With the wealth of data institutions have at their disposal, and with the emergence of more sophisticated analytics and decision-making capabilities, institutions have an opportunity to shift from using data merely to describe what is or has been to explore what is likely or possible. From Reactive to Proactive is issue #8 in the 2026 EDUCAUSE Top 10.
Higher education has a reputation for always being "on the back foot"—slow to change and innovate and behind on trends that are shaping other industries around the world.
With the wealth of data institutions have at their disposal, and with the emergence of more sophisticated analytics and decision-making capabilities, institutions have an opportunity to shift from using data merely to describe what is or has been to explore what is likely or possible. Strengthening these capabilities can make institutions more responsive and agile in their strategic planning and decision-making and help them avoid being caught off guard by emerging trends.
Proactive use of data is especially applicable to institutional academic and student support functions. By triangulating different sources of student-based data, institutions can gain a deeper understanding of the student journey, enrich educational experiences, and anticipate areas where student support is needed. It is important to note, however, that attempts to make student support more predictive can miss the mark. Models that overlook the emotional, social, and other human dimensions of the student journey risk offering incomplete or misleading characterizations of student needs and success.
In these and other institutional use cases of proactive, data-informed planning and decision-making, institutions must ensure that their guiding principle is beneficence toward the student. Students are not merely data points; they are whole humans, and institutions must balance sources and types of data to support this fact and avoid the harms of incomplete or misleading data. While more quantitative data can be useful for predictive modeling in areas such as enrollment and finances, qualitative data and anecdotal signals of potential changes within and around higher education leave room for nuance and uncertainty, encouraging institutions to cultivate more curiosity, exploration, and listening than traditional predictive analytics approaches have allowed.
While the future is never completely knowable, institutions that have a panoramic view of the possibilities on the horizon will be best prepared to adapt to uncertainty.
Campus Spotlight: Predictive Approaches to Marketing at London Business School
For institutions like the London Business School, which relies on marketing and brand recognition to grab the attention and interest of prospective students, effective marketing practices can be vital to ongoing success. In contrast to more traditional high-volume and often unsegmented marketing campaigns that "just hit as broad as possible" and "spend significant amounts without really having a good understanding of how effective those media campaigns are," London Business School is leveraging a more sophisticated analytics platform to build a predictive model for targeted marketing efforts, explained interim Chief Digital and Information Officer Karen Bates.
"We've built a data platform where we have integrated several of our core data sources, so we can start to do some real analytical thinking about the kind of linkages between media campaigns and traffic on our website and how that flows through into successful applications," she said. "Going forward, we can help support our brand and marketing team to ensure that all the spend that we're putting into those advertising campaigns is actually aimed at the right audiences that will bring the right quality students through for London Business School."
For a global higher education industry that is experiencing substantial resource constraints, predictive and targeted approaches can enable more efficient practices. "There is a place for digital and technology services to help broader institutional departments leverage their data to enable a better understanding of their business and target more effective spend," Bates said.
Ways to Get Started
Through our panelist interviews and community survey, technology leaders recommended some ways institutions might develop more proactive, future-focused approaches to data for decision-making:
- Enrollments and budgets may be two areas where data are robust and reliable enough to experiment with more quantitative predictive modeling methods. ERPs and other analytics and reporting systems offer increasingly sophisticated, turnkey capabilities, including forecasting and scenario building. These may be the lowest-hanging branches for institutions looking for somewhere to start.
- We live in a volatile social and political environment, and higher education has had a particularly turbulent year. This has created a greater sense of unpredictability in otherwise reliable data sources, making accurate predictions nearly impossible. Institutions should consider trend scanning and scenario development approaches that allow for more open explorations of what may be possible in the future. The EDUCAUSE Horizon Reports, for example, encourage engagement with strategic foresight methods that can support this kind of exploration and planning.
Karen Bates is Interim Chief Digital and Information Officer at London Business School and UCISA Trustee.
Shelly Belflower is Director of IT Software Licensing and Contract Management at Weber State University.
Diego Leal is Executive Lead of the Digital Educational Laboratory at Universidad de Los Andes.
© 2025 EDUCAUSE and the 2025–2026 EDUCAUSE Top 10 Panel. The text of this work is licensed under a Creative Commons BY-NC-ND 4.0 International License.