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