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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