Matching. Supply with. Demand. An Introduction to. Operations Management.
Third Edition. Gerard Cachon. The Wharton School,. University of Pennsylvania.
Matching Supply with Demand An Introduction to Operations Management Third Edition
Gerard Cachon The Wharton School, University of Pennsylvania
Christian Terwiesch The Wharton School, University of Pennsylvania
Me Gravu Hill
McGraw-Hill Irwin
Table of Contents Chapter 1 Introduction 1 1.1 1.2
4.5
Learning Objectives and Framework Road Map of the Book 6
Chapter 2 The Process View of the Organization 2.1 2.2 2.3 2.4 2.5
2.6 2.7 2.8 2.9
The Product-Process Matrix Summary 29 Further Reading 29 Practice Problems 29
3
10
26
27
Chapter 3 Understanding the Supply Process: Evaluating Process Capacity 32 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8
How to Draw a Process Flow Diagram 33 Bottleneck, Process Capacity, and Flow Rate (Throughput) 38 How Long Does It Take to Produce a Certain Amount of Supply? 40 Process Utilization and Capacity Utilization 41 Workload and Implied Utilization 43 Multiple Types of Flow Units 44 Summary 48 Practice Problems 50
Chapter 4 Estimating and Reducing Labor Costs 56 4.1 Analyzing an Assembly Operation 56 4.2 Time to Process a Quantity X Starting with an Empty Process
58
4.3 Labor Content and Idle Time 60 4.4 Increasing Capacity by Line Balancing 63 xiv
66
Increasing Capacity by Replicating the Line 67 Increasing Capacity by Selectively Adding Workers 67 Increasing Capacity by Further Specializing Tasks 69
Presbyterian Hospital in Philadelphia 10 Three Measures of Process Performance 15 Little's Law 16 Inventory Turns and Inventory Costs 19 Five Reasons to Hold Inventory 23 Pipeline Inventory 23 Seasonal Inventory 24 Cycle Inventory 25 Decoupling Inventory/Buffers Safety Inventory 26
Scale Up to Higher Volume
4.6 4.7 4.8
Summary 72 Further Reading 74 Practice Problems 74
Motivating Example 80 Critical Path Method 82 Computing Project Completion Time 83 Finding the Critical Path and Creating a Gantt Chart 84 Computing Slack Time 85 Dealing with Uncertainty 88 Random Activity Times 88 Potential Iteration/Rework Loops 91 Decision Tree/Milestones/Exit Option .91 Unknown Unknowns 92
5.7 5.8 5.9
How to Accelerate Projects 92 Literature/Further Reading 94 Practice Problems 94
Chapter 6 The Link between Operations and Finance 96 6.1 6.2 6.3 6.4 6.5 6.6 6.7
Paul Downs Cabinetmakers 97 Building an ROIC Tree 98 Valuing Operational Improvements 103 Analyzing Operations Based on Financial Data 106 Summary 111 Further Reading 112 Practice Problems 112
Chapter 7 Batching and Other Flow Interruptions: Setup Times and the Economic Order Quantity Model 114 7.1 The Impact of Setups on Capacity 115
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Table of Contents xv
7.2
Interaction between Batching and Inventory 118 7.3 Choosing a Batch Size in the Presence of Setup Times 121 7.4 Setup Times and Product Variety 124 7.5 Setup Time Reduction 125 7.6 Balancing Setup Costs with Inventory Costs: The EOQ Model 126 7.7 Observations Related to the Economic Order Quantity 130 7.8 Other Flow Interruptions: Buffer or Suffer 134 7.9 Summary 136 7.10 Further Reading 137 7.11 Practice Problems 137
Chapter 8 Variability and Its Impact on Process Performance: Waiting Time Problems 8.1
144
Motivating Example: A Somewhat Unrealistic Call Center 145 8.2 Variability: Where It Comes From and How It Can Be Measured 147 8.3 Analyzing an Arrival Process 149 Stationary Arrivals 151 Exponential Interarrival Times 153 Nonexponential Interarrival Times 154 Summary: Analyzing an Arrival Process 155 8.4 Processing Time Variability 155 8.5 Predicting the Average Waiting Time for the Case of One Resource 157 8.6 Predicting the Average Waiting Time for the Case of Multiple Resources 161 8.7 Service Levels in Waiting Time Problems 164 8.8 Economic Implications: Generating a Staffing Plan 165 8.9 Impact of Pooling: Economies of Scale 168 8.10 Priority Rules in Waiting Lines 172 Processing-Time-Dependent Priority Rules 172 Processing-Time-Independent Priority Rules 172 8.11 Reducing Variability 173 Ways to Reduce Arrival Variability 173 Ways to Reduce Processing Time Variability 174 8.12 Summary 176 8.13 Further Reading 177 8.14 Practice Problems 177
Chapter 9 The Impact of Variability on Process Performance: Throughput Losses 183 9.1 9.2 9.3 9.4 9.5
9.6 9.7 9.8
Motivating Examples: Why Averages Do Not Work 183 Ambulance Diversion 184 Throughput Loss for a Simple Process 185 Customer Impatience and Throughput Loss 189 Several Resources with Variability in Sequence 191 The Role ofBuffers 192 Summary 194 Further Reading 195 Practice Problems 195
Chapter 10 Quality Management, Statistical Process Control, and Six-Sigma Capability 198 10.1 10.2 10.3 10.4
Controlling Variation: Practical Motivation 199 The Two Types of Variation 200 Constructing Control Charts 202 Control Chart Example from a Service Setting 205 10.5 Design Specifications and Process Capability 208 10.6 Attribute Control Charts 210 10.7 Robust Process Design 211 10.8 Impact of Yields and Defects on Process Flow 214 Rework 215 Eliminating Flow Units from the Process 216 Cost Economics and Location of Test Points 217 Defects and Variability 218 10.9 A Process for Improvement 218 10.10 Further Reading 220 10.11 Practice Problems 220
Chapter 11 Lean Operations and the Toyota Production System 222 11.1 11.2 11.3 11.4
The, History of Toyota 222 TPS Framework 224 The Seven Sources of Waste 225 JIT: Matching Supply with Demand 228 Achieve One-Unit-at-a-Time Flow 228 Produce at the Rate of Customer Demand 229 Implement Pull Systems 229
xvi
Table of Contents
11.5 11.6
Quality Management 231 Exposing Problems through Inventory Reduction 233 11.7 Flexibility 234 11.8 Standardization of Work and Reduction of Variability 236 11.9 Human Resource Practices 236 11.10 Lean Transformation 237 11.11 Further Reading 239 11.12 Practice Problems 239
Chapter 14 Service Levels and Lead Times in Supply Chains: The Order-up-to Inventory Model 287 14.1 14.2 14.3 14.4 14.5
Chapter 12 Betting on Uncertain Demand: The Newsvendor Model 240 12.1 12.2 12.3 12.4 12.5
O'Neill Inc. 241 An Introduction to the Newsvendor Model 243 Constructing a Demand Forecast 243 The Expected Profit-Maximizing Order Quantity 250 Performance Measures 254 Expected Lost Sales 255 Expected Sales 256 Expected Leftover Inventory 25 7 Expected Profit 257 In-Stock Probability and Stockout Probability 258 '
12.6
Choosing an Order Quantity to Meet a Service Objective 259 12.7 Managerial Lessons 259 12.8 Summary 262 12.9 Further Reading 263 12.10 Practice Problems 263
Chapter 13 Assemble-to-Order, Make-to-Order, and Quick Response with Reactive Capacity 270 13.1
13.2 13.3 13.4 13.5 13.6 13.7
Evaluating and Minimizing the Newsvendor's Demand-Supply Mismatch Cost 271 When Is the Mismatch Cost High? 273 Reducing Mismatch Costs with Make-toOrder 276 Quick Response with Reactive Capacity 277 Summary 281 Further Reading 282 Practice Problems 282
14.6 14.7 14.8 14.9 14.10 14.11 14.12
Medtronic's Supply Chain 288 The Order-up-to Model Design and Implementation 291 The End-of-Period Inventory Level 294 Choosing Demand Distributions 295 Performance Measures 299 In-Stock and Stockout Probability 299 Expected Back Order 301 Expected On-Hand Inventory 302 Pipeline Inventory/Expected On-Order Inventory 303 Choosing an Order-up-to Level to Meet a Service Target 304 Choosing an Appropriate Service Level 304 Controlling Ordering Costs 308 Managerial Insights 311 Summary 313 Further Reading 314 Practice Problems 314
Chapter 15 Risk-Pooling Strategies to Reduce and Hedge Uncertainty 319 15.1
Location Pooling
319
Pooling Medtronic s Field Inventory 320 Medtronic s Distribution Center(s) 324 Electronic Commerce 325
15.2 15.3
15.4 15.5 15.6 15.7
Product Pooling 326 Lead Time Pooling: Consolidated Distribution and Delayed Differentiation 333 Consolidated Distribution 333 Delayed Differentiation 338 Capacity Pooling with Flexible Manufacturing 341 Summary 347 Further Reading 348 Practice Problems 348
Chapter 16 Revenue Management with Capacity Controls 353 16.1 16.2
Revenue Management and Margin Arithmetic 353 Protection Levels and Booking Limits
355
Table of Contents xvii
16.3 Overbooking 361 16.4 Implementation of Revenue Management 363
Material 404 Agriculture, Fishing, and Forestry People 405
18.2 18.3
Demand Forecasting 363 Dynamic Decisions 364 Variability in Available Capacity 364 Reservations Coming in Groups 364 Effective Segmenting of Customers 364 Multiple Fare Classes 364 Software Implementation 365 Variation in Capacity Purchase: Not All Customers Purchase One Unit of Capacity
18.4 18.5 18.6
365
16.5 Summary 367 16.6 Further Reading 368 16.7 Practice Problems 368
Chapter 17 17.1
373
19.4
The Bullwhip Effect: Causes and Consequences 373 Order Synchronization 3 76 Order Batching 377 Trade Promotions and Forward Buying 3 78 Reactive and Overreactive Ordering 382 Shortage Gaming 383
17.2 Bullwhip Effect: Mitigating Strategies
384
Sharing Information 384 Smoothing the Flow of Product 385 Eliminating Pathological Incentives 385 Using Vendor-Managed Inventory 386 The Countereffect to the Bullwhip Effect: Production Smoothing 388
17.6 Summary 397 17.7 Further Reading 398 17.8 Practice Problems 398
18.1
Sustainability: Background Energy 401 Water 404
Process Timing 418 Process Location 419 Process Standardization
19.5
401
y
19.6 19.7
421
Unsuccessful Business Model Innovation 422 Summary 423 Further Reading 423
/
Appendix A Statistics Tutorial 424 Appendix B Tables 433 Appendix C Evaluation of the Loss Function 445 Appendix D Equations and Approximations 448 Appendix E Solutions to Selected Practice Problems 456 Glossary
482 492
Index of Key "How to" Exhibits
401
405
Zipcar and Netflix 410 Innovation and Value Creation 412 The Customer Value Curve: ^ The Demand Side of Business Model Innovation 414 Solutions: The Supply Side of Business Model Innovation 417
References
Chapter 18
Sustainable Operations
Sustainability: The Business Case Sustainability and Operations Management 406 Summary 409 Further Reading 409 Practice Problems 409
Chapter 19 Business Model Innovation 410 19.1 19.2 19.3
