How machine learning will transform supply chain management: It does a better job of using data and forecasts to make decisions. (Record no. 525663)
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
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| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Agrawal, Narendra et al |
| 245 ## - TITLE STATEMENT | |
| Title | How machine learning will transform supply chain management: It does a better job of using data and forecasts to make decisions. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Harvard Business Review |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 102(2), Mar-Apr, 2024: p.129-137 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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.- Reproduced https://hbr.org/2024/03/how-machine-learning-will-transform-supply-chain-management |
| 773 ## - HOST ITEM ENTRY | |
| Main entry heading | Harvard Business Review |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) | |
| Subject DIP | CORPORATE GOVERNANCE |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Item type | Articles |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent location | Current location | Date acquired | Serial Enumeration / chronology | Barcode | Date last seen | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Indian Institute of Public Administration | Indian Institute of Public Administration | 2024-04-02 | 102(2), Mar-Apr, 2024: p.129-137 | AR131458 | 2024-04-02 | Articles |