Supply Chain Analytics, second edition, introduces the reader to data analytics and demonstrates the value of its effective use in the improvement of Supply Chain (SC) process performance. By describing four key SC processes and illustrating – through worked examples – how the descriptive, predictive, and prescriptive analytic methods can be applied to enhance those processes, this book presents a more comprehensive learning experience for the reader than has been offered previously.

Key topics and issues are addressed, including the capriciousness of modern SC operating environments; the imperative of SC sustainability; the need for heightened SC risk management; the building of SC resilience; the pursuit of SC optimisation; and the use of big data, data mining, cloud computing, machine learning, artificial intelligence (AI), and importantly the social issues confronting SC analysts in carrying out their work.

The author identifies four core SC processes – strategy, design, execution, and people – to which the analytic techniques explained can be applied to ensure continuous performance improvement and the growth of competitive advantage.

Pedagogy to aid learning is incorporated throughout, including an opening section for each chapter explaining the intended learning outcomes; worked examples illustrating how each analytic technique works, how it is applied, and what to be careful of; tables, diagrams, and equations to help ‘visualise’ the concepts and methods covered; end-of-chapter case studies; review questions; and assignment tasks.

Providing both management expertise and technical skills, which are essential to decision-makers in the SC, this textbook is essential reading for advanced undergraduate and postgraduate students of SC analytics, SC leaders, and SC operations management professionals. Its practice-based and applied approach also makes it valuable for teaching academics, organisational trainers and coaches, operating SC practitioners, and those pursuing professional qualifications.

Online resources include chapter-by-chapter PowerPoint slides, tutorial exercises, written assignments, worked examples using Excel, and a test bank of exam questions.