Modelling Supply Chain Dynamics

This book discusses supply chain management, focusing on developments within modelling the dynamic behaviour of the supply chain. Aimed at postgraduate students, researchers and practitioners, this book provides an in-depth knowledge of the dynamics of supply chains. Business trends such as the globalisation process and the increase of competition across many industrial sectors have forced companies to concentrate on their core competences and to outsource those activities in which they do not excel. As a consequence, companies no longer produce and distribute their goods in isolation, but being part of a supply chain or supply network, i.e. a set of interrelated companies who ultimately deliver the goods and services to the final customer. Despite the prevalence of supply chains as the primary form of production and distribution, their performance can be seriously hampered by the complex dynamics resulting from the collaboration and coordination (or lack thereof) among their members. This book provides the reader with modelling tools to understand, analyse and improve the dynamic behaviour of supply chains. It assembles seminal works on supply chain models and recent developments on the topic in order to provide a comprehensive, unified vision of the field for researchers and practitioners who wish to grasp the challenges of supply chain management. Aside presenting the main elements, equations and performance indicators governing the dynamics of a supply chain, and the book addresses issues such as the effect of timely and accurately sharing the information across members, the influence of restrictions on the productive capacities of their members, or the impact of the variability of the lead times, among others. Furthermore, more complex supply chain structures such as non-serial supply networks or closed-loop supply chains are modelled and discussed. Relevant managerial insights regarding the causes of supply chain underperformance, as well as avenues to improve their efficiency can be extracted from the resulting models. Preface Organisation of the Book Acknowledgements Contents Acronyms 1 Introduction to Supply Chains 1.1 Introduction 1.2 The Rise of Supply Chains 1.2.1 A Definition of Supply Chain 1.2.2 Factors Facilitating Supply Chains 1.2.3 Main Elements of a Supply Chain 1.3 New Problems, New Opportunities: The Bullwhip Effect 1.3.1 The Bullwhip Effect 1.3.2 Barriers to Overcome the Bullwhip Effect 1.4 Modelling Supply Chain Dynamics 1.5 Summary 1.6 Further Readings References 2 Supply Chain Management 2.1 Introduction 2.2 Main Activities in SCM: The SCOR Model 2.3 Demand Modelling and Forecast 2.3.1 Demand Modelling 2.3.2 Forecasting Techniques 2.3.3 Other Forecasting Techniques 2.3.4 Measuring the Error in the Estimations 2.3.5 MMSE Estimation 2.4 Source: Inventory Management 2.4.1 Forecasting the Demand 2.4.2 Estimating the On-Hand Inventory 2.5 Summary 2.6 Further Readings References 3 Supply Chain Dynamics 3.1 Introduction 3.2 The Dynamic Behaviour of a SC 3.3 Behavioural Causes 3.4 Operational Causes 3.5 Approaches to Mitigate the Bullwhip Effect 3.5.1 Behavioural Causes 3.5.2 Operational Causes 3.6 Performance Measures in SC/SCD 3.6.1 Measuring Order Variability 3.6.2 Measuring Inventory Variability 3.6.3 Slope Metrics 3.6.4 Other Metrics 3.7 Summary 3.8 Further Readings References 4 Basic Models for SC Dynamics 4.1 Introduction 4.2 The Role of Modelling in OM/SCM 4.3 Elements of a Basic Supply Chain Model 4.4 Measuring the Bullwhip Effect 4.5 Putting All Pieces Together 4.5.1 Inventory Update 4.5.2 Work in process Update 4.5.3 Issuing the Order 4.5.4 Demand Estimates 4.5.5 A Simple Simulation Model 4.6 The Model at Supply Chain Level 4.6.1 An Expression of the BWE for a Two- and Three-Echelon SC 4.7 Implications of the Model: The Causes of Bullwhip Effect Revisited 4.8 Summary 4.9 Further Readings References 5 The Effect of the Quality of Information in SCD 5.1 Introduction 5.2 Information Sharing 5.2.1 Expressing the Orders as a Function of the Customer Demand 5.2.2 Expressing the Orders Across the Supplier Lead Time as a Function of the Customer Demand 5.2.3 Orders Average and Standard Deviation for the No Info Sharing Scenario 5.2.4 Orders Average and Standard Deviation for the Info Sharing Scenario 5.2.5 The Impact of Information Sharing on Inventory 5.2.6 Using Past Orders to Forecast Demand 5.3 The Effect of Information Timeliness 5.3.1 Demand Estimate with Time-Lagged Data 5.3.2 The Error When Estimating with Time-Lagged Data 5.3.3 The Bullwhip Effect with Time-Lagged Data 5.4 Inaccuracies in the Inventory Information (IRI) 5.4.1 Shrinkage 5.4.2 Product Misplacement 5.4.3 Transaction Errors 5.5 Advance Demand Information 5.5.1 Perfect ADI in Make-to-Stock SCs 5.5.2 The Case of Imperfect ADI 5.6 Conclusions 5.7 Further Readings References 6 Enriching SC Models 6.1 Introduction 6.2 Revisiting Some Hypotheses in the Basic SC Model 6.2.1 Backlogged Demand 6.2.2 Returned Orders 6.3 Variable Lead Times 6.3.1 Estimating Both Demand and Lead Times Using the Moving Average 6.3.2 Simulation Models 6.4 Order Crossover 6.5 Capacitated SCs 6.5.1 Modelling Capacity Limits 6.5.2 Workload-Dependent Lead Times 6.5.3 Combining Capacity Limitation with Load-Depending Lead Times 6.6 Conclusions 6.7 Further Readings References 7 Closed-Loop Supply Chain 7.1 Introduction 7.2 Remanufacturing Scenarios 7.3 Market and Remanufacturing Visibility 7.3.1 Estimating the Flow of the Returns 7.4 Uncertainty in the Returns 7.4.1 No Consideration of the Return Flow 7.4.2 Estimation of the Return Flow 7.5 Conclusions 7.6 Further Readings References 8 Modelling Complex SC Structures 8.1 Introduction 8.2 Several Retailers/Order Batching 8.2.1 Case 1: Independent Retailers 8.2.2 Case 2: Positively Correlated Orders 8.2.3 Comparing the Cases 8.3 Several Retailers with a Competing Market 8.3.1 Non-MMSE Estimations in a Competing Market 8.4 Conclusions 8.5 Further Readings References 9 Further Issues in Modelling SC Dynamics 9.1 Introduction 9.2 Financial Considerations in SC Dynamics 9.3 Enhanced Forms of SC Collaboration 9.4 Supply Chain 4.0 9.5 Supply Chain Resilience and the Ripple Effect 9.6 Conclusions References Appendix A Useful Calculus Formulae A.1 Geometric Series A.2 Power Series A.3 Leibniz's Rule Appendix B Basic Probability Tools B.1 Random Variables B.1.0.1 Function of a RV B.1.1 Main Characteristics of a RV B.1.1.1 Expected Value B.1.1.2 Variance of an RV B.2 Random Vectors B.2.1 Properties of the Random Vectors B.2.2 Conditional Probability and Independence B.2.3 Law of Total Expectation B.2.4 Law of Total Variance B.2.5 Random Sum B.3 Independence of RVs B.4 Useful Distributions B.4.1 Bernoulli B.4.2 Binomial B.4.3 Normal B.4.4 Gamma Appendix C Time Series Basics for Demand Modelling C.1 Stationary Time Series C.1.1 AR(1) Series C.1.1.1 Mean, Variance and Covariance C.1.2 ARMA(p, q) Series C.2 Minimum Mean Square Estimation (MMSE) Index