More efficient inventory management at Athlon
Read moreThe client,
The challenge,
Inventory management for maintenance and repairs was reaching its limits. Parts were tracked in separate systems and spreadsheets, leaving no one with a complete, up-to-date picture. This led to unnecessary stock, missed reservations and longer turnaround times in the workshop.
Athlon wanted to move beyond gut feeling and make decisions based on reliable, current figures — so the right parts would be available at the right time, without tying up unnecessary capital in stock.
Our solution,
Together, we built a central data platform that brings all the relevant sources — purchasing, workshop and logistics — into one reliable environment. On that foundation, we developed a reservation system and predictive models that show which parts are needed and when.
Now every department has a clear picture of what to expect, and inventory management has shifted from reacting to planning ahead.
The approach,
We worked closely with the people on the workshop floor in short iterations, ensuring the system fitted seamlessly into their daily work. Using Azure, we set up a scalable data pipeline that automatically synchronises the sources, and we use machine learning to predict demand for parts.
The result: fewer lost sales due to unavailable parts, lower inventory costs and a workshop that can move faster.
“More efficient inventory management and a reservation system through our end-to-end data solution”
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