A CMO Confidential Interview with Dr. Joel Shapiro, Managerial Economics & Decision Sciences Professor at the Kellogg School of Management at Northwestern, formerly Varicent Chief Analytics Officer. Joel discusses the difference between Data Science and Data Leadership, how many "little, better decisions" aggregate into something meaningful, and why everyone should remember that "data doesn't make decisions." Key topics include: understanding asymmetric risk, how intangibles scuttled a profitable data driven opportunity; why you should never say "because the model says so;" and the need to set error expectations to build trust. Tune in to hear about his research on planning for adversity in the NFL.

📄 Show Description (Apple/Spotify/YouTube)

What happens when a grocery chain discovers a $100M+ opportunity through data science—and still says no?

In this episode of CMO Confidential, host Mike Linton welcomes Dr. Joel Shapiro, Professor at Northwestern’s Kellogg School of Management, to unpack the real-world lessons from “The Grocer Case.” Together, they explore what really kills data-driven decisions at the executive level—and why predictive analytics alone isn’t enough.

From pilot success to boardroom rejection, this episode goes deep on:

• Why organizations reject seemingly obvious, high-ROI data initiatives

• The hidden costs of model opacity, trust, and organizational culture

• What CMOs and business leaders must understand about data leadership

• The critical distinction between data science and data influence

• What the Euro Grocer case reveals about AI adoption challenges

• Lessons on decision asymmetry from child welfare to NFL roster management

If you’re navigating the gap between analytics and execution, this one’s for you.

📍 Hosted by Mike Linton, former CMO of eBay, Best Buy, Farmers Insurance, and Ancestry.com.

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