What Is the Value on Investment from Analytics? (Continued)

Just as I finished yesterday’s blog on VOI in Analytics, I came upon an interview in the Greentree Gazette with Tim Culver, Vice President of Consulting Services with Noel-Levitz, the firm that over the years has made a major contribution to defining the practice of strategic enrollment management (SEM) in higher education. http://www.greentreegazette.com/minute/load.aspx?art=1501

The interview focused on the major interests of Noel-Levitz’s community college clients and contains some useful examples of current best practice.

In response to the interviewer’s questions, Mr. Culver suggested that N-L’s community college clients were currently dealing with a variety of challenges that were utilizing analytics:

• Tracking student intent and outcome – are they seeking degree, transfer, or both?

• Understanding the student’s condition - is the student enrolled at multiple institutions concurrently?

• Using predictive modeling to improve fall-to-spring return rates, utilizing data-informed interventions,

• Increasing the success of online students by demonstrating and measuring readiness characteristics like commitment to time on task, critical thinking skills, and solid writing skills

Mr. Culver observed that the killer app for retention may lie in the retention modules that are now being made available by many of the ERP vendors. These include early alerts and modern communication modules so faculty, advisors, and counselors can track students and intervene easily.

Such modules are important steps. The establishment of analytic best practices in particular functional areas like strategic enrollment management or strategic planning or institutional advancement, each tied to a part of the ERP stack or a specialty shadow system, has been an evolutionary stage in the growth of analytics in higher education.

But the new gold standard is to loosen up the ERP stacks and create loosely coupled analytics that extract and combine data from the full range of data sources. These include non-ERP sources such as learning management systems, library systems, assessment shadow systems, continuing education management systems, and external data such as peer institution data, high school data sets, and cross-enrollment data with other institutions. The retention and student success killer app will be extended by these new wrinkles.