By Jon Hansen | Procurement Insights | December 2025
I recently joined Sam Gupta, Thomas Wieberneit, Ken Gonzalez, and John Santaferraro on the Analysts Gone Wild podcast for what was supposed to be a standard vendor news roundup.
It didn’t stay that way.
Within minutes, the conversation shifted from “what did vendors announce” to “why does none of this matter if organizations can’t absorb it?”
The question I raised:
“The overall truth over the last 30-40 years is that the challenges with implementation have never been about the technology. The technology has always worked. The challenge has always been about the readiness of an organization to absorb that technology and put it to use.”
What followed was a rare moment of analyst consensus: the 80% failure rate isn’t a technology problem. It never was.
Key Moments from the Discussion
The Four-Era Pattern: I walked through the documented failure rates across technology generations — 70-75% in the first application era, 75% in SaaS, 80-85% in AI. The technology improved exponentially. The failure rates climbed.
The Question AI Won’t Ask: I shared the Department of National Defence story — how asking “what time of day do orders come in?” revealed the real problem no automation could solve. Field technicians were sandbagging orders to maximize service calls. The $100 part at 9 AM became $1,000 by 4 PM. No AI would know to ask that question. A human with experience did.
Walk-Away Scores: I proposed a new metric: what percentage of providers would walk away from a sure deal if they knew the client wasn’t ready? What percentage of practitioners would admit “I don’t know what I’m doing”? Instead, everyone smiles at each other while initiatives fail.
The Ferrari Problem: As I noted during the discussion: “Even if you got the parts to assemble it and built the Ferrari, no one would be able to drive it anyway. So what’s the point of assembling it?”
What the Other Analysts Said
The responses validated what the Procurement Insights archives have documented for 18 years:
Thomas Wieberneit: “It’s also a matter of how success gets measured… they are not implemented for the users but for management.”
John Santaferraro: Shared an example of a CIO who required both a technology sponsor AND a business sponsor before any project entered the AI lab — and achieved 50 successful implementations as a result.
Ken Gonzalez: Predicted that 2026 must be the year organizations “meaningfully invest in employees to build an appropriate foundation for leveraging AI” — or face “more of a train wreck than 2025.”
The Uncomfortable Truth
Near the end, I asked the question no one wants to answer:
“How many analyst firms or consultancies or procuretech providers will say, ‘Yeah, let’s delay the sale’?”
The silence was telling.
This is why I’ve been championing the Hansen Fit Score and the concept of walk-away discipline. The ecosystem is structured to proceed regardless of readiness. Revenue is realized at signature, not outcome.
Until that changes, we’ll keep having this same conversation — era after era, technology after technology.
WATCH THE FULL DISCUSSION
Related Reading:
- The Failure Subsidy: Who Finances the Ecosystem?
- The Simple Question That Blew Up 5 of 6 AI Models
- The Prediction Industrial Complex: Gartner’s 2031 Forecast vs. 27 Years of Documented Reality
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Procurement Insights
When Analysts Go Wild: The Conversation the Industry Needs to Have
Posted on December 13, 2025
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By Jon Hansen | Procurement Insights | December 2025
I recently joined Sam Gupta, Thomas Wieberneit, Ken Gonzalez, and John Santaferraro on the Analysts Gone Wild podcast for what was supposed to be a standard vendor news roundup.
It didn’t stay that way.
Within minutes, the conversation shifted from “what did vendors announce” to “why does none of this matter if organizations can’t absorb it?”
The question I raised:
What followed was a rare moment of analyst consensus: the 80% failure rate isn’t a technology problem. It never was.
Key Moments from the Discussion
The Four-Era Pattern: I walked through the documented failure rates across technology generations — 70-75% in the first application era, 75% in SaaS, 80-85% in AI. The technology improved exponentially. The failure rates climbed.
The Question AI Won’t Ask: I shared the Department of National Defence story — how asking “what time of day do orders come in?” revealed the real problem no automation could solve. Field technicians were sandbagging orders to maximize service calls. The $100 part at 9 AM became $1,000 by 4 PM. No AI would know to ask that question. A human with experience did.
Walk-Away Scores: I proposed a new metric: what percentage of providers would walk away from a sure deal if they knew the client wasn’t ready? What percentage of practitioners would admit “I don’t know what I’m doing”? Instead, everyone smiles at each other while initiatives fail.
The Ferrari Problem: As I noted during the discussion: “Even if you got the parts to assemble it and built the Ferrari, no one would be able to drive it anyway. So what’s the point of assembling it?”
What the Other Analysts Said
The responses validated what the Procurement Insights archives have documented for 18 years:
Thomas Wieberneit: “It’s also a matter of how success gets measured… they are not implemented for the users but for management.”
John Santaferraro: Shared an example of a CIO who required both a technology sponsor AND a business sponsor before any project entered the AI lab — and achieved 50 successful implementations as a result.
Ken Gonzalez: Predicted that 2026 must be the year organizations “meaningfully invest in employees to build an appropriate foundation for leveraging AI” — or face “more of a train wreck than 2025.”
The Uncomfortable Truth
Near the end, I asked the question no one wants to answer:
The silence was telling.
This is why I’ve been championing the Hansen Fit Score and the concept of walk-away discipline. The ecosystem is structured to proceed regardless of readiness. Revenue is realized at signature, not outcome.
Until that changes, we’ll keep having this same conversation — era after era, technology after technology.
WATCH THE FULL DISCUSSION
Related Reading:
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