Share a link:
https://casecent.re/p/196982
Write a review
|
No reviews for this item
This product has not been used yet
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.
About
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.