## Matching Supply with Demand: An Introduction to Operations Management, Fourth Edition

By Gérard Cachon and Christian Terwiesch

**Table of Contents:**

Chapter 1

Introduction 1

1.1 Learning Objectives and Framework 3

1.2 Road Map of the Book 6

Chapter 2

The Process View of the Organization 10

2.1 Presbyterian Hospital in Philadelphia 10

2.2 Three Measures of Process Performance 14

2.3 Little’s Law 16

2.4 Inventory Turns and Inventory Costs 19

2.5 Five Reasons to Hold Inventory 23

Pipeline Inventory 23

Seasonal Inventory 24

Cycle Inventory 25

Decoupling Inventory/Buffers 26

Safety Inventory 26

2.6 The Product–Process Matrix 27

Chapter 3

Understanding the Supply Process: Evaluating Process Capacity 33

3.1 How to Draw a Process Flow Diagram 34

3.2 Bottleneck, Process Capacity, and Flow Rate (Throughput) 39

3.3 How Long Does It Take to Produce a Certain Amount of Supply? 41

3.4 Process Utilization and Capacity Utilization 42

3.5 Workload and Implied Utilization 44

3.6 Multiple Types of Flow Units 45

Chapter 4

Estimating and Reducing Labor Costs 57

4.1 Analyzing an Assembly Operation 57

4.2 Time to Process a Quantity X Starting with an Empty Process 59

4.3 Labor Content and Idle Time 61

4.4 Increasing Capacity by **Line Balancing** 64

4.5 Scale Up to Higher Volume 67

Increasing Capacity by Replicating the Line 68

Increasing Capacity by Selectively Adding Workers 68

Increasing Capacity by Further Specializing Tasks 70

Chapter 5

Batching and Other Flow Interruptions: Setup Times and the Economic Order Quantity Model 81

5.1 The Impact of Setups on Capacity 82

5.2 Interaction between Batching and Inventory 85

5.3 Choosing a Batch Size in the Presence of Setup Times 88

5.4 Setup Times and Product Variety 91

5.5 Setup Time Reduction 93

5.6 Balancing Setup Costs with Inventory Costs: The EOQ Model 94

5.7 Observations Related to the Economic Order Quantity 99

Chapter 6

The Link between Operations and Finance 109

6.1 Paul Downs Cabinetmakers 110

6.2 Building an ROIC Tree 111

6.3 Valuing Operational Improvements 116

6.4 Analyzing Operations Based on Financial Data 119

Chapter 7

Quality and Statistical Process Control 125

7.1 The Statistical Process Control Framework 126

7.2 Capability Analysis 128

Determining a Capability Index 129

Predicting the Probability of a Defect 132

Setting a Variance Reduction Target 134

Process Capability Summary and Extensions 135

7.3 Conformance Analysis 135

7.4 Investigating Assignable Causes 139

7.5 Defects with Binary Outcomes: p-Charts 141

7.6 Impact of Yields and Defects on Process Flow 141

Rework 143

Eliminating Flow Units from the Process 143

Cost Economics and Location of Test Points 144

Defects and Variability 145

7.7 A Process for Improvement 146

Chapter 8

Lean Operations and the Toyota Production System 149

8.1 The History of Toyota 149

8.2 TPS Framework 150

8.3 The Seven Sources of Waste 151

8.4 JIT: Matching Supply with Demand 155

Achieve One-Unit-at-a-Time Flow 155

Produce at the Rate of Customer Demand 155

Implement Pull Systems 156

8.5 Quality Management 158

8.6 Exposing Problems through Inventory Reduction 159

8.7 Flexibility 160

8.8 Standardization of Work and Reduction of Variability 162

8.9 Human Resource Practices 163

8.10 Lean Transformation 165

Chapter 9

Variability and Its Impact on Process Performance: Waiting Time Problems 168

9.1 Motivating Example: A Somewhat Unrealistic Call Center 169

9.2 Variability: Where It Comes From and How It Can Be Measured 171

9.3 Analyzing an Arrival Process 173

Stationary Arrivals 175

Exponential Interarrival Times 177

Nonexponential Interarrival Times 179

Summary: Analyzing an Arrival Process 179

9.4 Processing Time Variability 179

9.5 Predicting the Average Waiting Time for the Case of One Resource 181

9.6 Predicting the Average Waiting Time for the Case of Multiple Resources 185

9.7 Service Levels in Waiting Time Problems 188

9.8 Economic Implications: Generating a Staffing Plan 189

9.9 Impact of Pooling: Economies of Scale 193

9.10 Reducing Variability 196

Ways to Reduce Arrival Variability 196

Ways to Reduce Processing Time Variability 197

Chapter 10

The Impact of Variability on Process Performance: Throughput Losses 205

10.1 Motivating Examples: Why Averages Do Not Work 205

10.2 Ambulance Diversion 206

10.3 Throughput Loss for a Simple Process 207

10.4 Customer Impatience and Throughput Loss 211

10.5 Several Resources with Variability in Sequence 213

The Role of Buffers 214

Chapter 11

Scheduling to Prioritize Demand 220

11.1 Scheduling Timeline and Applications 221

11.2 Resource Scheduling—Shortest Processing Time 222

Performance Measures 223

First-Come-First-Served vs. Shortest Processing Time 224

Limitations of Shortest Processing Time 228

11.3 Resource Scheduling with Priorities— Weighted Shortest Processing Time 230

11.4 Resource Scheduling with Due Dates— Earliest Due Date 232

11.5 Theory of Constraints 234

11.6 Reservations and Appointments 236

Scheduling Appointments with Uncertain Processing Times 237

No-Shows 239

Chapter 12

Project Management 245

12.1 Motivating Example 245

12.2 Critical Path Method 247

12.3 Computing Project Completion Time 248

12.4 Finding the Critical Path and Creating a Gantt Chart 249

12.5 Computing Slack Time 250

12.6 Dealing with Uncertainty 253

Random Activity Times 253

Potential Iteration/Rework Loops 256

Decision Tree/Milestones/Exit Option 256

Unknown Unknowns 257

12.7 How to Accelerate Projects 257

Chapter 13

Forecasting 261

13.1 Forecasting Framework 262

13.2 Evaluating the Quality of a Forecast 266

13.3 Eliminating Noise from Old Data 269

Naïve Model 269

Moving Averages 270

Exponential Smoothing Method 271

Comparison of Methods 273

13.4 Time Series Analysis—Trends 274

13.5 Time Series Analysis—Seasonality 279

13.6 Expert Panels and Subjective Forecasting 285

Sources of Forecasting Biases 287

13.7 Conclusion 287

Chapter 14

Betting on Uncertain Demand: The Newsvendor Model 290

14.1 O’Neill Inc. 291

14.2 The Newsvendor Model: Structure and Inputs 293

14.3 How to Choose an Order Quantity 295

14.4 Performance Measures 299

Expected Leftover Inventory 300

Expected Sales 301

Expected Lost Sales 301

Expected Profit 303

In-Stock Probability and Stockout

Probability 303

14.5 How to Achieve a Service Objective 304

14.6 How to Construct a Demand Forecast 304

14.7 Managerial Lessons 309

Chapter 15

Assemble-to-Order, Make-to-Order, and Quick Response with Reactive Capacity 320

15.1 Evaluating and Minimizing the Newsvendor’s Demand–Supply Mismatch Cost 321

15.2 When Is the Mismatch Cost High? 323

15.3 Reducing Mismatch Costs with Make-to-Order 326

15.4 Quick Response with Reactive

Capacity 327

Chapter 16

Service Levels and Lead Times in Supply Chains: The Order-up-to Inventory Model 337

16.1 Medtronic’s Supply Chain 338

16.2 The Order-up-to Model Design and Implementation 340

16.3 The End-of-Period Inventory Level 343

16.4 Choosing Demand Distributions 345

16.5 Performance Measures 348

In-Stock and Stockout Probability 348

Expected On-Hand Inventory 350

Pipeline Inventory/Expected On-Order Inventory 351

Expected Back Order 351

16.6 Choosing an Order-up-to Level to Meet a Service Target 353

16.7 Choosing an Appropriate Service Level 354

16.8 Controlling Ordering Costs 357

16.9 Managerial Insights 361

Chapter 17

Risk-Pooling Strategies to Reduce and

Hedge Uncertainty 368

17.1 Location Pooling 368

Pooling Medtronic’s Field Inventory 369

Medtronic’s Distribution Center(s) 373

Electronic Commerce 374

17.2 Product Pooling 375

17.3 Lead Time Pooling: Consolidated Distribution and Delayed Differentiation 381

Consolidated Distribution 382

Delayed Differentiation 387

17.4 Capacity Pooling with Flexible Manufacturing 389

Chapter 18

Revenue Management with Capacity Controls 402

18.1 Revenue Management and Margin Arithmetic 402

18.2 Protection Levels and Booking Limits 404

18.3 Overbooking 409

18.4 Implementation of Revenue Management 412

Demand Forecasting 412

Dynamic Decisions 412

Variability in Available Capacity 412

Reservations Coming in Groups 412

Effective Segmenting of Customers 412

Multiple Fare Classes 413

Software Implementation 413

Variation in Capacity Purchase: Not All

Customers Purchase One Unit of Capacity 413

Chapter 19

Supply Chain Coordination 421

19.1 The Bullwhip Effect: Causes and Consequences 421

Order Synchronization 424

Order Batching 425

Trade Promotions and Forward Buying 426

Reactive and Overreactive Ordering 430

Shortage Gaming 431

19.2 The Bullwhip Effect: Mitigating Strategies 432

Sharing Information 432

Smoothing the Flow of Product 433

Eliminating Pathological Incentives 433

Using Vendor-Managed Inventory 434

The Countereffect to the Bullwhip Effect:

Production Smoothing 435

19.3 Incentive Conflicts in a Sunglasses Supply Chain 437

19.4 Buy-Back Contracts 440

19.5 More Supply Chain Contracts 443

Quantity Discounts 443

Options Contracts 444

Revenue Sharing 444

Quantity Flexibility Contracts 444

Price Protection 445

Appendix A Statistics Tutorial 449

Appendix B Tables 456

Appendix C Evaluation of the Expected

Inventory and Loss Functions 472

Appendix D Equations and

Approximations 474

Appendix E Solutions to Selected Practice Problems 482

Glossary 507

References 515

Index of Key “How to” Exhibits 518

Summary of Key Notation and

Equations 519

Index 523