Predictive analytics–a way that statistics can be used to gather data and use it to predict future trends–has been increasing in popularity among college administrators. Recently, according to an article by Laura Devaney, IBM asked a group of college administrators how they use predictive analytics.
The College at Brockport said that they use historical data, graduation and retention rates, application counts, and demographic data to help increase their number of applicants. It also helps them see what sort of students will probably enroll and to target their marketing toward those groups.
Meanwhile, Wichita State University said that predictive analytics helps them unify data about students, financial aid, housing, and more. It also helps them predict which students will probably be “high-yield” and which will be “at-risk” (in Devaney’s words) even before they begin their first classes. As a result, they can offer “at-risk” students extra assistance, which can encourage those students to stay in school longer. Predictive analytics has helped the college to revamp their admissions process, making it more “evidence-based”. They can now predict which prospective students are most likely to attend the school and where, geographically, to focus their enrollment-related events. Overall, WSU states that the use of predictive analytics has saved them roughly tens of thousands of dollars.
Devaney predicts that, given predictive analytics’s success in the areas of recruitment and retention, schools will begin to use it more for financial practices, as it will help them see which financial plans will be most likely to work without needing to spend money and time testing it in the real world.
Hopefully, the use of predictive analytics will spread to more universities, allowing them to save more money and divert it towards where it can best help the students.
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