Synopsis
This book introduces the Decision Data Base (DDB), a resource for business decision-making. The author emphasizes its value in analyzing complex, data-intensive problems in value chain management and financial decision-making. The DDB is constructed by inductively analyzing business problems to create coherent models. The author presents two case studies demonstrating the DDB's practical significance in logistics and portfolio selection. They highlight the DDB's ability to capture costs, capacities, inventory management, and facilities location decisions, providing a realistic representation of complex business scenarios. The book explores the relationship between business process redesign, integrated planning, and the DDB. It emphasizes the role of mathematical programming models in unraveling complex interactions and ripple effects that make integrated planning challenging. The DDB, complemented by business process software, facilitates effective decision-making and promotes coordinated planning within organizations. This book serves as a valuable guide for managers seeking to enhance their decision-making capabilities. Its insights help readers understand the DDB's construction, meaning, and use in various business applications. By leveraging the DDB, organizations can make informed and strategic decisions, ultimately improving their performance and achieving their business objectives.
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About the Author
Jeremy Shapiro is a professor emeritus in the Sloan School of Management at MIT. For nine years he served as the co-director of MIT's Operations Research Center. Previously, he was employed by Procter and Gamble, Hughes Aircraft Company, and the Port of New York Authority. He received his B.M.E. and M.I.E. degrees from Cornell University and a Ph.D. degree in Operations Research from Stanford University. Dr. Shapiro has published over 60 papers in the areas of operations research, mathematical programming, logistics, supply chain management, finance, and marketing. He is also president of SLIM Technologies, LLC, a Boston-based firm specializing in the implementation and application of modeling systems for supply chain management and other business problems. His outside interests include reading, traveling, biking and playing tennis. He is married to Martha J. Heigham and has three children, Alexander, Lara, and Nicholas.
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The Decision Data Base (Classic Reprint)
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Paperback. Condition: New. Print on Demand. This book introduces the Decision Data Base (DDB), a resource for business decision-making. The author emphasizes its value in analyzing complex, data-intensive problems in value chain management and financial decision-making. The DDB is constructed by inductively analyzing business problems to create coherent models. The author presents two case studies demonstrating the DDB's practical significance in logistics and portfolio selection. They highlight the DDB's ability to capture costs, capacities, inventory management, and facilities location decisions, providing a realistic representation of complex business scenarios. The book explores the relationship between business process redesign, integrated planning, and the DDB. It emphasizes the role of mathematical programming models in unraveling complex interactions and ripple effects that make integrated planning challenging. The DDB, complemented by business process software, facilitates effective decision-making and promotes coordinated planning within organizations. This book serves as a valuable guide for managers seeking to enhance their decision-making capabilities. Its insights help readers understand the DDB's construction, meaning, and use in various business applications. By leveraging the DDB, organizations can make informed and strategic decisions, ultimately improving their performance and achieving their business objectives. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781332257201_0
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