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December 20, 2021 | Institutional data analytics, Revenue Growth & ROI

5 ways higher ed can harness financial aid beyond just boosting yield

On most campuses, academic affairs and student services—but rarely other units—prioritize student success. Colleges and universities dedicate significant time and resources to increasing engagement in and out of the classroom and to monitoring early warnings to identify students who need additional attention.

However, whether students will retain next fall and the subsequent one is often influenced long before courses begin. In some cases, data shows that if institutions want to positively impact student success, they should start by understanding the impact financial aid has on retention.

Typically confined to the last leg of the admissions process, financial aid is frequently understood primarily as a tool to boost yield, but in many cases it is more than an inducement to attend. Financial factors are fundamental to student success, and approaches and policies that govern how and where aid is allocated have a significant impact on students’ likelihood of persisting.

Colleges and universities should take a holistic approach to student success, and this can represent the difference between students matriculating and dropping out. Instead of a hand-off approach—where various offices, such as financial aid, student services, and academic affairs, define their purview more narrowly and keep their data siloed while passing students along as blank slates to other colleagues—institutions can greatly improve student success by adopting an all-hands mentality. This means a variety of touch points along each student’s academic journey and an institutional through-line wherein several offices collaborate.

Financial factors must be appreciated at every step, and they should be contextualized continually with data. For the nuts and bolts of how exactly an institution needs to view financial aid more extensively through a student-success lens, I recommend these five-steps:

1. Analyze historical performance:

Ask yourself the following questions: Have we aligned our historical use of institutional aid strategically? Can we change the mix of aid we offer to different populations to maximize the impact of our limited institutional aid dollars?

Many colleges and universities have not updated their financial aid policies in many years and lack the data to understand how those policies should change. This is critical to understand which financial aid leveraging strategies can be updated to maximize the benefits for students.

2. Look at merit- vs. need-based scholarships: 

Less selective institutions tend to over-index on merit aid packages to attract an aspirational profile of student that may diverge greatly from that same profile of a student who is enrolled and retained at the institution. They pursue students who “just aren’t that into them.” In many cases, it’s better to shift monies from merit- to need-based scholarships, which perform significantly better.

3. Address “unmet-need break points”:

When families receive bills—tuition, fees, room and board—they are told how they will pay attendance costs. Universities detail institutional aid and federal loans, families’ expected contributions, and unsubsidized loans covering the gap. “Look, you can pay for college!” families are told.

But that’s not how families, who are very aware of the gap between what they can afford and college costs, tend to think. To increase retention, leverage the data to identify thresholds that significantly impact students’ ability to pay for their education.

4. Do a price-sensitivity analysis:

Crunch the numbers to understand which types of students respond to various aid packages. Likely, you’re over-packaging support for both the already highly-likely and the highly-unlikely to enroll. Resources are better deployed to students who are most price-sensitive and for whom aid makes the biggest difference.

5. Scenario modeling:

Once you’ve done the previous four steps, you’re in a position to build a model that will identify student segments that respond to different levels of aid and explore different scenarios to determine the impact of financial aid on yield and retention.

Connecting all the data dots

As you undertake these five steps, some potholes may surface. Many colleges hinge financial aid on a certain grade point average—say 3.0—without realizing 2.8 is more realistic for many target students, who then have to drop out.

As you look further into the student journey, other financial barriers may emerge, such as punitive punishments for even minor unpaid student debts, which could steer students away from graduation for as little as a $20 fee. Some policies were more relevant in a since-changed world while others were implemented when institutions were in positions of greater strength. Now, they have to be more competitive for students.

This is only one facet, but a very important one, of how a broader view of institutional data can be used to strategically improve student success. Conducting these steps to evaluate and better plan your institutional aid strategy can set a positive tone for how to critically look at your policies and practices with a student success lens. These conversations on campus will also bring together key leadership stakeholders from enrollment management, finance, and academic areas to work together on key strategies that go beyond the admissions cycle and can lead to other holistic solutions to benefit both the university and student outcomes.

Financial aid helps get students in through your front door, and that’s vital. You can’t help students succeed if you don’t meet them and welcome them to campus—brick-and-mortar or virtual—but there are longer-term implications as well. To truly help students succeed, you need to make sure you’re connecting all the data dots appropriately and learning and acting upon the right lessons you glean therein.

Darren Catalano is the former vice president of analytics at the University of Maryland Global Campus. He currently serves as CEO of HelioCampus, a data analytics company.

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