NJIT Implements Advanced Predictive and Prescriptive Analytics for Enrollment
New Jersey Institute of Technology (Newark), New Jersey’s public polytechnic university, has implemented new software to better design future classes and predict enrollment and scholarship needs.
The software gives enrollment officials a better way to model and create classes that meet the university’s goals of increasing enrollment, elevating SAT and ACT scores, maintaining and increasing diversity in classes, and balancing scholarship expenses, according to Wendy W. Lin-Cook, associate provost for enrollment management and academic services.
The software the university is implementing was developed by Othot, a predictive and prescriptive analytic company based in Pittsburgh, Pa. Predictive analytics provide higher education institutions with insights into which students are most likely (or least likely) to enroll by analyzing historical student data. Many higher education institutions are using predictive analytics to better understand and optimize recruitment and retention.
Lin-Cook explains that NJIT had always been doing some predictive modeling in-house, but the school recognized that it didn’t have the expertise it needed to fully leverage the technique. It did, however, have domain knowledge of enrollment.
“For a university like ours, it’s very important that we meet our enrollment targets, and we realize there are a lot of variables that go into influencing a student’s enrollment decision,” said Lin-Cook. “We understand what best practices are in the field, but we wanted to individualize them to NJIT. When we learned about the Othot product, we were very interested because it takes best practices and personalizes [them] to NJIT.
“Universities might want to give more scholarships for more quality students or students in some underperforming majors, majors that aren’t attracting enough enrollment,” she said. “In admissions, we have to balance our demographic profile so we have a diverse class of students from multiple locations and socioeconomic levels. There are many, many variables to consider.” Before getting the Othot software, Lin-Cook had difficulty taking all the demographics into account because there were too many variables.
The product helps universities identify the variables that will increase student yield, Lin-Cook said. And knowing those variables has enabled NJIT to target and craft class sizes and to quantify the types of students the school is looking for. “Enrollment management is very much a guessing game. I have to know a year and a half ahead of time what my future class will be. We need to make sure the class meets size requirements, quality requirements and revenue projections. So, I have to build my enrollment funnels through the process and monitor the numbers at every stage, so I will hit my end target.”
The software also allows Lin-Cook to play with the variables and predict what would happen if she changed one or more of them, before committing to a course of action. “I can test the models before I act. So what I do becomes a more calculated action.”
She noted that NJIT not only wants to enroll students, but to accept students while still reaching its revenue targets. “To do that, we need to make sure we are not overspending on scholarships and offering too much. So, when we review each student’s admissions information, we determine his or her likelihood of coming to NJIT, and then project the appropriate scholarship package. These are calculations that we previously did manually, and it was very difficult to do,” Lin-Cook explained.
“Othot was unique in projecting expected revenue and scholarship spending,” she said. “While other products we looked at allowed us to create a strategy at the beginning of the cycle, they didn’t give us support throughout the cycle. With this product, anytime we have problems we keep running those projections and adjust our course of action.” Lin-Cook and Othot also collaborated on a customized financial aid matrix to help NJIT allocate aid funding more efficiently.
