That distinction matters more now than ever. We live in a world awash in data, metrics, and analytics, all promising clarity. But data does not decide what matters. Humans do. When we confuse the two, we risk mistaking big data for wisdom.

My industry, higher education, is experiencing something like a winter storm. Budgets are tightening, enrollments are shifting, and public confidence has declined. As Utahns know, driving in a winter storm requires steady hands and clear judgment. Sudden moves and overcorrections are often what send a car into the ditch. When institutions let data drive rather than inform, they risk reacting to noise instead of signal, and overcorrecting just when steadiness matters most.

We have all seen the driver who overreacts to everything: every warning light, every bump in the road, every gust of wind. That driver is not safer; they are dangerous. Good drivers learn to distinguish signal from noise. They know which inputs require action and which can be ignored. Data works the same way. Not every fluctuation is meaningful. Not every trend deserves a response. When leaders treat all data as equally urgent, they end up chasing noise and missing the underlying signal.

This problem is increasingly visible in the rise of so-called dashboards. Dashboards are collections of charts, graphs, and performance indicators designed to summarize complex systems at a glance. In higher education, those indicators typically include enrollment trends, graduation and retention rates, time to degree, student satisfaction surveys, job placement statistics, and budget metrics. A recent report from the James G. Martin Center for Academic Renewal asks a simple but important question: Do these dashboards actually illuminate anything? Their answer is often no. Dashboards can be visually impressive and technically sophisticated while still obscuring what matters most. Institutions become data-rich but insight-poor, mistaking colorful charts for understanding.

There is a deeper danger here as well. Dashboards are rarely transparent in how they are constructed. Decisions about what to include, what to exclude, how to aggregate, and how to scale the data are usually made by a small group of people long before the charts ever reach a committee or board. Those choices embed assumptions and priorities that most users never see.

This is where Nobel Prize-winning economist James Buchanan’s essay “Politics Without Romance” becomes relevant. Buchanan’s point was simple: Self-interest does not disappear just because an organization is nonprofit or mission-driven. Universities are no exception. Faculty and administrators respond to career pressures, reputational concerns, and internal politics just like everyone else.

These questions about self-interest and institutional structure are also why the Crossroads Economics Center at Weber State University is hosting a community book club this spring on “Cracks in the Ivory Tower: The Moral Mess of Higher Education” by Jason Brennan and Phillip Magness. The book examines how individual self-interest interacts with the structure of higher education, and how well-intentioned people can produce troubling outcomes when incentives are misaligned. On March 25, Dr. Magness, the David J. Theroux Chair in Political Economy at the Independent Institute, will visit Weber State to share insights from the book with faculty, staff, students, and the broader community. Details about the book club and event are available at weber.edu/cetl/list.html.

The stated goal of dashboards is data-driven decision making, which I have already suggested is misguided. But they also open the door to something worse: decision-driven data. When outcomes are known in advance, metrics can be engineered to support them regardless of what the underlying data actually show. I once heard a senior data analyst remark, casually, that a particular metric was “designed to be difficult to interpret.” When numbers are hard to interpret, they are easier to manipulate.

None of this means data is useless. Maps matter. But no one confuses a map with a driver. Higher education has long been understood as a public good not because it produces tidy metrics, but because it cultivates judgment, independence of thought, and the ability to weigh evidence carefully in uncertain environments. Those human capacities cannot be automated, visualized, or outsourced to dashboards. If universities mistake big data for wisdom, they risk abandoning the very public purpose that justifies their existence in the first place.

Gavin Roberts is an associate professor of economics and chair of the economics department at Weber State University. He is a recipient of the Gordon Tullock Prize from the Public Choice Society and regularly shares his research locally, nationally and internationally. This commentary is provided through a partnership with Weber State. The views expressed by the author do not necessarily represent the institutional values or positions of the university.