Supply Chain Analytics and Modelling

Quantitative Tools and Applications
Harness data within the supply chain using this accessible guide on how to examine, evaluate and apply business analytics models.

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.

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