Supply Chain Analytics: Using Data to Optimise Supply Chain Processes

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.

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Supply Chain Analytics: Using Data to Optimise Supply Chain Processes

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.

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Supply Chain Analytics: Using Data to Optimise Supply Chain Processes

Supply Chain Analytics: Using Data to Optimise Supply Chain Processes

by Peter W. Robertson
Supply Chain Analytics: Using Data to Optimise Supply Chain Processes

Supply Chain Analytics: Using Data to Optimise Supply Chain Processes

by Peter W. Robertson

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$62.99 
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Overview

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.


Product Details

ISBN-13: 9780367540067
Publisher: Taylor & Francis
Publication date: 11/26/2020
Series: Mastering Business Analytics
Pages: 320
Product dimensions: 6.88(w) x 9.69(h) x (d)

About the Author

Peter W. Robertson is Honorary Research Fellow at the University of Wollongong (UOW), Australia.

Table of Contents

Examples included in this book by analytic technique xi

Examples included in this book by supply chain process xiv

About the author xv

Foreword xvi

Preface xix

Acknowledgments xxi

1 Introduction to supply chain analytics 1

1.1 What you will learn in this chapter 1

1.2 Data science 1

1.3 Context 13

1.4 SC analytics components 16

1.5 SC partners and analytics 17

1.6 Why use this book? What is its value-add? 19

1.7 Review questions 19

1.8 Assignment topics 20

2 Supply chain analytics in practice 22

2.1 What you will learn in this chapter 22

2.2 Caterpillar vignette 22

2.3 DHL case study 24

2.4 What are SC analytics and why are they important? 27

2.5 Problem solving, decision-making and analytics 29

2.6 SC analytics relevance to service and manufacturing SCs 30

2.7 The SC analytics lifecycle 30

2.8 Overview of the four-process SCM framework 32

2.9 Overview of the three SC analytics categories 33

2.10 Worked example - analytics in-practice problem and solution 35

2.11 The 'social' dimension and its importance 49

2.12 Summary 50

2.13 Review questions 50

2.14 Assignment topics 50

3 Getting started with supply chain analytics 52

3.1 What you will learn in this chapter 52

3.2 Writing competent problem statements 52

3.3 What should be measured and how is the right measure identified? 54

3.4 Variables, variable types and how they relate to each other 56

3.5 Probability and Bayes' theorem 59

3.6 Data collection, sampling and pre-processing 63

3.7 Data analysis 68

3.8 Presenting results of data analysis 70

3.9 Review questions 73

3.10 Assignment topics 73

4 Using supply chain analytics to enhance supply chain strategy processes 74

4.1 What you will learn in this chapter 74

4.2 SC strategy processes in detail 74

4.3 PESTLE analysis 77

4.4 Strengths, weaknesses, opportunities and threats (SWOT) analysis 77

4.5 State-of-play analysis 77

4.6 SC vision 84

4.7 SC purpose 86

4.8 SC goals 87

4.9 SC strategies 87

4.10 SC strategy alignment 88

4.11 SC strategy implementation planning 90

4.12 SC strategy risk analysis 91

4.13 Financial analysis of projects 93

4.14 Case study - using analytics to improve operations performance 97

4.15 Review questions 97

4.16 Assignment topics 98

5 Using supply chain analytics to enhance supply chain design processes 99

5.1 What you will learn in this chapter 99

5.2 SC design processes in detail 99

5.3 Basic statistics, deviation and compliance analysis applied to safety 104

5.4 Economic analysis applied to economic performance sustainability 108

5.5 Queuing theory applied to design of facility layouts 113

5.6 Simulation applied to SC physical design 117

5.7 Network models applied to SC physical design 122

5.8 Mathematical programming applied to design for economic performance 131

5.9 Case study - analytics applied to SC design processes 142

5.10 Review questions 146

5.11 Assignment topics 147

6 Using supply chain analytics to enhance supply chain execution processes 148

6.1 What you will learn in this chapter 148

6.2 SC execution processes in detail 148

6.3 Forecasting applied to order fulfilment planning 153

6.4 Theory of constraints applied to order fulfilment planning 174

6.5 Pull inventory management applied to order fulfilment 179

6.6 Constraint-based inventory management applied to order fulfilment 182

6.7 Statistical process control applied to order fulfilment 186

6.8 Logistics and flow models applied to order fulfilment 190

6.9 Inventory management applied to managing supplier performance 196

6.10 Supplier analysis - categorise supply base 199

6.11 Advanced SC partnership models 205

6.12 Markov forecasting methods 212

6.13 Case study - using analytics to improve demand forecasting 216

6.14 Review questions 218

6.15 Assignment topics 218

7 Using supply chain analytics to enhance supply chain people processes 220

7.1 What you will learn in this chapter 220

7.2 SC people processes in detail 220

7.3 Segmentation and clustering applied to SC culture 222

7.4 Regression models applied to suitability of leaders 232

7.5 Decision analysis applied to personnel decisions 237

7.6 Markov analysis applied to requisite organisation 243

7.7 Assignment models applied to requisite organisation 247

7.8 Case study - using analytics to improve SC people processes 249

7.9 Review questions 251

7.10 Assignment topics 251

8 How to deal effectively with organisational social issues 253

8.1 What you will learn in this chapter 253

8.2 How to convince managers to act on things that matter 253

8.3 Change management 256

8.4 Acceptance of SC analytics and analysts 264

8.5 Promotion of the SC analytics service offer 269

8.6 Interventions to improve negative organisational behaviour 271

8.7 Selling and engagement - the extended role of the business analyst 276

8.8 Case study - sometimes things go 'off the rails' 278

8.9 Review questions 282

8.10 Assignment topics 282

Appendix 284

Index 297

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