The Institutional Data Myth: Why Higher Ed Leaders Can’t Afford to Ignore It

Many institutional leaders believe that data management is a ‘big university problem.’ They assume fixing The Data Trap requires expensive software, a dedicated analytics team, and expertise they simply don’t have. The truth? Poor data habits cost institutions more than they realize—wasting staff time, eroding trust in decision-making, and limiting their ability to respond to challenges. This article challenges the myth that structured, reproducible data practices are out of reach for smaller colleges and academic units. With insights from Seth Godin, Marcus Lemonis, and Brené Brown, we’ll show you why data isn’t about complexity—it’s about clarity, control, and confidence. And why, if you’re leading an academic institution, fixing your data isn’t a luxury—it’s a survival strategy.

Authors

Affiliations

Scott Moore

Furman University Center for Innovative Leadership

Palmetto Insights

David Eubanks

Furman University Institutional Assessment and Research

1 Introduction: The Data Excuse That’s Holding Higher Ed Back

Let’s be honest: colleges and universities can’t afford bad data—yet many of them operate as if they can.

Ask an academic leader about their institution’s data strategy, and you’ll get one of three responses:

1. “That’s for the big research universities, not us.” (Reality: Data inefficiencies impact every institution.)
   
2. “We just use spreadsheets, it works fine.” (Reality: It’s working until it doesn’t—and then it’s an accreditation or funding nightmare.)
   
3. “We don’t have the staff or budget to fix this.” (Reality: You don’t have the staff or budget not to.)

This mindset is why institutions struggle with enrollment forecasting, accreditation reporting, and student success initiatives. Seth Godin would say the problem isn’t data—it’s fear. Colleges don’t need an army of data scientists; they need a repeatable system that gives them confidence. Marcus Lemonis would remind us that if you don’t know your numbers, you don’t know your institution. And Brené Brown would point out that fear of being unprepared keeps many leaders from fixing their data issues in the first place.

Here’s the truth: Fixing The Data Trap isn’t about resources—it’s about mindset. Let’s break it down.

2 Three Steps That Institutions Need to Take

2.1 Step 1: Stop Thinking of Data as a ‘Big University Problem’

Seth Godin: Fear is the real problem.

Seth Godin talks a lot about the stories we tell ourselves—and higher education tells itself a powerful (and false) story about data: “It’s too complicated, it’s too expensive, it’s not for us.”

Reality check: - You don’t need a dedicated data science department. - You don’t need expensive, enterprise-level software. - You don’t need to be an IT expert.

What you need: A simple, repeatable way to collect, store, and use data without spending weeks rebuilding the same reports.

Next move: Stop making accreditation reports and student success analyses a last-minute scramble. Find one critical metric (like retention rates, course completion trends, or faculty workload balance) and build a structured way to track it consistently.

2.2 Step 2: If You Don’t Know Your Numbers, You Don’t Know Your Institution

Marcus Lemonis: Your data tells the truth—even when you don’t want to hear it.

Marcus Lemonis doesn’t sugarcoat things: institutions that don’t know their numbers make poor decisions.

Here’s what happens when your data is unreliable: - You underreport faculty workload, leading to burnout and attrition. - You fail to predict enrollment shifts, affecting financial sustainability. - You make program decisions based on anecdotes rather than evidence.

Reality check: If your leadership team is making decisions without accurate, up-to-date numbers, you’re not managing an institution—you’re guessing.

Next move: Pick one area—enrollment projections, student retention, or budgeting—and automate data collection instead of relying on manual spreadsheet updates. Even this simple step can save time and prevent errors.

2.3 Step 3: Face the Fear & Take Control

Brené Brown: Data avoidance is a vulnerability issue.

Many academic leaders avoid improving their data systems because they don’t want to admit they have a problem. Brené Brown’s research shows that shame keeps people from taking action—in higher ed, that means:

• Ignoring messy data systems because fixing them feels overwhelming.
• Avoiding assessment reports because they highlight weaknesses.
• Pretending everything is fine because it’s easier than admitting data gaps.

Reality check: No one expects small institutions to have perfect data. But taking the first step is what separates successful colleges from struggling ones.

Next move: Start small. Pick one messy process (student tracking, course demand forecasting, financial aid projections) and make it better. Even a 10% improvement in data accuracy can mean more efficient resource allocation and improved decision-making.

3 Conclusion: You Can’t Afford NOT to Fix Your Data

We get it. Institutions don’t have endless budgets. But here’s the thing: fixing The Data Trap is NOT about spending more—it’s about wasting less.

Stop thinking data is a ‘big university’ luxury.

It’s your survival tool.

Start small, but start now.

Pick one metric, one process, one system—and make it better.

Own the problem, don’t avoid it.

If you don’t fix it, no one else will.

Your Next Step: Take 15 minutes today and ask: What’s one institutional number I rely on, but don’t fully trust? Then, start fixing it. Because in higher education, the difference between sustainability and struggle isn’t luck—it’s clarity.

Let’s get to work.