Predictive analytics in supply chain management

Abstract

For effective management of the organization and making optimal management decisions at all levels, it is necessary to carry out an analysis of the results of activities. Intellectual analytics of big data is a modern trend in the analysis of financial, economic and operational activities. Predictive analytics can be attributed to intellectual analytics of big data, the results of which are formed on the basis of historical facts processed by the system that has undergone machine learning. The direction of predictive analytics is actively developing, including in the field of supply chain management. Predictive analytics can be effectively used at each stage of supply chain management: inventory planning, distribution, demand forecasting, warehousing, production planning, and delivery. This article discusses the use of predictive analytics and the effects of its use to improve the efficiency of supply chain management. As confirmation of this conclusion, the author cites examples of large international companies using forecast analysis to forecast demand for their products, supply planning, pricing, after-sales service planning, etc. The author concludes that it is necessary to introduce forecast analytics systems into the business intelligence system of production and supply of products.