Maxime C. Cohen – författare

From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture.This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.

From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture.This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.

Bringing together some of the world’s foremost supply-chain thinkers, this book shows how artificial intelligence (AI) is rewriting the rules of global supply chain management. It explores machine learning, computer vision, large-language models, and generative AI in action – how they’re used to refine demand forecasts, optimize inventories, and drive down costs while service levels soar. The book examines AI-driven demand forecasting and inventory optimization, which enhances the accuracy of predicting customer demand and managing inventory levels to reduce costs and improve service. It covers intelligent logistics and transportation management, and utilizing AI to optimize routing, scheduling, and fleet management, which leads to increased efficiency and sustainability. The discussion extends to procurement and supplier relationship management, where procurement processes are streamlined and supplier partnerships are strengthened through AI-driven analytics and decision-making tools. In turn, the book confronts the hard questions of ethics, data privacy, and algorithmic bias, equipping readers to harness AI’s power responsibly and ethically across the entire supply chain. These topics are vital, as they address the pressing need for supply chains to become more agile, resilient, and responsive in today’s rapidly changing global market. By exploring these areas, the book aims to provide readers with a nuanced understanding of the current landscape and future directions of AI in supply chain management. The problem this book sets out to solve is the knowledge gap between the theoretical potential of AI and its practical application within supply chains around the globe. By presenting real-world examples, case studies, and expert analyses, it offers actionable insights that can be applied to enhance operational efficiency and strategic decision-making. The book is intended for supply chain professionals, business leaders, academics, policymakers, and students seeking a better grasp of the intersection of AI and supply chain management. It serves as both a reference guide and a source of inspiration for those looking to leverage AI technologies to drive innovation and competitiveness in their organizations.