Artificial Intelligence in Supply Chain 4.0: Using Machine Learning in Demand Forecasting

Research in operations has demonstrated the significant role that supply chain management plays in the sustainability of many firms, particularly in the disruptive period we live in today. The accuracy of demand forecasting is a crucial component of supply chain management effectiveness. Therefore, it is necessary to create trustworthy demand forecasting models in order to provide predictions that are better and more accurate. One disruptive tool that has promise for improving demand forecasting models over those now employed in supply chain management is machine learning. This paper’s major goal is to provide a better understanding of how demand volatility affects forecasting models’ accuracy and how it might be modeled in the supply chain. A model using machine learning is deployed to predict customers demand using past orders data. Results shows that the best model is the one elaborated using linear regression with a MAE score of 0.00057 and a RMSE score of 0.0014.