Browsing All Posts filed under »Commentary«

Thirty Years of Evidence Says You Can’t Metric or Govern Your Way Out of a Readiness Problem

March 9, 2026

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"The question isn't whether you build an AI factory. It's whether you run Phase 0 before you turn it on."

Is Data Governance Really About Data?

March 9, 2026

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What is the difference between "clean" data and "blind" data?

When Five AI Models Analyze the Same Data Three Months Apart — and Reach the Same Conclusion

March 8, 2026

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Five AI models. Three verification layers. Two graphs. Thirty years of data. One conclusion the industry has overlooked for multiple tech generations.

The Shadows on the Wall: Why the ProcureTech Failure Rate Has Survived Every Technology Era

March 7, 2026

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Thirty years. Five technology eras. One statistic that never moved. The problem was never the technology.

What Mattel, North Carolina, and Virginia’s eVA Knew About AI Failure Before AI Existed

March 6, 2026

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18 years later, Gartner names the AI failure pattern. The Procurement Insights archive documented it in 2008.

The Procurement Intelligence Gap: Why the Industry’s Silence Speaks Louder Than Its Reports

March 6, 2026

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Logically, how many vendors would pay to licence the marketing rights to a bad report?

Understanding the Procurement Industry’s DNA Through the Procurement Insights Archives

March 6, 2026

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Two 2010 predictions on Coupa. One held up. Here's why archives matter.

The Difference Between Longitudinal Depth and Dataset Size in Predicting Successful Initiative Outcomes

March 5, 2026

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When it comes to dataset size versus longitudinal depth, "Broad tells you what exists. Deep tells you what works."

“The Moment You Turn the Hansen Fit Score™ Into a Vendor Sales Tool, You Become Gartner”

March 4, 2026

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We were offered the faster path. We said no. Here's why — and what it means for every procurement leader who relies on analyst scores to make technology decisions.

Understanding the Mathematics Behind Measuring True ProcureTech Implementation Success

March 4, 2026

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Traditional analysts measure one number. The Hansen Fit Score™ measures four. The "one number" math explains the 80% failure rate.