The importance of higher education to our world and future well-being cannot be overstated. However, like healthcare, it is a complex environment with multiple often competing priorities. Institutions are mission-driven and manage a diverse set of objectives such as enrollment growth, academic achievement, efficient operations, thriving athletics, reputation management, and the essential development of constituents from students to alumni to large donors.

Most colleges and universities also face serious operational pressures around resource and operations management, and cost containment. In addition, trends in state funding, cost concerns, and national demographics have created fierce competition to successfully attract, retain, and graduate students.

Investments in performance management software have been staggering

For institutions without massive endowments, the best way to thrive in this environment is to develop an end-to-end student and constituent management process that utilizes predictive analytics and machine learning to deliver on your mission and optimize limited resources.

Colleges and universities have invested heavily in various expensive systems to manage and integrate a wide range of activities such as:

  • Marketing
  • Admissions and aid
  • Enrollment planning
  • Academic program management
  • Student persistence
  • Constituent engagement

Unfortunately, the investment in these systems has produced too few success stories where institutions have demonstrated tangible success and measurable ROI.

So what is the problem? The data are there and plentiful; the software and methods are powerful, but the results have yet to broadly materialize.

The unfortunate little secret of data science and AI

Though widely hyped, predictive analytics and machine learning methods are enormously powerful and are here to stay. In fact, they represent one of the larger competitive risks that organizations will face over the next 5-10 years. Organizations that effectively utilize these methods stand to marginalize their competitors and for most colleges and universities, the competition is strong.

With that said, successfully developing and deploying predictive analytics and machine learning is difficult. The percentage of successfully deployed projects is around 25% at best. Utilizing the analytical and predictive tools built into these program management systems does not happen with a successful installation.

Success requires a team approach. This is where eCapital can help.

Getting traction with predictive analytics and your educational management systems requires a team of stakeholders that can work together to prioritize where and when to apply predictive methods, how outputs and insight can be integrated into the daily operations, and how results can be reliably measured. The eCapital predictive analytics and machine learning team can be at the center of this team to significantly increase your odds of ROI.

Chris Engstrom

Chris has spent over 25 years building analytics and data science solutions. His passion for technology, new ideas and business value-driven solutions brought him to eCapital Advisors where he currently leads the Advanced Analytics and Machine Learning consulting practice.

Comments are closed.