Leveraging Predictive Analytics In Management Information Systems To Enhance Supply Chain Resilience And Mitigate Economic Disruptions

Abstract

The role of management information systems is to act as an enabler for incorporating predictive analytics as a support system in the supply chain. There is now an emphasis on supply chain management. Predictive analytics particularly on the supply chain vulnerability due to the various economic instabilities such as those that result from global calamities, natural disasters and fluctuations in the markets. The integration of two fields of predictive analytics and Management Information Systems. Their functions in managing risks and facilitating flexibility in SCM are discussed. The study uses the case study analysis as well as model simulation. Supply chain data from around the world are processed with complex tools of predictive analytics such as time series analysis, regression analysis, and machine learning. Management Information Systems platforms are developed with an interface that allows data to be fed in real-time and for real-time decision-making. The results indicate that when the Management Information Systems has embedded the predictive analytics. The supply chain vulnerability is significantly reduced and resources effectively be successfully marshalled. The organizations that have adopted this approach seem to have attained higher operational efficiency, less economic loss and the ability to rebound to disruptions. The relevance of using predictive analysis within Management Information Systems as a tactical approach to enhancing strong and flexible supply chain functionality is critical in coping with the complexity of the current global economic environment.