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Article Type

Professional Proficiency

Article Abstract

Related Issue:

Ever since the beginning of the Great Recession, higher education has braced for the impending age of austerity and changing demographics. Now a reality, these conditions threaten the ability of institutions of higher education to remain competitive in an ever growing global marketplace. This article presents several core SEM strategies that can be implemented for four-year public colleges and universities in weathering these times of economic uncertainty and greater accountability. The authors weave in strategic recommendations for enrollment management leaders designed to more effectively expand the admissions funnel and engage in effective financial aid leveraging. Special attention is placed on how econometrics and elasticity of demand play in crafting an effective SEM response to fiscal exigency at their institutions of higher education.

Author(s)

Randall Langston serves as the assistant vice president for enrollment management at the College of Brockport, State University of New York, where he provides leadership to the Admissions, Financial Aid, Registration & Records, and the Academic Advisement areas within the Enrollment Management and Student Affairs division. In his role at Brockport, Randall is responsible for initiating strategic high-level discussion surrounding campus-wide enrollment management issues, preparing enrollment and revenue projections collaboratively with other departments on campus, interpreting predictive modeling, and collaborating on institutional financial aid leveraging strategy for new and continuing students. Randall earned a bachelor’s degree in 1994 from Sam Houston State University in Texas and a master’s degree from Texas Tech University in 1995.

Jamie Scheid is an Enrollment Analyst in the Office of Research, Analysis and Planning at The College at Brockport–State University of New York. He is involved with analyzing data related to recruitment and retention and has extensive experience with financial aid leveraging and predictive modeling. He earned a bachelor’s degree in mathematics from Cedarville University in 2001 and a master’s degree in applied statistics from Rochester Institute of Technology in 2005.

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