Predictive Analytics and the Future of Enrollment Management
Data-informed enrollment management is the standard in higher education. Many institutions are harnessing the power of predictive analytics, which can enable leaders to improve everything from incoming class headcounts and academic quality to key performance indicators for diversity and financial aid outlays.
This web seminar focused on predictive analytics and the future of enrollment management. It featured the vice chancellor for enrollment management at Arkansas State University.
Vice Chancellor for Enrollment Management
Arkansas State University
Bryan Terry: One of the pressures that some enrollment managers are facing is: How much of the recruiting budget should be allocated to different populations? Most of us don’t have unlimited budgets, and money is an issue. But it’s not just about money. It’s about people, it’s about time and it’s about bandwidth. And we need to be prepared for an even rockier road ahead in the admissions world.
On the predictive analytics side, I believe in the bell curve. To the right of the curve are the students who are coming, no matter what. On the left side of the curve are students who are not coming, no matter what we do. But how much time do we spend with that population of students we’re not sure are coming? We have a gut feeling, but we don’t know for sure. The bell curve helps us work with that. That’s why we like Rapid Insight. The product helps us understand who the students in the middle are, and gives us ways to reach out to them.
The middle group is the fence-sitter group. We have teams of financial aid and admissions people who go out and try to move those students into the “great fits” group because time is critical. We use Rapid Insight to say, “Let’s focus on this population of students because it’s going to make the most sense.” Another reason is the ease with which you can review your data. Rapid Insight allows us to take stock of our information about our prospects and students.
Finally, many institutions do a great deal of work with data to predict how well a student does on the way in. But how often do we see students dropping out based on financial need? You have to ask if your student success model looks beyond the first year. It can help with retention. Pay attention to the student success side. I don’t think we do nearly enough of that kind of work at our institutions.
Working with Rapid Insight, we’ve been able to identify easy wins. We can collect information not only to enroll students, but also to help those students succeed and graduate. I’m not saying that a personal touch doesn’t help, but it’s not going to help all students. You have to do what’s right and back it up with data. Invest in predictive modeling because it will tell you what population to stay in contact with. Then, you can work hard on making sure you’re interacting with students you actually have a chance to enroll.
James Cousins: The most significant aspect of Rapid Insight’s background is that we’ve been doing this for quite a while. Our company mindset is providing our customers with a tool that they can use to build in-house capacity. We pride ourselves on the partnerships that we have with our users and the support that we offer.
You need to be able to assess the impact of your admissions from your in-state and out-of-state recruiting efforts and from other initiatives. It involves gathering as much data as you’re able to gather, with the confidence of being able to explore it and blend it into a single source.
A lot of the upper-level insights you can easily act on are a result of predictive modeling. There are many ways you can accomplish that, but I’m looking forward to showing you the way that Predict can help.
Enrollment management is definitely not a one-person effort, and it’s definitely not an effort undertaken by people who all think the same way. It’s all about outputting your data, and being able to take the results and share them in whatever format allows you, your team and your institution to act on them most effectively.
To watch this web seminar in its entirety, please visit UBmag.me/ws021820