This powerful predictive analysis allows clients using precipice admission (e.g., communicating admissions decisions in late March or early April after all applications are in) to see the likely class profile (size, quality, discount rate, etc.) before admission decisions are sent.
How It Works
- In the fall, S&K receives a data file containing three prior years of admits which is used to construct a predictive enrollment model in order to assess the impact of various student characteristics on enrollment behavior.
- Prior to regular admissions decisions in the spring, S&K receives a “likely to admit” data file of applicants for the upcoming fall. The predictive enrollment model developed using prior years’ data is then used to tag each likely admit record with a probability of enrollment based on their individual characteristics. Note: aid awards for the analysis would be based on either the awards the financial aid office recorded on the system for the likely admits, or on awards calculated by S&K provided that need and packaging policies are supplied by the institution.
- The probability of enrollment tags allow S&K to estimate the class size and profile if those students were indeed admitted. The class profile analysis would include predicted net tuition revenue (NTR) and discount rate as well as other class characteristics such as academic profile, racial/ethnic diversity, etc.
- Based on those findings, the institution would then determine if there were applicants they wished to include or exclude from the likely admit pool and S&K would provide updated class profile analyses based on each new set of changes.
This iterative process provides timely updates and ensures that objectives are met in time for actual admissions decisions to be sent, based on the institution’s desired schedule. It can also assist an institution in better managing its wait list.
Visit our S&K enrollment management blog! Check out Getting the Most Value Out of Your Data by data team member, Don Gray.