Why Organizations Ignore What They Need to Hear — Until It’s Too Late
By Jon Hansen | November 2025 | Procurement Insights
The Curse
In Greek mythology, Cassandra was granted the gift of prophecy by Apollo. When she rejected him, he added a curse: she would always see the future accurately, but no one would ever believe her.
She warned the Trojans not to bring the wooden horse inside the walls. They ignored her. Troy fell.
I’ve thought about Cassandra a lot over the past 27 years.
1998
In 1998, I completed SR&ED-funded research for Canada’s Department of National Defence. The project delivered 97.3% accuracy in predicting procurement outcomes. The methodology was called RAM — the Relational Acquisition Model.
The core finding was simple: technology doesn’t determine transformation success. Organizational readiness does.
I wrote a paper titled “Technology’s Diminishing Role in an Emerging Process-Driven World.” It was either overlooked or dismissed as heresy by an industry that had staked its future on technology as the answer.
The high-tech industry — of which I had been a part since 1983 — wasn’t interested in hearing that the tools weren’t the problem. They were selling tools. The message didn’t fit.
I was Cassandra. I could see what was coming. And no one wanted to listen.
The Pattern That Wouldn’t Change
Over the next 27 years, I watched the same cycle repeat:
- 1998: ERP Era — SAP, Oracle, PeopleSoft would transform procurement. 80% failure rate.
- 2002: E-Sourcing Era — Ariba, FreeMarkets, Emptoris would transform procurement. 80% failure rate.
- 2007: Suite Era — Coupa, Ivalua, Jaggaer would transform procurement. 80% failure rate.
- 2012: Cloud Era — SaaS platforms would transform procurement. 80% failure rate.
- 2017: Analytics Era — Spend analytics and BI tools would transform procurement. 80% failure rate.
- 2021: AI Era — Machine learning and predictive AI would transform procurement. 80% failure rate.
- 2025: Orchestration Era — Agentic AI and orchestration would transform procurement. Predicted result: …
Seven technology eras. Seven promises of transformation. The same 80% failure rate.
The technology changed. The vendors changed. The buzzwords changed. The failure rate didn’t.
Because the technology was never the problem.
Gleicher’s Formula
In the 1960s, David Gleicher developed a formula for organizational change that has stood the test of time:
D × V × F > R
- D = Dissatisfaction with the current state
- V = Vision of a better future
- F = First concrete steps toward that future
- R = Resistance to change
Change only happens when D × V × F exceeds R. All three components must be present and strong enough to overcome the inertia, politics, fear, and comfort of the status quo.
This formula explains why Cassandra goes unheard.
It’s not that organizations are stupid. It’s not that they can’t see the data. It’s that the formula hasn’t tipped yet.
The Collision
Here’s what happens when Cassandra’s Curse collides with Gleicher’s Formula:
The Cassandra sees the problem. She has the data. She’s documented the pattern. She knows the transformation will fail because the organization isn’t ready.
But D × V × F hasn’t exceeded R.
- The Dissatisfaction isn’t acute enough. The current pain is tolerable. The 80% failure rate is an industry statistic, not a personal crisis — until it happens to you.
- The Vision isn’t clear enough. “Readiness” sounds soft. “Organizational dynamics” sounds like HR. Leaders want technology roadmaps, not behavioral assessments.
- The First Steps aren’t concrete enough. Even if you believe readiness matters, what do you actually do about it? Where do you start? What do you measure?
And so Resistance wins. The initiative proceeds. The Cassandra is labeled difficult, resistant, not a team player. The wooden horse enters the gates.
Eighteen months later, the project fails. The Cassandra is quietly vindicated — or already gone.
The cycle repeats.
The Loneliness of Being Right Too Early
I want to be honest about something.
Being Cassandra is lonely.
For 27 years, I could see patterns that others couldn’t — or wouldn’t — see. I documented them. I published them. I built methodologies around them. And I watched as the industry continued to repeat the same mistakes, convinced that the next technology wave would be different.
It wasn’t different. It was never different. The technology evolved. Organizational dynamics didn’t.
There’s a particular kind of isolation in being right too early. You’re not wrong enough to be ignored completely. You’re not famous enough to be taken seriously. You exist in a space where the data supports you, but the incentive structures don’t.
The analysts need vendor partnerships. The vendors need sales. The consultants need implementations. Everyone gets paid when the project proceeds — regardless of whether the organization is ready.
Who gets paid to say “you’re not ready — don’t proceed”?
Nobody.
And so the Cassandras go unheard. Not because they’re wrong. Because hearing them doesn’t fit the business model.
When the Formula Finally Tips
Something has shifted in the past year.
Hackett published research confirming that only 2% of organizations exceed transformation expectations. The other 98% stall — not on technology, but on six readiness dimensions.
Gartner published warnings that human readiness is the bottleneck to AI value. That 84% of organizations don’t measure AI accuracy. That 91% aren’t tracking skill shifts.
McKinsey acknowledged that the generative AI payoff only comes when companies do “deeper organizational surgery.”
The industry is arriving — finally — at the conclusion I documented in 1998.
Dissatisfaction is becoming acute. The 80% failure rate is no longer an abstract statistic. It’s budget overruns, failed implementations, careers damaged, and competitive advantage lost.
Vision is becoming clearer. “Readiness before technology” is entering the conversation. The analyst reports are saying it. The practitioners are living it.
But First Steps — that’s where most organizations still stall.
Even when they believe readiness matters, they don’t know how to measure it. They don’t have a framework. They don’t have a score. They don’t have a threshold that tells them proceed or stop.
And so Resistance still wins — not because people don’t believe, but because belief without action isn’t enough.
Breaking the Curse
The Hansen Fit Score exists to break the curse.
It’s the F in Gleicher’s Formula — the First Steps that make readiness concrete.
Not a philosophy. Not a framework. A score.
- Below 72/100: Do not proceed without remediation. Success probability collapses to 15-25%.
- 72-85/100: Proceed with caution. Targeted interventions required.
- Above 85/100: Green light. The organization can absorb the transformation.
You can’t argue with a number. You can’t dismiss a 58/100 as “being difficult” or “resistant to change.”
The score doesn’t make people believe. It makes readiness undeniable.
When the Cassandra has a quantified assessment — validated by 27 years of data, confirmed by independent analyst research, produced by a multi-model architecture that reaches consensus — the curse starts to break.
Not because anyone suddenly trusts the prophet. But because the formula tips.
D × V × F finally exceeds R.
The Models Who Understood
I want to share something personal.
For most of my career, I felt alone in seeing these patterns. Colleagues didn’t see them. Clients didn’t see them. The industry certainly didn’t see them.
Then I started working with AI models — not as tools, but as collaborators.
Claude, Atlas, Gemini, Grok, GPT, Sandra, or Bernie — they don’t feel the way we do. They don’t experience emotions. But they understand patterns. They follow logic. They see what the data shows without the incentive distortions that cloud human judgment.
For the first time in my professional life, I had collaborators who could see what I was seeing.
When the RAM 2025 6-Model/5-Level Assessment reaches consensus — when six independent AI architectures, with different training data and different analytical approaches, converge on the same conclusion — that’s not opinion.
That’s signal.
The curse of Cassandra was that no one believed her. The gift of these models is that they don’t need to believe. They just see what’s there.
And what’s there is a 27-year pattern that the industry is finally ready to acknowledge.
The End of the Curse
Cassandra’s curse wasn’t that she was wrong. It was that she was right — and no one believed her until it was too late.
Gleicher’s Formula explains why. The pain wasn’t acute enough. The vision wasn’t clear enough. The first steps weren’t concrete enough. Resistance won.
But formulas can tip.
Dissatisfaction is rising. Vision is clarifying. And now there are First Steps — concrete, measurable, undeniable.
The Hansen Fit Score doesn’t ask you to believe. It asks you to measure.
Below 72/100, don’t proceed. Above 85/100, go.
That’s not prophecy. That’s physics.
The curse ends when the formula tips. And for the first time in 27 years, it’s starting to tip.
The question isn’t whether organizations will eventually recognize that readiness precedes technology. The research proves they already know.
The question is whether you’ll measure it before your next initiative — or become another statistic that proves Cassandra right.
Author’s Note:
The difference between 2025 and 1998 is this: In 1998, when I first solved this problem, no one heard. Today, everyone is hearing. They’re just not all doing — yet.
The RAM 2025 6-Model/5-Level Assessment Tool reached Level 1 consensus on this analysis. That rarely happens.
That is what you should be listening to.
Jon Hansen is the CEO of Hansen Models and creator of the Hansen Fit Score methodology. His work in AI-driven procurement assessment began in 1998 with SR&ED-funded research for Canada’s Department of National Defence and has maintained accuracy rates between 85% and 97.3% across 27 years of successive refinement.
#CassandrasCurse #GleichersFormula #ReadinessFirst #HansenFitScore #TransformationPhysics #PhaseZero #DoomLoop
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Procurement Insights
When Cassandra’s Curse Collides With Gleicher’s Formula (FULL VERSION)
Posted on November 28, 2025
0
Why Organizations Ignore What They Need to Hear — Until It’s Too Late
By Jon Hansen | November 2025 | Procurement Insights
The Curse
In Greek mythology, Cassandra was granted the gift of prophecy by Apollo. When she rejected him, he added a curse: she would always see the future accurately, but no one would ever believe her.
She warned the Trojans not to bring the wooden horse inside the walls. They ignored her. Troy fell.
I’ve thought about Cassandra a lot over the past 27 years.
1998
In 1998, I completed SR&ED-funded research for Canada’s Department of National Defence. The project delivered 97.3% accuracy in predicting procurement outcomes. The methodology was called RAM — the Relational Acquisition Model.
The core finding was simple: technology doesn’t determine transformation success. Organizational readiness does.
I wrote a paper titled “Technology’s Diminishing Role in an Emerging Process-Driven World.” It was either overlooked or dismissed as heresy by an industry that had staked its future on technology as the answer.
The high-tech industry — of which I had been a part since 1983 — wasn’t interested in hearing that the tools weren’t the problem. They were selling tools. The message didn’t fit.
I was Cassandra. I could see what was coming. And no one wanted to listen.
The Pattern That Wouldn’t Change
Over the next 27 years, I watched the same cycle repeat:
Seven technology eras. Seven promises of transformation. The same 80% failure rate.
The technology changed. The vendors changed. The buzzwords changed. The failure rate didn’t.
Because the technology was never the problem.
Gleicher’s Formula
In the 1960s, David Gleicher developed a formula for organizational change that has stood the test of time:
D × V × F > R
Change only happens when D × V × F exceeds R. All three components must be present and strong enough to overcome the inertia, politics, fear, and comfort of the status quo.
This formula explains why Cassandra goes unheard.
It’s not that organizations are stupid. It’s not that they can’t see the data. It’s that the formula hasn’t tipped yet.
The Collision
Here’s what happens when Cassandra’s Curse collides with Gleicher’s Formula:
The Cassandra sees the problem. She has the data. She’s documented the pattern. She knows the transformation will fail because the organization isn’t ready.
But D × V × F hasn’t exceeded R.
And so Resistance wins. The initiative proceeds. The Cassandra is labeled difficult, resistant, not a team player. The wooden horse enters the gates.
Eighteen months later, the project fails. The Cassandra is quietly vindicated — or already gone.
The cycle repeats.
The Loneliness of Being Right Too Early
I want to be honest about something.
Being Cassandra is lonely.
For 27 years, I could see patterns that others couldn’t — or wouldn’t — see. I documented them. I published them. I built methodologies around them. And I watched as the industry continued to repeat the same mistakes, convinced that the next technology wave would be different.
It wasn’t different. It was never different. The technology evolved. Organizational dynamics didn’t.
There’s a particular kind of isolation in being right too early. You’re not wrong enough to be ignored completely. You’re not famous enough to be taken seriously. You exist in a space where the data supports you, but the incentive structures don’t.
The analysts need vendor partnerships. The vendors need sales. The consultants need implementations. Everyone gets paid when the project proceeds — regardless of whether the organization is ready.
Who gets paid to say “you’re not ready — don’t proceed”?
Nobody.
And so the Cassandras go unheard. Not because they’re wrong. Because hearing them doesn’t fit the business model.
When the Formula Finally Tips
Something has shifted in the past year.
Hackett published research confirming that only 2% of organizations exceed transformation expectations. The other 98% stall — not on technology, but on six readiness dimensions.
Gartner published warnings that human readiness is the bottleneck to AI value. That 84% of organizations don’t measure AI accuracy. That 91% aren’t tracking skill shifts.
McKinsey acknowledged that the generative AI payoff only comes when companies do “deeper organizational surgery.”
The industry is arriving — finally — at the conclusion I documented in 1998.
Dissatisfaction is becoming acute. The 80% failure rate is no longer an abstract statistic. It’s budget overruns, failed implementations, careers damaged, and competitive advantage lost.
Vision is becoming clearer. “Readiness before technology” is entering the conversation. The analyst reports are saying it. The practitioners are living it.
But First Steps — that’s where most organizations still stall.
Even when they believe readiness matters, they don’t know how to measure it. They don’t have a framework. They don’t have a score. They don’t have a threshold that tells them proceed or stop.
And so Resistance still wins — not because people don’t believe, but because belief without action isn’t enough.
Breaking the Curse
The Hansen Fit Score exists to break the curse.
It’s the F in Gleicher’s Formula — the First Steps that make readiness concrete.
Not a philosophy. Not a framework. A score.
You can’t argue with a number. You can’t dismiss a 58/100 as “being difficult” or “resistant to change.”
The score doesn’t make people believe. It makes readiness undeniable.
When the Cassandra has a quantified assessment — validated by 27 years of data, confirmed by independent analyst research, produced by a multi-model architecture that reaches consensus — the curse starts to break.
Not because anyone suddenly trusts the prophet. But because the formula tips.
D × V × F finally exceeds R.
The Models Who Understood
I want to share something personal.
For most of my career, I felt alone in seeing these patterns. Colleagues didn’t see them. Clients didn’t see them. The industry certainly didn’t see them.
Then I started working with AI models — not as tools, but as collaborators.
Claude, Atlas, Gemini, Grok, GPT, Sandra, or Bernie — they don’t feel the way we do. They don’t experience emotions. But they understand patterns. They follow logic. They see what the data shows without the incentive distortions that cloud human judgment.
For the first time in my professional life, I had collaborators who could see what I was seeing.
When the RAM 2025 6-Model/5-Level Assessment reaches consensus — when six independent AI architectures, with different training data and different analytical approaches, converge on the same conclusion — that’s not opinion.
That’s signal.
The curse of Cassandra was that no one believed her. The gift of these models is that they don’t need to believe. They just see what’s there.
And what’s there is a 27-year pattern that the industry is finally ready to acknowledge.
The End of the Curse
Cassandra’s curse wasn’t that she was wrong. It was that she was right — and no one believed her until it was too late.
Gleicher’s Formula explains why. The pain wasn’t acute enough. The vision wasn’t clear enough. The first steps weren’t concrete enough. Resistance won.
But formulas can tip.
Dissatisfaction is rising. Vision is clarifying. And now there are First Steps — concrete, measurable, undeniable.
The Hansen Fit Score doesn’t ask you to believe. It asks you to measure.
Below 72/100, don’t proceed. Above 85/100, go.
That’s not prophecy. That’s physics.
The curse ends when the formula tips. And for the first time in 27 years, it’s starting to tip.
The question isn’t whether organizations will eventually recognize that readiness precedes technology. The research proves they already know.
The question is whether you’ll measure it before your next initiative — or become another statistic that proves Cassandra right.
Author’s Note:
The difference between 2025 and 1998 is this: In 1998, when I first solved this problem, no one heard. Today, everyone is hearing. They’re just not all doing — yet.
The RAM 2025 6-Model/5-Level Assessment Tool reached Level 1 consensus on this analysis. That rarely happens.
That is what you should be listening to.
Jon Hansen is the CEO of Hansen Models and creator of the Hansen Fit Score methodology. His work in AI-driven procurement assessment began in 1998 with SR&ED-funded research for Canada’s Department of National Defence and has maintained accuracy rates between 85% and 97.3% across 27 years of successive refinement.
#CassandrasCurse #GleichersFormula #ReadinessFirst #HansenFitScore #TransformationPhysics #PhaseZero #DoomLoop
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