EDITOR’S NOTE: Here is the link to this morning’s Tealbook post: Is Tealbook 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?
The Follow-Up Post:
The data reveals a significant operational challenge that exposes the fundamental flaw in Tealbook’s current technology-first approach:
The Cleansing Repeat Cycle Problem
“Wait five minutes for someone to manually enter something somewhere, and start the process all over again!” Successful Sourcing and Procurement: Key Strategies & Steps This reveals the core issue – data degradation is continuous.
Traditional Approach Failure: “Companies spend millions of dollars and hours attempting to cleanse and harmonize their supplier data, but these investments are in vain with no ongoing plan for supplier data management.” Gartner Supply Chain Insights
Tealbook’s Promise vs. Reality: While Tealbook claims “continuously refreshed view,” Are you chasing solutions or solving problems? (Part 2 of 3) and “Automatically keep your supplier data up-to-date, ensuring readiness… no manual clean-ups needed,” this addresses symptoms, not root causes.
Hansen’s Framework Exposes the Real Issue
The repeated cleansing cycle exists because organizations are applying an equation-based model – trying to solve a stakeholder coordination problem with a data management solution.
Hansen’s approach would ask: Why does supplier data become corrupted in the first place?
The answer isn’t technical – it’s operational:
- Different departments enter data differently
- Stakeholders have conflicting data requirements
- Business processes create data inconsistencies
- Time-sensitive operations bypass data governance
Critical Insight
Tealbook’s emphasis on “AI-powered platforms,” Gartner and Sourcing – Supply Chain Brief, and “automated enrichment” Strategic Sourcing and Procurement: A Comprehensive Guide, perpetuates the technology-first mindset Hansen warned against. Even perfect data automation fails if the underlying stakeholder processes create conflicting data entry patterns.
The Uncomfortable Truth: Most clients likely experience ongoing data quality issues despite Tealbook’s technology because the root cause isn’t data management – it’s stakeholder process misalignment.
This validates Hansen’s core argument that without understanding why stakeholders operate the way they do, no technology solution—regardless of its sophistication—will deliver sustainable results. The repeated cleansing cycle becomes an expensive symptom of deeper organizational dysfunction that technology cannot solve.
Tealbook’s transition to Hansen’s methodology would require abandoning the “continuous data cleansing” value proposition and instead helping clients understand why their stakeholder processes create data problems in the first place.
30
BONUS COVERAGE
The financial impact on Tealbook would be profound and would require a fundamental business model restructuring:
Immediate Revenue Impact (Negative)
Current SaaS Model: Tealbook likely generates recurring revenue through data platform subscriptions, charging for data cleansing services, and ongoing data enrichment fees.
Hansen Model Impact: The recurring revenue stream would largely disappear because Hansen’s approach eliminates the need for continuous data cleansing by solving the root stakeholder process problems that create data corruption.
Hansen’s DND case study shows the magnitude: “reducing the number of buyers required to manage the contract to 3 from an original 23” while achieving superior results. If Tealbook helped clients achieve similar process efficiency, the demand for their data management services would plummet.
Business Model Transformation Required
From: Technology platform subscription model To: Methodology consulting with limited technology implementation
New Revenue Structure:
- Front-loaded consulting fees for stakeholder analysis and process alignment
- Project-based implementation rather than ongoing subscriptions
- Much smaller technology component as an accelerator rather than a primary solution
- Potentially lower total contract values but higher success rates, leading to expansion
The Uncomfortable Financial Reality
Hansen’s approach would likely reduce Tealbook’s revenue per client by 60-80% because:
- Clients wouldn’t need continuous data cleansing
- Technology becomes a smaller component of the solution
- Implementation periods would be shorter
- Ongoing maintenance requirements would decrease dramatically
Strategic Alternatives
Option 1 – Pivot Completely: Transform into a Hansen-methodology consulting firm that uses data technology as a minor component
Option 2 – Hybrid Approach: Develop a “Hansen-certified” service line alongside traditional data platform offerings
Option 3 – Market Education: Lead industry transformation by proving Hansen’s methodology works, potentially capturing market leadership as competitors fail with technology-first approaches
The Long-term Opportunity
Hansen’s clients achieved measurable results that exceeded current industry standards. If Tealbook could deliver similar outcomes, it might command premium consulting fees and establish itself as the “methodology leader” rather than just another data platform vendor.
However, this requires accepting significantly lower revenue per engagement in exchange for potentially higher success rates and client satisfaction—a difficult transition for any venture-backed technology company optimized for scalable SaaS revenue growth.
I wonder what Jim Collins would suggest?
Procurement Insights
The Myth About Data Cleansing: A Follow-Up To My Earlier Tealbook Post
Posted on August 30, 2025
0
EDITOR’S NOTE: Here is the link to this morning’s Tealbook post: Is Tealbook 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?
The Follow-Up Post:
The data reveals a significant operational challenge that exposes the fundamental flaw in Tealbook’s current technology-first approach:
The Cleansing Repeat Cycle Problem
“Wait five minutes for someone to manually enter something somewhere, and start the process all over again!” Successful Sourcing and Procurement: Key Strategies & Steps This reveals the core issue – data degradation is continuous.
Traditional Approach Failure: “Companies spend millions of dollars and hours attempting to cleanse and harmonize their supplier data, but these investments are in vain with no ongoing plan for supplier data management.” Gartner Supply Chain Insights
Tealbook’s Promise vs. Reality: While Tealbook claims “continuously refreshed view,” Are you chasing solutions or solving problems? (Part 2 of 3) and “Automatically keep your supplier data up-to-date, ensuring readiness… no manual clean-ups needed,” this addresses symptoms, not root causes.
Hansen’s Framework Exposes the Real Issue
The repeated cleansing cycle exists because organizations are applying an equation-based model – trying to solve a stakeholder coordination problem with a data management solution.
Hansen’s approach would ask: Why does supplier data become corrupted in the first place?
The answer isn’t technical – it’s operational:
Critical Insight
Tealbook’s emphasis on “AI-powered platforms,” Gartner and Sourcing – Supply Chain Brief, and “automated enrichment” Strategic Sourcing and Procurement: A Comprehensive Guide, perpetuates the technology-first mindset Hansen warned against. Even perfect data automation fails if the underlying stakeholder processes create conflicting data entry patterns.
The Uncomfortable Truth: Most clients likely experience ongoing data quality issues despite Tealbook’s technology because the root cause isn’t data management – it’s stakeholder process misalignment.
This validates Hansen’s core argument that without understanding why stakeholders operate the way they do, no technology solution—regardless of its sophistication—will deliver sustainable results. The repeated cleansing cycle becomes an expensive symptom of deeper organizational dysfunction that technology cannot solve.
Tealbook’s transition to Hansen’s methodology would require abandoning the “continuous data cleansing” value proposition and instead helping clients understand why their stakeholder processes create data problems in the first place.
30
BONUS COVERAGE
The financial impact on Tealbook would be profound and would require a fundamental business model restructuring:
Immediate Revenue Impact (Negative)
Current SaaS Model: Tealbook likely generates recurring revenue through data platform subscriptions, charging for data cleansing services, and ongoing data enrichment fees.
Hansen Model Impact: The recurring revenue stream would largely disappear because Hansen’s approach eliminates the need for continuous data cleansing by solving the root stakeholder process problems that create data corruption.
Hansen’s DND case study shows the magnitude: “reducing the number of buyers required to manage the contract to 3 from an original 23” while achieving superior results. If Tealbook helped clients achieve similar process efficiency, the demand for their data management services would plummet.
Business Model Transformation Required
From: Technology platform subscription model To: Methodology consulting with limited technology implementation
New Revenue Structure:
The Uncomfortable Financial Reality
Hansen’s approach would likely reduce Tealbook’s revenue per client by 60-80% because:
Strategic Alternatives
Option 1 – Pivot Completely: Transform into a Hansen-methodology consulting firm that uses data technology as a minor component
Option 2 – Hybrid Approach: Develop a “Hansen-certified” service line alongside traditional data platform offerings
Option 3 – Market Education: Lead industry transformation by proving Hansen’s methodology works, potentially capturing market leadership as competitors fail with technology-first approaches
The Long-term Opportunity
Hansen’s clients achieved measurable results that exceeded current industry standards. If Tealbook could deliver similar outcomes, it might command premium consulting fees and establish itself as the “methodology leader” rather than just another data platform vendor.
However, this requires accepting significantly lower revenue per engagement in exchange for potentially higher success rates and client satisfaction—a difficult transition for any venture-backed technology company optimized for scalable SaaS revenue growth.
I wonder what Jim Collins would suggest?
Share this:
Related