Here is an excerpt from a recent email I received from Staphany Lapierre regarding an upcoming webinar:
Twelve years ago, we set out to help procurement teams gain access to supplier data they could trust. Data with integrity, that is structured in a way that could power systems and decision-making across the enterprise.
Along the way, we expanded from discovery to enriching supplier records with attributes like diversity, building matching capabilities, and partnering closely with global leaders to address what was missing: a reliable supplier data foundation that could anchor records, map relationships, and enable continuous updates wherever teams use supplier data.
That’s why, over the past 18 months, we’ve rebuilt our model from the ground up. It now covers 228M+ entities across 145+ jurisdictions, enriched with registry-level names, aliases, addresses, statuses, company types, and officers.
We’d love to walk you through it.
Webinar: TealBook Platform Update – What’s New
Date/Time: August 20, 2 PM ET
Travis Mattern (our VP of Product) and I will discuss:
- How legal entity resolution now anchors supplier identity across systems, creating a reusable, trusted reference point.
- Parent-child relationship mapping and how it improves hierarchy reporting and enables clearer risk and spend visibility.
- API architecture and enrichment pipelines that keep supplier data current, consistent, and actionable.
- How TealBook now acts as a core data layer for platforms like SAP Ariba, delivering cleaner supplier data that drives better performance and higher ROI.
We’ll also share early outcomes from customers, such as Kraft Heinz and Nasdaq, and how they’re already applying this approach in live environments.
Reserve your spot
Several points stand out in the above text. Still, for the sake of keeping today’s post to a relatively short read, I am going to share the following regarding Stephany’s reference to the “Parent Child Relationship.” More specifically, how it originated in RAM 1998 is now a foundational component of today’s Hansen Fit Score.
THE HANSEN FIT SCORE – 6 MODEL, 5 LEVEL FRAMEWORK (1998 to 2025)
Here’s the Strand-Based Taxonomy Map, which illustrates how core procurement concepts (Strands), such as Supplier, Category Management, Compliance, and others, are surrounded by domain-specific, contextual synonyms.
- Core Procurement Strands (in blue): foundational concepts such as Supplier, Compliance, Intake, etc.
- Contextual Synonyms (in gray): alternate terms used across systems, teams, or tools that often cause semantic misalignment.
The above visualization reveals why the Hansen Fit Score’s 6 Model, 5 Level framework strengthens semantic mapping:
- It anchors taxonomies in organizational meaning rather than generic categories.
- It surfaces contextual synonym drift, helping avoid misalignment between what practitioners say and what systems record.
- It creates cross-strand bridges—enabling procurement teams, IT, and ProcureTech solution providers to speak the same language across silos.
Here is a question I was asked earlier today regarding the above:
Is the 6 Model, 5 Level Hansen Fit Score framework reflective of how you addressed the DND’s Parent-Child SKU nightmare in the late 1990s and early 2000s?
The 6 Model, 5 Level Hansen Fit Score framework is directly reflective of Jon W. Hansen’s approach to tackling the Department of National Defence’s (DND) Parent-Child SKU nightmare in the late 1990s and early 2000s. Contemporary accounts and Hansen’s own documentation show that the foundational principles underpinning the modern HFS framework were present—albeit in an earlier form—during his work to resolve complex SKU data management failures at DND.
How the Framework Reflects Hansen’s DND Approach
- Multi-Dimensional Problem Mapping:
Hansen’s resolution of the DND SKU issue centered on surfacing and aligning diverse stakeholder requirements (logistics, finance, IT, operations), which mirrors the “6 Model” structure that maps requirements across multiple operational and functional domains.
- Progressive Maturity and Customization:
His methodology did not impose a one-size-fits-all solution; instead, it recognized various “levels” of process maturity and capability across DND units—precisely the logic that is formalized in the HFS’s “5 Level” structure.
- Semantic Mapping and Taxonomy:
Hansen’s approach relied heavily on reconciling differing data definitions and business terminologies—what would later become known as semantic mapping—to ensure consistent interpretation of SKUs across multiple systems and teams. This emphasis on a shared, evolving taxonomy is a central tenet of the HFS.
- Continuous Recalibration:
One of Hansen’s key innovations was to build in mechanisms for ongoing feedback and adaptation, allowing the SKU framework to evolve with process changes—reflected in the HFS’s continuous recalibration and maturity tracking.
- Contextual Synonym Drift Management:
Hansen explicitly addressed how similar terms (or SKUs) could mean different things to different groups, and built controls to minimize miscommunication—a challenge that the 6 Model, 5 Level structure is designed to systematically solve.
Evidence from Hansen’s Later Commentaries
In recent retrospectives and briefings (see “Simplifying the TealBook architecture” and “Are You A Victim of Data Delinquency?”), Hansen states that the parent-child SKU model he developed for DND became the prototype for later agent-driven, multi-level fit scoring. He explicitly describes how scalable, context-aware taxonomy and dynamic requirements mapping—now codified in the HFS—emerged from those early government projects.
Conclusion
The 6 Model, 5 Level Hansen Fit Score is not just inspired by, but is a direct evolution of the methodologies Hansen used to conquer the DND Parent-Child SKU nightmare. Its current form formalizes and expands on the same core strategies that proved effective—multi-dimensional mapping, maturity alignment, semantic precision, and adaptive processes—demonstrating a lineage that traces back to that formative work in the late 1990s and early 2000s.
30
BONUS COVERAGE (A WORD ABOUT CONTEXTUAL SYNONYMS AND SYNONYM DRIFT)
“Contextual synonyms are both an opportunity and a risk. The HFS model uses them to audit semantic alignment across strands, detect language-based misfits, and enhance recalibration precision—especially post-implementation. – Jon Hansen
What Are Contextual Synonyms?
These are semantically overlapping terms that serve similar roles in different parts of an organization (or across organizations), but are not standardized. They are not generic synonyms (like a thesaurus entry); they are use-case-bound terms that carry domain-specific meaning.
Why Are Contextual Synonyms Important in the HFS Framework?
Recalibration Sensitivity: HFS recalibration depends on subtle shifts in meaning. If two systems report on “Vendor Status” vs. “Partner Fit,” they may diverge without synonym tracing.
Strand Alignment: They help the HFS identify whether teams are talking about the same concepts using different words—crucial for effective Strand Commonality auditing.
Agent Interoperability: In agent-based modeling, systems and users must share aligned meanings; synonyms disrupt that unless mapped semantically.
Metaprise Integration: Across the enterprise ecosystem (Metaprise), these synonyms must be harmonized for workflows, intake, ESG, and analytics to function seamlessly.
Challenges with Contextual Synonym Drift
The Hansen Fit Score (HFS) addresses contextual synonym drift through a multilayered diagnostic and calibration framework that ensures semantic consistency across people, processes, platforms, and performance metrics. The original framework was RAM 1998. Today, that framework has evolved into a 6 Model, 5 Level framework – RAM 2025.
***ALMOST FORGOT: The reason why I like the potential of a Tealbook and ApolloRise “teaming agreement”- or at least a discussion between the two providers is that, based on a preliminary 6 Model, Level 1 assessment, there appears to be some unique and essential synergies that can benefit procurement practitioner clients. In short, it is worth a look, so have a coffee together.
Procurement Insights
Why I Like The Potential Of A Tealbook And ApolloRise Collaborative Partnership For Procurement Practitioners***
Posted on July 26, 2025
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Here is an excerpt from a recent email I received from Staphany Lapierre regarding an upcoming webinar:
Twelve years ago, we set out to help procurement teams gain access to supplier data they could trust. Data with integrity, that is structured in a way that could power systems and decision-making across the enterprise.
Along the way, we expanded from discovery to enriching supplier records with attributes like diversity, building matching capabilities, and partnering closely with global leaders to address what was missing: a reliable supplier data foundation that could anchor records, map relationships, and enable continuous updates wherever teams use supplier data.
That’s why, over the past 18 months, we’ve rebuilt our model from the ground up. It now covers 228M+ entities across 145+ jurisdictions, enriched with registry-level names, aliases, addresses, statuses, company types, and officers.
We’d love to walk you through it.
Webinar: TealBook Platform Update – What’s New
Date/Time: August 20, 2 PM ET
Travis Mattern (our VP of Product) and I will discuss:
We’ll also share early outcomes from customers, such as Kraft Heinz and Nasdaq, and how they’re already applying this approach in live environments.
Reserve your spot
Several points stand out in the above text. Still, for the sake of keeping today’s post to a relatively short read, I am going to share the following regarding Stephany’s reference to the “Parent Child Relationship.” More specifically, how it originated in RAM 1998 is now a foundational component of today’s Hansen Fit Score.
THE HANSEN FIT SCORE – 6 MODEL, 5 LEVEL FRAMEWORK (1998 to 2025)
Here’s the Strand-Based Taxonomy Map, which illustrates how core procurement concepts (Strands), such as Supplier, Category Management, Compliance, and others, are surrounded by domain-specific, contextual synonyms.
The above visualization reveals why the Hansen Fit Score’s 6 Model, 5 Level framework strengthens semantic mapping:
Here is a question I was asked earlier today regarding the above:
Is the 6 Model, 5 Level Hansen Fit Score framework reflective of how you addressed the DND’s Parent-Child SKU nightmare in the late 1990s and early 2000s?
The 6 Model, 5 Level Hansen Fit Score framework is directly reflective of Jon W. Hansen’s approach to tackling the Department of National Defence’s (DND) Parent-Child SKU nightmare in the late 1990s and early 2000s. Contemporary accounts and Hansen’s own documentation show that the foundational principles underpinning the modern HFS framework were present—albeit in an earlier form—during his work to resolve complex SKU data management failures at DND.
How the Framework Reflects Hansen’s DND Approach
Hansen’s resolution of the DND SKU issue centered on surfacing and aligning diverse stakeholder requirements (logistics, finance, IT, operations), which mirrors the “6 Model” structure that maps requirements across multiple operational and functional domains.
His methodology did not impose a one-size-fits-all solution; instead, it recognized various “levels” of process maturity and capability across DND units—precisely the logic that is formalized in the HFS’s “5 Level” structure.
Hansen’s approach relied heavily on reconciling differing data definitions and business terminologies—what would later become known as semantic mapping—to ensure consistent interpretation of SKUs across multiple systems and teams. This emphasis on a shared, evolving taxonomy is a central tenet of the HFS.
One of Hansen’s key innovations was to build in mechanisms for ongoing feedback and adaptation, allowing the SKU framework to evolve with process changes—reflected in the HFS’s continuous recalibration and maturity tracking.
Hansen explicitly addressed how similar terms (or SKUs) could mean different things to different groups, and built controls to minimize miscommunication—a challenge that the 6 Model, 5 Level structure is designed to systematically solve.
Evidence from Hansen’s Later Commentaries
In recent retrospectives and briefings (see “Simplifying the TealBook architecture” and “Are You A Victim of Data Delinquency?”), Hansen states that the parent-child SKU model he developed for DND became the prototype for later agent-driven, multi-level fit scoring. He explicitly describes how scalable, context-aware taxonomy and dynamic requirements mapping—now codified in the HFS—emerged from those early government projects.
Conclusion
The 6 Model, 5 Level Hansen Fit Score is not just inspired by, but is a direct evolution of the methodologies Hansen used to conquer the DND Parent-Child SKU nightmare. Its current form formalizes and expands on the same core strategies that proved effective—multi-dimensional mapping, maturity alignment, semantic precision, and adaptive processes—demonstrating a lineage that traces back to that formative work in the late 1990s and early 2000s.
30
BONUS COVERAGE (A WORD ABOUT CONTEXTUAL SYNONYMS AND SYNONYM DRIFT)
“Contextual synonyms are both an opportunity and a risk. The HFS model uses them to audit semantic alignment across strands, detect language-based misfits, and enhance recalibration precision—especially post-implementation. – Jon Hansen
What Are Contextual Synonyms?
These are semantically overlapping terms that serve similar roles in different parts of an organization (or across organizations), but are not standardized. They are not generic synonyms (like a thesaurus entry); they are use-case-bound terms that carry domain-specific meaning.
Why Are Contextual Synonyms Important in the HFS Framework?
Recalibration Sensitivity: HFS recalibration depends on subtle shifts in meaning. If two systems report on “Vendor Status” vs. “Partner Fit,” they may diverge without synonym tracing.
Strand Alignment: They help the HFS identify whether teams are talking about the same concepts using different words—crucial for effective Strand Commonality auditing.
Agent Interoperability: In agent-based modeling, systems and users must share aligned meanings; synonyms disrupt that unless mapped semantically.
Metaprise Integration: Across the enterprise ecosystem (Metaprise), these synonyms must be harmonized for workflows, intake, ESG, and analytics to function seamlessly.
Challenges with Contextual Synonym Drift
The Hansen Fit Score (HFS) addresses contextual synonym drift through a multilayered diagnostic and calibration framework that ensures semantic consistency across people, processes, platforms, and performance metrics. The original framework was RAM 1998. Today, that framework has evolved into a 6 Model, 5 Level framework – RAM 2025.
***ALMOST FORGOT: The reason why I like the potential of a Tealbook and ApolloRise “teaming agreement”- or at least a discussion between the two providers is that, based on a preliminary 6 Model, Level 1 assessment, there appears to be some unique and essential synergies that can benefit procurement practitioner clients. In short, it is worth a look, so have a coffee together.
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