How Data Can Fix Higher-Ed’s Pricing Problem

In this episode of EdTech Connect, host Jeff Dillon sits down with Emily Chase Coleman, CEO and co-founder of HAI Analytics, to explore how data is reshaping higher education strategy.

With over two decades of experience blending social psychology and statistics, Emily shares her journey from academia to entrepreneurship and how HAI’s AI-powered platform helps colleges predict enrollment, optimize financial aid, and improve retention—without overwhelming internal resources.

From challenging outdated tuition models to advocating for test-optional admissions, Emily offers a candid look at the equity gaps in data, the pitfalls of "gut instinct" leadership, and why real-time metrics are non-negotiable in today’s volatile landscape.

Tune in for a conversation that’s equal parts analytical and actionable, and discover how to turn campus data into a competitive advantage.

Key Takeaways:

1. Data Over Gut Instinct:

• Leadership often relies on intuition, but data reveals hidden patterns (e.g., dorm placement impacting retention, course selection signaling struggle).
• Combining quantitative analysis with qualitative insights prevents bias and creates a fuller picture of student behavior.

The High-Discount Model is Unsustainable:

• Rising discount rates are squeezing out middle-income families and straining institutional budgets.
• Schools must articulate their value proposition clearly to justify costs and reduce reliance on discounts to aid enrollment.

Test-Optional Isn’t a Silver Bullet for Equity:

• While test-optional policies reduce bias, holistic reviews can still favor affluent students (e.g., via extracurriculars).
• True equity requires deeper scrutiny of all admissions factors and their socioeconomic implications.

Predictive Modeling Demands Transparency:

• HAI prioritizes open algorithms and explainable results to build trust with presidents and boards.
• AI and machine learning can process vast datasets but require human oversight to avoid flawed conclusions.

Real-Time Data is Non-Negotiable:

• Pandemics and shifting demographics make historical data unreliable.
• Presidents should track enrollment, financial aid, and retention metrics in real time to adapt quickly.

Founding Challenges for Women in EdTech:

• Female founders face disproportionate funding barriers.
• Supporting women-led startups is critical for diversifying innovation in higher ed.

From Consultancy to Self-Sufficiency:

• HAI helps schools build internal data capabilities but remains a partner for ongoing strategy and context.
• The goal is empowerment, not dependency.

 

Ready to rethink your data strategy? Learn more at https://haianalytics.com/ and follow Emily’s work at the intersection of human intuition and artificial intelligence.

 

Find Emily here:

LinkedIn                              

https://www.linkedin.com/in/emily-chase-coleman-95062779/

HAI Analytics

https://haianalytics.com/

 

And find EdTech Connect here:

Web: https://edtechconnect.com/

 

Chapters

• (00:00:00) - AI models have allowed us to take huge data sets
• (00:00:42) - Emily Chase Coleman
• (00:02:00) - What Inspired You to Start HAI Analytics?
• (00:03:03) - Advisers to Colleges and Universities Turn Campus Data Into Stories
• (00:06:00) - Enrollment Dashboards: Should Colleges Buy Them?
• (00:07:53) - Have we Found the Secret to Predicting Student Retention?
• (00:11:34) - Private schools' high-price tuition model
• (00:13:16) - Predicting Future Student Behavior with the Pandemic
• (00:15:06) - Race and Equity in College Admissions
• (00:16:34) - Can HAIS Forecasts Affect Financial Aid Awards?
• (00:18:49) - How do you keep institutions from becoming dependent on your analysts?
• (00:20:17) - WSJDLive: The Use of AI in Business
• (00:22:05) - What Measures Should Colleges Track to Prepare Students?
• (00:24:27) - EdTech Connect