GO TO BOOKĭigital Supply Chains: A Practitioner’s Guide to Successful Digitalization OUR TAKE: This 2021 book provides readers with concrete instructions and insights into digital transformation initiatives in supply chain environments. Specific topics covered in the Second Edition of his book include machine learning, statistical models, demand forecasting, process management, feature optimization, external demand rivers, and other supply chain forecasting models and concepts. Topics covered include the horizontalization of the supply chain, risk management, process mining, supply chain segmentation, digital twins, robotic process automation, and more.ĭata Science for Supply Chain Forecasting OUR TAKE: The Second Edition of this title almost doubles the amount of content covered in its pages, with four new chapters that introduce and cover topics like neural networks and value-added frameworks.ĭescription: In Data Science for Supply Chain Forecasting, readers will learn how to apply the scientific method to their supply chains and use experimentation, observations, and questions to improve their forecasting efforts. Nicolas Vandeput uses his expertise as a Supply Chain Data Scientist to provide readers with do-it-yourself walkthroughs and insights into demand forecasting, inventory optimization, quantitative models, and more. With this book, supply chain expert Murillo Xavier explores the latest trends in supply chains worldwide and uses examples of advanced strategies and best practices to help executives stay ahead of industry fluctuations. The Best Supply Chain Books You Should Be ReadingĪdvanced Strategies in Supply Chain: Competing in the New Normal OUR TAKE: Global supply chains are changing faster than ever, which is why Murillo Xavier has written a book to help industry leaders stay ahead of the competition and remain agile in the face of a “new normal.”ĭescription: Changes and disruptions in the economy, society, and technology have forced companies across industries to redefine how their business operates or risk obsolescence.
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