Last year, the student success coordinator at a client institution of mine shared a story that may be familiar to those who lead the efforts to improve student retention and graduation rates on your own campuses.
A faculty member was nonplussed when the most recent freshman cohort retention figures showed that first-to-second-year retention had improved by about 2 percentage points. A “what’s the big deal” comment was followed by “is it even statistically significant?” After hearing this story, I suggested to the student success coordinator that if her colleague doesn’t see improved student success as good news for both students and the institution serving them, than an appeal to her colleague’s understanding of the bottom line might be convincing.
In this case, net revenue per freshman was about $15,000/year, and a 2 percentage point increase in retention rate translated to 12 additional students persisting to sophomore year. That’s $180,000 in additional net revenue in the second year, not counting room revenue. Using average persistence rates to junior year, 10 would still be enrolled, and eventually 9 students would persist to senior year. That equates to $150,000 and $135,000 in years three and four. In total, the 2 percentage point improvement in retention was likely to result in about $465,000 additional net revenue over a three-year period for the first cohort alone, not counting the additional revenue gained from each subsequent cohort cycle. For small, tuition-dependent institutions, that’s nothing to sneeze at.
Calculating revenue from specific majors
At the same institution, the institutional research officer was interested in gaining a better understanding of the internal migration patterns of students who change majors, especially those who began as biology majors. They were seeking to answer not only the question of whether students in a particular major were leaving the institution at higher rates than other majors, but also whether they were remaining as science majors or migrating to majors within another academic division. This need for additional data aligned nicely with the fact that an intentional by-product of our retention predictive modeling and best-practice review is to encourage our clients to do a better job of tracking retention by various subpopulations. To that end, we provide reports to demonstrate movement among majors over time. In this instance, a custom report was designed that the IR director could then replicate internally. This provided the institution with valuable data for planning as they sought to identify majors that, even though initial demand (first-time majors) may not have been strong, showed enrollment increases over time as a result of internal transfers. The financial consequences of enrollments by major would not have been obvious from looking exclusively at initial enrollment data.