Skip Content
Back to stories

Cache Cache Improves Order Fulfillment with AIMMS-based Warehouse Optimization

Young couple in front of the showcase

CACHE-CACHE logo

About Cache Cache

Cache Cache is an International Fashion retailer and part of the French Groupe Beaumanoir. They operate in 21 countries with 1520 stores, 500 of which are located in France and 1000 in China. They were looking for a warehouse optimization solution to meet increasing demand.

Problem

Cache Cache operates their own semi-automated warehouses to fulfill their stores’ demand. With turnover inChina increasing by 30% every year, shipments experienced a steep increase. This put warehouse operations under heavy stress. Their Best-of-Breed Warehouse Management System could not cope with it this added demand and they needed to increase their capacity to process larger volumes. Moreover, the standard batch picking process they were using reached its limits. In order to pick up goods, each operator would have to travel 700 meters on average. They wanted to minimize the walking distance and optimize the picking path to increase their ability to meet demand.

Solution

Cache Cache decided to add a smart optimization solution to their existing system. They built a model in AIMMS to minimize picking distance taking parameters like picking cart capacity, orders, locations, and picking paths into account. The output of the model enables them to identify which orders can be combined into individual picking carts for optimal fulfillment. Data is fed into AIMMS from the company’s ERP and Warehouse Management System. The optimized result is then printed on a picking label for operators.

Results

The immediate benefit of this optimization solution was a reduction of picking path length of over 15% and a comparable increase in warehouse capacity. Productivity also increased by 10%. This increased their ability to service demand. The team is now planning to use AIMMS to optimize the delivery of e-commerce orders and streamline additional distribution center operations, such as the picking method (massive vs multi-order) and put-away strategy.

In a context of labor cost increases and economic growth, we had to increase our Distribution Centers’ operations productivity. AIMMS provided us a flexible and efficient platform to optimize order fulfillment for stores and e-commerce” – Bruno Alix, Head of IT at Groupe Beaumanoir (Cache-Cache China)

 

Supply Chain Brief