In a recent discussion about AI adoption, Hassan Ahmed made an observation that stopped me in my tracks:
“Let’s not ignore the fact that the majority of iPhone users nowadays are using only 10-30% of iPhone features that can be gained from low-class phones.”
He’s right. And the same pattern plays out in enterprise technology — only the stakes are measured in millions, not hundreds.
The Data Is Damning
Here’s what the research shows:
- 96% of organizations have shelfware — software they’ve purchased but don’t use
- 44% of SaaS licenses go completely unused
- The average large enterprise runs 367 software applications (Forrester, 2022)
- That number rises to 660 SaaS applications (Zylo, 2023)
- Annual waste: $3.5 million to $99 million — per organization, per year
Organizations buy enterprise Ferraris and drive them like golf carts.
The “Siebel Effect”
This isn’t new. The pattern has a name.
In the early 2000s, Siebel Systems became the poster child for CRM implementation disasters — overaggressive, excessively large projects that never came close to realizing their promised benefits. The “Siebel Effect” became shorthand for the fear of large, expensive, lengthy technology projects that fail to deliver.
But we didn’t learn. We just moved the failure from CRM to ERP to SaaS to AI.
The technology changed. The utilization gap didn’t.
I Wrote About This in 2007
In May 2007, I documented a government-sponsored study that found 75-85% of all initiatives failed — what they called the “valley of death.”
The cause? Siloed planning applied to horizontal challenges:
“The majority of initiatives employ a ‘vertical’ or ‘silo’ approach to ‘horizontal’ challenges (i.e. the needs of individual stakeholders). This silo approach rarely takes into account the different yet interdependent requirements of stakeholders such as the front line buyers or the supplier community.”
The very nature of a silo is that its vertical walls create barriers to collaborative understanding.
Each department buys technology for their vertical needs. No one maps the horizontal interdependencies. The result: 367 applications, 660 SaaS tools, and utilization rates stuck at 20-30%.
The Graph That Explains 35 Years
Two lines. One uncomfortable truth.
- Blue line: Technology capability purchased — rising steeply across every era (ERP, CRM, Suite, Cloud, SaaS, AI, Agentic)
- Burgundy line: Actual feature utilization — flat at 20-30%
The gap between them is the waste. The shelfware. The $99 million annually that disappears into unused licenses and abandoned implementations.
Why Does This Keep Happening?
Because no one asks the readiness question before the purchase decision.
- Vendors are incentivized to sell capability, not utilization
- Consultants are paid to implement, not to assess whether implementation makes sense
- Departments buy in silos without mapping horizontal dependencies
- Executives approve based on features, not absorptive capacity
The technology gets purchased. The organization can’t absorb it. The capability sits unused. The next vendor arrives with the next solution. Repeat.
The iPhone Parallel
Hassan’s iPhone observation is perfect because it captures the psychology:
People buy premium technology believing they’ll use premium features. They don’t. They use 10-30% of capability and pay 100% of the price.
In consumer tech, that’s a personal choice with personal consequences.
In enterprise tech, it’s an organizational pattern with organizational consequences — measured in millions of dollars and decades of accumulated waste.
What Would Change This?
Phase 0: Readiness before purchase.
Before selecting technology, ask:
- Do we understand the horizontal interdependencies across stakeholders?
- Can our organization absorb this capability?
- What’s our realistic utilization target — and how will we measure it?
- Who has walk-away authority if readiness isn’t there?
Until someone gets paid to ask these questions — and act on the answers — the Utilization Gap will persist.
The technology will keep improving. The waste will keep accumulating. And organizations will keep buying Ferraris they drive like golf carts.
Related Reading:
Related Video:
And Another Thing: The Technology That Didn’t Need Phase 0
Just when you thought the case was closed, there’s one more graph that explains everything.
Look at that burgundy line. Seventy percent of critical business processes still run on spreadsheets — despite $1.3 trillion in digital transformation spending between 2020 and 2025 alone.
We’ve invested 35 years and countless billions trying to move organizations off spreadsheets. The line barely moved.
Three Graphs. Three Flat Lines. One Truth.
Three different measurements. Three stubbornly horizontal lines. Thirty-five years of proof that something fundamental isn’t working.
Why Spreadsheets Won
Here’s the question no one asks: Why did spreadsheets succeed where enterprise software keeps failing?
The answer is readiness.
Spreadsheets didn’t require:
- Implementation projects
- Change management consultants
- Executive sponsorship campaigns
- Training programs
- Organizational readiness assessments
They just… worked. Because they matched how people already think — rows, columns, formulas, immediate feedback. They’re horizontal by nature, crossing departmental silos without asking permission. People chose them rather than having them imposed.
Spreadsheets didn’t need a Phase 0 assessment because they matched existing readiness. They met organizations where they were.
Enterprise software fails because it demands readiness change without first assessing whether that change is possible — or even desired.
The Trillion-Dollar Blind Spot
The industry keeps asking: “How do we get people to stop using spreadsheets?”
Wrong question.
The right question: “Why do spreadsheets work when our enterprise software doesn’t?”
The answer has been hiding in plain sight for 35 years. Spreadsheets succeeded because adoption was voluntary, self-service, and matched existing behavior. Enterprise software fails because adoption is mandated, consultant-driven, and demands behavioral transformation without readiness assessment.
Those three flat lines aren’t measuring technology failures. They’re measuring the gap between imposed change and actual readiness.
The Synthesis
Every graph tells the same story:
- 80% failure rate — organizations weren’t ready
- 20-30% utilization — organizations couldn’t absorb the capability
- 70% spreadsheet reliance — organizations defaulted to what matched their actual readiness
The technology was never the problem. The readiness gap was always the problem.
Phase 0 exists because someone has to ask the question before the purchase decision: Can this organization actually absorb what it’s about to buy?
Spreadsheets never needed that question asked. Everything else does.
The Through-Line
The 2007 diagnosis of silo planning. The 2022 data on horizontal sprawl. The 2025 utilization statistics. These connections only become visible when you have 18 years of documented pattern recognition in one place.
This is the power of the Procurement Insights proprietary archives — institutional memory that no analyst report or consulting deck can replicate.
Three graphs. Thirty-five years. One pattern. The evidence was always there — we just needed to see it together.
-30-
A Personal Observation Based On 42 Years In The Industry
The variable that determines success or failure across every technology era.
The Design Intent Test:
Spreadsheets never threatened anyone’s job. They made people better at their jobs. That’s why they won.
The enterprise software industry got it backwards — they sold efficiency through elimination. “Automate the human out of the process.” And for 35 years, humans resisted. Not because they feared technology, but because they recognized the intent.
The AI Parallel
The current AI narrative is “replacement” — and it’s triggering the same resistance. But AI’s true purpose is extension. The AI Whisperer model works because you’re using AI as a thinking partner, not a human substitute.
This could be a fourth graph — or it could be the thesis statement for everything we’re building:
“Technology succeeds when it extends human capability. It fails when it attempts to replace human judgment.”
That’s not just a philosophy. That’s the pattern the three flat lines prove.
Procurement Insights
The Utilization Gap: Why Organizations Buy Ferraris and Drive Them Like Golf Carts
Posted on December 15, 2025
0
In a recent discussion about AI adoption, Hassan Ahmed made an observation that stopped me in my tracks:
He’s right. And the same pattern plays out in enterprise technology — only the stakes are measured in millions, not hundreds.
The Data Is Damning
Here’s what the research shows:
Organizations buy enterprise Ferraris and drive them like golf carts.
The “Siebel Effect”
This isn’t new. The pattern has a name.
In the early 2000s, Siebel Systems became the poster child for CRM implementation disasters — overaggressive, excessively large projects that never came close to realizing their promised benefits. The “Siebel Effect” became shorthand for the fear of large, expensive, lengthy technology projects that fail to deliver.
But we didn’t learn. We just moved the failure from CRM to ERP to SaaS to AI.
The technology changed. The utilization gap didn’t.
I Wrote About This in 2007
In May 2007, I documented a government-sponsored study that found 75-85% of all initiatives failed — what they called the “valley of death.”
The cause? Siloed planning applied to horizontal challenges:
The very nature of a silo is that its vertical walls create barriers to collaborative understanding.
Each department buys technology for their vertical needs. No one maps the horizontal interdependencies. The result: 367 applications, 660 SaaS tools, and utilization rates stuck at 20-30%.
The Graph That Explains 35 Years
Two lines. One uncomfortable truth.
The gap between them is the waste. The shelfware. The $99 million annually that disappears into unused licenses and abandoned implementations.
Why Does This Keep Happening?
Because no one asks the readiness question before the purchase decision.
The technology gets purchased. The organization can’t absorb it. The capability sits unused. The next vendor arrives with the next solution. Repeat.
The iPhone Parallel
Hassan’s iPhone observation is perfect because it captures the psychology:
People buy premium technology believing they’ll use premium features. They don’t. They use 10-30% of capability and pay 100% of the price.
In consumer tech, that’s a personal choice with personal consequences.
In enterprise tech, it’s an organizational pattern with organizational consequences — measured in millions of dollars and decades of accumulated waste.
What Would Change This?
Phase 0: Readiness before purchase.
Before selecting technology, ask:
Until someone gets paid to ask these questions — and act on the answers — the Utilization Gap will persist.
The technology will keep improving. The waste will keep accumulating. And organizations will keep buying Ferraris they drive like golf carts.
Related Reading:
Related Video:
And Another Thing: The Technology That Didn’t Need Phase 0
Just when you thought the case was closed, there’s one more graph that explains everything.
Look at that burgundy line. Seventy percent of critical business processes still run on spreadsheets — despite $1.3 trillion in digital transformation spending between 2020 and 2025 alone.
We’ve invested 35 years and countless billions trying to move organizations off spreadsheets. The line barely moved.
Three Graphs. Three Flat Lines. One Truth.
Three different measurements. Three stubbornly horizontal lines. Thirty-five years of proof that something fundamental isn’t working.
Why Spreadsheets Won
Here’s the question no one asks: Why did spreadsheets succeed where enterprise software keeps failing?
The answer is readiness.
Spreadsheets didn’t require:
They just… worked. Because they matched how people already think — rows, columns, formulas, immediate feedback. They’re horizontal by nature, crossing departmental silos without asking permission. People chose them rather than having them imposed.
Spreadsheets didn’t need a Phase 0 assessment because they matched existing readiness. They met organizations where they were.
Enterprise software fails because it demands readiness change without first assessing whether that change is possible — or even desired.
The Trillion-Dollar Blind Spot
The industry keeps asking: “How do we get people to stop using spreadsheets?”
Wrong question.
The right question: “Why do spreadsheets work when our enterprise software doesn’t?”
The answer has been hiding in plain sight for 35 years. Spreadsheets succeeded because adoption was voluntary, self-service, and matched existing behavior. Enterprise software fails because adoption is mandated, consultant-driven, and demands behavioral transformation without readiness assessment.
Those three flat lines aren’t measuring technology failures. They’re measuring the gap between imposed change and actual readiness.
The Synthesis
Every graph tells the same story:
The technology was never the problem. The readiness gap was always the problem.
Phase 0 exists because someone has to ask the question before the purchase decision: Can this organization actually absorb what it’s about to buy?
Spreadsheets never needed that question asked. Everything else does.
The Through-Line
The 2007 diagnosis of silo planning. The 2022 data on horizontal sprawl. The 2025 utilization statistics. These connections only become visible when you have 18 years of documented pattern recognition in one place.
This is the power of the Procurement Insights proprietary archives — institutional memory that no analyst report or consulting deck can replicate.
Three graphs. Thirty-five years. One pattern. The evidence was always there — we just needed to see it together.
-30-
A Personal Observation Based On 42 Years In The Industry
The variable that determines success or failure across every technology era.
The Design Intent Test:
Spreadsheets never threatened anyone’s job. They made people better at their jobs. That’s why they won.
The enterprise software industry got it backwards — they sold efficiency through elimination. “Automate the human out of the process.” And for 35 years, humans resisted. Not because they feared technology, but because they recognized the intent.
The AI Parallel
The current AI narrative is “replacement” — and it’s triggering the same resistance. But AI’s true purpose is extension. The AI Whisperer model works because you’re using AI as a thinking partner, not a human substitute.
This could be a fourth graph — or it could be the thesis statement for everything we’re building:
That’s not just a philosophy. That’s the pattern the three flat lines prove.
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