The census is upon us. Now what?

Students have moved in, parents are back home, relationships have started … and ended, first exams delivered and disciplinary counsels are full of agenda items. Yup, it’s that time of year. Oh, and the traditional census is underway, with a crowd awaiting the puffs of smoke, signaling the year’s revenue projection has been calculated.

There are other anxious times of the year involving the business office but none rival the mid- September forecast. Will my budget be safe? Are my people at risk of termination? Will the pain be felt with next year’s budget instead? Did we get it right?

With each campus visit, I find fascinating the many ways that revenue is forecast. Some look at the budget for financial aid, calculating what has been awarded in the financial aid sub-system against that budget. Others use FTE calculations to determine how close the revenue should be against the budget. Few have different budgets for fall and spring, even though a spring reduction in headcount is all but guaranteed (and surprisingly predictable.)

I suffer from being a CPA who believes in the role of the general ledger in providing the data needed for forecasting. No matter what financial aid or enrollment systems report, the institution’s financial statements will be based on whatever is posted in the G/L. The FTE number could be skewed by a surge in part-time students who pay a much lower cost per hour than their full-time counterparts. What financial aid believes has been posted to student’s accounts might not account properly for tuition remission, guest students and/or potential changes during the semester. The GL cuts through all of this throughout the semester and forms the basis for full-year financial statements. It is the most reliable predictor of performance.

I take the current year tuition and fee billings, along with institutional aid and compare this year’s actual with two other columns of information. The first comparison is with last year’s fall. How did we fare? What was the differential between fall and spring last year and what happens if that relationship remains the same this year?

The second comparative column is for the budget and I compare it with the extrapolation of the current year (CY). Were we off? By how much? Was it due to fewer students, more financial aid spending or both? What factors drove performance this fall? What kind of information does this provide for next year’s budget?

Those of you who are my clients know that I like to look at the performance of individual classes versus using an overall fall to spring retention ratio. This is because of the improved retention that occurs as one progresses through the classes over their four (or more) years. For instance, if population is up but skewed toward freshmen, the losses will tend to be greater between fall and spring. And, if a low retention program brought in those added numbers (certain sports come to mind) then the losses may well be magnified. Better to prepare for such eventualities than to presume a static relationship.

In the end, all of this constitutes an educated guess and the CFO’s role is to mitigate variability risk. We don’t guarantee our results but are happy to share our methodology in arriving at the conclusions that are drawn.

Having trouble making your predictions work? Send me an email. One of my free models might just be right for you.

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