Procurement Analytics: Data-Driven Decision-Making in Procurement and Supply Management (Springer Series in Supply Chain Management, Band 22) - Softcover

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Christian Mandl is a Professor of Digital Procurement and Supply Chain Analytics at Deggendorf Institute of Technology (Germany) and a consultant in the field of procurement analytics. His research has been published in top-ranked journals such as Manufacturing & Service Operations Management and Production and Operations Management and has been honored with various awards (e.g. the Practice-Based Research Award, by the Manufacturing and Service Operations Management Society; and the Science Prize, by the German Federal Association of Materials Management, Purchasing and Logistics.) He holds a Ph.D. in Operations Research from the Technical University of Munich (TUM, Germany) and is a visiting scholar at Cornell University (USA).

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This unique textbook explicitly addresses the intersection of advanced analytics and procurement. It is motivated by one core question: How can firms generate (economic) value from procurement data? It demonstrates that procurement is one of the major functions within a firm where data analytics, artificial intelligence, and operations research can successfully be leveraged to reduce cost and risk and to achieve resilience and sustainability goals.

The book provides a methods-based overview of data-driven optimization of purchasing decisions. Besides presenting key concepts and applications, it particularly focuses on implementation, so as to help (future) procurement managers and data scientists quickly evaluate the value generated by a given data-driven solution. What sets this textbook apart is its combination of rigorous, state-of-the-art methodologies from academic research and first-hand experience from various application-oriented consulting projects in a range of industries. 

Though primarily intended for graduate students with a major in procurement and supply chain management, the book will also benefit purchasing managers with and without specific knowledge of advanced analytics techniques, and data scientists with and without specific experience in procurement.