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ML Solutions to Enhance Supply Chain Management

Food and Beverages | Thursday, May 16, 2019

FREMONT, CA: The algorithms and systems powered by Machine Learning (ML) are utilized to point out anomalies, note trends, and predict insights by processing massive data assets. ML has numerous applications and proves to be the ideal technology to handle supply chain management challenges. The problems are primarily drifting amidst time, budget, and resource limitations, which have been faultily managed to cause complicated issues.

Supply chain-based enterprises that have employed ML as part and parcel of their analytics have already experienced benefits in the form of on-time shipments and enhancements in demand projections, cost-efficiency, and resource planning.    

ML is revolutionizing supply chains to increase the efficiency of the operations in the following ways:

•    Improved utilization of assets and resources:

The foundation of numerous emerging logistics, supply chain software and solutions have been ML and AI-based algorithms. The technology is viable in the provision of insights, to help plan the resources efficiently by accounting the anomalies. Other than optimizing asset utilization and capacity, the tools enable powerful automation and various autonomous operations.

•    Forecast of errors reduced:

Machine Learning algorithm can process vast arrays of data occurring from varied sources like IoT devices, intelligent transportation systems, and telematics enabling better insights. With the provision of improved insights, reduction in uncertainty is observed to help provide precise forecasts.  

•    Prevention of fraud/Avoiding scams:

The implementation of ML-based solutions will not only decrease the risk of fraud but also enhance the quality of service and products. ML is capable of automating inspections, regulating auditing processes, and simultaneously performing real-time scrutiny of results. 

•    Holistic transparency:

The platforms based on ML and AI provide full access to all operations in the supply chain, by combining multiple enterprise commerce networks for handling the global trade. 

With increased visibility, companies are fully prepared with data and insights to respond to anomalies quicker than ever before.

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