Voice of the customer : capture and analysis

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Summary

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Discover All the Advantages of Using Design for Six Sigmato Develop and Build Customer Value-Based Products

Voice of the Customer Capture and Analysis equips Six Sigma you with the skills needed to create and deploy surveys, capture real customers need with ethnographic methods, immediately analyze the results, and coordinate and drive responsive actions.

Quality expert Kai Yang explains how to utilize the statistical methods of Design for Six Sigma to identify key customer needs and assess the cost of poor quality. He then shows how to design robust products to meet those needs, optimize product life cycles, and accurately validate their findings.

Voice of the Customer Capture and Analysis features a wealth of information on Six Sigma and value creation...customer survey design, administration, and analysis...ethnographic research...process management and Lean Product Development...the deployment of customer value into products-DFSS...and value engineering. This product design tool enables you to:

Minimize sources of response and measurement error Discern customer preferences Design VOC research to minimize mistranslation Respond to analytical implications of VOC data Optimize design to decrease sensitivity of CTQs to process parameters

With the help of Voice of the Customer Capture and Analysis, you can now acquire the skills needed to truly understand a customer's wants and needs, in order to develop and build optimal products.

Most Design for Six Sigma product development teams fall short of truly understanding their customers' want and needs until it is too late. Market research studies and reports simply do not provide sufficient guidance. Today's Six Sigma practitioners need a comprehensive approach to designing and building customer value-based products.

Voice of the Customer Capture and Analysis now gives you the ability to create and deploy surveys, capture real voice of the customer in the field, immediately analyze the results, and coordinate and drive responsive actions.

This powerful product-development tool demonstrates how to utilize the statistical methods of Design for Six Sigma to identify key customer needs ...assess the cost of poor quality...design robust products to meet those needs...optimize product life cycles...and accurately validate their findings.

By using the expert methods, strategies, and guidelines presented in Voice of the Customer Capture and Analysis, you can:

Harness VOC data to create value-based products Employ Design for Six Sigma to optimize value creation Become proactive in gathering VOC information Improve customer survey design, administration, and analysis Accurately process VOC data Deploy customer value into products-DFSS Perform effective quality function deployment (QFD) Get the most out of value engineering Capitalize on creative design methods Utilize process management and Lean Product Development Apply statistical techniques and Six Sigma metrics

This wide-ranging resource will give you the ability to minimize sources of response and measurement error ...clearly discern customer preferences...design VOC research to minimize the perils of mistranslation...respond to analytical implications of VOC data ...and optimize design to decrease sensitivity of CTQs to process parameters.

Comprehensive and authoritative, Voice of the Customer Capture and Analysis provides you with all the tools you need to fully understand custome

Author Notes

Kai Yang, Ph.D. has extensive experience in many areasof quality and reliability engineering. He is also an associate professor ofindustrial and manufacturing engineering at Wayne State University.

Chapter 1 Value, Innovation, and the Voice of the Customer	p. 1
1.1 Defining Customer Value	p. 2
1.2 Innovation Roadmap	p. 5
1.3 Voice of the Customer: Mining for the Gold	p. 6
1.4 Overview of This Book	p. 8
Chapter 2 The Product Development Process	p. 9
2.1 Defining Product Cost and Development	p. 9
2.1.1 Product Development Process Flowchart	p. 13
2.2 The Product Development Process-End to End	p. 14
2.2.1 Opportunity Identification and Idea Generation: Stage 0	p. 14
2.2.2 Customer and Business Requirement Study: Stage 1	p. 17
2.2.3 Concept Development: Stage 2	p. 18
2.2.4 Product Design and Prototype: Stage 3	p. 25
2.3 The Nature of Product Development: Information and Knowledge Creation	p. 33
2.3.1 Axiomatic Design	p. 35
2.3.2 Design as an Information Production Factory	p. 43
2.3.3 Information and Knowledge Mining	p. 45
2.3.4 Information Transformation	p. 53
2.3.5 Information and Knowledge Creation	p. 56
2.3.6 The Ideal Product Development Process	p. 60
2.4 Customer-Value-Based Lean Product Development Process	p. 64
2.4.1 Lean Operation Principles	p. 64
2.4.2 Waste Elimination in Process	p. 65
2.4.3 Value-Stream Mapping	p. 66
2.4.4 One-Piece Flow	p. 68
2.4.5 Pull-Based Production	p. 70
2.4.6 Lean Principles for Product Development	p. 71
2.4.7 Mining the Voice of the Customer to Capture Value	p. 74
2.4.8 Maximizing Technical Competence	p. 75
2.4.9 Front-Loading the Product Development Process	p. 76
2.4.10 Optimizing Information Transformation and Flow	p. 78
2.4.11 Creating a Lean Product	p. 86
Chapter 3 Customer Value and the Voice of the Customer	p. 89
3.1 Customer Value and Its Elements	p. 91
3.1.1 Value and Other Commonly Used Metrics	p. 94
3.1.2 The Versatility and Dynamics of Value	p. 95
3.2 Customer Value Analysis	p. 97
3.2.1 Market-Perceived Quality Profile	p. 98
3.2.2 Market-Perceived Price Profile	p. 102
3.2.3 Customer Value Map	p. 104
3.2.4 Competitive Customer Value Analysis	p. 107
3.3 Customer Value Deployment	p. 109
3.4 Evolution of Customer Values-Blue Ocean Strategy	p. 111
3.4.1 Formulating a Blue Ocean Strategy	p. 116
3.5 Customer Value and the Voice of the Customer	p. 123
3.6 Capturing the Voice of the Customer	p. 126
3.6.1 Plan for Capturing the Voice of the Customer	p. 127
Chapter 4 Customer Survey Design, Administration, and Analysis	p. 133
4.1 Customer Survey Types	p. 133
4.1.1 Mail-Out Surveys	p. 134
4.1.2 In-Person Interviews	p. 134
4.1.3 Telephone Surveys	p. 135
4.1.4 Other Methods of Gathering Information	p. 135
4.2 Stages of the Customer Survey	p. 136
4.2.1 Stage 1: Establish Goals and Objectives of the Survey	p. 137
4.2.2 Stage 2: Set the Survey Schedule and Budget	p. 138
4.2.3 Stage 3: Establish an Information Base	p. 138
4.2.4 Stage 4: Determine the Population and Sampling Frame	p. 139
4.2.5 Stage 5: Determine Sample Size and Selection Procedure	p. 139
4.2.6 Stage 6: Design the Survey Instrument	p. 139
4.2.7 Stage 7: Pretest the Survey Instrument	p. 140
4.2.8 Stage 8: Select and Train Survey Interviewers	p. 140
4.2.9 Stage 9: Implement the Survey	p. 140
4.2.10 Stage 10: Analyze the Data and Report	p. 140
4.3 Survey Instrument Design	p. 141
4.3.1 Close-Ended Questions	p. 141
4.3.2 Open-Ended Questions	p. 144
4.3.3 The Wording of Survey Questions	p. 144
4.3.4 Order of Questions in Surveys	p. 145
4.3.5 Questionnaire Length	p. 147
4.4 Administering the Survey	p. 147
4.4.1 Administering Mail-Out Surveys	p. 147
4.4.2 Administering Telephone Surveys	p. 148
4.4.3 Administering In-Person Surveys	p. 148
4.5 Survey Sampling Method and Sample Size	p. 148
4.5.1 Population and Sampling Frame	p. 149
4.5.2 Sampling Methods	p. 150
4.5.3 Sample Size Determination	p. 153
4.6 Internet Surveys	p. 157
4.6.1 Drawing People to the Internet-Based Survey	p. 158
4.6.2 Administering a Survey on the Internet	p. 162
4.6.3 Comparing Paper-Based Surveys with Internet Surveys	p. 166
Chapter 5 Proactive Customer Information Gathering-Ethnographic Methods	p. 169
5.1 What Are Ethnographic Methods?	p. 171
5.1.1 Frequently Used Ethnographic Methods	p. 173
5.1.2 Data Recording Methods	p. 174
5.1.3 Types of Ethnographic Research Used in Product Development	p. 175
5.1.4 Key Winning Factors for Ethnographic Methods	p. 177
5.2 Ethnographic Research Project Planning	p. 178
5.2.1 Determining Research Objectives	p. 178
5.2.2 Recruiting Informants	p. 180
5.2.3 Selecting Research and Data Collection Methods	p. 185
5.2.4 Developing the Ethnographic Research Team and Ground Rules	p. 189
5.3 Ethnographic Project Execution	p. 191
5.3.1 Ethnographic Interviews and Documentation	p. 191
5.3.2 Ethnographic Observations in Shops	p. 196
5.3.3 Ethnographic Observations in Product Usage Processes	p. 198
5.3.4 Ethnographic Studies of Customer Cultures	p. 203
Chapter 6 VOC Data Processing	p. 213
6.1 Types of VOC Data	p. 213
6.2 Analyzing VOC Data	p. 214
6.2.1 Methods of Analyzing VOC Data	p. 214
6.2.2 Affinity Diagram-KJ Method	p. 214
6.3 Quantitative VOC Data Analysis	p. 221
6.4 Critical-to-Quality Characteristics (CTQ)	p. 223
Chapter 7 Quality Function Deployment (QFD)	p. 229
7.1 History of QFD	p. 231
7.2 QFD Benefits, Requirements, and Practicalities	p. 231
7.3 QFD Methodology Overview	p. 232
7.3.1 Customer Attributes (Whats)	p. 234
7.3.2 CTSs (Hows)	p. 235
7.3.3 Relationship Matrix	p. 235
7.3.4 Importance Ratings	p. 237
7.3.5 Planning Matrix	p. 237
7.3.6 CTS Correlation (Hows Correlation)	p. 238
7.3.7 Targets and Limits (How Much)	p. 238
7.3.8 Competitive Benchmarks	p. 239
7.4 Kano Model of Quality	p. 239
7.5 QFD Analysis	p. 240
7.6 Example 7.1 Information System Design	p. 241
7.6.1 Ranking Customer Input	p. 241
7.6.2 Ranking the Functional Requirements	p. 243
7.7 QFD Case Study 1: Global Commercial Process Design	p. 244
7.7.1 QFD Steps	p. 245
7.7.2 The Hows Importance Calculation	p. 248
7.7.3 Phase I QFD Diagnostics	p. 249
7.8 QFD Case Study 2: Yaesu Book Center	p. 251
7.8.1 Determine Customer Attributes (Whats)	p. 254
7.8.2 Determine Quality Characteristics (Hows)	p. 255
7.8.3 Assign Degree of Importance to Customer Attributes	p. 255
7.8.4 Determine Operations Items	p. 255
7.8.5 Two-Phase QFD Analysis for Yaesu Book Center	p. 255
Chapter 8 Customer Value Creation by Brand Development	p. 259
8.1 The Anatomy of Brands	p. 262
8.1.1 People's Buying Behavior and Brands	p. 262
8.1.2 Brand Identity	p. 264
8.1.3 Brand Equity	p. 275
8.2 Brand Development	p. 277
8.2.1 Key Factors in Brand Development	p. 278
8.2.2 The Brand Development Process	p. 281
8.2.3 Strategic Brand Analysis	p. 283
8.2.4 Brand Strategy Development	p. 287
8.2.5 Brand Implementation	p. 293
8.2.6 Brand Evaluation	p. 293
Chapter 9 Value Engineering	p. 297
9.1 An Overview of Value Engineering	p. 298
9.1.1 Collecting Information and Creating Design Alternatives	p. 298
9.1.2 Evaluating, Planning, Reporting, and Implementing	p. 300
9.1.3 The Job Plan	p. 300
9.2 Information Phase	p. 300
9.2.1 Information Development	p. 301
9.2.2 Function Determination	p. 306
9.2.3 Function Analysis and Evaluation	p. 314
9.3 Creative Phase	p. 328
9.3.1 Brainstorming	p. 328
9.4 Evaluation Phase	p. 329
9.4.1 Relatively Simple Evaluations	p. 330
9.4.2 More Complex Evaluations	p. 331
9.4.3 Selection and Screening Techniques	p. 332
9.5 Planning Phase	p. 335
9.6 Reporting Phase	p. 336
9.7 Implementation Phase	p. 337
9.7.1 Setting a Goal	p. 338
9.7.2 Develop An Implementation Plan	p. 338
9.8 Automobile Dealership Construction (Park 1999)	p. 339
9.9 Engineering Department Organization Analysis (Park 1999)	p. 341
Chapter 10 Customer Value Creation Through Creative Design (TRIZ)	p. 345
10.1 Theory of Inventive Problem Solving (TRIZ)	p. 345
10.1.1 What Is TRIZ?	p. 347
10.2 TRIZ Fundamentals	p. 349
10.2.1 Function Modeling and Analysis	p. 349
10.2.2 Use of Resources	p. 353
10.2.3 Ideality	p. 354
10.2.4 Contradictions	p. 355
10.2.5 Evolution	p. 357
10.3 The TRIZ Problem-Solving Process	p. 360
10.3.1 Problem Definition	p. 360
10.3.2 Problem Classification and Tool Selection	p. 362
10.3.3 Problem-Solution Generation	p. 363
10.3.4 Problem Concept Evaluation	p. 363
10.4 Technical Contradiction Elimination and Inventive Principles	p. 363
Chapter 11 Statistical Basics and Six Sigma Metrics	p. 379
11.1 Six Sigma and Data Analysis	p. 379
11.2 Descriptive Statistics	p. 380
11.2.1 Dot Plot	p. 380
11.2.2 Histogram	p. 380
11.2.3 Box Plot	p. 382
11.2.4 Numerical Descriptive Statistics	p. 382
11.3 Random Variables and Probability Distributions	p. 386
11.3.1 Discrete and Continuous Random Variables	p. 386
11.3.2 Expected Values, Variance, and Standard Deviation	p. 387
11.3.3 Probability Distribution Models	p. 388
11.3.4 Statistical Parameter Estimation	p. 391
11.4 Quality Measures and Six Sigma Metrics	p. 392
11.4.1 Process Performance	p. 392
11.4.2 Process Capability Indices	p. 393
11.4.3 Sigma Quality Level (Without Mean Shift)	p. 395
11.4.4 Sigma Quality Level (With Mean Shift)	p. 396
References	p. 399
Index	p. 403

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