THE IMPACT OF PREDICTIVE ANALYTICS ON JUST-IN-TIME (JIT) INVENTORY SYSTEMS

Abstract

In the rapidly competitive and data-rich business world, companies are constantly being pressured to ensure that they manage their inventory to the maximum and at the minimum cost and waste of operation. Just-in-Time (JIT) inventory systems that attempt to minimize waste through receiving goods once they are required during the production process have been known to be a good inventory management approach. Nevertheless, the conventional JIT systems are very sensitive to the change of demand, supply chain interruptions, and forecasting errors. With the advent of predictive analytics, which uses big data, machine learning, and sophisticated statistical methods, organizations have changed the way they predict demand and manage stocks.