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First Learning Outcome: Identifying your own culture of SEM
Second Learning Outcome: Real solutions to take back to campus
Third Learning Outcome: Model basics
Core Competencies: Collaborative Decision-Making and Consensus-Building, Interpretation and Application of Institutional and External Data
Proficiencies: Admissions: Market Analysis, Records & Acad. Svcs.: Reporting & Institutional Research
Intended Audience: Significant experience in the profession, Senior management (President, Provost, Vice President, Vice Provost)
Utilizing Faculty as Specialists and Building an In-house Data Team
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Description
In the summer of 2018 we discovered that the college was facing a potential budget crisis for the 2019 academic year that was attributed to declining enrollment and a raise in discount rate. Something about the numbers was just not adding up. Our Dean of Enrollment and Dean of Academic Success, who is also a Math Faculty member, begin to dig into the numbers alongside our institutional research person.We discovered that the budget office had been using an old model for retention and enrollment that was not being updated with live data and was not accounting for a 3% drop in retention in 2015 and for the fact that transfer students did not take as long to graduate as modeled for.
As we dug further into the data we also discovered that financial aid spending on returning students was not properly budgeted on and assumptions were made that real time data would have caught as not accurate.
In close collaboration with the AVP for finance, we were able to reconstruct all of the old data with proper data and see where the revenue miss came from. This gave us ample time to adjust budget projections for the upcoming year and also to get a head start on the 2-19-20 budget process, which also had flawed data.
Seeing the overall need for a better solution for forecasting, we developed real time dashboards using our CRM for student revenue and retention, looking at anticipated graduation semester instead of the traditional cohort view. With many high school students enrolling with college credit and transfer students all over the board with earned credits, we needed to develop a more efficient way to look at projected revenue by each individual student.
This project brought together Faculty and staff to build an in house data team with collaboration among them not usually seen on campuses. Their are Faculty members on most campuses that are subject matter experts on data, analytics, marketing and human behavior that can be utilized in a modern SEM structure.
Submission ID:
6625
Presenter(s):
bill sliwa Moravian College
Kevin Hartshorn Moravian College
Sharon Maus Moravian College