Colleges and universities turn to self-service analytics for better results, solving data challenges.
Colleges and universities are home to the most advanced thinking and research in all fields: medicine, law, mathematics, business and beyond. Ironically, such schools haven’t always been as smart when it comes to data. This has been unfortunate, because the data needs of today’s two- and four-year degree granting institutions are as diverse and multidimensional as they come.
Institutional Effectiveness offices need to track trends across the current student population as well as assess future applicants. Institutional researchers and administration rely on timely data to drive decision-making and planning across all functions of the campus, and faculty involved in large research grant programs encounter a whole new set of data requirements. The smorgasbord of data is almost as varied as the course offerings provided to students today. And, the data challenges are further compounded by extraneous factors such as surges in enrollment and global competition.
But many academic institutions are learning new tricks by adopting self-service analytics. The following are four ways higher education is smartening up when it comes to data.
1. Empowering people to work with data
Like other industries and organizations, the traditional way of dealing with data in higher education was fragmented and slow. The IT department—and only the IT department—had access to the data, which was doled out in reports that were slow to come. IT was like an ivory tower within the ivory tower, and the faculty, staff and administrators who needed the data spent most of their time waiting for reports that would be out-of-date on arrival.
This cycle of long waits, static results and general inefficiency is going the way of chalk and blackboards at many schools, like the University of Washington (UW), which has been using UW Profiles since 2012. This project is a set of 23 dashboards that give administrators and faculty more flexible and powerful insight into data, such as performance, retention and support. Now inquisitive UW leaders have a recursive relationship with their data where answering one set of questions leads them down a path of seeking answers to a deeper set of questions.