Using Machine Learning to Forecast Sales for a Retailer with Prices & Promotions

Using cutting-edge machine learning models, SupChains delivered a forecasting model for an international FMCG reducing its forecast error by 30% compared to the benchmark and cutting its bias to virtually zero. The client used the forecast to plan its 2023 purchasing budget.

Business Situation

The client, an international FMCG retailer operating more than 10,000 stores, enjoys the position of a European leader. They partnered with SupChains to develop a forecasting model for a selection of their most critical products.

Every year by Q2, the retailer must provide purchasing budgets to their suppliers for the upcoming year. To support their purchasing process, they need to forecast the following year’s sales per country per product.

As for most FMCG retailers, part of the clients’ business is promotion-driven: around 20% of its sales are made during promotions. You can see the impact of promotions and pricing on sales in the (anonymized) figure hereunder (Xs highlight promotions).

Forecast Challenge

To generate an accurate forecast per country per product, we decided to work on a forecast per store, week, and product. This level of aggregation would allow the…