It began with the client suspecting their inventory was bloated. They invited us to scrutinize their supply chain.
We started with the shipping lanes — quantifying, in days, how long it took to move raw materials into the plant and finished goods out to customers, including customs processing. We then analyzed historical demand variation. Together, these let us build a predictive model that mapped the tradeoff directly: for any target customer service level, exactly how much working capital it would require.
The client was right. Using the model, we showed them how to cut inventory by 30% — freeing $9M in working capital — while improving service levels.
