Supply Chain Analytics introduces the reader to data analytics and
demonstrates the value of their effective use in supply chain
management. By describing the key supply chain processes through worked
examples, and the descriptive, predictive and prescriptive analytic
methods that can be applied to bring about improvements to those
processes, the book presents a more comprehensive learning experience
for the reader than has been offered previously.
Key topics are addressed, including optimisation, big data, data mining
and cloud computing. The author identifies four core supply chain
processes - strategy, design, execution and people - to which the
analytic techniques explained can be applied to ensure continuous
improvement. Pedagogy to aid learning is incorporated throughout,
including an opening section for each chapter explaining the learnings
designed for the chapter; 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; chapter case studies; and end-of-chapter review questions and
assignment tasks.
Providing both management expertise and technical skills, which are
essential to decision-makers in the supply chain, this textbook should
be essential reading for advanced undergraduate and postgraduate
students of supply chain analytics, supply chain leadership, and supply
chain and operations management. Its practice-based and applied approach
also makes it valuable for operating supply chain practitioners and
those studying for professional qualifications.
Online resources include chapter-by-chapter PowerPoint slides, tutorial
exercises, written assignments and a test bank of exam questions.
