Towards Supply Chain Risk Analytics (eBook)

Iris Heckmann started as a research scientist at the FZI Research Centre for Information Technology in Karlsruhe and headed the department of Risk-aware Logistics: Supply Chain and Health. Since April 2016 she is division head of the research division Information Process Engineering. Her research focuses on developing mathematical optimization approaches for supply chain risk analytics.

Acknowledgments 5
Abstract 7
Contents 9
List of Figures 14
List of Tables 19
1 Introduction 21
1.1 Motivation for Beginners 21
1.2 Advanced Risk 25
1.3 The Real Introduction: The Name of the Game 28
1.4 Outline and Course of Discussion 32
Part I Supply Chain Risk Concepts – Fundamentals 36
2 The Genesis of Supply Chain Risk 37
2.1 Logistics Innovations – A Blessing and a Curse 38
2.2 Supply Chain Disruptions 41
2.2.1 Environmental Disruptions 47
2.2.2 Economic Disruptions 48
2.2.3 Socio-Geopolitical Disruptions 51
2.2.4 Technological Disruptions 52
2.3 Coping with Risk 53
2.3.1 Enterprise Risk 53
2.3.2 Following the footsteps of Management 55
2.3.3 Identification needs Quantification – Quantification needs Definition 58
3 A New Definition of Supply Chain Risk 60
3.1 The Evolution of Risk 62
3.2 Requirements for a Definition of Supply Chain Risk 64
3.3 Existing Approaches of Supply Chain Risk Definitions 65
3.4 Core Characteristics of Supply Chain Risk 67
3.4.1 Risk Objective 69
3.4.2 Risk Exposition 73
3.4.3 Risk Attitude 89
3.5 Re-defining Supply Chain Risk 91
4 Supply Chain Risk Analysis – Common Flaws, Core Areas, and Main Tasks 93
4.1 The Risk of Supply Chain Risk Analysis 95
4.1.1 Biases of Risk Identification 99
4.1.2 Biases of Risk Countermeasures 104
4.1.3 Breaking of Biases 111
4.2 Main Elements of Supply Chain Risk Analysis 112
4.2.1 Analysis of Potential Triggers 112
4.2.2 Analysis of Performance Measurement 123
4.2.3 Analysis of Supply Chain Constitution 133
4.3 Tasks of Supply Chain Risk Analysis 143
5 Supply Chain Risk Analytics 146
5.1 Supply Chain Risk Analytics – Concept Definition 147
5.2 The Value of Supply Chain Risk Analytics 150
5.2.1 Risk Acceptance 152
5.2.2 Risk Reduction Measures 155
5.2.3 Risk Spreading Measures 164
5.3 Quantification Measures for Supply Chain Risk 167
5.3.1 Deviation Measures 168
5.3.2 Downside Risk 168
5.3.3 Expected Values 169
5.3.4 Probability and other measures 170
5.4 Risk-aware Supply Chain Optimization 172
5.4.1 Modeling Approaches 173
5.4.2 Solution Techniques 176
5.5 Research Gaps 176
Part II Supply Chain Risk Identification and Assessment – Simulation-based Framework 178
6 Simulation for Supply Chain Analysis 179
6.1 Simulation at a Glance 181
6.1.1 Basics 181
6.1.2 Technical entities of Simulation Tools 185
6.1.3 Simulation Paradigms 186
6.2 Simulation of Supply Chain Problems 189
6.3 Simulation and Optimization 190
7 Design, Metamodeling, and Analysis of Simulation Experiments 194
7.1 Meta-Models 197
7.2 Designs 200
7.2.1 Purpose of Design 201
7.2.2 Classic Factorial Designs 206
7.2.3 Design construction 209
7.3 Analysis 211
7.3.1 Regression Analysis 212
7.3.2 Method of Least Squares 213
7.3.3 Analysis of Variance (ANOVA) 215
7.3.4 Measures of Factor Effects 215
7.4 Illustrative Examples 219
7.4.1 A 2 Full Factorial Experiment for the Analysis of Production Characteristics 219
7.4.2 A 2 Fractional Factorial Experiment for the Analysis of Production Characteristics 224
7.5 Cautions with the Design of Experiments 226
8 A Simulation-based Approach for Supply Chain Risk Analysis (SimSCRF) 229
8.1 Requirements 230
8.2 A New Approach for Supply Chain Risk Analysis – Basic Models 232
8.2.1 Scenario-based Procedure 232
8.2.2 Screening Procedure 239
8.2.3 Procedure for Risk Quantification 241
8.3 Summarized Main Features of the Approach 245
9 Representative Master Planning Module for Supply Chains 247
9.1 Planning Tasks of Supply Chains 248
9.2 Mathematical formulation of a Master Planning Problem 250
9.2.1 Determinants 253
9.2.2 Objective Function 259
9.2.3 Restrictions 260
10 A Conceptual Information Meta-Model for Supply Chains 273
10.1 Requirements for a Supply Chain Information Meta-Model 274
10.2 Related Work 276
10.3 Modeling Supply Chain Information 278
10.3.1 Concepts 278
10.3.2 Properties 280
10.3.3 Relations 280
10.3.4 Constraints 281
10.4 A Supply Chain Model 283
11 A Real Case Evaluation of the SimSCRF Approach 289
11.1 The Case 291
11.2 Contemporary Risk Quantification 293
11.3 A new View on Supply Chain Risk Analysis 298
11.4 Supply Chain Risk Analysis 300
11.4.1 Work Flow 300
11.4.2 Effect Analysis 312
11.4.3 Risk Line Identification 315
11.5 Conclusions and Outlook 320
Part III Strategic Supply Chain Risk Mitigation – Optimization Approaches 322
12 Embedding Comprehensive Risk in Supply Chain Network Design Models 323
12.1 Mathematical Model Formulations 326
12.1.1 Notations 326
12.1.2 The Risk-aware Capacitated Plant Location Problem (CPLP-Risk) 329
12.2 Illustrative Example 337
12.2.1 Data Input 338
12.2.2 Solution Plausibility 343
12.2.3 The Value of Risk Consideration 349
12.2.4 Quantification of Supply Chain Risk 353
12.3 Preliminary Computational Results 355
12.4 Model Extensions 364
12.4.1 Model Extensions for the Affected Supply Chain 364
12.4.2 Model Extensions for the Risk Objective 367
12.4.3 Model Extensions for the Risk Attitude 368
12.5 Conclusions and Outlook 370
13 Conclusions and Outlook 372
13.1 Conlusions 373
13.2 Outlook 378
Bibliography 381