If you want to gain more supply chain analytics knowledge, you’re in the right place. We’ve compiled a list of 10 great supply chain analytics books to help you better understand the concepts and strategies behind this vital business field. From foundational reads to more advanced topics, these books will help you start your journey into the world of supply chain analytics!
We have written other blogs recommending a curated list of highly-rated books, such as:
You will also find best practices, tools, and a list of helpful supply chain resources.
List of Top 10 Supply Chain Analytics Books
This book offers an in-depth guide to understanding the link between corporate financials and supply chain maturity, evaluating the progress of over a hundred companies from 2006-2013. The author provides a clear, concise framework for a more modern, effective supply chain, exploring the relationship between supply chain efficiency and financial growth. Topics include outlining important metrics, progress in industry sub-segments, management techniques, and a roadmap for improvement. The book is recommended for companies and professionals seeking new solutions and improvement opportunities to drive differentiation in a market where growth is stalled.
A reader of this book who rated it five stars on Amazon described it as a thick read, but also a comprehensive guide on change management. The author uses a storytelling approach to provide readers with methods, techniques and a process for re-evaluating how to manage their supply chain by focusing on what is important. It takes time to get through, but it is a valuable resource for anyone looking to improve their understanding of change management in the supply chain.
This book is a comprehensive introduction to supply chain management for beginners written by an experienced professor and practitioner in the field. The book is mainly intended for students studying the field and preparing for their careers. It provides a business-focused overview of the use of data analytics and machine learning in supply chain management, teaching essential concepts and techniques for data analysis and decision-making. The book includes hands-on practice using popular programming software and is suitable for upper-level undergraduate, postgraduate, and MBA courses in supply chain management. It covers major supply chain processes such as managing supply and demand, warehousing, inventory control, transportation, and route optimization. It includes real-world examples from companies like Amazon and Starbucks, case study discussion questions, computer-assisted exercises, and programming projects, making it an ideal choice for anyone looking to learn about supply chain management and the analytics involved.
“Data Science for Supply Chain Forecasting, Second Edition” is a comprehensive guidebook that covers different types of supply chain analytics. It emphasizes the importance of applying a scientific method, including experimentation, observation, and constant questioning, to achieve excellence in demand forecasting. The book covers various forecast models, new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. It includes do-it-yourself sections with implementations provided in Python and Excel, to show readers how to apply these models themselves. This hands-on guidebook, covering the entire range of forecasting, from the basics to leading-edge models, will benefit supply chain practitioners, forecasters, and analysts looking to improve their demand forecasting skills and stay informed and up-to-date with the current practices related to different types of supply chain analytics.
A reader reviews it with five-stars and continues on to say “As both a consultant and a teacher, I found this book to be a pleasure to read. In addition to the clear and easy-to-understand Python code it provides, the author also offers valuable insights on commonly confusing concepts in supply chain management. I highly recommend it to anyone looking for a comprehensive guide on the subject.”
Supply Chain Planning and Analytics is a book that covers the decision-making process of determining how many goods to procure, make, and deliver without knowing the exact product demand. It covers the three main procedures that make up effective supply chain planning: demand planning, sales and operations planning, and inventory and supply planning. The book explains these procedures, how they link, and the difficulties in putting them into practice, as well as how to apply analytical techniques and tools to improve supply chain planning choices. It is a valuable resource for professionals involved in the field of supply chain planning.
Supply Chain Analytics is a book that provides readers with an in-depth understanding of the key concepts and techniques needed to analyze and make strategic decisions in modern supply chains. The book covers key supply chain processes through real-world examples, explains different analytic methods that can be used to improve them and covers topics such as optimization, big data, data mining and cloud computing. The author also identifies four core supply chain processes – strategy, design, execution and people – to which the analytic techniques can be applied to ensure continuous improvement. The book includes pedagogy such as worked examples, tables, diagrams, equations, chapter case studies, review questions and assignment tasks to aid in learning. This book is ideal for operating supply chain practitioners and those studying to fulfil these roles.
Uncover the Supply Chain Analytics challenges you’re facing and generate better solutions with this innovative guidebook. Unlike traditional textbooks, this “Supply Chain Analytics Guide” focuses on the importance of asking great questions and provides the tools to conduct an in-depth self-assessment. The book includes digital components that have new and updated case-based questions organized into seven core levels of Supply Chain Analytics maturity. This self-assessment will help you identify areas for improvement and provide a roadmap for achieving Supply Chain Analytics excellence.
This textbook provides a detailed overview of the process of using analytics in supply chain management. It covers a variety of topics including supply chain planning, optimization, demand forecasting, and product allocation. The book includes case studies and examples to help readers understand and apply the concepts discussed. It also includes a critical view on how performance measurement systems have been developed and supported by data in the supply chain. The book is a valuable resource for students, practitioners, and professionals looking to improve their supply chain analysis skills.
This edited collection explores how automation, predictive analytics, and the latest technologies are used to optimize logistics and supply chain processes, reduce costs and create new business opportunities.
The book includes contributions from leading international researchers in academia and industry and covers topics such as automation, big data, the Internet of Things, and decision support systems for transportation and logistics. It also includes case studies of cutting-edge applications from innovators in the logistics industry, providing valuable insights into the market requirements for practical and effective value chain analysis.
Learn the ins and outs of analyzing supply chains with this practice-oriented textbook. This guidebook provides an introduction to the use of analytics-based inventory management in complex supply chains.
With a focus on Prescriptive Analytics and Business Analytics, the book covers both single-level and multi-level inventory models for optimal allocation of safety inventory. It also delves into dynamic lot sizing problems under random demand and random yield and their relation to Material Requirements Planning (MRP). The models and algorithms are clearly explained with the help of numerous examples, making this a comprehensive guide on how to analyze supply chains.
For practitioners and professionals who deal with inventory management in their day-to-day work, this book is a fantastic resource.
Demand Prediction in Retail covers every step of the process: from data collection to evaluation and visualization of predicted results.
The book provides detailed code and implementation examples to demystify how historical data can be used to predict future demand. The tools and methods presented can be applied to a wide range of retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture.
This comprehensive book is designed as a thorough guide to help students in business analytics and data scientists learn and master the use of data in order to help predict demand in retail applications. It can also be used as a guide for supply chain practitioners interested in forecasting demand.
The book helps readers comprehend how to use data, clean and pre-process it, and evaluate prediction accuracy, recurring errors and mistakes, and gaps in the implementation process.
These books cover a wide range of topics, from the basics of supply chain analytics to advanced data-driven strategies for improving performance. Whether you’re a seasoned supply chain professional or just starting out, these books will provide valuable insights and actionable advice to help you excel in your field.
If you’re looking to improve your supply chain analytics skills and stay ahead of the curve, these books are a great place to start. So go ahead, pick one up and start reading!