Posted in: Procurement Insights · CIO Insights · CFO Insights
What This Means for CIOs, CFOs, CDOs, and CPOs
What does this acquisition actually mean beyond another ProcureTech M&A story?
For CIOs, CFOs, CDOs, and CPOs, it raises a more important question than the announcement answers: will better data and more advanced platforms finally translate into sustained outcomes — or will they accelerate the same patterns that have limited returns for decades?
The capability is real. Atlas is the most comprehensive supplier data platform the market has seen. The question is whether the organizational conditions required to make that capability produce the right outcomes — not just clean data, but right data — are in place before deployment.
That is the difference between another system implementation and a measurable business result. And it is the question the acquisition announcement does not address.
In May 2020, I interviewed Stephany Lapierre for my 18 Minutes series. Tealbook was building a universal supplier record — aggregating hundreds of millions of data sources, applying machine learning to normalize and validate supplier information, and delivering a continuously enriched data foundation that organizations could plug into any procurement system. The technology was real. The data problem it addressed was real.
Three years later, in November 2023, I spoke with Stephany again. Tealbook was preparing to launch an entirely new Supplier Data Platform covering 228 million entities across 145 jurisdictions. But in that conversation, Stephany said something that stopped me. She described what she was seeing in the market: organizations that had invested heavily in procurement technology were still struggling. They had built, in her words, “Frankenstein architecture.” Technology that didn’t communicate. Data that didn’t flow. ROI that hadn’t materialized. The dependency on suppliers to update portals had failed. The swivel chair between systems remained.
She was describing the organizational readiness gap in her own language. She didn’t call it that. But that is what she was describing.
Now Supplier.io has acquired Tealbook, launching a combined platform called Atlas covering 225 million global supplier profiles. The announcement describes “clean supplier data” as “the foundation for every sourcing decision, every spend analysis, and every procurement platform.”
It is a genuine capability advance. And it raises the same question the 2020 and 2023 interviews didn’t ask.
What the Interviews Were Designed to Assess
Both conversations were built around the right questions for their moment. Tealbook answered both questions clearly and honestly — the technology was sound, the 2023 pivot to a full Supplier Data Platform reflected genuine market learning, and Stephany’s observation about Frankenstein architecture was not marketing language. It was a practitioner-level diagnosis.
What neither conversation formally asked was the pre-commitment question: are the organizations deploying this capability operating processes that are structurally sound enough to generate the right signals in the first place — not just clean data, but right data?
What the Supplier.io White Paper Already Knew
In early 2024, I conducted research for a white paper on Supplier.io, based on independent interviews with the top 20 percent of supplier diversity performers across 466 companies representing more than $1.4 trillion in collective diverse spend.
The findings were unambiguous. The top 20 percent of performers were not distinguished by which technology platforms they used. They were distinguished by five organizational behaviors:
They were more data-driven — not just in having data, but in the organizational commitment to actively manage it as a daily discipline. They were more proactive — planning further ahead and embedding themselves in the planning process before the budget cycle began. They were more connected to the business — actively linked to sales, finance, operations, and the C-suite. They were more collaborative — building genuine relationships with both diverse suppliers and internal stakeholders. And they were more balanced between data and relationships — understanding that neither alone produced sustained outcomes.
None of these five differentiators are technology choices. Every one of them is an organizational readiness condition.
The research Supplier.io commissioned — and that I conducted — independently confirmed that what separates successful from unsuccessful programs is not platform capability. It is whether the organizational conditions are in place to generate and act on the right signals. That was the answer sitting inside Supplier.io’s own archive before the acquisition was announced.
What Facebook and Apple Already Demonstrated
Before any platform claimed to solve the supplier diversity data problem, two of the most technically sophisticated organizations in the world had already answered the question of what actually makes diversity programs work.
In 2021, I ghostwrote for Jason Trimiew, Director for Global Supplier Diversity at Facebook. His position was unambiguous: “Diversity is more than a program; it is a cultural imperative — it is who we are and what we believe, and as a result, it is much more than a system with a scorecard.” Facebook built an internal Diverse Supplier Locator platform — genuine technology investment — and then made clear that the technology enabled transparency but did not constitute the program.
The behavioral proof was specific. During COVID-19, when organizations across the market extended payment terms to preserve cash, Facebook did the opposite — introducing an early payment plan for diverse suppliers because they understood that a financially weak diverse supplier network was bad for everyone. That decision was not a technology choice. It was an organizational commitment.
In the same 2020 panel I covered, Apple’s Manager of Supplier Diversity, Scott Vowels, offered what may be the most precise diagnosis of the organizational readiness problem in the diversity space. He called it two truths and a lie.
The two truths: diverse suppliers are just as capable and qualified as any other supplier — and can be just as bad as any other supplier. The lie: the persistent belief that you have to sacrifice something on quality, time, or price to engage them.
That lie is the organizational readiness problem stated in practitioner language. Organizations that believe it are organizations whose pre-commitment conditions make meaningful diversity outcomes structurally impossible — regardless of which platform they deploy. Atlas delivers on the data layer. What no platform is designed to do is examine the organizational belief and incentive structures that shape which signals get generated before the data reaches it — the same incentive structure that had DND service technicians sandbagging orders until 4 PM, producing clean data from a structurally broken process. That is what Phase 0™ is designed to assess before the commitment is made.
What the Archive Documented in 2007
The diversity organizational readiness problem is not new. In July 2007, the Procurement Insights archive documented The Greening of Procurement — finding that 91 percent of organizations recognized green procurement as important, yet practical adoption was low because “the translation of policy to practice is mixed and incomplete.” In 2023, writing for Scoutbee on Jamie Crump’s white paper on supplier diversity, the same structural pattern emerged. Wide recognition of importance. Limited sustained adoption. The same gap between policy and practice, sixteen years later.
This is not coincidence. It is strand commonality. The same structural condition — organizational commitment not in place before the initiative is deployed — produces the same outcome across green procurement, supplier diversity, ERP, e-procurement, cloud analytics, and now agentic AI. The technology advances. The organizational condition does not change because no technology asks whether it should.
To better understand how belief and incentive structures influence diversity and technology adoption at a foundational level, John Elkington’s Triple Bottom Line — first articulated in his 1997 book Cannibals With Forks — remains the most durable explanation for why organizations recognize the right thing to do and still fail to build the conditions required to do it: What Does Sultan Al Jaber and John Elkington’s Seminal 1997 Book Have In Common?
It is also worth noting that while supplier diversity is the lens through which this post examines the organizational readiness gap, the challenge extends well beyond it. The same belief and incentive structures that limit diversity program outcomes also produce what the archive calls data delinquency — organizations operating on signals they cannot trust because the processes generating them were never structurally assessed. The DND parent-child SKU problem was not a diversity failure. It was a data integrity failure rooted in the same organizational conditions. For a broader view of how this manifests across procurement data intelligence: Are You A Victim of Data Delinquency?
The Acquisition Arc: 2014 to 2026
2007: Procurement Insights publishes “The Greening of Procurement” — documenting the recognition-to-adoption gap that will reappear in supplier diversity sixteen years later.
2014: Tealbook founded by Stephany Lapierre to solve the supplier data problem that has plagued procurement since the ERP era.
2017–2021: Tealbook raises $78 million across six funding rounds, including a $50 million Series B.
May 2020: First Procurement Insights interview. Tealbook positioned as supplier intelligence aggregator — 18 minutes on the data problem and the technology solution.
2020–2021: Procurement Insights documents Facebook’s Jason Trimiew and Apple’s Scott Vowels on supplier diversity — establishing that organizational commitment, not platform capability, drives outcomes.
November 2023: Second Procurement Insights interview. Stephany describes Frankenstein architecture and undelivered ROI — the organizational readiness problem in practitioner language.
Early 2024: Procurement Insights researches the Supplier.io white paper. Five organizational differentiators. None of them technology choices.
August 2025: Procurement Insights formally asks: is Tealbook technology optimization or methodology-centric? The honest answer: technology optimization.
April 2026: Supplier.io acquires Tealbook. Atlas launches. The question the arc does not answer is the same question none of these moments formally asked before the commitment was made.
The Question the Arc Doesn’t Answer
The success rate line on the thirty-year chart has not moved. Not during ERP. Not during e-procurement. Not during cloud analytics. Not during the first wave of AI.
In February 2026, a RAM 2025™ validation — our multimodel framework that puts the same research question to multiple independent AI reasoning systems simultaneously, treating convergence as a signal of robustness — measured that 72% of ProcureTech vendor logos no longer exist as independent entities — within three percentage points of a longitudinal prediction made by RAM 2025 a year earlier. Tealbook is now in that 72%, in the absorbed category. The full analysis: James, About That 75% Number.
What the top 20% of diversity performers had that the other 80% did not was not better technology. It was organizational readiness — the conditions to generate and act on the right signals in place before deployment. As Facebook and Apple demonstrated independently, and as the 2007 archive documented before any of these platforms existed, the gap between policy recognition and outcome realization has always been organizational, not technical. That is the gap the 72% measures. And it is the same gap the Atlas announcement leaves open.
The Structural Irony
The Supplier.io white paper — research conducted independently by Procurement Insights — identified five organizational differentiators that separate the top 20% of performers from everyone else. None of them are platform features. All of them are pre-commitment organizational conditions.
And now Supplier.io has acquired a technology platform.
The organizations that will deploy Atlas and find themselves in the 80% rather than the 20% will not be there because Atlas failed. They will be there because the organizational conditions that determine whether technology produces sustained outcomes were not formally assessed before the commitment was made. Stephany Lapierre described exactly what those conditions look like when they are absent: Frankenstein architecture, undelivered ROI, portal fatigue, swivel chair between systems. Atlas addresses the data layer. The organizational readiness question remains formally unanswered.
What the Projected Trajectories Tell Us
The chart shows two scenarios from 2026 to 2030.
Without a pre-commitment assessment: the success rate continues its historical pattern — flat at best, declining as AI amplifies whatever signals the existing processes generate. McKinsey’s State of AI 2025 confirms that 51 percent of organizations have already experienced negative impacts from AI use.
With a pre-commitment diagnostic: the five organizational conditions the Supplier.io white paper identified as differentiating the top 20% are assessed and addressed before deployment. The technology then operates on a foundation the research already confirms produces materially better outcomes.
These projections were produced using the same RAM 2025™ validation approach that confirmed the 72% survivability finding. Convergence across independent models is a signal of robustness, not a guarantee of outcome. The prospective case documentation that will confirm or challenge the specific magnitude is what the first engagements produce.
A Note on the Relationship
I have interviewed Stephany Lapierre multiple times over more than five years. I interviewed Supplier.io clients directly. I ghostwrote for Facebook’s Jason Trimiew. I documented Apple’s Scott Vowels. I wrote diversity content for Coupa and Scoutbee. I have been publicly positive about Tealbook’s technology and publicly honest about its structural limitations. This post names the question the announcement leaves open. The Atlas capability is real. The organizational readiness question is also real. Both can be true simultaneously.
For Organizations Evaluating Atlas
If your organization is currently using Tealbook, Supplier.io, or is evaluating the combined Atlas platform, the capabilities described in the announcement are a valid starting point for technology assessment.
What the announcement was not designed to assess is whether your organization’s processes are generating the right signals for Atlas to manage — not just clean data, but data from processes that are structurally sound enough to make that data meaningful.
That is the pre-commitment question. It is still open. And with enterprise AI now running on the data foundation Atlas is designed to provide, the cost of leaving it open has increased.
If your organization is evaluating Atlas — or already using Tealbook or Supplier.io — the 30-minute readiness conversation is where we ask the question the acquisition announcement left open.
Book a readiness conversation: calendly.com/jon-toq/30min
For more information on Hansen Models™: hansenprocurement.com
The Power of the Archive: Understanding the Complexity of the Layers That Collectively Contribute to Assessing Outcomes
For those who want to see how this pattern was validated across multiple domains and years, the reference layers are included below.
Longitudinal record of the same structural pattern across 19 years — none coordinated, all converging.
The archive is not a collection of opinions. It is a longitudinal record of a structural pattern repeating across domains, decades, and organizations — each confirmation from a different direction, none coordinated, all converging on the same finding.
That is what RAM 2025™ treats as a signal worth taking seriously.
That is what Phase 0™ was built to address before the commitment is made.
Phase 0™ · HFS™ Hansen Fit Score™ · RAM 2025™ · Hansen Models™ 18 years · 3,300+ documents · Zero vendor sponsorships · Zero paid analyst relationships
Jon W. Hansen conducted two interviews with Tealbook CEO Stephany Lapierre (May 2020 and November 2023), researched the independent white paper on supplier diversity top performers, ghostwrote for Facebook’s Jason Trimiew, documented Apple’s Scott Vowels, and wrote diversity content for Coupa and Scoutbee. All primary sources referenced in this post are part of the Procurement Insights archive.
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Procurement Insights 
What the 2020 and 2023 Tealbook Interviews Missed — And What the Supplier.io White Paper Already Knew
Posted on April 3, 2026
0
Posted in: Procurement Insights · CIO Insights · CFO Insights
What This Means for CIOs, CFOs, CDOs, and CPOs
What does this acquisition actually mean beyond another ProcureTech M&A story?
For CIOs, CFOs, CDOs, and CPOs, it raises a more important question than the announcement answers: will better data and more advanced platforms finally translate into sustained outcomes — or will they accelerate the same patterns that have limited returns for decades?
The capability is real. Atlas is the most comprehensive supplier data platform the market has seen. The question is whether the organizational conditions required to make that capability produce the right outcomes — not just clean data, but right data — are in place before deployment.
That is the difference between another system implementation and a measurable business result. And it is the question the acquisition announcement does not address.
In May 2020, I interviewed Stephany Lapierre for my 18 Minutes series. Tealbook was building a universal supplier record — aggregating hundreds of millions of data sources, applying machine learning to normalize and validate supplier information, and delivering a continuously enriched data foundation that organizations could plug into any procurement system. The technology was real. The data problem it addressed was real.
Three years later, in November 2023, I spoke with Stephany again. Tealbook was preparing to launch an entirely new Supplier Data Platform covering 228 million entities across 145 jurisdictions. But in that conversation, Stephany said something that stopped me. She described what she was seeing in the market: organizations that had invested heavily in procurement technology were still struggling. They had built, in her words, “Frankenstein architecture.” Technology that didn’t communicate. Data that didn’t flow. ROI that hadn’t materialized. The dependency on suppliers to update portals had failed. The swivel chair between systems remained.
She was describing the organizational readiness gap in her own language. She didn’t call it that. But that is what she was describing.
Now Supplier.io has acquired Tealbook, launching a combined platform called Atlas covering 225 million global supplier profiles. The announcement describes “clean supplier data” as “the foundation for every sourcing decision, every spend analysis, and every procurement platform.”
It is a genuine capability advance. And it raises the same question the 2020 and 2023 interviews didn’t ask.
What the Interviews Were Designed to Assess
Both conversations were built around the right questions for their moment. Tealbook answered both questions clearly and honestly — the technology was sound, the 2023 pivot to a full Supplier Data Platform reflected genuine market learning, and Stephany’s observation about Frankenstein architecture was not marketing language. It was a practitioner-level diagnosis.
What neither conversation formally asked was the pre-commitment question: are the organizations deploying this capability operating processes that are structurally sound enough to generate the right signals in the first place — not just clean data, but right data?
What the Supplier.io White Paper Already Knew
In early 2024, I conducted research for a white paper on Supplier.io, based on independent interviews with the top 20 percent of supplier diversity performers across 466 companies representing more than $1.4 trillion in collective diverse spend.
The findings were unambiguous. The top 20 percent of performers were not distinguished by which technology platforms they used. They were distinguished by five organizational behaviors:
They were more data-driven — not just in having data, but in the organizational commitment to actively manage it as a daily discipline. They were more proactive — planning further ahead and embedding themselves in the planning process before the budget cycle began. They were more connected to the business — actively linked to sales, finance, operations, and the C-suite. They were more collaborative — building genuine relationships with both diverse suppliers and internal stakeholders. And they were more balanced between data and relationships — understanding that neither alone produced sustained outcomes.
None of these five differentiators are technology choices. Every one of them is an organizational readiness condition.
The research Supplier.io commissioned — and that I conducted — independently confirmed that what separates successful from unsuccessful programs is not platform capability. It is whether the organizational conditions are in place to generate and act on the right signals. That was the answer sitting inside Supplier.io’s own archive before the acquisition was announced.
What Facebook and Apple Already Demonstrated
Before any platform claimed to solve the supplier diversity data problem, two of the most technically sophisticated organizations in the world had already answered the question of what actually makes diversity programs work.
In 2021, I ghostwrote for Jason Trimiew, Director for Global Supplier Diversity at Facebook. His position was unambiguous: “Diversity is more than a program; it is a cultural imperative — it is who we are and what we believe, and as a result, it is much more than a system with a scorecard.” Facebook built an internal Diverse Supplier Locator platform — genuine technology investment — and then made clear that the technology enabled transparency but did not constitute the program.
The behavioral proof was specific. During COVID-19, when organizations across the market extended payment terms to preserve cash, Facebook did the opposite — introducing an early payment plan for diverse suppliers because they understood that a financially weak diverse supplier network was bad for everyone. That decision was not a technology choice. It was an organizational commitment.
In the same 2020 panel I covered, Apple’s Manager of Supplier Diversity, Scott Vowels, offered what may be the most precise diagnosis of the organizational readiness problem in the diversity space. He called it two truths and a lie.
The two truths: diverse suppliers are just as capable and qualified as any other supplier — and can be just as bad as any other supplier. The lie: the persistent belief that you have to sacrifice something on quality, time, or price to engage them.
That lie is the organizational readiness problem stated in practitioner language. Organizations that believe it are organizations whose pre-commitment conditions make meaningful diversity outcomes structurally impossible — regardless of which platform they deploy. Atlas delivers on the data layer. What no platform is designed to do is examine the organizational belief and incentive structures that shape which signals get generated before the data reaches it — the same incentive structure that had DND service technicians sandbagging orders until 4 PM, producing clean data from a structurally broken process. That is what Phase 0™ is designed to assess before the commitment is made.
What the Archive Documented in 2007
The diversity organizational readiness problem is not new. In July 2007, the Procurement Insights archive documented The Greening of Procurement — finding that 91 percent of organizations recognized green procurement as important, yet practical adoption was low because “the translation of policy to practice is mixed and incomplete.” In 2023, writing for Scoutbee on Jamie Crump’s white paper on supplier diversity, the same structural pattern emerged. Wide recognition of importance. Limited sustained adoption. The same gap between policy and practice, sixteen years later.
This is not coincidence. It is strand commonality. The same structural condition — organizational commitment not in place before the initiative is deployed — produces the same outcome across green procurement, supplier diversity, ERP, e-procurement, cloud analytics, and now agentic AI. The technology advances. The organizational condition does not change because no technology asks whether it should.
To better understand how belief and incentive structures influence diversity and technology adoption at a foundational level, John Elkington’s Triple Bottom Line — first articulated in his 1997 book Cannibals With Forks — remains the most durable explanation for why organizations recognize the right thing to do and still fail to build the conditions required to do it: What Does Sultan Al Jaber and John Elkington’s Seminal 1997 Book Have In Common?
It is also worth noting that while supplier diversity is the lens through which this post examines the organizational readiness gap, the challenge extends well beyond it. The same belief and incentive structures that limit diversity program outcomes also produce what the archive calls data delinquency — organizations operating on signals they cannot trust because the processes generating them were never structurally assessed. The DND parent-child SKU problem was not a diversity failure. It was a data integrity failure rooted in the same organizational conditions. For a broader view of how this manifests across procurement data intelligence: Are You A Victim of Data Delinquency?
The Acquisition Arc: 2014 to 2026
2007: Procurement Insights publishes “The Greening of Procurement” — documenting the recognition-to-adoption gap that will reappear in supplier diversity sixteen years later.
2014: Tealbook founded by Stephany Lapierre to solve the supplier data problem that has plagued procurement since the ERP era.
2017–2021: Tealbook raises $78 million across six funding rounds, including a $50 million Series B.
May 2020: First Procurement Insights interview. Tealbook positioned as supplier intelligence aggregator — 18 minutes on the data problem and the technology solution.
2020–2021: Procurement Insights documents Facebook’s Jason Trimiew and Apple’s Scott Vowels on supplier diversity — establishing that organizational commitment, not platform capability, drives outcomes.
November 2023: Second Procurement Insights interview. Stephany describes Frankenstein architecture and undelivered ROI — the organizational readiness problem in practitioner language.
Early 2024: Procurement Insights researches the Supplier.io white paper. Five organizational differentiators. None of them technology choices.
August 2025: Procurement Insights formally asks: is Tealbook technology optimization or methodology-centric? The honest answer: technology optimization.
April 2026: Supplier.io acquires Tealbook. Atlas launches. The question the arc does not answer is the same question none of these moments formally asked before the commitment was made.
The Question the Arc Doesn’t Answer
The success rate line on the thirty-year chart has not moved. Not during ERP. Not during e-procurement. Not during cloud analytics. Not during the first wave of AI.
In February 2026, a RAM 2025™ validation — our multimodel framework that puts the same research question to multiple independent AI reasoning systems simultaneously, treating convergence as a signal of robustness — measured that 72% of ProcureTech vendor logos no longer exist as independent entities — within three percentage points of a longitudinal prediction made by RAM 2025 a year earlier. Tealbook is now in that 72%, in the absorbed category. The full analysis: James, About That 75% Number.
What the top 20% of diversity performers had that the other 80% did not was not better technology. It was organizational readiness — the conditions to generate and act on the right signals in place before deployment. As Facebook and Apple demonstrated independently, and as the 2007 archive documented before any of these platforms existed, the gap between policy recognition and outcome realization has always been organizational, not technical. That is the gap the 72% measures. And it is the same gap the Atlas announcement leaves open.
The Structural Irony
The Supplier.io white paper — research conducted independently by Procurement Insights — identified five organizational differentiators that separate the top 20% of performers from everyone else. None of them are platform features. All of them are pre-commitment organizational conditions.
And now Supplier.io has acquired a technology platform.
The organizations that will deploy Atlas and find themselves in the 80% rather than the 20% will not be there because Atlas failed. They will be there because the organizational conditions that determine whether technology produces sustained outcomes were not formally assessed before the commitment was made. Stephany Lapierre described exactly what those conditions look like when they are absent: Frankenstein architecture, undelivered ROI, portal fatigue, swivel chair between systems. Atlas addresses the data layer. The organizational readiness question remains formally unanswered.
What the Projected Trajectories Tell Us
The chart shows two scenarios from 2026 to 2030.
Without a pre-commitment assessment: the success rate continues its historical pattern — flat at best, declining as AI amplifies whatever signals the existing processes generate. McKinsey’s State of AI 2025 confirms that 51 percent of organizations have already experienced negative impacts from AI use.
With a pre-commitment diagnostic: the five organizational conditions the Supplier.io white paper identified as differentiating the top 20% are assessed and addressed before deployment. The technology then operates on a foundation the research already confirms produces materially better outcomes.
These projections were produced using the same RAM 2025™ validation approach that confirmed the 72% survivability finding. Convergence across independent models is a signal of robustness, not a guarantee of outcome. The prospective case documentation that will confirm or challenge the specific magnitude is what the first engagements produce.
A Note on the Relationship
I have interviewed Stephany Lapierre multiple times over more than five years. I interviewed Supplier.io clients directly. I ghostwrote for Facebook’s Jason Trimiew. I documented Apple’s Scott Vowels. I wrote diversity content for Coupa and Scoutbee. I have been publicly positive about Tealbook’s technology and publicly honest about its structural limitations. This post names the question the announcement leaves open. The Atlas capability is real. The organizational readiness question is also real. Both can be true simultaneously.
For Organizations Evaluating Atlas
If your organization is currently using Tealbook, Supplier.io, or is evaluating the combined Atlas platform, the capabilities described in the announcement are a valid starting point for technology assessment.
What the announcement was not designed to assess is whether your organization’s processes are generating the right signals for Atlas to manage — not just clean data, but data from processes that are structurally sound enough to make that data meaningful.
That is the pre-commitment question. It is still open. And with enterprise AI now running on the data foundation Atlas is designed to provide, the cost of leaving it open has increased.
If your organization is evaluating Atlas — or already using Tealbook or Supplier.io — the 30-minute readiness conversation is where we ask the question the acquisition announcement left open.
Book a readiness conversation: calendly.com/jon-toq/30min
For more information on Hansen Models™: hansenprocurement.com
The Power of the Archive: Understanding the Complexity of the Layers That Collectively Contribute to Assessing Outcomes
For those who want to see how this pattern was validated across multiple domains and years, the reference layers are included below.
Longitudinal record of the same structural pattern across 19 years — none coordinated, all converging.
The archive is not a collection of opinions. It is a longitudinal record of a structural pattern repeating across domains, decades, and organizations — each confirmation from a different direction, none coordinated, all converging on the same finding.
That is what RAM 2025™ treats as a signal worth taking seriously.
That is what Phase 0™ was built to address before the commitment is made.
Phase 0™ · HFS™ Hansen Fit Score™ · RAM 2025™ · Hansen Models™ 18 years · 3,300+ documents · Zero vendor sponsorships · Zero paid analyst relationships
Jon W. Hansen conducted two interviews with Tealbook CEO Stephany Lapierre (May 2020 and November 2023), researched the independent white paper on supplier diversity top performers, ghostwrote for Facebook’s Jason Trimiew, documented Apple’s Scott Vowels, and wrote diversity content for Coupa and Scoutbee. All primary sources referenced in this post are part of the Procurement Insights archive.
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