PART ONE Introduction to Supply Chain Management 1
1 Supply Chain Management, Integrated Planning, and Models 3
1.1 Fundamentals of Supply Chain Management 5
Supply Chain Networks 6
Integrated Supply Chain Planning 7
Objectives of Supply Chain Management 8
1.2 Overview of Supply Chain Models and Modeling Systems 10
1.3 Supply Chain Modeling Incorporates Concepts from Several Management Disciplines 12
Strategy Formation and the Theory of the Firm 13
Logistics, Production, and Inventory Management 17
Management Accounting 19
Demand Forecasting and Marketing Science 20
Operations Research 22
1.4 Innovations in Information Technology Require and Support Supply Chain Modeling 23
1.5 Organizational Adaptation to Integrated Supply Chain Management and Modeling 25
Notes 26
References 27
2 Information Technology 29
2.1 Developments in Enterprise Resource Planning Systems and E-Commerce 30
ERP Systems 31
E-Commerce 32
2.2 Comparison of Transactional IT and Analytical IT 36
Time Frame Addressed 37
Purpose 37
Business Scope 37
Nature of Databases 38
Response Time for Queries 39
2.3 Hierarchy of Supply Chain Systems 40
Components of the Supply Chain System Hierarchy 40
Implications for Business Process Redesign 40
Frequency of Analysis, Cycle Times, and Run Times of Supply Chain Systems 46
Communication Among Supply Chain Systems of Data and Decisions 46
Balancing Centralized and Decentralized Decision Making 53
2.4 Legacy Systems and Legacy Thinking 53
2.5 Final Thoughts 55
Exercises 56
Notes 57
References 59
PART TWO Modeling and Solution Methods 61
Practical Issues of Price Competition 63
3 Fundamentals of Optimization Models: Linear Programming 63
3.1 Linear Programming Modeling Examples 64
Resource Allocation Model 65
Infeasible and Unbounded Models 69
Spreadsheet Optimization 70
Multiperiod Resource Allocation Model 72
Network Models 78
3.2 Properties of Linear Programming Models 84
Linearity 85
Separability and Additivity 89
Indivisibility and Continuity 89
Single Objective Function 90
Data Known with Certainty 90
3.3 Interpreting an Optimal Linear Programming Solution 91
Shadow Prices 92
Reduced Cost Cefficients 94
Dual Linear Programming Model 96
Parametric and Sensitivity Analysis 98
3.4 Multiple Objective Optimization 101
3.5 Stochastic Programming 104
Generalizations 109
3.6 Final Thoughts 109
Exercises 110
Notes 113
References 114
Appendix 3A The Simplex Method of Linear Programming 115
4 Fundamentals of Optimization Models: Mixed Integer Programming 125
4.1 Mixed Integer Programming Modeling Vignettes 126
Fixed Costs 127
Economies of Scale 130
Production Changeovers 131
Multiple Choice and Other Nonnumeric Constraints 132
4.2 Distribution Center Location Models 133
DC Location Model 134
Generalizations 138
4.3 Supply Chain Network Optimization Models 139
Strategic Planning at Ajax 139
Generalizations 151
4.4 Designing and Implementing Optimization Modeling Systems for Strategic and Tactical Planning 151
System Design 152
System Implementation 154
4.5 Optimization Software 158
Optimizers 159
Algebraic Modeling Language Development Kits 161
Spradsbeet Optimizers 163
4.6 Final Thoughts 163
Exercises 164
Notes 166
References 167
Appendix 4A The Branch-and-Bound Method for Mixed Integer Programming 169
5 Unified Optimization Methodology for Operational Planning Problems 177
5.1 Heuristic Methods for Combinatorial Optimization Problems 179
Local Delivery Heuristics 180
5.2 Overview of the Unified Optimization Methodology 188
Production Scheduling Example of Decomposition 189
Unified Optimization Methodology 193
5.3 Unified Optimization Methodology Applied to Vehicle Routing 197
Statements of the Optimization Models 198
Numerical Solution 202
Generalizations 205
5.4 Unified Optimization Methodology Applied to Production Scheduling 207
Company Background and Numerical Data 207
Unified Optimization Methodology Specialized to Goodstone s Production Scheduling Problem 209
Production Scheduling Solution 213
5.5 Final Thoughts 218
Generalizations 218
Exercises 219
Notes 222
References 223
6 Supply Chain Decision Databases 225
6.1 Data Aggregations 228
Aggregating Products 229
Aggregating Customers and Markets 231
Recipes, Processes, Resources, and Costs 232
Aggregating Suppliers 232
6.2 Facility Data 232
6.3 Transportation Network Data 237
Transportation Network Submodels 237
Transportation Costs and Capacities 240
Modal Choice and Shipment Sizes 241
Utilities for Generating Networks 242
6.4 Supplier Data 242
Vendor Costs and Constraints 243
6.5 Role of Management Accounting 245
Develop Causal Cost Relationships of Direct and Indirect Costs 247
Activity-Based Costing 248
Connection of ABC to Optimization Models and the Taxonomy of Costs 250
Computation of Transfer Prices, Product and Customer Costs from an Optimal Solution to a Supply Chain Model 250
6.6 Demand Forecasting 257
Background 257
Types of Forecasting Models 258
Demand Data Specifications for Optimization Models 260
Forecasting Software 261
6.7 Global and Policy Data 261
6.8 Model Output Data 262
Management Reports of Output Data 263
Shadow Prices and Reduced Costs 264
Derived Output 265
6.9 Connections Among Supply Chain Decision Databases 266
Scenarios 267
Multiperiod Decision Databases 268
Hierarchies 269
6.10 Graphical Displays of Data Inputs and Outputs 270
6.11 Final Thoughts 271
Exercises 273
Notes 274
References 275
PART THREE APPLICATIONS 277
7 Strategic and Tactical Supply Chain Planning: State-of-the-Art Modeling Applications 279
Taxonomy of Resources 281
7.1 Resources and the Resource-Based View of the Firm 281
Summary of the Resource-Based View of the Firm 282
Connections with Optimization Models 283
7.2 Strategic Analysis of Logistics Supply Chains 286
A Framework for Logistics Strategy Formation 286
Constructing an Optimization Model for Strategic Logistics Planning 289
7.3 Redesigning the Distribution Network of an Electronics Products Company 292
7.4 Strategic Analysis of Manufacturing Supply Chains 294
A Framework for Manufacturing Strategy Formation 294
Constructing an Optimization Model for Strategic Manufacturing Planning 298
7.5 Two Manufacturing Strategy Applications 302
Worldwide Sourcing at Delta Industrial Chemicals 303
Postmerger Consolidation of Consumer Paper Companies 306
7.6 Tactical Planning 310
7.7 Two Tactical Planning Applications 312
Monthly Planning at an Industrial Gases Company 312
Monthly Planning at a Beer Company 315
7.8 Final Thoughts 316
Exercises 317
Notes 319
References 320
8 Strategic and Tactical Supply Chain Planning: Advanced Modeling Applications 323
8.1 Integrating Supply Chain and Demand Management 324
8.2 Price and Location Sensitive Revenue Curves 326
8.3 Integrating Supply Chain and Marketing Models for Consumer Products 330
Consumer Products Supply Chains 331
Modeling the Effects of Marketing Decisions on Demand for Consumer Products 333
Integrating Supply Chain and Marketing Models for Manufacturers of Consumer Products 337
Illustrative Numerical Model 340
8.4 Planning for New Product Introduction and Growth 346
8.5 Optimization Models for Competitive Analysis 349
Structural Analysis of Industries 349
Theory of Industrial Organization 351
A Model of Price Competition 353
Illustrative Numerical Model 355
8.6 Application of Competitive Analysis in the Forest Products Industry 362
8.7 Decision Trees and Stochastic Programming 364
Decision Trees 366
An Inventory Example of Stochastic Programming 370
8.8 Supply Chain Strategies for Managing Product Variety 375
Exploit Component Commonality and Postponement of Product Differentiation 376
Assemble Differentiated Products from Vanilla Boxes 377
Implement Quick Response to Early Sales 378
8.9 Scenario Planning 382
Methodology 382
8.10 Final Thoughts 384
Connections to Optimization Modeling 384
Exercises 386
Notes 387
References 389
9 Integration of Financial and Physical Supply Chains 391
9.1 Optimization Models for Corporate Financial Planning 392
Modeling the Balance Sheet 393
Numerical Example of an Optimization Model for Corporate Financial Planning 395
Model and Methodological Extensions 401
9.2 Financial Planning Issues Facing the Multinational Corporation 402
9.3 A Network Illustration 403
9.4 Financial Flows Model 406
Statement of the Financial Flows Model 408
Financial Flows Model Results 412
9.5 Modeling Exchange Rate Risks 415
9.6 Real Options for Hedging Risks in the Global Economy 419
9.7 Final Thoughts 421
Exercises 422
Notes 426
References 427
10 Operational Supply Chain Planning 429
10.1 Taxonomies of Operational Planning Problems 430
Production Planning and Scheduling 431
Vehicle Routing and Scheduling 438
Human Resources Scheduling 440
10.2 Modeling Systems for Operational Planning 441
System Integration 441
Steps to Follow in Using a System 443
Real-Time Operational Planning 446
Other Uses of a Modeling System 447
Trajning，Learning，and System Evolution 447
10.3 Vehicle Routing System for an E-Commerce Company 448
Company Background 449
Routing System Description and Use 450
Driver Assignment 455
10.4 Production Planning System for a Semiconductor Company 455
Manufacturing and Marketing Background 456
Planning and Modeling Approaches 458
Implementation 461
Results 462
10.5 Simulation Models and Systems 463
Deterministic Simulation 463
Monte Carlo Simulation 463
Simulation Software 468
Simulation versus Optimization 469
10.6 Final Thoughts 470
Exercises 471
Notes 474
References 475
11 Inventory Management 477
11.1 Inventory Theory Models 479
Deterministic Models 479
Probabilistic Models 481
ABC Classification 485
11.2 Incorporating Inventory Management Decisions in Strategic and Tactical Supply Chain Models 486
Incorporating Inventory Management Decisions in Strategic Supply Chain Models 487
Incorporating Inventory Management Decisions in Tactical Supply Chain Models 492
11.3 Inventory Management in Distribution Supply Chains 495
Distribution Scheduling in a Reverse Logistics Company 495
Multiechelon Spare Parts Distribution System at IBM 500
11.4 Inventory Management in Manufacturing Supply Chains 504
Optimizing Inventory across Hewlett-Packard s Printer Supply Chains 504
Optimal Safety Stock Placement in Kodak s Manufacturing Supply Chains 508
11.5 Final Thoughts 512
Exercises 514
Notes 515
References 516
PART FOUR The Future 517
12 Organizational Adaptation to Optimization Modeling Systems 519
12.1 How Organizations Make Decisions 521
The Theory of Rational Choice versus the Reality of Organizational Behavior 522
Uncertainty and Risk 524
Rule-Based Decision Making 524
Deriving Meaning from the Decision Environment 525
Decision-Making Ecologies 526
12.2 Contested Issues about Organizational Decision Making 527
Choice-Based versus Rule-Based Decision Making 528
Clear versus Ambiguous Decision Making 530
Instrumental versus Interpretive Decision Making 535
Supply Chain Management as an Interacting Ecology 538
12.3 Information Technology as Competitive Advantage 539
Recent History of IT as Competitive Advantage 539
Resource-Based Analysis 540
Attributes of IT as Possible Sources of Competitive Advantage 541
Complementary Organizational Resources 544
12.4 Exploitative versus Exploratory IT Developments 547
Acquisition or Development of a Modeling System 548
Use of a Modeling System 549
Enhancement of a Modeling System 550
12.5 Business Process Redesign and IT 550
Modeling Systems Invoke Business Process Redesign 553
12.6 Supply Chain Coordination Processes and Incentive Contracts 557
Selecting Coordination Processes 558
Principal-Agent Theories of Incentives 559
12.7 No Gain without Pain 562
Stages of a Strategic Supply Chain Study 563
Summary 566
12.8 Outlook for the Future of Modeling Systems and Their Applications 567
Exercises 572
Notes 573
References 575
Index 577
Credits 583