Big Data and its Impact on Demand-Driven Material Requirements Planning

Abstract

Integrating Big Data into Demand-Driven Material Requirements Planning (DDMRP) has become a game- changer in supply chain management. This study explores Big Data’s significant impact in the context of DDMRP. Big Data, sourced from various channels such as online transactions, sensor data, social interactions, and more, can transform demand forecasting, inventory management, and overall supply chain optimization. By allowing real-time data analysis and predictive modeling, organizations can make informed and agile decisions that drive cost reduction, inventory optimization, and improved customer service. However, implementing Big Data in DDMRP has its challenges, including data security and the need for advanced analytics capabilities. This research delves into the application, benefits, challenges, and impact of Big Data implementation in DDMRP. The study provides valuable insights for organizations seeking to leverage their potential. The findings underscore the significance of Big Data in reshaping supply chain strategies and enhancing the responsiveness of modern businesses in a dynamic market environment. The uniqueness of this paper lies in examining how Big Data, sourced from various channels, can revolutionize demand forecasting, inventory management, and overall supply chain optimization. The research also highlights the challenges of Big Data adoption in DDMRP, including data security and the need for advanced analytics capabilities.