Bob Massa and Bill Conley explain that algorithms were created by enrollment leaders to manage modern-day college admissions and to help make if financially possible for students to attend their institutions.
It’s an honor to work with institutions of higher education. They have the honor and responsibility of expanding and transferring knowledge and awareness to individuals who are hungry to learn and grow intellectually.
Every school should be glued to information about their specific enrollment futures, as they may change dramatically and quickly. Then they should plan and prepare just like it’s an actual storm. In many ways, it kind of is.
In the knowable future, the pool of newly eligible college freshmen will shrink. That freshmen recession will start somewhere around 2026 and may continue for a decade or longer. That forecast is well known.
Colleges usually rely on marketing, alumni networks, and positive word-of-mouth to attract new students, but what if predictive analytics could do a better job of creating the perfect match between students and universities?
Andrew Hannah has embarked on a new direction with startup, Othot, a cloud-based predictive analytics company. Initially targeting higher education, its first product predicts the likelihood that a prospect will turn into a customer.
Big data can be a powerful tool. And while many companies scramble to collect data with hopes of mining it for key information, most lack the means to interpret and parse the data — or to use it to make decisions for the future.