Linda Peckham, Senior Training Strategist, Great Lakes Higher Education Corporation

With the proliferation of headlines on the fiscal cliff, aid cuts, and possible sequestration in the news, aid leaders are often asked to predict how funding cuts will impact the campus community. The request for instant information about the impact of policy shifts can leave the aid office struggling with ways to piece information together in meaningful ways. The aid office usually has most of the data they need to respond to these requests, but often, new leaders are not sure how to organize the information into a compelling narrative that informs or shapes new policy. As Rick Shipman, Director of Financial Aid at Michigan State University says about his early days as a new director, “I was immersed and surrounded by good data but I had no idea what to do with it to shape policy.” 

Shirley Ort, Associate Provost and Director of Student Aid and Scholarships at the University of North Carolina – Chapel Hill (UNC), recommends that aid offices start organizing their data by working with the office of institutional research on campus in order to merge financial aid data with that from other campus offices, such as admissions and career planning. The goal is to build a baseline database from which to work. Once the data is organized into a comprehensive file, the aid office can easily track and display how aid policies and expenditures are shaping the class and the campus. 

Additionally, the database can help model the impact of changes in aid policy on specific cohorts of students. “When we’re asked to predict the impact of a budget change, we can do so quickly and show a visual of exactly what type of students might be impacted by the change.” This approach has allowed UNC to communicate more effectively, both with senior leaders on campus and with state governing bodies when aid cuts are under consideration. 

The UNC database includes over 40 variables based on student information from each class. Most of the data is culled from the financial aid and admissions files, and includes standard information that is commonly tracked. But Ort also recommends that aid offices dig deeper for data and think about the information that decision-makers might find useful when making policy decisions. “At UNC, we pull in parent job data and socioeconomic status (SES) as part of the student profile. After graduation, we can link career placement data to determine where a student is employed and at what income. The longitudinal data tells a powerful story about the impact of the Carolina Covenant® and other need-based programs on student outcomes.” As an example, UNC has been able to illustrate the connection between the investment in aid through the Carolina Covenant® program and significantly increased graduation rates, which results in long-term payoffs for the taxpayers of North Carolina. 
“We can show how the expenditure for our high-achieving, low-income Covenant Scholars results in graduate student and employment opportunities which will essentially pay back the grant over time through income taxes. It’s a powerful story when we show results from beginning to end,” asserts Ort.

Once the data are organized into a useable framework, you have options for how to show results: charts, graphs, or scatterplots. Although these traditional illustration tools are useful, “don’t be afraid to make the data personal,” recommends Susan Murphy, Senior Associate Dean of Academic and Enrollment Services at the University of San Francisco (USF). Recently, the university had to communicate to both campus leaders and state legislators about the potential impact of cuts to the Cal Grant program, including how the cuts might result in lower enrollments, less diversity, and changes to academic programs. But the most meaningful data the university shared with decision-makers was about the individual students who would be impacted. “It’s easier to understand the result of budget cuts when the student impacted is someone you know. It’s not just the nameless student who can’t return to school – it’s the Dean’s favorite work-study student who he’s known for three years.” USF’s campaign to offset potential Cal Grant cuts was highly successful because it told a story about who, how, and why specific students would be impacted. “Basically, we provided a narrative with pictures that resulted in a very clear picture of long term impacts of the grant cuts,” states Murphy. 

Together, Ort and Murphy have several recommendations for aid leaders seeking to use their data to tell a compelling story:

• Build a baseline for every class. Include overall aid expenditures, family income levels, academic preparation, SES, ethnicity, and any other variables your institution finds important (athletes, academic major, state residency, etc.)
• Isolate trends over time: show how aid expenditures are helping certain cohorts of students in five-year intervals. When the audience can see steady results over time, they are more likely to embrace the evidence of the impact of funding.
• When asked for data, think beyond just showing the information visually; learn to shape the narrative. Studies show that our brains respond to stories, not just visual graphics, and that decision-makers are more likely to take action when they feel involved with the story.
• Keep your visual displays simple and concrete. Your audience is more likely to comprehend data (and thus agree with you) when you isolate simple and concrete messages about what the data means for your campus.