Challenge
No reliable forecasting or replenishment while stock lives outside the tool.
The club equips its teams throughout the season. Its ERP, in place for two years, was meant to support the entire logistics chain. In practice, the teams worked around it.
- Stock movements were tracked in spreadsheets.
- Bills of materials lived on paper.
- End-of-season returns and alerts were handled outside the tool.
Without reliable stock data in a single tool, forecasting demand per item or automating replenishment was impossible.
The need: bring logistics flows back into the tool, starting from the teams' actual work, to lay the foundation for forecasting and replenishment.
Solution
Actual flows first, and adoption as the measure of success.
We treated the club's supply chain as a product, with its users and its indicators. Three principles guide the work.
- Start from the field. We describe stock flows from what the teams actually do, not from the software configuration.
- Allocate the work. We assign each step to the teams, the tool or an AI agent.
- Measure usage. We set adoption indicators before building and report them every week to the sponsor.
Set-up
One day on site, three personas, a first use case.
- Immersion. One day on site with the teams and three personas defined.
- Event storming. Mapping of logistics flows in three lanes: teams, tool, AI agents.
- Adoption indicators. Defined before any build.
- Prioritization. Ranking of use cases with the WSJF method; the first one moves to POC, then to MVP.
- Weekly report. Actual usage of the tool presented every week to the sponsor.
A Diametral Product Delivery team, working closely with the club's teams, from the on-site workshop to the delivery launched at the end of September 2026.
Results
A mapped supply chain and adoption indicators set before the first line of code.
The club has a shared map of its logistics flows, which specifies who handles each step: the teams, the tool or an AI agent. The adoption indicators are set and the priority use case is under construction.
Since the delivery launch at the end of September 2026, the sponsor has tracked the actual usage of the tool every week. The decision to go further will rest on these measurements, not on deployment alone.
Expertises mobilisées
Savoir-faire
- Supply chain
- Inventory management
- Product management
- Adoption
- Event storming
- WSJF prioritization
Technologies
Signature
Four mechanisms that make the difference.
- The field before the tool. Flows start from what the teams do, not from the software configuration.
- Three explicit lanes. We decide step by step what the teams, the tool and the AI agents handle.
- Data before the algorithm. Reliable stock data in the tool is the prerequisite for any forecasting and any automated replenishment.
- The sponsor in the loop. We report usage to the sponsor every week.
For you
A supply chain ready for forecasting and automated replenishment.
This approach addresses four situations.
- Your stock is tracked in spreadsheets rather than in your ERP.
- You want to forecast demand per item and per site, but your stock data is unreliable.
- You are considering automated replenishment and first need to secure the flows.
- You want to steer the adoption of your tools with indicators, not impressions.
We start from your teams' actual work, set the adoption indicators with you before building and report usage to you every week.
