As college costs continue to rise against stagnant family incomes, the pressure to provide more financial aid from an institution’s operating budget has also risen. This rise in aid is accompanied by questions of its place in the financial health of the university. Are we spending too much? Is it being spent on the right students? These are common questions in university board rooms, faculty senate meetings and enrollment management committees. A strategic analysis of financial aid can help the enrollment manager and his or her institution to answer these difficult and sometimes elusive questions. It can also lead to an improved financial aid strategy, which is an important component of attracting and retaining students the institution seeks to serve.
Like many enrollment management techniques, leveraging uses data to inform decision-making. In a rare place within the realm of data utilization, leveraging rivals predictive modeling and retention analysis in its complexity and use of data across variables from different data areas of the institution and (in best practices) external data, as well. Leveraging may be defined as an analysis of student enrollment behavior through the lens of financial aid that leads to confirmation of or changes to institutional aid strategy. It is also a Continuous Quality Improvement process that uses analysis to refine and improve the institution’s financial aid strategy within the constraints of its available resources.
Financial aid leveraging seeks to achieve three goals:
- Provide aid packages that yield the optimal mix of students, including those who may not otherwise enroll at the institution (recruitment);
- Help close gaps between costs and resources that may prevent students from persisting to degree (retention); and
- Meet net tuition goals.
Before embarking on a leveraging analysis, there are two preliminary steps that you must take. These are more conceptual and strategic in nature than the process steps that follow them. First, you must determine the lens through which you will examine the gap between resources and costs (“need gap”). Will you look at the cost of attendance through the lens often used by the financial aid office, which includes direct and indirect costs? This is a common calculation of costs and is also known as the student budget. It includes estimates for books, transportation, miscellaneous costs and room and board when the student does not live in campus housing. Or, will you look at costs through the lens used by many students and parents to include just those paid directly to the university — tuition, fees and campus housing for your residents? There are good arguments for both lenses but the way in which you leverage aid will have different results, depending upon your answer to this question.
Second, you need to have clear enrollment goals that go beyond the number of students you seek to enroll. These goals will form the inquiry questions that impact the design of the analysis and variables included in the data set. For example, if a college seeks more out-of-state students, state of residence must be included in the data set. If it seeks more math majors or men, intended major and gender, respectively, must be included.
The process of financial aid leveraging is then broken into four additional steps that comprise the process of leveraging financial aid: data gathering and cleansing, analysis, implementation and review.
Step One: Getting Your Ducks (Data) in a Row
Possibly the most difficult of all the steps is gathering and cleaning data in preparation for the leveraging analysis. It is critically important to include the correct variables. You will need to know who enrolled and who did not and the financial aid packages offered to students who were admitted. Some financial aid offices delete aid packages for those who do not enroll, requiring these to be recreated in simulated packaging, a time-consuming task. It is also common to find incomplete and inconsistent records with the assembled data set. Old codes that were supposed to be inactive have a strange way of appearing, once the data is examined for consistency.
Many enrollment managers want to know if their aid packages are competitive with peer institutions. It is possible to complete a competition analysis using National Student Clearinghouse data. Data requests can be made to the Clearinghouse by member institutions for an annual research fee, which is usually a bargain for what can be learned from it when wisely studied and incorporated into a data set with other variables.
Assembling a data set for analysis requires expertise that may be beyond even experienced enrollment managers. It is important to partner with the institutional researchers at your institution and you will need someone on the project with experience and skill in working with large data sets, statistical analysis and the accompanying software required to assemble and assess your data. For this reason, it is common for institutions to enlist the help of a consultant.
Step Two: Making Sense of the Data
Analysis of the data can answer several questions. The most common analysis performed is the assembly of a “grid” that places the student’s ability to pay against the student’s willingness to pay. Ability is usually measured as the Expected Family Contribution (EFC) from the Free Application for Federal Student Aid (FAFSA). Students who do not send FAFSA results to your institution can also be assess but they are placed into their own category on the grid. It is also important to separate out those students who come to your institution through special financial incentives. These could be athletic aid offers, institutional employee benefits or special talents, such as art or music. The behavior of these students within the context of financial offers is so different from the majority of students that leaving them in the analysis with other students may skew the results.
Willingness to pay may be expressed through academic preparation data. Those students with higher academic preparation levels will have more options for enrollment at various institutions and will likely receive merit aid offers from your competitors. Students with lower preparation levels may be thankful to be admitted to your institution and jump at the chance to enroll with less financial incentive to do so.
The grid of need and ability will contain many cells where these two variables intersect. There are multiple ways to assemble these data into the grid but standard for any assessment is the inclusion of institutional gift aid and total gift aid for each cell, along with the number and ratio of students enrolled to those admitted. Smaller institutions will need multiple years of data (also a good idea for larger ones, as one year’s data may be anomalous to overall performance) to avoid problems resulting from small sample sizes. Separation of student cohorts (freshmen, transfers, graduate, adult learners, in-state or out-of-state, etc.) is an important step, as different cohorts may react quite differently to various aid offers.
Each cell in the grid is carefully analyzed to determine to what extent financial aid may play a role in student enrollment decisions. For example, in the highest ability, lowest need cell, students may be receiving full-ride offers and yielding at very low rates. There may be no financial issue that improves this and these results may be a function of institutional position and/or recruitment techniques. Other students with very high need may not be yielding at high rates because they lack the basic financial resources to cover costs. At this stage, it is a good idea to have someone with extensive experience in financial aid analysis to take a look at these data to help the enrollment manager and institution walk through the questions and possible reasons for low or high yield rates. Using an analysis tool such as an Excel pivot table to construct the grid will allow analysts to “drill down” into each cell and examine the cases that comprise its summary averages.
There are several additional analyses that can add to the understanding of student enrollment behavior through the lens of financial aid. With large enough sample sizes, it is possible to assess behavior between academic programs, seeking to understand if the same merit or need awards elicit similar or different behaviors for engineering or history majors, for example. Behavior may also be different between students from varying regions of your recruitment territory, such as in-district or faraway states. A leveraging analysis can also be used to view the retention of students at your institution, substituting return to studies for initial enrollment as the dependent variable in the analysis.
Step Three: Adjusting Aid Strategies to Meet Institutional Enrollment Goals
From the analysis of institutional aid performance, changes to institutional aid may be made to help improve the yield of students desired to achieve institutional enrollment goals. One example of this is that institutions may decide to meet a higher percentage of the need gap for more desirable students than those less desirable to meet the qualitative enrollment goals of the institution (academic profile, geographic diversity, etc.).
This may be as simple as “tweaking” awards in certain cells to achieve marginal improvement in several areas or as radical as an overhaul of the institution’s aid scheme. Expected results are placed into a model matrix as targets for the entering class for whom these aid awards will be available. Documentation of the rationale for each change in awards should be made and kept, so that there is a record of why these new expectations were set. From this model, the expected net tuition revenue for each entering cohort can be modeled and incorporated into the overall tuition revenue projections for the institution. Needless to say, the timing of the entering classes should be far enough in advance that the awards have an opportunity to play a part in the recruitment of and yield of the entering students.
It is important to consider how these changes will be communicated to key audiences, including students, parents, guidance personnel, faculty, recruitment staff, financial aid staff, alumni and others who may have a vested stake in the recruitment and enrollment of your students. Making changes to scholarship or grant programs but failing to promote them may minimize the overall enrollment results you hoped to achieve.
Step Four: Rinse and Repeat – Continuous Quality Improvement
Once the entering class has matriculated, it is important to assemble the leveraging matrix for that cohort against the numbers you expected to achieve in each cell. Where expectations were different in any significant way, it is important to review the documentation for the assumptions made to see why the results over or under-performed the expected levels. From this review, additional changes can be made for the next entering classes.
As the institution gains experience with leveraging, it will be better able to forecast the impact of changes in aid strategy on net revenue for new and continuing cohorts of students. It may take several years of purposeful changes to acquire the desired results, especially if they require the infusion of significant new financial aid resources. It may not be prudent to add these new resources in a single year and enrollment managers must be mindful that increased discounting has a long-term rollout as students persist toward their degrees.
It was tempting to title this brief “Financial Aid Leveraging: Six Simple Steps to Enrollment Health” in hopes that readers would quickly see its irony – financial aid leveraging is anything but “simple” and it is not a magic elixir to improve the institution overnight. It is, however, a potentially powerful tool that can be employed by enrollment managers in combination with other proven enrollment techniques. As pressures mount to provide greater amounts of aid to students, having a firm grasp of aid at your institution and a purposeful plan for awarding it will be important assets for enrollment managers.
If you are interested in learning more about financial aid leveraging at your college or university, please contact consulting.aacrao.org.
Written by Tom Green, Director of Technology and Managing Consultant for AACRAO Consulting.
Download this paper here: Leveraging Financial Aid: A Powerful Tool for Enrollment Success