Business Process Analytics: Modeling, Simulation, and Design, Fourth Edition
Manuel Laguna and Johan Marklund
Contents
Preface……………………………………………………………………………………………………….xv
- Introduction to Business Process Design……………………………………………1
1.1 What Is a Business Process?………………………………………………………..2
1.1.1 Process Types and Hierarchies………………………………………..3
1.1.2 Determinants of the Process Architecture……………………….5
1.1.3 Workflow Management Systems……………………………………11
1.2 The Essence of Business Process Design……………………………………12
1.2.1 Incremental Process Improvement and Process Design………………………………………………………………14
1.2.2 An Illustrative Example…………………………………………………15
1.3 Business Process Design, Overall Business Performance, and Strategy………………………………………………………………………………19
1.3.1 Business Process Design and Overall Business Performance…………………………………………………………………..19
1.3.2 Business Process Design and Strategy…………………………..20
1.4 Why Do Inefficient and Ineffective Business Processes Exist?…………………………………………………………………………21
1.5 Summary…………………………………………………………………………………..24
Discussion Questions and Exercises……………………………………………………25
References…………………………………………………………………………………………..31
- Data Analytics and Process Improvement………………………………………..33
2.1 Process Management and a Process View…………………………………33
2.1.1 An Illustrative Example: Managing a Document Distribution Process………………………………………………………35
2.1.2 Summary and Final Remarks………………………………………..41
2.2 Data-Driven Process Improvement……………………………………………42
2.2.1 Data Collection………………………………………………………………43
2.2.2 Data Visualization…………………………………………………………45
2.3 Six Sigma Quality Programs……………………………………………………..51
2.3.1 Six Sigma Definitions…………………………………………………….51
2.3.2 The Six Sigma Cost and Revenue Rationale…………………..52
2.3.3 Six Sigma in Product and Process Design………………………57
2.3.4 The Six Sigma Framework……………………………………………..58
2.3.5 Control Charts……………………………………………………………….63
2.3.6 Key Reasons for the Success of Six Sigma………………………72
2.4 Business Process Management………………………………………………….72
2.4.1 Types of BPM…………………………………………………………………75
2.4.2 BPM Lifecycle………………………………………………………………..76
2.4.3 BPM Potential Benefits…………………………………………………..77
2.4.4 Typical Areas of Application………………………………………….77
2.5 Revolutionary versus Evolutionary Change………………………………78
2.6 Summary…………………………………………………………………………………..82
Discussion Questions and Exercises……………………………………………………84
References…………………………………………………………………………………………..91
- A Framework for Business Process Design Projects…………………………94
3.1 Step 1: Case for Action and Vision Statements…………………………..97
3.2 Step 2: Process Identification and Selection……………………………….99
3.3 Step 3: Obtaining Management Commitment………………………….101
3.4 Step 4: Evaluation of Design Enablers………………………………………102
3.4.1 Example: The Internet-Enabling Change at Chase Manhattan Bank……………………………………………104
3.4.2 Example: New Technology as a Change Enabler in the Grocery Industry……………………………………………….105
3.5 Step 5: Acquiring Process Understanding……………………………….107
3.5.1 Understanding the Existing Process…………………………….108
3.5.2 Understanding the Customer……………………………………….111
3.6 Step 6: Creative Process Design……………………………………………….112
3.6.1 Benchmarking……………………………………………………………..113
3.6.2 Design Principles…………………………………………………………116
3.6.3 The Devil’s Quadrangle……………………………………………….124
3.7 Step 7: Process Modeling and Simulation………………………………..124
3.8 Step 8: Implementation of the New Process Design…………………127
3.9 Summary…………………………………………………………………………………129
Discussion Questions and Exercises………………………………………………….130
References…………………………………………………………………………………………133
- Basic Tools for Process Design…………………………………………………………135
4.1 Process Flow Analysis……………………………………………………………..137
4.1.1 General Process Charts………………………………………………..138
4.1.2 Process Flow Diagrams………………………………………………..139
4.1.3 Process Activity Charts………………………………………………..143
4.1.4 Flowcharts……………………………………………………………………144
4.1.5 Service System Maps……………………………………………………147
4.2 Workflow Design Principles and Tools…………………………………….152
4.2.1 Establish a Product Orientation in the Process…………….152
4.2.2 Eliminate Buffers…………………………………………………………154
4.2.3 Establish One-at-a-Time Processing……………………………..155
4.2.4 Balance the Flow to the Bottleneck………………………………156
4.2.5 Minimize Sequential Processing and Handoffs…………..161
4.2.6 Establish an Efficient System for Processing of Work………………………………………………………………………..162
4.2.7 Minimize Multiple Paths through Operations……………..168
4.3 Additional Diagramming Tools……………………………………………….168
4.4 From Theory to Practice: Designing an Order-Picking Process……………………………………………………………..170
4.5 Summary…………………………………………………………………………………172
Discussion Questions and Exercises………………………………………………….172
References…………………………………………………………………………………………179
- Managing Process Flows………………………………………………………………….180
5.1 Business Processes and Flows………………………………………………….180
5.1.1 Throughput Rate………………………………………………………….182
5.1.2 Work-in-Process…………………………………………………………..184
5.1.3 Cycle Time……………………………………………………………………186
5.1.4 Little’s Law…………………………………………………………………..187
5.2 Cycle Time and Capacity Analysis…………………………………………..189
5.2.1 Cycle Time Analysis…………………………………………………….189
5.2.2 Capacity Analysis………………………………………………………..195
5.3 Managing Cycle Time and Capacity………………………………………..200
5.3.1 Cycle Time Reduction………………………………………………….201
5.3.2 Increasing Process Capacity…………………………………………203
5.4 Theory of Constraints………………………………………………………………205
5.4.1 Drum–Buffer–Rope Systems………………………………………..211
5.5 Summary…………………………………………………………………………………212
Discussion Questions and Exercises………………………………………………….213
References…………………………………………………………………………………………221
- Introduction to Queuing Modeling…………………………………………………223
6.1 Queuing Systems, the Basic Queuing Process, and Queuing Strategies……………………………………………………………226
6.1.1 The Basic Queuing Process………………………………………….227
6.1.2 Strategies for Mitigating the Effects of Long Queues……………………………………………………………233
6.2 Analytical Queuing Models…………………………………………………….234
6.2.1 The Exponential Distribution and Its Role in Queuing Theory…………………………………………………………..236
6.2.2 Terminology, Notation, and Little’s Law Revisited………242
6.2.3 Birth-and-Death Processes…………………………………………..247
6.2.4 The M/M/1 Model………………………………………………………259
6.2.5 The M/M/c Model………………………………………………………264
6.2.6 The M/M/c/K Model………………………………………………….268
6.2.7 The M/M/c/∞/N Model……………………………………………..272
6.2.8 Queuing Theory and Process Design…………………………..278
6.3 Summary…………………………………………………………………………………288
Appendix 6A: Mathematical Derivations and Models with Generally Distributed Service Times………………………………………..289
6A.1 Mathematical Derivations of Key Results………………………………..290
6A.1.1 The Exponential Distribution (Section 6.2.1)………………..290
6A.1.2 Birth-and-Death Processes (Section 6.2.3)…………………….290
6A.1.3 The M/M/1 Model (6.2.4)…………………………………………….291
6A.2 Queuing Models with Generally Distributed Service Times……………………………………………………………………………………….292
6A.2.1 The M/G/1 Queuing Model…………………………………………293
6A.2.2 The M/G/∞ Queuing Model………………………………………..293
Discussion Questions and Exercises………………………………………………….295
References…………………………………………………………………………………………307
- Introduction to Simulation………………………………………………………………308
7.1 Simulation Models…………………………………………………………………..310
7.2 Monte Carlo Simulation…………………………………………………………..313
7.3 Discrete-Event Simulation……………………………………………………….317
7.4 Getting Started in Simulation Modeling………………………………….321
7.4.1 Step 1: Defining the Problem………………………………………..321
7.4.2 Step 2: Understanding the Process……………………………….322
7.4.3 Step 3: Determining Goals and Objectives…………………..322
7.4.4 Step 4: Obtaining Support from Management……………..323
7.4.5 Step 5: Choosing Simulation Software…………………………324
7.4.6 Step 6: Determining Data Requirements and Availability………………………………………………………………….324
7.4.7 Step 7: Developing Assumptions about the Problem………………………………………………………………….325
7.4.8 Step 8: Determining Desired Outputs………………………….325
7.4.9 Step 9: Building the Simulation Model…………………………326
7.4.10 Step 10: Project Kickoff…………………………………………………326
7.5 An Illustrative Example…………………………………………………………..327
7.6 Spreadsheet Simulation of a Process………………………………………..335
7.7 Successful Simulation in Practice…………………………………………….337
7.8 When Not to Simulate……………………………………………………………..340
7.9 Summary…………………………………………………………………………………344
Discussion Questions and Exercises………………………………………………….345
References…………………………………………………………………………………………350
- Modeling and Simulating Business Processes with ExtendSim………………………………………………………………………………………..351
8.1 Developing a Simulation Model—Principles and Concepts…………………………………………………………………………..352
8.1.1 Model Verification………………………………………………………..354
8.1.2 Model Validation………………………………………………………….355
8.2 ExtendSim Elements………………………………………………………………..355
8.3 ExtendSim Tutorial: A Basic Queuing Model…………………………..360
8.4 Basic Data Collection and Statistical Analysis………………………….364
8.5 Adding Randomness to Processing Times and the Use of Attributes…………………………………………………………………………….370
8.6 Adding a Second Underwriting Team……………………………………..378
8.7 Modeling Resources and Resource Pools…………………………………381
8.8 Customizing the Animation…………………………………………………….386
8.9 Calculating Activity-Based Costs…………………………………………….387
8.10 Cycle Time Analysis………………………………………………………………..392
8.11 Modeling Advanced Queuing Features…………………………………..396
8.11.1 Blocking……………………………………………………………………….396
8.11.2 Balking………………………………………………………………………..397
8.11.3 Reneging……………………………………………………………………..399
8.11.4 Priorities and Priority Queues……………………………………..401
8.12 Modeling Routing in Multiple Paths and Parallel Paths…………..403
8.12.1 Multiple Paths………………………………………………………………404
8.12.2 Parallel Paths……………………………………………………………….408
8.13 Model Documentation and Enhancements………………………………410
8.14 Summary…………………………………………………………………………………411
Discussion Questions and Exercises………………………………………………….412
References…………………………………………………………………………………………425
- Input and Output Data Analysis……………………………………………………..426
9.1 Dealing with Randomness………………………………………………………427
9.2 Characterizing Probability Distributions of Field Data……………430
9.2.1 Goodness-of-Fit Tests…………………………………………………..434
9.2.2 Using Stat::Fit for Distribution Fitting………………………….434
9.2.3 Choosing a Distribution in the Absence of Sample Data…………………………………………………………………439
9.3 Random Number Generators…………………………………………………..442
9.3.1 The Runs Test………………………………………………………………444
9.4 Generation of Random Variates……………………………………………….446
9.5 Analysis of Simulation Output Data………………………………………..450
9.5.1 Nonterminating Processes…………………………………………..452
9.5.2 Terminating Processes…………………………………………………454
9.5.3 Confidence Intervals…………………………………………………….456
9.5.4 Sample Size Calculation……………………………………………….461
9.5.5 Comparing Output Variables for Different Process Designs……………………………………………………………464
9.6 Modeling and Analysis of Process Design Cases…………………….467
9.6.1 Process Design of a Call Center for Software Support………………………………………………………………………..467
9.6.2 Design of a Hospital Admissions Process…………………….472
9.7 Summary…………………………………………………………………………………484
9.8 Training Cases…………………………………………………………………………484
9.8.1 Case 1: Improving the X-Ray Process at County Hospital……………………………………………………………………….484
9.8.2 Case 2: Process Modeling and Analysis in an Assembly Factory…………………………………………………………489
9.8.3 Case 3: Redesign of a Credit Applications Process…………………………………………………………………………492
9.8.4 Case 4: Redesigning the Adoption Process in a Humane Society…………………………………………………………..493
9.8.5 Case 5: Performance Analysis and Improvement of an Internet Ordering Process…………………………………..496
Appendix 9A: Hypothesis Testing, Confidence Intervals, and Statistical Tables……………………………………………………………….499
9A.1 Goodness-of-Fit Tests (Section 9.2.1)…………………………………………499
9A.1.1 The Chi-Square Test…………………………………………………….499
9A.1.2 The Kolmogorov–Smirnov Test……………………………………503
9A.2 Confidence Interval for a Population Proportion (Section 9.5.3)……………………………………………………………………………506
9A.3 Hypothesis Testing (Section 9.5.5)……………………………………………507
9A.4 Statistical Tables………………………………………………………………………511
Exercises……………………………………………………………………………………………513
References…………………………………………………………………………………………518
- Prescriptive Analytics for Process Performance Optimization……………………………………………………………………………………519
10.1 Identifying the Main Drivers of Process Performance……………..520
10.1.1 Factorial Design for Simulation Models……………………….521
10.1.2 Illustrative Example of Design of Experiments…………….523
10.2 Business Process Optimization………………………………………………..525
10.3 The Role of Simulation Optimization in Business Process Management……………………………………………………………………………528
10.4 Simulation Optimization with ExtendSim……………………………….533
10.4.1 Tutorial: Process Optimization with ExtendSim…………..537
10.4.2 Alternative Optimization Models………………………………..546
10.5 Optimization of Process Simulation Models……………………………548
10.5.1 Configuring a Hospital Emergency Room Process…………………………………………………………………………548
10.5.2 Staffing Levels for a Personal Insurance Claims Process…………………………………………………………………………551
10.6 Summary…………………………………………………………………………………553
Appendix 10A: Evolutionary Computation……………………………………..554
Exercises……………………………………………………………………………………………555
Simulation Optimization Projects……………………………………………………..557
References…………………………………………………………………………………………566
- Business Process Analytics………………………………………………………………567
11.1 Competing on Analytics………………………………………………………….570
11.2 Business Process Management Systems…………………………………..575
11.2.1 Business Rules……………………………………………………………..576
11.2.2 Monitor and Control…………………………………………………….578
11.2.3 Process Mining…………………………………………………………….579
11.3 Machine Learning……………………………………………………………………583
11.3.1 Support Vector Machines…………………………………………….584
11.3.2 k-Nearest Neighbor Classifier………………………………………587
11.3.3 Neural Networks…………………………………………………………591
11.3.4 Classification Problems in Business Processes……………..597
Discussion Questions and Exercises………………………………………………….598
References…………………………………………………………………………………………602
Epilogue………………………………………………………………………………………………….603
Index……………………………………………………………………………………………………….605