Bibliographic Details
| Title: |
How Machine Learning Will Transform Supply Chain Management. |
| Authors: |
Agrawal, Narendra, Cohen, Morris A., Deshpande, Rohan, Deshpande, Vinayak |
| Superior Title: |
Harvard Business Review. Mar/Apr2024, Vol. 102 Issue 2, p128-137. 10p. 4 Color Photographs. |
| Subject Terms: |
*SUPPLY chain management, *ARTIFICIAL intelligence in business, *ARTIFICIAL intelligence in industry, *SUPPLY chain disruptions, MACHINE learning, CLOUD computing |
| Abstract: |
Businesses need better planning to make their supply chains more agile and resilient. After explaining the shortcomings of traditional planning systems, the authors describe their new approach, optimal machine learning (OML), which has proved effective in a range of industries. A central feature is its decision-support engine that can process a vast amount of historical and current supply-and-demand data, take into account a company’s priorities, and rapidly produce recommendations for ideal production quantities, shipping arrangements, and so on. The authors explain the underpinnings of OML and provide concrete examples of how two large companies implemented it and improved their supply chains’ performance [ABSTRACT FROM AUTHOR] |
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| Database: |
Business Source Premier |
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