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Supply Chain Analytics and Modelling
Quantitative Tools and Applications
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About the book
A comprehensive guide for analysing, interpreting and improving supply chain systems through data.
Supply Chain Analytics and Modelling by Nicoleta Tipi provides MSc students and supply chain professionals with a practical and structured introduction to the analytical tools and business models used across modern logistics and operations environments. The fully updated, latest edition of this core resource helps readers make sense of complex supply chain data and build the modelling skills needed to improve performance, resilience and decision-making.
Beginning with the foundations of analytics and business modelling, the textbook guides students and professionals through increasingly advanced techniques, from simulation and optimization to machine learning, AI and digital twins. It shows how to critically evaluate supply chain performance using accurate data, and how to apply model outputs to solve real-world problems. Throughout, readers will gain the tools to manage data complexity, assess risk and apply intelligent models to support effective decision-making.
To support academic study and independent learning, this edition includes:
- A wide range of modelling approaches, from descriptive to predictive analytics
- New content on digital twins, machine learning, AI and simulation tools
- Analysis of supply chain performance measurement and data reliability
- Real-world examples that connect theory to logistics and operations practice
- Online resources including lecturer slides and solved model examples
Supply Chain Analytics and Modelling equips students and practitioners with the analytical confidence and technical fluency to interpret, model and manage today's data-intensive supply chain systems.
About the authors
Table of contents
- Section - One: An introduction to business analytics and modelling in the supply chain
- Chapter - 01: Introduction to business analytics;
- Chapter - 02: The role of modelling in the supply chain;
- Chapter - 03: The role of data in the supply chain;
- Chapter - 04: Big data and data visualization;
- Section - Two: Advances in supply chain analytics and modelling
- Chapter - 05: Supply chain performance measurement systems;
- Chapter - 06: Business analytics models;
- Chapter - 07: Supply chain analytics;
- Section - Three: Future opportunities in supply chain analytics and modelling
- Chapter - 08: The future of supply chain analytics
Reviews
The second edition of Supply Chain Analytics and Modelling is a significant step forward from an already excellent first edition. Nicoleta Tipi introduces business analytics with clarity and simplicity, using practical examples that make complex ideas easy to grasp. While many book texts discuss supply chain modelling, this book goes further by addressing the critical question of why modelling matters, offering clear explanations of the complexities of supply chain environments and the tools available to navigate them.
Data and performance measurement, often abstract or ambiguously presented elsewhere, are explained here in a straightforward and accessible way. The progression into advanced techniques and models in the second part of the book is particularly valuable, providing readers with both breadth and depth of understanding.
The book concludes with a thoughtful research agenda that highlights what has been explored so far and where future work should go. This makes the book not only an outstanding resource for practitioners and students but also an inspiring guide for researchers in the field.
- A fundamental text for the analytics modelling revolution. Drawing from years of experience, Nicoleta Tipi has made the increasingly complex decision tools become more accessible for students in industrial, business and supply chain analytics fields.
- Chukwuneke Okorie, Associate Professor Supply Chain Operations Management, College of Business and Management (CBM), Metro State University
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