Big Data can Generate Major Opportunities for Manufacturing Supply Chains

Abstract

Big Data utilization can transform manufacturing supply chains, potentially delivering substantial impacts through better planning, operating, and controlling supply chains. Because modern supply chains are highly data-driven, Big Data technologies can enable data-driven decisions and achieve optimized supply chain performance by integrating data from external and internal environments. Such data come from a multitude of sources, capturing a variety of information types such as market events, climate, traffic, survey results, etc. Optimizing different aspects of supply chains can be complemented with Big Data analyses using descriptive, predictive, and prescriptive techniques. Demand forecasting and planning, inventory optimization and warehousing, and customer management represent well-explored topics, supported by positive findings from recent industry case studies. The data infrastructure is crucial for Big Data applications, especially with respect to integration, preparation, and readiness. Full operational capacity requires a Big Data ecosystem delivering real-time information and analytics. Roadmaps supporting companies along the data-readiness journey enable Big Data utilization for optimized supply chain performance. Supply chains connecting manufacturing sectors with Big Data affected companies – e.g., automobile, pharmaceuticals, and electronics – tend to benefit from deeper, supply-side changes in planning, operating, and controlling through better incorporation of external data. The technology also enables substantial performance improvements in various non-manufacturing supply-chain-related factors such as customer service, sales growth, and capacity allocation. Demand forecasting and planning, inventory optimization and warehousing, and customer service and management are major activities of an integrated supply chain, achieving significant enhancements through Big Data technologies.