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Shaping Your Incoming Class and Maximizing New Revenue

Shaping Your Incoming Class and Maximizing New Revenue. OKLAHOMA CITY UNIVERSITY Kevin Windholz, Vice President of Enrollment Management Jacob Dearmon, Associate Professor of Economics. About Us. Kevin Windholz

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Shaping Your Incoming Class and Maximizing New Revenue

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  1. Shaping Your Incoming Class and Maximizing New Revenue OKLAHOMA CITY UNIVERSITY Kevin Windholz, Vice President of Enrollment Management Jacob Dearmon, Associate Professor of Economics

  2. About Us • Kevin Windholz • Vice President of Enrollment Management, Oklahoma City University (2012-present) • Associate Director of Admission Operations, Saint Louis University (2006-2012) • Assistant Director of Admissions, Washburn University (2003-2006) • Admissions Counselor, Washburn University (2001-2003)

  3. About Us • Dr. Jacob Dearmon • Education • Chemical Engineering, B.S. • Economics, Ph.D. • Work • Quorum Business Solutions: • Software Development • OCU: • Associate Professor of Economics, 2012 Faculty Fellow • Devon Energy: • Spatial Modeling and Machine Learning • Economic Research and Policy Institute: • Sales Tax Forecasting for the City of OKC • Energy Policy Analysis

  4. Challenges • Less overall ability to pay • Increase in unpaid balances • Fear of a tuition hike • Significant increase in discount rates to preserve headcount • Less university revenue • Harder to prove our value

  5. Parent Plus Loans at OCU

  6. Financial Awareness Campaign • Done extensively with fall 2013 incoming students, but started small with fall 2012 incoming • Combination of items new at Oklahoma City University and those brought from Saint Louis University • Involves communication plan in various forms, and constant review of different types of financial data

  7. Financial Aid Communication Plan • Senior Year Plan • Always ‘proudly’ display cost, with detailed financial aid and scholarship info close by • October: • ‘Financing Your Education’ mailer • Personal accounts of financial aid • Financial Aid webinar • Parent newsletter covering full process • Scholarship notices begin • November • FAFSA 4Caster information

  8. Financial Aid Communication Plan • December • File FAFSA Card • January/February • Financial Aid (FAFSA Process) Chats • March • Awards Packets Begin • April • Financial Aid Interviews (with admissions)

  9. Financial Aid Communication Plan • May/June • Explanation of charges at STARS 101 • July • Student Accounts webinar • Statements are mailed

  10. Financial Aid Interviews • Admissions counselors are trained as financial aid counselors • Give every admit the opportunity to have a one on one interview about their financial aid package and potential charges • Benefits to doing this pre-STARS 101 *credit to Mark Steinlage, Associate Director of Freshman Recruitment, Saint Louis University

  11. Award Packets • Converted to paper for all new students • Paper letter and cost calculation sheet • Booklet with full explanation of loans • Glossary of financial aid terms • Instructions on how to accept online • Introduction of OCU email *credit to Cari Wickliffe, Assistant Vice President of Enrollment and Retention Management and Director of Student Financial Services, Saint Louis University

  12. Paper Statements • Once a new student has enrolled, they receive a letter in the email explaining the timeline of when charges will be billed • Statement comes in the form of paper (new students only), with an attachment of how to understand terms and further explanation of payment plans • Instructions on how to pay online are enclosed

  13. Results: Summer Melt

  14. Results: Incoming Statistics • Grew headcount by 7% • Raised annual incoming freshman net revenue almost $800,000 • Lowered discount rate by a percentage point • Freshman-Sophomore Retention Rate – 82% • up from 80% year prior

  15. Discount Drop • Modeled the class in house the summer prior, then set firm budgets with discount giving areas • More ‘financial education’ caused less requests for need based aid

  16. DATA, DATA, DATA • Looked at Zip Code Household Buying Power (HBP) for applicants • FAFSA Data for admits • Look at EFC levels • FAFSA positions

  17. FAFSA Positions

  18. Negotiated Amounts Jacob Dearmon

  19. Introduction • Scenario: • An admitted Business student with a 27 ACT who lives 10 miles away has come into your office asking for more aid. • Questions: • Will you give him additional aid? • If so, what amount will you give? • What factors play into your decision?

  20. Introduction • The scholarship negotiation affects two key items: • The probability that an admitted student will enroll. • The net revenue that an admitted student will generate should he/she enroll.

  21. Introduction • As the student’s aid increases, so does the probability of enrollment. Probability Add’l Sch. Amt.

  22. Introduction • Trade-Off: • Give the admitted student too little scholarship, he/she won’t come. • Give the admitted student too much, he/she won’t generate any revenue. • Key Question: • Where is the sweet spot???

  23. Negotiated Amounts • We use data-mining and optimization processes to identify the sweet spot and help inform scholarship allocation decisions. • This process • Is Automated • Uses Historical Data • Is Able to Identify the Student’s Sweet Spot • Is Able to Recommend Scholarship Allocation Across a Pool of Admitted Students Based on the Greatest Return

  24. Negotiated Amounts: Student Level • This process depends on ExpectedNetRevenuewhich consists of two parts: • Probability of enrollment • Net revenue should the admitted student enroll • The next slide shows the relationship between scholarship, enrollment probability and expected net revenue for an individual student.

  25. Negotiated Amounts: Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Increasing

  26. Negotiated Amounts: Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Increasing

  27. Negotiated Amounts: Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Increasing

  28. Negotiated Amounts: Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Increasing

  29. Negotiated Amounts:Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Increasing

  30. Negotiated Amounts:Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Decreasing

  31. Negotiated Amounts:Student Level Graphs Prob. Of Enrollment Increasing Exp. Net Rev. Decreasing

  32. Negotiated Amounts:Student Level Graphs “Sweet Spot”

  33. Student Level Report: Recommendation and Background

  34. Student Level Report:Add’l Scholarship Data Current Rec.

  35. Student Level Report: Graphs

  36. Negotiated Amounts: Managerial Concerns • The availability of discounts might be limited. • Given this constraint, how should discounts be allocated across a pool of admitted students? • How does one control for input quality?

  37. Global Scholarship Allocation • Allocate dollars based on some user defined increment up to some maximum amount on a per student basis. • Allocation proceeds based on some user-defined combination of gains in Expected ACT and Expected Net Revenue. • In other words, dollars are allocated based on the “biggest bang for the buck”.

  38. Aggregate Level Report:Current

  39. Aggregate Level Report:Configuration Settings

  40. Aggregate Level Report:Optimized Values

  41. Aggregate Level Report:Scholarship Allocation Rec.

  42. Aggregate Level Report: Forecast Maps

  43. Aggregate Level Report: Census Maps

  44. Details: A Closer Look • Expected Net Revenue depends on the probability of enrollment. • How is probability of enrollment determined?

  45. Probability Estimate:Possible Factors • Academic Input Quality- HS GPA, ACT • Financial Aid- Tuition, Fees, Scholarships (Discount and Endowed), Grants, Loans, Remission • Financial Need- EFC • Demographic Characteristics • Location- Distance, Census Data • Preference for OCU • Economic Data • School or College

  46. Probability Estimate: Objective and Considerations • Objective: 1) To determine a robust estimate of the student’s enrollment probability accounting for the student’s characteristics and 2) to capture its sensitivity to changes in the aid amount. • Considerations: • How are the appropriate set of factors determined? • How does one account for the uncertainty regarding the true set of factors? • How is the appropriate relationship between these variables and enrollment determined? • How many methods should be used? • If more than one, how should they be combined? • How should results be assessed?

  47. Conclusion • We have extended, or are in the process of extending, this program to other areas as well including: • Setting the Tuition Amount • Setting the Scholarship Matrix Amounts • Assessing Retention Outcomes

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