Data-Informed Decision-Making in Education: Building Smarter, More Equitable Institutions

We all know that data-informed decision-making is better than intuition and face value judgment. Data, whether cold or warm, does not always underscore our impressions and can be counterintuitive, telling a different story to the one we would like to believe. Fundamentally, decisions taken using data well and intentionally will tend to address genuine institutional needs rather than mere speculation and belief.

Knowing which data to use and designing the best data-capturing mechanisms is an art and a science. I’m a fan of mixed methods, using quantitative and qualitative metrics, surveys, semi-structured interviews, focus groups, and individual discussions, results, and trends. The more granular and ingenious we become in thinking through what sort of data we require and how we can drill down into the data, the more precise and exact our research becomes. 

Take admissions: it is not enough to simply know how many people sign up for admissions visits and what that converts to in terms of requests; you need to know who does not come and why, what the reasons for non-joiners are, what the market share looks like, what yearly trends on the same metrics look like, and more. Once you have triangulated all of these points, the picture will become clearer.

An area of education that needs more data analysis is student learning: pre and post assessments, understanding student predilections, motivations, and keeping a close track of performance metrics will lead to a much richer appreciation of a student’s profile than crude testing of items with little in between. Again, a mixture of methods and an ongoing search for salient data points will develop a more precise picture of the learner’s pathway.

Data-informed decision-making is becoming central to how universities enhance student success, improve teaching quality, and allocate resources effectively.

In the article, “Toward a Holistic Approach to Data-Informed Decision-Making in Education,” Steve Baule emphasizes that “data must inform decisions, not dictate them — professional judgment, teacher intuition, and contextual knowledge must guide final actions.” It underscores the idea that educational leaders should blend quantitative insights with human expertise and context-aware interpretation to make truly effective and equitable decisions for students.

With the rise of real-time analytics, predictive models, and early-alert systems, institutions can identify student needs earlier and design more targeted academic and support interventions. This highlights the growing potential of data to strengthen institutional planning while emphasizing the need for ethical use, transparency, and safeguards that protect student privacy and prevent bias. 

By building data literacy across faculty and staff and encouraging collaboration between academic and administrative units, universities can use data not only to drive efficiency but also to promote equity and more responsive learning environments.

At the end of it, though, let’s not forget human wisdom. All the data in the world cannot replace the judicious mind that interprets it and puts it to ethical use.

At University of the People, data-informed decision-making is built into the very fabric of how we support students. As a tuition-free, online institution serving learners across more than 200 countries and territories, UoPeople relies on continuous analysis of student engagement, learning outcomes, and support trends to ensure every learner has the opportunity to progress. From early academic alerts to targeted advising and curriculum improvements, data helps us identify where students need help most — while human educators, advisors, and volunteers apply judgment, empathy, and mentorship. By combining analytics with human insight, UoPeople is able to deliver an education model that is flexible, equitable, and deeply responsive to learner needs.