Using organizational models to reap big data benefits for EM

Topics: Enrollment Management, Organizational Structures, Data Driven University, Administration and Finance, Strategic Planning

This is a preview of restricted content.

  • If you are an Education Advisory Board member, please log in.
  • If you are logged in and still see this message, the content is outside your membership portfolio, and we invite you to learn more by contacting us.
  • If you are not an Education Advisory Board member and wish to learn more, please contact us.
Pete Talbot

Pete Talbot, Managing Director

Enrollment management (EM) hinges on the ability to harness data to inform strategic enrollment planning and day-to-day operations. Although EM divisions generate a wealth of data, many enrollment shops lack the staff and organizational oversight to analyze these data and remain reliant on Institutional Research (IR) departments.

The Problem: Plenty of Data, Limited Analytic Resources

Unfortunately, IR departments are so overburdened with regulatory reporting and compliance responsibilities that they often have little excess capacity. As a result, enrollment managers face:

  • Inaccessible data lacking reliable and immediate access to up-to-date trends
  • Campus data confusion resulting from different conclusions drawn from disparate data analyses
  • Limited analytics capacity due to a lack of data and analytics expertise within the enrollment unit

The Solution: Organizational Models that Promote Data-Driven EM

Enrollment Management Forum research identified three organizational models facilitating a data-driven enrollment shop, while limiting the need for outsourced enrollment analysis. These models require varying degrees of enrollment manger time and resource allocation, from funding dedicated enrollment analysts within Institutional Research to establishing enrollment manager oversight over all IR operations and funding.