By: Dave Babst, VP of Marketing & Customer Success at Othot

If there’s one thing to glean from successful enrollment managers over the last fifty years, it’s that the field must, to quote Brad Pitt as Billy Beane in Moneyball, “adapt or die.”

Admissions and financial aid units have served as the foundation of nearly every consolidated enrollment unit. I’m here to argue that, over the last decade, a third element has emerged as a necessity: analytics. Like the Moneyball’s dive into baseball’s adaptation to sabermetrics, higher ed enrollment management is at a crossroads; one that centers on advanced analytics, both predictive and prescriptive, and the ability to provide the needed insight to drive impactful actions that change outcomes.

Brad Pitt and Jonah Hill as Billy Beane and Peter Brand in Moneyball

We’ve all read Grawe. We’ve all seen WICHE’s reports. The times of rising college-going rates and increased demand have come and gone. The competition for students is fierce. According to the Chronicle of Higher Ed, a large number of private colleges are expected to miss their enrollment goals for the fall semester. This is something new for this type of institution, who historically fill their classes year over year.

That’s why understanding data – most importantly, your institution’s data – is a must.

But, which students should I target to recruit? What marketing mediums are the most effective at reaching my pool? What is the most precise allocation of aid, and which families are most receptive?

Those are the big questions for a Chief Enrollment Officer and his or her staff, and they are best answered with advanced analytics.

So what does that really mean?

Before investing in a future strategy, teams need to educate themselves on key advancements that have been made in analytics today. Most colleges and universities have been using conventional predictive models to help them. But predictive analytics alone only gets higher ed halfway to what is needed to truly advance your institution and its goals. It tells you what will occur, but what happens when that outcome isn’t what you need or what you expected?

Analytics chart analysis

You need something that will tell you specifically how to change that outcome.

That’s where prescriptive analytics comes into play for colleges and universities.

Prescriptive analytics uses continuous data to go beyond anticipating what will happen to explain why something will happen and recommends specific actions to take. This type of advanced analytics is all about providing higher ed institutions advice on how to make something happen by prescribing a list of actions to guide you towards changing outcomes.

Prescriptive analytics attempts to quantify the effect of future decisions in order to advise on possible outcomes before the decisions are actually made.

For example, it’s April, and your enrollment office receives a prediction that it’s currently tracking below enrollment targets and you need to find out how to change this outcome between now and May 1.

During that window, your institution is immersed in the appeals process as well as planning to host prospective students for a campus day visit.

If you have a pool of prospective students that are undecided and the two options above, wouldn’t it be nice to know which action to take and its impact to make up that gap to hit enrollment targets?

Analytics report on laptop

With prescriptive analytics, you can understand if they’re more motivated by a campus visit or additional aid and why to prescribe the best action for each student. Taking these actions can exponentially increase the likelihood of them enrolling at your school.

Sounds great, right?

However, because prescriptive analytics is so incredibly powerful, it’s essential to cut through the noise to understand what it can do.

The 5 things you need to know about prescriptive analytics in higher education:

1. Prescriptive analytics’ superpower is explaining the ‘why’

Prescriptive analytics predicts not only what will happen, but also why it will happen. It provides recommendations regarding activities that will take advantage of those predictions. This allows for data-driven advice created by simulation and optimization.

2. Prescriptive analytics is applicable across higher education

Higher education institutions can use prescriptive analytics at all levels and functional groups within the organization.

Meaningful applications exist in marketing, recruitment, admissions decisions, financial aid awards, student advising, academic planning, financial forecasting, and executive planning.

On top of that, they can be utilized from the President down to individual recruiters and advisors.

3. Prescriptive analytics improves outcomes

Higher education institutions can use prescriptive analytics to improve the relationship between the student and the institution to change outcomes.

Colleges and universities using prescriptive analytics have been able to increase enrollment yield (see example above), optimize net tuition revenue, optimize financial aid, and improve retention or graduation rates.

By understanding what drives each student’s behavior and by how much, optimized plans can be created to meet goals.

4. Prescriptive analytics offers continuous, real-time advice

Prescriptive analytics runs 24-hours a day and continually processes new data as it becomes available to re-predict and re-prescribe solutions.

Taking into account the results of prescribed actions is important in continuing to be accurate with predictions and advice.

5. Prescriptive analytics is hard

Prescriptive analytics relies on sophisticated analytics tools, techniques, and technology—like artificial intelligence, machine learning, heuristics, and algorithms—which makes it a costly challenge to implement and manage.

This begs the questions on whether it’s in your institution’s best interest to build a prescriptive analytics engine internally or to partner with a point solution, which you can read about here.


Given the circumstances mentioned earlier, understanding your students better is a must. By incorporating prescriptive analytics into your strategy you’ll identify and reach the right students for your college or university. It’s what is required now.

Good luck out there. It’s an adapt or die world after all…

*Special thanks to Dave Babst, VP of Marketing & Customer Success at Othot for guest-writing this blog post. Othot is a Gold sponsor of the 2019 TargetX Summit.

About Othot

Othot is a higher education software company that provides cloud-based predictive analytics solutions with explainable AI to identify and empower–in real time–higher education institutions to optimize its relationship with students from the day they first meet them through their days as active alumni. The platform takes the cost and complexity out of adopting advanced analytics for the enrollment, financial aid and retention challenges facing colleges and universities today.

Partner schools can obtain a deeper understanding of each individual student and implement seamlessly with TargetX (and other systems) with an intuitive user interface. Othot’s prescriptive analytics and ‘what-if’ simulation functionality identify how to influence outcomes through specific actions, and the continuous intelligence provided by predictive scoring is constantly updated by more current data to inform decision making and improve outcomes in measurable ways. Learn more about how improved data-driven decision making is impacting outcomes for Othot’s partner schools.