000			01332nam a22001457a 4500
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008			240402b ||||| |||| 00| 0 eng d
100			_aAgrawal, Narendra et al _951510
245			_aHow machine learning will transform supply chain management: It does a better job of using data and forecasts to make decisions.
260			_aHarvard Business Review
300			_a102(2), Mar-Apr, 2024: p.129-137
520			_aBusinesses 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.- Reproduced https://hbr.org/2024/03/how-machine-learning-will-transform-supply-chain-management
773			_aHarvard Business Review
906			_aCORPORATE GOVERNANCE
942			_cAR