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Luxury sector (B2C)

Context :

Big name in the luxury goods industry, the company has 4 physical stores, as well as an e-commerce site. The main issues for this company are the launching of new products, with the renewal of collections every season, as well as the preparation of Fashion Week several times a year. 

The challenge for us was to be able to accompany them in the launching of new products, by offering them reliable sales forecasts, to optimize the launching and the restocking of products. But also to help them detect the end of life of products, to know when a product should be withdrawn from the catalog. They were also looking to create optimal product assortments to boost their sales.

Objectives :

  •  To have 6-month forecasts, with a weekly granularity, by SKU, i.e. 24,000 time series (product/shop)

  • Reduce inventory

  • Prediction of end-of-life leather goods

  • Product assortment on the e-commerce site

Results :

Thanks to DSales, the company was able to gain 50% reliability on their sales forecasts. As a result, we were able to reduce their inventory by 60% and increase their sales by 10%.

Optical industry (B2C et B2B)

Context :

French eyewear brand, which has 6 stores, and an e-commerce site. Being an eyewear manufacturer, the weather factor is very important, and is therefore sensitive to the seasons. Therefore, the brand wanted to have a solution that would take into account this weather factor, in the sales forecasts. DSales integrates this parameter to have more reliable forecasts.

It also wanted to have a consensus between the supply chain and sales people, so that the forecasts could be refined manually. Therefore, DSales produces forecasts that the supply chain manager can compare with those of the sales representatives, in order to establish the confidence rate of both, and thus obtain personalized forecasts, closer to reality.

Objectives :

  • To have forecasts with a 6-month horizon, with a daily granularity, by SKU and by family, i.e. 200 000 time series (product/shop)

  • Reduce inventory
  • Reduce stock-outs

Résults :

Thanks to DSales, the company was able to gain 30% reliability on their sales forecasts. As a result, we were able to reduce their inventory by 80%, and to reach 0 out-of-stocks.

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