Demand forecasting and inventory management based on AI and BIG DATA

Case

Demand forecasting and inventory management based on AI and BIG DATA

Problem

Current automation systems can help with sales forecasting. However, in order to be competitive in the market, predicting sales is not enough, it is customer demand that must be predicted.

Efficient inventory management is based on it, e.g. production and supply of goods belonging to the “fresh” category.

Solution

AI module for demand forecasting and supply efficiency.

The module allows:

  •  Forecast demand for a specific commodity group;
  • Calculate inventory requirements based on demand variability.

Advantages: Qualitative demand forecasting: the system searches for anomalies using sliding windows, predictive models, hidden Markov models, IRF, recurrent neural networks.

Technology stack

  • Python
  • Pytorch
  • Sklearn

Benefits

  • Reduced dependence on human factors. Even the best manager will not be able to perform equally well for a long period of time and on large amounts of data.
  • Optimized inventory – reduced storage costs.
  • Sustained demand satisfaction – improved customer experience.