabilized enrollments in two years, versus the five-year decline that many of its competitors experienced.
In addition, last fall UMUC used data to reduce its new-student recruitment expenses by 20 percent by identifying marketing and recruitment activities that yielded new students.
Last but not least, UMUC increased its undergraduate course-completion rate by seven points and its undergraduate persistence by four points. Data helped college leaders see that students who enroll too close to registration have much lower course-completion rates, so the college instituted a major policy change: Students are not allowed to enroll within four days of the start of a class, and they are allowed to drop classes within the first four days of the class, without consequences. Data analysis also led the college to go from a 12-week to an eight-week undergraduate session when the numbers proved that the shorter session did not negatively affect student success.
Shifting the culture
According to Catalano, there are five steps to creating a data-driven culture:
- Make an investment. As he says, “It’s not for the faint of heart.”
- Organize for success. UMUC created an autonomous, independent Office of Analytics. “We were Switzerland — a neutral data distributor,” Catalano says.
- Empower leaders to use the data. College employees are required to use data for all major decisions and investments.
- Embrace transparency. “We went from having only a handful of administrators seeing enrollment and other data to sending out key metrics to hundreds of leaders daily.”
- Highlight successes. UMUC publicized its enrollment increases, higher rates of student persistence and completion, and major policy changes. “We showed that using data is making a difference,” Catalano says.
To aid in the overall success, UMUC hired data analysts who are aligned with functional areas and disseminate information to the appropriate decision-makers. Their job is to foster the conversations and move the process along.
Getting started on your campus
It’s important to remember that data does not lead to change; it starts the conversations that lead to action. The goal is to build a strong data infrastructure that feeds into a continuous improvement cycle.
For colleges without data analysts or the financial resources to build the appropriate infrastructure, UMUC has launched a company called HelioCampus (www.heliocampus.com). It’s based on the model developed at the college and intends to help other colleges use data for decision-making.
“It’s hard to hire technical talent at higher-ed pay scales, especially in analytics,” Catalano says. “HelioCampus will be able to hire at market rates because we’ll spread the costs across multiple institutions.”