Browsing All Posts filed under »Commentary«

Stuck on Your RFP Decision? Your Foundation May Be the Problem—Not Your Vendors

October 10, 2025

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ProcureTech Rule # 1: Technology changes; failure patterns don't.

Why 95% of ProcureTech AI Implementations Fail—And How to Beat the Odds

October 9, 2025

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"The Mirror No One's Looking At: How Ecosystem Multiplication Explains—And Fixes—The 80% Failure Rate"

Behind the curtain of the DPW car show post (the working mechanics)

October 9, 2025

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How to translate ProcureTech AI theory into real-world, working mechanics.

DPW Showcases the Body — IBM and Anthropic Just Introduced the Engine

October 9, 2025

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Innovation looks exciting from the showroom floor, but without governance, interoperability, and readiness, procurement doesn’t move.

From AI Headlines to Readiness Reality: What IBM + Anthropic Means for Procurement

October 8, 2025

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In the world of procurement, why do practitioners, providers, and analyst firms have a Hansen Fit Score?

What are ProcureTech solution silos, and why must we break them down to succeed?

October 8, 2025

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When it comes to ProcureTech selection and implementation why do we have to stop looking at the trees and start managing the forest?

What is measurable alignment when selecting a ProcureTech solution provider?

October 8, 2025

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What is Technical Capability, Behavioral Alignment, and Organizational Readiness, and why is it important with ProcureTech selection?

Coupa Acquisition Of Scoutbee And What It Means To TealBook And The Market In General

October 8, 2025

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A deeper assessment of the Coupa acquisition of Scoutbee - what does it reveal and why?

Deloitte just proved why the current tech-first approach to ProcureTech AI selection and implementation will continue to fail for most organizations

October 7, 2025

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How a Deloitte $440K report demonstrates why most tech-led ProcureTech AI initiatives will fail.

Pattern Recognition, Not Prophecy: Why I See What Others Miss (And My Certa/Vertice Assessment)

October 7, 2025

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Challenge the norm. Get it right over being right. Document what others won't. This is how pattern recognition (and AI) actually works.