Jon, as usual you hit the nail on the head (apologies for the pun). Technology alone is not a successful solution; it has to have fit for purpose and experienced implementation, change management, and process and policy redesign (If needed) to be successful.
We need experienced design and construction managers who understand the need for a variety of skilled craftspeople , not just those adept with a hammer and a nail.
Exactly right, Canda. But here’s the challenge: most organizations hire the ‘experienced design and construction managers’ AFTER they’ve already purchased the hammer.
The sequence is backwards:
1. Buy Data Fabric (the hammer) 2. Hire consultants to implement it 3. Discover the organization isn’t ready 4. Blame ‘change management’
The Hansen Method inverts this:
1. Conduct process archaeology (what’s actually broken?) 2. Agent behavior analysis (are your craftspeople ready?) 3. Organizational readiness assessment (do you have the right skills?) 4. THEN select technology that fits
That’s why the DND project achieved 97.3% delivery – we identified the nails first, then brought the right tools. Most organizations do the opposite and wonder why they join the 80% failure rate.
Your ‘variety of skilled craftspeople’ insight is critical. That’s exactly what agent-based modeling reveals – you need different capabilities at different stages, not just one hammer solution.”
Single instance db, enterprise warehouse, lake – all were expensive cons of gullible IT managers. What is different now? Just another label for the same misguided idea.
Duncan Jones You’re right that we’ve seen this pattern before—single instance DB, enterprise warehouse, data lake. Each promised unified data architecture, each had high failure rates.
But here’s the critical question: Did they fail because the technical concept was flawed, or because organizations weren’t ready to implement them?
Data Fabric’s technical architecture is sound. The problem—same as with data warehouses and lakes—isn’t the horseshoe. It’s the missing nail: organizational readiness, behavioral adoption, governance that actually works in practice.
Gartner keeps designing better horseshoes. The industry keeps missing the nail. That’s why the 80% failure rate never changes, regardless of how sophisticated the technology gets. The cynicism is warranted. But it’s aimed at the wrong target.
I’m curious—given your Forrester experience seeing these cycles, what would you need to see to believe an approach actually breaks the pattern? I’ve got 25 years of documented outcomes, but what is your criteria for success?
Follow-up thought:
Duncan – just saw you’re building Unbiasly. Interesting parallel: you’re addressing bias in talent decisions; I’m addressing behavioral barriers in technology adoption. Both require understanding how humans actually make decisions versus how organizations assume they do.
Your ‘gullible IT managers’ comment resonates—the same cognitive patterns that undermine hiring (confirmation bias, authority bias) drive technology selection. Organizations buy Data Fabric because ‘Gartner recommended it’ without assessing readiness.
How does Nura identify bias patterns? Curious if there’s overlap with the agent behavior modeling I use to predict implementation failures
Canda Rozier, I would love your take on the above as well.
Procurement Insights
Why a Bias-Detection Expert Sees the Same Pattern in Technology Adoption
Posted on September 29, 2025
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Canda Rozier, Procurement Evangelist,CPO ♦ Sourcing Executive ♦ Interim Leader ♦ Procurement Transformation ♦ Thought Leader ♦ Advisor
Jon, as usual you hit the nail on the head (apologies for the pun). Technology alone is not a successful solution; it has to have fit for purpose and experienced implementation, change management, and process and policy redesign (If needed) to be successful.
Jon W. Hansen
Canda Rozier, Procurement Evangelist, great pun 😉
So, how do we change this hammer first mindset?
Canda Rozier, Procurement Evangelist
(trying to continue the building analogy)
We need experienced design and construction managers who understand the need for a variety of skilled craftspeople , not just those adept with a hammer and a nail.
Jon W. Hansen
Exactly right, Canda. But here’s the challenge: most organizations hire the ‘experienced design and construction managers’ AFTER they’ve already purchased the hammer.
The sequence is backwards:
1. Buy Data Fabric (the hammer)
2. Hire consultants to implement it
3. Discover the organization isn’t ready
4. Blame ‘change management’
The Hansen Method inverts this:
1. Conduct process archaeology (what’s actually broken?)
2. Agent behavior analysis (are your craftspeople ready?)
3. Organizational readiness assessment (do you have the right skills?)
4. THEN select technology that fits
That’s why the DND project achieved 97.3% delivery – we identified the nails first, then brought the right tools. Most organizations do the opposite and wonder why they join the 80% failure rate.
Your ‘variety of skilled craftspeople’ insight is critical. That’s exactly what agent-based modeling reveals – you need different capabilities at different stages, not just one hammer solution.”
Duncan Jones • Software company Investor and Advisor
Single instance db, enterprise warehouse, lake – all were expensive cons of gullible IT managers. What is different now? Just another label for the same misguided idea.
Duncan Jones You’re right that we’ve seen this pattern before—single instance DB, enterprise warehouse, data lake. Each promised unified data architecture, each had high failure rates.
But here’s the critical question: Did they fail because the technical concept was flawed, or because organizations weren’t ready to implement them?
Data Fabric’s technical architecture is sound. The problem—same as with data warehouses and lakes—isn’t the horseshoe. It’s the missing nail: organizational readiness, behavioral adoption, governance that actually works in practice.
Gartner keeps designing better horseshoes. The industry keeps missing the nail. That’s why the 80% failure rate never changes, regardless of how sophisticated the technology gets. The cynicism is warranted. But it’s aimed at the wrong target.
I’m curious—given your Forrester experience seeing these cycles, what would you need to see to believe an approach actually breaks the pattern? I’ve got 25 years of documented outcomes, but what is your criteria for success?
Follow-up thought:
Duncan – just saw you’re building Unbiasly. Interesting parallel: you’re addressing bias in talent decisions; I’m addressing behavioral barriers in technology adoption. Both require understanding how humans actually make decisions versus how organizations assume they do.
Your ‘gullible IT managers’ comment resonates—the same cognitive patterns that undermine hiring (confirmation bias, authority bias) drive technology selection. Organizations buy Data Fabric because ‘Gartner recommended it’ without assessing readiness.
How does Nura identify bias patterns? Curious if there’s overlap with the agent behavior modeling I use to predict implementation failures
Canda Rozier, I would love your take on the above as well.
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