Customer
Large logistics operator. 200+ regional branches, 400 000 sq.meters of warehouses, 10 000+ employees, 3,5M+ clients.
Challenge
Implement a model for forecasting the warehouse stock volume in all departments of the logistics company to increase the accuracy of transport resources planning.
Project Results
Enfint has developed a set of time series models using various approaches (STL + SARIMA, ARIMA+Fourier, TBATS, Prophet, LSTM). The SARIMA model has shown the best results; median weighted percentage error is ~28%. The accuracy of the developed planning algorithm has allowed the planning accuracy to be increased by more than 5% compared to the previously used algorithms.
Large logistics operator. 200+ regional branches, 400 000 sq.meters of warehouses, 10 000+ employees, 3,5M+ clients.
Challenge
Implement a model for forecasting the warehouse stock volume in all departments of the logistics company to increase the accuracy of transport resources planning.
Project Results
Enfint has developed a set of time series models using various approaches (STL + SARIMA, ARIMA+Fourier, TBATS, Prophet, LSTM). The SARIMA model has shown the best results; median weighted percentage error is ~28%. The accuracy of the developed planning algorithm has allowed the planning accuracy to be increased by more than 5% compared to the previously used algorithms.