Big Data Analysis and Machine Learning for Efficient Supply Chain Management

The increased use of digital technology in business and industry has contributed significantly to the recent fast expansion of the supply chain ecosystem. It would be an understatement to claim that machine learning is not central to this shift. The way businesses operate has been profoundly altered as a result of the advent of these new modes of communication, the automation of formerly manual operations, the increased significance of digital records, etc. In an era of decreasing profit margins and more discriminating clients, supply chain management is becoming increasingly vital as businesses attempt to differentiate themselves. Management and optimization of the Supply Chain at all levels based on data. Decision-making in the supply chain may benefit from machine learning approaches in a data-rich setting. These days, no business can afford to ignore Machine Learning technology since they are everywhere. In highly competitive marketplaces, this fact stands out like a sore thumb. In this research, we investigate the feasibility of implementing machine learning strategies into existing supply chain management systems. To better use the huge amounts of data presently being created by the supply chain, the primary goal of this study is to ascertain whether or not machine learning methods can be incorporated into the existing toolbox accessible to supply chain decision-makers.