How big data can help recruitment and retention
“It is a capital mistake to theorize before one has data.”
What is big data and how can it help higher education administrators to recruit and retain students?
Big data is the use of predictive analyses and user behavior to examine large amounts of data to uncover hidden patterns and correlations.
In higher education, big data and predictive analytics has the ability to construct analytical databases that can provide speedy, actionable information in order to make smart enrollment and retention decisions and allocate both staff time and financial resources to increase the enrollment and retention of students. Simply put, big data and predictive analytics has the ability to help college administrators create a set of assumptions to learn which students are likely to enroll and persist.
Since the 2000s, with the increased focus on accountability in higher education, higher education administrators have used technology to provide insights into student choice, engagement and success. The principles of big data have also been applied to curriculum development, registration procedures, and library use. In the future, big data may be applied to alumni and fundraising programs.
Several colleges and universities are already using big data and predictive analytics in their recruitment and retention campaigns. For example, Florida Polytechnic University uses analytics to focus on specific enrollment markets and increase the university’s yield rate.
Georgia State University, with a student enrollment of more than 24,000 undergraduates, uses predictive analytics to increase its retention rate. University retention officials have developed more than 700 red flags aimed at helping advisors determine which students are likely to withdraw and persist. The universities of Michigan, Arizona, Michigan, Ohio, Colorado and Denver, as well as Miami Dade College, are among schools using analytics to improve progression and graduation rates.
The value of producing reliable data to influence enrollment and retention programs is not without risk. For example, it is reasonable to ask what administrators do with all of the actionable information analytics reveal. Is there a college and university structure in place that allows schools to respond, in actionable time, to what the analytics reveal? In most schools this would require a shift in culture and administrative alignments.
How many enrollment and retention managers are part of a committee or team that includes the director of technology and the director of research? How many deans of admission know what triggered applicants to apply and when, in the application process, that took place? How many directors of admission know why and when applicants decided not to apply?
The same questions could be applied to progression and retention programs. How many directors or deans of retention have intervention practices based on analytics beginning before enrollment and continuing to first and second semester trigger points? How many directors of retention have a profile of the persister as well as the dropout?
In order to effectively and efficiently use big data and predictive analytics it is necessary to ask the right questions. It also requires the ability to “drill down” from massive data to implement change. Martin Lindstrom, an international educator, calls this “small data,” or small clues that uncover huge trends. Clearly there are limitations of using big data.
Data collection and a commitment to insight and discovery are key elements but if there is not a structure in place to use the information, the analytics will simply be relegated to a shelf in someone’s office.
Flexibility will be the currency of higher education in the future and data analytics and predictive modeling are two of the tools necessary to bring flexibility into strategic planning.
Big data has the ability to unearth the meaningful differences between your school and your competitors, allowing the marketing and admission teams to leverage differences, rather than similarities, into future outreach programs.
Big data has the ability to focus on the needs and expectations of enrolled students to shape meaningful progression and graduation strategies by providing personalized assistance for enrolled students.
For a number of reasons, the future of higher education both in the United States, and around the world, is in flux. Moving from standalone data to actionable information, from uncertainty to accountability, deserves consideration.