EDITOR’S NOTE: At the end of today’s post, I will be sharing the two links related to what you are about to read below. One is to and article titled Dangerous Supply Chain Myths. The second is to a video that provides a high-level overview of an actual case study that utilized the Metaprise, Agent-based, and Strand Commonality models.
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This 2007 post combined with the transcript creates an absolutely compelling illustration of the “aspirin approach” problem. Here’s why this example is so powerful:
The Perfect “Aspirin Approach” Case Study
The Symptom Everyone Focused On The transcript shows that SHL/MCI was delivering only 51% next-day performance when the contract required 90%. The conventional “aspirin approach” would have been exactly what they initially requested: “automate our system we need to automate” – treat the visible symptom (poor delivery performance) with more technology.
The Root Cause Discovery Instead of prescribing technology aspirin, Hansen asked a simple process archaeology question: “what time of the day do orders come in?” This revealed the real problem wasn’t automation – it was agent behavior conflicts:
Service technicians were incentivized to maximize daily service calls
Policy required ordering parts after each call
The cumbersome system led to “sandbagging” – holding orders until 4 PM
Late orders meant higher prices (Dynamic Flux commodities) and customs delays
Her suggestion about “get your supplier data well structured with legal entities and hierarchy, classification etc.” would have been completely irrelevant to SHL/MCI’s actual problem. Even perfect supplier data wouldn’t have solved:
Technicians batching orders at day’s end
Dynamic pricing throughout the day
Customs clearance delays
Courier coordination issues
The Real Solution: Process Archaeology + Agent-Based Design
Hansen’s approach addressed the human behavioral layer:
Identified competing incentives (service call volume vs. ordering efficiency)
Designed around agent behavior rather than fighting it
Aligned technology with process rather than using technology to define process
The Stunning Results
51% to 97.3% next-day delivery performance
23% sustained cost reduction over seven years
Reduced buyers from 23 to 3
All achieved in three months
Why This Demolishes the “Data Quality First” Argument
The 2007 post emphasizes that “between 2001 and 2005 75 to 85% of all e-procurement initiatives failed to achieve the promised results precisely because they led with technology and data structure rather than process understanding. “Process and not technology is the driving force behind a successful e-procurement initiative” Dangerous Supply Chain Myths (Part 7).
The video transcript proves this principle in action – the breakthrough came from understanding why agents behaved as they did, not from better data about suppliers or more sophisticated analytics dashboards.
Connection to Modern S2P Suite Failures
This 2007 case study perfectly predicts today’s S2P suite challenges. Organizations are still making the same mistake – implementing Coupa expecting 80% spend visibility while ignoring the agent behavior patterns that drive workarounds. Stéphany’s data quality suggestion is 2025’s version of “automate our system” – treating symptoms while ignoring root causes.
The lesson: Process archaeology and agent-based design work. Data quality aspirin doesn’t.
Procurement Insights
Process archaeology and agent-based design work. Data quality aspirin doesn’t.
Posted on September 17, 2025
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EDITOR’S NOTE: At the end of today’s post, I will be sharing the two links related to what you are about to read below. One is to and article titled Dangerous Supply Chain Myths. The second is to a video that provides a high-level overview of an actual case study that utilized the Metaprise, Agent-based, and Strand Commonality models.
30
This 2007 post combined with the transcript creates an absolutely compelling illustration of the “aspirin approach” problem. Here’s why this example is so powerful:
The Perfect “Aspirin Approach” Case Study
The Symptom Everyone Focused On The transcript shows that SHL/MCI was delivering only 51% next-day performance when the contract required 90%. The conventional “aspirin approach” would have been exactly what they initially requested: “automate our system we need to automate” – treat the visible symptom (poor delivery performance) with more technology.
The Root Cause Discovery Instead of prescribing technology aspirin, Hansen asked a simple process archaeology question: “what time of the day do orders come in?” This revealed the real problem wasn’t automation – it was agent behavior conflicts:
Why Stéphany’s Comment Represents Classic Aspirin Thinking
Her suggestion about “get your supplier data well structured with legal entities and hierarchy, classification etc.” would have been completely irrelevant to SHL/MCI’s actual problem. Even perfect supplier data wouldn’t have solved:
The Real Solution: Process Archaeology + Agent-Based Design
Hansen’s approach addressed the human behavioral layer:
The Stunning Results
Why This Demolishes the “Data Quality First” Argument
The 2007 post emphasizes that “between 2001 and 2005 75 to 85% of all e-procurement initiatives failed to achieve the promised results precisely because they led with technology and data structure rather than process understanding. “Process and not technology is the driving force behind a successful e-procurement initiative” Dangerous Supply Chain Myths (Part 7).
The video transcript proves this principle in action – the breakthrough came from understanding why agents behaved as they did, not from better data about suppliers or more sophisticated analytics dashboards.
Connection to Modern S2P Suite Failures
This 2007 case study perfectly predicts today’s S2P suite challenges. Organizations are still making the same mistake – implementing Coupa expecting 80% spend visibility while ignoring the agent behavior patterns that drive workarounds. Stéphany’s data quality suggestion is 2025’s version of “automate our system” – treating symptoms while ignoring root causes.
The lesson: Process archaeology and agent-based design work. Data quality aspirin doesn’t.
REFERENCED LINKS
Procurement Insights Post – Dangerous Supply Chain Myths (Part 7)
Procurement Insights Video – Problem-Solving, Agent-Based Modelling And What A ProcureTech Demo Should Do
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