Enrollment Projections and the Budget Process: A Technique for Smart Planning

1. Enrollment Projections and the Budget Process: A Technique for Smart Planning SCUP-39 Annual Conference Toronto, Canada July 20, 2004 Carol Rylee, Director Budget Office University of Delaware Phone: 302-831-1234 Fax: 302-831-8530 Email: rylee@udel.edu Dale Trusheim, Associate Director Office of Institutional Research and Planning University of Delaware Phone: 302-831-2021 Fax: 302-831-8530 Email: trusheim@udel.edu

2. Summary of Presentation • Enrollment Projection Methods • UD Enrollment Model • Brief Demo of Excel Enrollment Proj Model • IR Enrollment Model informs Budget Office Tuition Model • Parameters & Relevance of Tuition Model • Brief Demo of Tuition Model • Questions

3. Enrollment Projection Methods • Ad Hoc • Cohort Survival • Moving averages • Exponential smoothing • Time series (Box-Jenkins) • Linear regression and auto regression • SPSS Trends

4. UD Method • Enrollment in a given semester is simply a function of the behaviors of two groups of students: 1. New Students (Inputs) 2. Continuers

5. UD Method NewStudents Continuing Students + Freshmen Total number enrolled from prior semester minus (number of graduates + number of withdrawals) Transfers Readmitted

6. UD Method Historical Data Predicted Data FALL 2002 FALL 2003 FALL 2004 History SPRING 2003 SPRING 2004

7. UD Method • Primary task is to develop a model to depict student flow and to generate a prediction for future enrollment . . . . . . MS EXCEL

8. Excel Model — 3 Components • Input headcount enrollment for three groups of students (historical average or one-time) • New Freshmen • Transfers • Readmits • Predict headcount enrollment for • Continuing students • Estimate percentage of full-time and part-time students

9. Enrollment Projection Accuracy

10. EnrollmentProjection Model

11. Tuition Model • Budget Office Model uses separate Excel model to projection tuition income • Request Enrollment Model 3-4 times per year • Use numbers from enrollment model in spreadsheet model of tuition income

12. Tuition Model Parameters • FT/PT mix • Resident/NonResident Mix • Fall to Spring Attrition • Upcharge over 17 credits • Grad vs. Undergrad

13. Uses of Model • Forecast Full-time Undergrad • Construct what-if scenarios in regard to enrollment • Easily calculate each x% or $x change in tuition • Identify source of variances of actual from budgeted.

14. Relevance of models • Accurate budgeting of tuition • Don’t want to underbudget – campus confidence in numbers Is important • Don’t want to overbudget – leads to shortfall in income at year-end • Assessment of accuracy of model • Can quickly identify source of variances • Allows fine-tuning of models

15. Relevance of Models • Allows viewing of all factors related to enrollment and tuition income in succinct fashion • Facilitates comparision of tuition budgets from year to year

16. Other than Full-time Tuition • Part-time, Graduate and Special Sessions • Model is based on numbers of credit hours by residency. • Model is used in years when major changes are anticipated in mix and/or credit hours • Otherwise, use projection of prior year actual increased by estimated tuition increase

17. TuitionProjection Model

18. Questions & Info • Questions? • Copy of Powerpoint and Excel Models are available at: http://www.udel.edu/ir/reports/presentations.html