Below is the response by Stephany Lapierre to what has been a most necessary discussion regarding the difference between a technology optimization model for improving the way the world does work, versus a methodology-centric model that focuses on building for the way the world should work.

I will first share with you the series of comments Stephany was kind enough to share on LinkedIn. I will then share the results of the RAM 2025 Multi-Model/Level 1 Assessment.

RAM 2025 ASSESSMENT (SUMMARIES)

MODEL 5/Level 1

Final Verdict

Stephany Lapierre’s responses confirm that TealBook is indeed a technology optimization model focused on improving how the world currently does work, rather than building for how the world should work. Her sophisticated defense of this approach, while technically impressive, validates Hansen’s core critique that the procurement technology industry perpetuates problems through feature-driven solutions rather than solving them through methodology transformation.

The $30-32M cost she quantifies will persist until organizations adopt Hansen’s methodology-first approach – making TealBook’s current strategy a sophisticated form of expensive incrementalism rather than transformative solution.

MODEL 1/Level 1

Bottom line: Stephany’s responses make a strong, credible case for a tech-optimized data foundation. To meet Hansen’s bar, anchor that foundation inside a methodology with gates and strand outcomes—then the platform stops merely improving today’s work and starts reshaping how the work should run.

MODEL 2/Level 1

In contrast, Hansen’s methodology-centric model (e.g., “building for the way the world should work”) starts with outcomes (e.g., DND’s 85% reduction via PCF/SGS, solving “why data becomes corrupted” through stakeholder alignment), not tech features. Lapierre’s “without… data foundation, organizations fall back into costly cycles” echoes Hansen’s myths but attributes persistence to lacking TealBook-like tech, not flawed approaches—validating Deloitte’s warning (Page 16: GenAI risks from poor data/governance, needing holistic change for payouts).

Bottom line: Lapierre’s responses are credible and customer-focused, effectively defending TealBook’s niche, but they highlight the tech-methodology divide Hansen critiques—her model optimizes the present (incremental wins like leverage/Prevention), while Hansen’s transforms for the future (systemic prevention via redesign). This debate underscores Deloitte’s call for “human-centered” bets (Page 8) to bridge the gap.

MODEL 3/Level 1

Conclusion

Stephany Lapierre and TealBook are advocating a technology optimization solution that makes current systems work better, not a methodology-centric revolution that fundamentally alters how data systems are conceived and constructed. While TealBook offers important operational value, the deep and persistent supplier data issues identified by Procurement Insights and Hansen’s methodology require a transformation of business processes at the core, beyond what technology alone can deliver.

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BONUS COVERAGE – IMPACT OF THE OPTIMIZATION MODEL V. THE METHODOLOGY MODEL

MODEL 1

KPI impacts by time window

Why the patterns differ

• TealBook tech-optimization: rapid early gains (dedupe + enrichment + basic hierarchy) drive AP and data-ops metrics, but without a method that changes how work flows (strand by strand, with gates), the organization keeps fixing symptoms and hits a plateau.
• Hansen methodology: slightly slower start (you introduce agent/strand maps, sprint-gated proof, evented coexistence), then benefits compound because every new strand reuses the operating method, not just the tool.

MODEL 5