AI & Machine Learning


Large distribution company, 30+ years on the market, 42 warehouses, 600 suppliers, 4000+ employees.

To develop a set of algorithms based on the basis of machine learning tools, which will be used to automatically forecast the demand for the purchase of goods in the company's warehouse system.

Project Results
We have developed a model which uses ML-algorithms of time series forecasting. With this model, it is possible to forecast the demand for particular products or groups of product categories on the horizon of 1-2 months.

For different product categories (depending on the demand characteristics), the model uses different algorithms (ARIMA, Exponential smoothing, Prophet, LSTM) and predictor sets.

Business Value
New models improved existing forecast accuracy for 5-10% depending on the region/group of goods.