Methods and Techniques of Enrollment Forecasting

Abstract

Enrollment forecasters have much to consider. A combination of quantitative and qualitative methods can sometimes be the best approach. Methods and Techniques of Enrollment Forecasting Paul T. Brinkman, Chuck McIntyreInstitutional researchers are often called on to conduct or assist with enrollment forecasts. Occasionally, personnel in institutional-planning offices, in state agencies, or in the marketing offices of continuing education divisions will be called on to produce such forecasts. Enrollment forecasts are fundamental elements of planning and budgeting at any higher education institution that depends on student enrollments or at any agency or organization that has responsibilities for supporting those institutions. Numerous institutional policy issues are related to enrollment forecasts-tuition policy, budget forecasting, faculty staffing, institutional closure or consolidation, and optimizing objectives related to the size and composition of enrollment (Weiler, 1987a).There is no one right way to forecast enrollment. In this chapter, we discuss a variety of approaches and associated issues. We relate choices of method or technique to specific circumstances and situations in an effort to provide some guidance to readers in choosing their own approaches. We focus on forecasting institutional enrollments. Factors Affecting EnrollmentNo one factor determines enrollments at a college or university. For the economist, enrollment will be determined by the intersection of measured supplyand-demand curves. For the demographer, enrollments are related to numbers of people and where they are located. For the higher education administrator, enrollment is determined by the combined effects of many manageable and unmanageable factors, categories that are roughly, though not completely, equivalent to supply and demand. In addition, there is always the possibility that a

Applying mixed methods techniques in strategic planning

“…Many institutions create enrollment projections based on a variety of techniques (see, for example, Brinkman and McIntyre, 1997). I have a preference for projecting future institutional enrollments from two key pieces of information: (1) current enrollments at the institution and (2) actual and projected population counts for the institution' s catchment area.…”

The Impact of Lengths of Time Series on the Accuracy of the ARIMA Forecasting

“…In enrollment forecasting, multiple factors influence projection accuracies such as the forecasting method, length of time series, frequency of enrollment occurrence, and other institution-related predictors (e.g., enrollment policy, financial aid policy, and economic situation). Two traditional approaches to enrollment forecasting are causal modeling and time-series analysis (Brinkman & McIntyre, 1997). The causal modeling approach predicts future enrollment, regressing on factors that affect enrollment levels such as financial aid policy, students' demographics (e.g., gender, ethnicity, age), employment status, and prior educational experience (Brinkman & McIntyre, 1997).…”

Seamless Integration of Predictive Analytics and CRM Within An Undergraduate Admissions Recruitment and Marketing Plan

“…Gone are the days where a skilled admissions professional could develop a recruitment plan and implement it effectively with minimal training and expertise. Contemporary enrollment management (EM) leaders thrive in data‐driven environments where concepts like econometrics (Brinkman & McIntyre, ; Brooks, ), elasticity of demand (Curs & Singell, 2010; DesJardins & Bell, ), tuition discounting (Hillman, ), technology (Dennis, , p. 23; Penn, , p. ix), data mining (Goyal & Vohra, ; Kabakchieva, ; Linoff & Berry, ; Yu, DiGangi, Jannasch‐Pennell, & Kaprolet, ), constituent relationship marketing, and predictive analytics have replaced old scattershot approaches with rudimentary aims and objectives. Dolence () noted that dependable EM plans must comprise several components, which include being (a) comprehensive, (b) deliberately designed, (c) one that achieves meaningful goals, (d) strives for optimal enrollment, and (e) involves recruitment and retention activities (pp.…”