Case Study: Cache Cache achieves faster order fulfillment with AIMMS warehouse optimization

Cache Cache cuts picking distance by 15% with AIMMS

Cache Cache, an international fashion retailer, faced a challenge in its warehouse operations as a 30% annual growth in turnover strained its existing systems. Their warehouse management system could not cope with the increased demand, and order pickers were walking an average of 700 meters per trip. To increase capacity and minimize walking distances, they turned to vendor AIMMS for an optimization solution.

Using the AIMMS platform, Cache Cache built a prescriptive analytics model to optimize order fulfillment by minimizing picking paths. This solution integrated data from their ERP and warehouse systems to determine the most efficient way to combine orders onto picking carts. The implementation resulted in a over 15% reduction in picking path length, a 10% increase in productivity, and a comparable increase in overall warehouse capacity, allowing them to better service growing demand.

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