Optimize the Supply and Stock of Textile Outlets
Challenges
- Achieve the optimal daily distribution of the large number of references
- Maximize turnover
- Minimize stock
- Increase store stock rotation
Okaidi is a ready-to-wear brand specialized in children’s fashion from 0 to 14 years old. Founded in 1996, the flagship structure of the ID Kids group has nearly 1,000 stores in some 50 countries.
The Okaïdi project with Vekia
In order to manage the supply and replenishment of its points of sale, the company decided to use the Vekia solution. This represents between 15 and 20 million stock positions being calculated nightly. To meet this challenge, the Machine Learning algorithms developed by Vekia use all the data deemed relevant, combines them with the parameters integrated by users, and offers suppliers the top recommendations.
By taking into account information such as product life curves, promotions, weather conditions and the location of the company’s warehouses, the solution is designed to “ensure that customers find what they are looking for, and even anticipate what they need”, explains Pierre-Yves Lobry, Director of Management and Flow at IDKids.
Results
2%
inventory reduction
2%
increased turnover
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