19 Best Books on Supply Chain Analytics

How will the Supply Chain Analytics team and the organization measure the complete success of Supply Chain Analytics? What are the business objectives to be achieved with Supply Chain Analytics? Are accountability and ownership for Supply Chain Analytics clearly defined? In a project to restructure Supply Chain Analytics outcomes, which stakeholders would you involve? What are specific Supply Chain Analytics Rules to follow?

Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role… In EVERY company, organization, and department.

Unless you are talking about a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, ‘What are we really trying to accomplish here? And is there a different way to look at it?’

For more than twenty years, The Art of Service’s Self-Assessments empower people who can do just that – whether their title is marketer, entrepreneur, manager, salesperson, consultant, business process manager, executive assistant, IT Manager, CxO, etc… – they are the people who rule the future. They are people who watch the process as it happens and ask the right questions to make the process work better.

This book is for managers, advisors, consultants, specialists, professionals, and anyone interested in Supply Chain Analytics assessment.

All the tools you need to an in-depth Supply Chain Analytics Self-Assessment. Featuring 371 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Supply Chain Analytics improvements can be made.

In using the questions you will be better able to:

– diagnose Supply Chain Analytics projects, initiatives, organizations, businesses, and processes using accepted diagnostic standards and practices

– implement evidence-based best practice strategies aligned with overall goals

– integrate recent advances in Supply Chain Analytics and process design strategies into practice according to best practice guidelines

Using a Self-Assessment tool known as the Supply Chain Analytics Scorecard, you will develop a clear picture of which Supply Chain Analytics areas need attention.

Included with your purchase of the book is the Supply Chain Analytics Self-Assessment downloadable resource, which contains all questions and Self-Assessment areas of this book in a ready to use Excel dashboard, including the self-assessment, graphic insights, and project planning automation – all with examples to get you started with the assessment right away. Access instructions can be found in the book.

You are free to use the Self-Assessment contents in your presentations and materials for customers without asking us – we are here to help.

This book, developed in collaboration with the Rutgers Center for Supply Chain Management and based upon research projects conducted with over 100 participating corporations, combines theory and practice in presenting the concepts necessary for the strategic implementation of supply chain management techniques in a global environment. Coauthored by top teaching and research faculty and a senior industry executive, this academic/industry partnership ensures the relevance of the text in terms of both practical application and academic rigor.

This book introduces students to the key drivers of supply chain performance, including demand forecasting, sales, and operations planning, inventory control, capacity analysis, transportation models, supply chain integration, and project management and risk analysis. It is enhanced by real-life examples and case studies as well as strategies from best practices and a focus on social and economic impact. The content reaches beyond a traditional operations management text and draws on the extensive experience of the authors conducting industry projects through the Rutgers Center for Supply Chain Management. The input of senior business executives has been an invaluable asset in presenting a balanced knowledge of both quantitative models and qualitative insights.

In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations.

From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research.

Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.

‘Supply Chain 4.0’ has introduced automation into logistics and supply chain processes, exploiting predictive analytics to better match supply with demand, optimizing operations, and using the latest technologies for the last mile delivery such as drones and autonomous robots. Supply Chain 4.0 presents new methods, techniques, and information systems that support the coordination and optimization of logistics processes, reduction of operational costs as well as the emergence of entirely new services and business processes.

This edited collection includes contributions from leading international researchers from academia and industry. It considers the latest technologies and operational research methods available to support smart, integrated, and sustainable logistics practices focusing on automation, big data, the Internet of Things, and decision support systems for transportation and logistics. It also highlights market requirements and includes case studies of cutting-edge applications from innovators in the logistics industry.

This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics, and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply-demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least-cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves.

The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.

The industry standard in supply chain management―fully revised and updated to provide today’s logistics solutions

The proven pillars of success in logistics and supply chain management introduced in the first edition of Supply Chain Strategy now guide the supply chains of many of the world’s most successful organizations, including 3M, Abbott, BP, Coca-Cola, Disney, Hallmark, Honda, Mitsubishi, Oxxo-FEMSA, Payless, P&G, Pratt & Whitney, Wal-Mart, Rio Tinto, and many others.

This Second Edition features up-to-date case studies showing how those companies and more meet supply chain goals and helps you overcome your own challenges with the latest supply chain innovations, including big-data analytics, supply chain command and control centers, large-scale supply chain optimization, integrated supply chain planning, real-time global supply chain visibility, omnichannel logistics, re-shoring, global-sourcing optimization, cloud-based supply chain management, supply chain finance, global trade management, and fourth-party logistics.

Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a truly scientific method that includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting.

This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value-added framework. Part I focuses on statistical “traditional” models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves.

This hands-on book, covering the entire range of forecasting–from the basics all the way to leading-edge models–will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting.

How to Conquer the Effective Frontier and Drive Improved Value in Global Operations

Growth has slowed. Volatility has increased and the world is more global. Brands are defined by innovation and services. Supply chain excellence matters more than ever. It makes a difference in corporate performance.

One cannot snap their fingers and deliver supply chain success. It happens over the course of many years. It is measured in inches not miles. In this book, the author evaluates the progress of over a hundred companies over the period of 2006-2013.

Success drives value. The effective supply chain makes a difference in winning a war, saving a patient, and driving commerce; but it also makes a difference in a community having clean air, potable water, and a standard of living. Mistakes are hard to overcome. Supply Chain Metrics that Matter tells this story. The book links corporate financials to supply chain maturity. In the book, the author analyzes which metrics matter.

The author Lora M. Cecere is a supply chain researcher as well as an authority in supply chain technology. She helps companies gain first mover advantage. In the book, Cecere provides concrete, actionable steps to align and balance the supply chain to drive value. The book explores the crossover between supply chain efficiency and financial growth with topics such as:

• Outlining the metrics that matter, the metrics that don’t
• Progress in industry sub-segment in improving inventory, cash, productivity and margin
• The management techniques that improve performance
• Sharing insights on how metrics change as the supply chain matures
• The roadmap to improve performance.

Today, supply chains are global and dynamic. They are rapidly evolving. Companies that constantly seek out new solutions and opportunities for improvement drive differentiation. In a market where growth is stalled and many companies are stuck in driving supply chain performance, this book provides a clear, concise framework for a more modern, effective supply chain.

Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material, and product delivery… using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data-Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You’ll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind the strategy, dissolving organizational boundaries to sense demand and make better decisions and choosing the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain — and earn big profits from the data you’re already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance.

This book is aimed at an important and under-served niche within the supply chain market: strategic supply chain design. Almost all supply chain professionals need to know about this discipline. No current book covers the theory and practice in a way that ensures readers will be successful with this discipline in the field.

Strategic network design is about selecting the right number, location, and size of warehouses, plants, and production lines. It is about determining the territories of your facilities, what product should be made where, and how the product should flow through the supply chain. It is about developing a good model of your supply chain so you can make good operational decisions.

Network design is important because a good design helps a firm execute its strategy.

To do it right, it requires analytics and optimization. And, when firms do it right, they can reduce supply chain costs by 5-15% which can translate into tens of millions of dollars of savings for the firm.

The book brings together our experience in completing 100s of these projects, our teaching of this material, and our understanding of the science that drives these studies.

The book is ideal for supply chain managers, analysts, and consultants who must do these studies, for people who work for a company or organization with a supply chain and want to understand the design and strategy better, and for professors who want to bring a practical and intellectually interesting material to the classroom.

Our goal is to help you deeply understand this topic. We cover the topics with realistic case studies, discussions of practical consideration, and a mix of science. This helps you understand the topic, understand how it applies to you, and build your intuition.

We hope you enjoy the book!

Are there dominant suppliers, or is the market evenly distributed (market concentration)?

Do you and your customers have complete visibility of order and product inventory status?

Does your supply chain have differentiating capabilities that lead to market leadership?

How can supply chain practitioners put theory into practice and make changes real?

How easy is it to get trusted and harmonized product information across the enterprise?

How well will your supply chain support your business strategy in an uncertain world?

What are the best alternatives for the effective implementation of sustainable supply chains?

What areas are giving you sustainable margin growth and what attributes can be replicated?

What is the percentage of products/raw materials supplied to you by your core suppliers?

Who are your top trading partners and how many transactions have you completed with them?

This Supply Chain Analytics Guide is unlike books you’re used to. If you’re looking for a textbook, this might not be for you. This book and its included digital components are for you who understand the importance of asking great questions. This gives you the questions to uncover the Supply Chain Analytics challenges you’re facing and generate better solutions to solve those problems.

Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role… In EVERY group, company, organization, and department.

Unless you’re talking about a one-time, single-use project, there should be a process. That process needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, ‘What are we really trying to accomplish here? And is there a different way to look at it?’

This Self-Assessment empowers people to do just that – whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc… – they are the people who rule the future. They are the person who asks the right questions to make Supply Chain Analytics investments work better.

This Supply Chain Analytics All-Inclusive Self-Assessment enables You to be that person.

INCLUDES all the tools you need for an in-depth Supply Chain Analytics Self-Assessment. Featuring new and updated case-based questions, organized into seven core levels of Supply Chain Analytics maturity, this Self-Assessment will help you identify areas in which Supply Chain Analytics improvements can be made.

In using the questions you will be better able to:

Diagnose Supply Chain Analytics projects, initiatives, organizations, businesses, and processes using accepted diagnostic standards and practices.

Implement evidence-based best practice strategies aligned with overall goals.

Integrate recent advances in Supply Chain Analytics and process design strategies into practice according to best practice guidelines.

Using the Self-Assessment tool gives you the Supply Chain Analytics Scorecard, enabling you to develop a clear picture of which Supply Chain Analytics areas need attention.

The Fifth Edition of Operations and Supply Chain Management: The Core focuses on the essential core concepts in the dynamic field of operations. Jacobs aims to prepare future managers by imparting the perspective that good operational practices are central to any effective business. This new edition has an increased focus on using supply chain analytics to better solve business problems.

McGraw-Hill Connect is an award-winning digital teaching and learning solution that empowers students to achieve better outcomes and enables instructors to improve course management efficiency.  New to Connect are enhanced algorithmic problems, Application-Based Activities for Operations Management, and Practice Operations interactive game-based simulation.

To further complement Jacobs 5e, the Canadian Companion Connect offers 12 Canadian cases, covering topics such as Inventory, Manufacturing, Service Process, Warehousing, Blockchain, Supply-chain Manufacturing, Transportation & Logistics, Forecasting. Each case is supported by instructors’ notes, suggested activities, and Multiple Choice questions assignable through Connect.

The 5e offers a unique balanced approach to logistics and supply chain, enhanced by the wealth of practice and cases.

Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization.

The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple yet powerful framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions.

Inventory managers, demand planners, and academics interested in gaining cost-effective solutions will benefit from the “do-it-yourself” examples and Python programs included in each chapter.