Part 1 in a 3-part series on how data-driven ISAs are transforming enrollment management practices
However dark forecasts of college enrollment may look, the reality promises much more nuance. Not all schools with enrollment challenges will enter crisis mode. Not all schools with enrollment crises face the same challenges. When the demographic cliff plunges in the next ten to fifteen years, some elite colleges will notice little change in application volume, while other schools will have adapted and enrolled higher numbers of nontraditional students. Higher education, as it were, is not a monolith.
Why the impulse then to flatten diverse enrollment narratives into one sad diagonal? Why prescribe the same generic treatment for different diagnoses? The temptation isn’t so hard to understand. On average, university and college enrollment has fallen over nine percent since 2010. This percentage includes a number of schools whose yields have remained constant or grown, meaning the drop for many private institutions has an even steeper slope. For these schools, the prospect of a continued decline is grave indeed.
While they seek solutions for enrollment shortages, and while consultants scramble to rebrand the same one-size-fits-all methods they’ve marketed for years, an evidence-based strategy is emerging in the background. To support enrollment, drive retention, accelerate completion, and optimize financial resources, a growing number of institutions are turning to a new approach: analytics-driven income share agreements (ISAs).
A Catalyst for Student Success
An ISA is an agreement in which a student receives up-front education funding. In exchange, the student agrees to pay a fixed percentage of post-college income for a defined period of time. As a component of tuition, ISAs reduce students’ up-front education costs and expand student pathways.
In the last few years, the number of schools and universities offering ISAs has increased dramatically. For students seeking pay-as-you-succeed financing, or alternative financing in general, a school with ISAs has a competitive edge.
An ISA still won’t be right for every student. But schools that offer ISAs to the right candidates demonstrate their dedication to student success. They signal good faith by linking career outcomes to the recovery of tuition resources. In time, students awarded their ISAs “pay it forward,” and the institutions are able to recycle ISA revenue to future student cohorts.
By offering funding options to students who might not otherwise have the means to pay for college, ISAs directly help enrollment. Early in the enrollment management cycle, predictive modeling can help identify students who demonstrate the greatest need and who either may not meet the requirements for federal aid or whose needs may not all be covered by federal aid or existing institutional aid components. An analytics-driven ISA can offer such students the resources they need to start—and finish—their education.
Driving Enrollment with Real-world Data
For decades, consultants and colleges have looked to data analytics to make informed decisions about marketing campaigns, diversity initiatives, and more. But as valuable as data can be, it’s the language used to interpret, frame, and leverage data that determines their actual utility to a school.
Vemo Education uses thoughtful, holistic applications of data in higher education to help institutions grow and evolve. Now, Vemo is partnering with HAI Analytics to provide school partners more context on the applications of ISA, and to help them more effectively pinpoint target recipients for ISA programs. HAI’s objective? To combine predictive modeling and ongoing experience-based data interpretation to shape higher education enrollment strategies.
HAI pulls historical data from census reports, public financial records, institutional student records, and other sources. They aggregate the data and uncover interactions between descriptive variables, such as students’ short– and long-term financial security and their parents’ education levels. When HAI translates these interactions into algorithms, it can predict student outcomes and provide context for informed enrollment decisions.
Higher education has increasingly turned to predictive modeling to inform enrollment yield models. Admitted student data, including demonstrated financial need and institutional gift aid amounts, are used to build customized yield models at an institution. These models enable a school to project a wide array of outcomes, such as:
- The number of admitted students who will enroll
- The demographic composition of the enrolling pool
- Institutional aid expenditures, discount rates, and revenue
- Effects of different admissions and financial aid strategies on the future class
Predictive modeling can also be employed to predict future retention behaviors. As an example, educational ISA platform provider Vemo Education used predictive analytics to help a school partner identify target students for an ISA program in 2019. By analyzing which characteristics were most predictive of retention in different segments of students, and identifying the students who were most likely to leave before graduating, the school was able to pinpoint and prioritize the best recipients of its tuition aid. After successful allocation of initial program resources, the school made plans to increase its investment by four times the current level by 2021.
Predictive models allow institutions to design enrollment management solutions that are truly customized. In a comprehensive predictive modeling strategy, enrollment, retention, and completion intertwine. Together, they offer a holistic perspective of a school’s future. The more detailed the perspective becomes, the more that targeted ISA programs become the tool to support success across all stages of the enrollment management lifecycle.
A Holistic Solution
Beyond driving enrollment yields, the combination of ISAs and analytics can support institutions in diverse long-term objectives. Schools can leverage a similar predictive modeling process to target and improve retention and completion rates, and to revise their measures of success. With careful examination of student performance metrics, institutions are able to identify students likely to drop out or stop out and offer ISAs to help them graduate on time. With long-term income and career outcomes data, schools see a more complete picture of the impact they have on students’ post-graduation experiences across programs. They can then adapt their programs accordingly.
Because analytics-driven ISAs approach enrollment management from a high-level view, they can help optimize institutional funds to better serve schools and students. We’ll explore some of the applications schools have found for analytics-driven ISA programs in further installments of this blog series, “What Can Analytics-driven ISAs Do for You?”
Learn more about data-driven ISAs and how the leading school-based educational ISA platform provider, Vemo Education, can benefit your institution. Contact us today online, at email@example.com, or at 703-831-7231.