Methods for analyzing and incorporating customer feedback in automotive design and manufacturing

111 Pages·2015·12.24 MB·English

Methods for Analyzing and Incorporating Customer
Feedback in Automotive Design and Manufacturing
by
Cynthia Lin
B.S., MIT, Cambridge, 2008
Submitted to the Department of Mechanical Engineering and the MIT Sloan School of
Management in partial fulfillment of the requirements for the degrees of
Master of Science in Mechanical Engineering
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and
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Master of Business Administration
in conjunction with the Leaders for Global Operations Program at the
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MASSACHUSETTS INSTITUTE OF TECHNOLOGY
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June 2015
@ Cynthia Lin, MMXV. All rights reserved.
The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic
copies of this thesis document in whole or in part in any medium now known or hereafter created.
Signature redacted
A u th or ............................
Department of Mechanical Engineering and the MIT Sloan School of Management
May 8, 2015
Signature redacted
Certified by .....................
Maria Yang, Thesis Sipervisor
Associate Professor of Mechanical Engineering and Engineering Systems
Signature redacted
Certified by...
Roy Welsch, Thesis Supervisor
Professor of Statistics and Managemenk< lnce and En ngpring Systems
Signature redacted
.............................
Approved by...
David E. Hardt
Committee Chairman, Mechanical Engineering Graduate Program
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Signature reAdacted
A pproved by ....................................
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Maura Herson
Director of MBA Program, MIT Sloan School of Management

Methods for Analyzing and Incorporating Customer Feedback in
Automotive Design and Manufacturing
by
Cynthia Lin
Submitted to the Department of Mechanical Engineering and the MIT Sloan School of
Management on May 8, 2015, in partial fulfillment of the requirements for the degrees of
Master of Science in Mechanical Engineering
and
Master of Business Administration
Abstract
One of the key focus areas of the General Motors (GM) Company's leadership is to collect,
quickly analyze, and respond to customer feedback pertaining to product quality issues in
newly built vehicles. This project is intended to complement the Quality team's initiative
to develop a tool to combine data sources on product quality. Currently, the tool prioritizes
issues based on the frequency of reported incidents, and does not integrate responses to
open-ended survey questions. The objective of this project is to recommend methods in
which customer satisfaction input can be used to improve product quality.
We leveraged customer data and analytical tools to do three things. First, we identified
sources of customer feedback across the organization to strengthen collaboration on listening
to the customer. We then created a survey to assess the gap between customers and GM
employees' definitions of terms such as quality, dependability, and advanced technology.
Lastly, we used text analytics to provide structure to open-ended survey responses, which
enabled us to identify concerns expressed by customers that were not otherwise captured
using the current tool.
The cross-functional approach enabled us to gather quantitative results to support ob-
servations and anecdotes of misalignments between consumers and GM employees define
terms. Analysis shows that Dependability definitions are similar between employees and
consumers, but that there is a significant gap for High Quality. Text analytics uncovered
that customers were highly dissatisfied to discover that their vehicles did not have features
they expected to be basic attributes.
Thesis Supervisor: Maria Yang
Title: Associate Professor of Mechanical Engineering and Engineering Systems
Thesis Supervisor: Roy Welsch
Title: Professor of Statistics and Management Science and Engineering Systems
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Acknowledgments
I would like to extend my sincere appreciation to the following individuals and teams who
made my two years in grad school and internship a fantastic learning experience.
Firstly, thank you to General Motors for its continued support of the MIT Leaders for
Global Operations program. To my former and current supervisors and sponsors in the GM
Global Quality and Consumer Experience division - Chuck Dryer (supervisor), Jennifer Shin-
ska (former supervisor), Scott Young (current sponsor), and Mike Hardie (former sponsor)
- thank you for hosting me and for sparking my interest on the topic of customer needs and
satisfaction. Sigal Cordeiro (General Director, Chevrolet Global Marketing) and Richard
Choi (Director, Chevrolet Global Brand Strategy) for providing me resources to connect the
dots, for setting me up with the Market Research team to run the survey, and for throwing
a great holiday party - I cannot thank you and your teams enough! Mansoor Zaman (Sloan
'14), Mike Peterson (LFM '94), and Todd Huston (LFM '96) - thank you for arranging plant
tours. Thank you to all my unnamed colleagues who provided insightful anecdotes that led
to all the pieces coming together. To my new Michigan friends - thanks for welcoming me
to your climbing and running clubs and for making the Midwest experience truly fun and
wonderful!
Professors Roy Welsch (Management), Maria Yang (Engineering), and John R. Hauser -
thank you for enthusiastically supporting me through the experience, for patiently guiding me
as I scoped my project, and for encouraging me to pursue cross-functional collaboration! MIT
professors, LGO staff, and classmates - thanks for providing the platform for experimentation
and growth in this exhilarating chapter of our lives. I look forward to more opportunities to
interact!
Shannon Seeger, Juan Pablo Mendieta (MIT '08), and Carl Brown - without the three
of you being my personal cheerleader, sounding board, and best friends as I applied to grad
school, I would not be here today. Thank you!
Thank you mom, dad, and sister Christie (MIT '12/MEng '13) for your unconditional
love, continued support, shared excitement, and endless encouragement when I decided to
tackle MIT a second time! I love you!
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Contents
List of Figures 10
List of Tables 12
1 Introduction 13
1.1 Project Motivation . . . . . . . . . . . . . . . 13
1.2 Hypothesis . . . . . . . . . . . . . . . . . . . . 14
1.3 The Approach . . . . . . . . . . . . . . . . . . 14
1.3.1 Gap Analysis . . . . . . . . . . . . . . 15
1.3.2 Sources of Customer Input . . . . . . . 15
1.3.3 Text Analytics of Customer Responses 15
1.4 Thesis Overview. . . . . . . . . . . . . . . . . 16
2 Background 17
2.1 Overview of the Global Automotive Industry . . . . . . . . . 17
2.2 General Motors Company . . . . . . . . . . . . . . . . . . . . 21
2.3 The Customer Purchase Funnel . . . . . . . . . . . . . . . . . 22
2.4 Customer Focus at GM . . . . . . . . . . . . . . . . . . . . . . 24
2.4.1 GM Quality Strategy Team's Initiative . . . . . . . . . 24
2.5 The Kano Model . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.6 Product Quality . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.7 Customer Needs and Customer Satisfaction . . . . . . . . . . 32
2.8 Quality Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . 34
7
2.9 Text A nalytics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3 Methodology 37
3.1 Phase 1: Develop Current State Analysis . . . . . . . . . . . . . . . . . . . . 37
3.2 Phase 2: Identify "Voice of Customer" Inputs . . . . . . . . . . . . . . . . . 38
3.3 Phase 3: Develop Method for Conducting Gap Assessment . . . . . . . . . . 39
3.4 Phase 4: Text Analytics of Survey Responses . . . . . . . . . . . . . . . . . . 40
3.5 Phase 5: Generate Recommendations . . . . . . . . . . . . . . . . . . . . . . 41
4 "Voice of the Customer" Inputs 42
4.1 Summary of Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4.2 Flow Diagram of Customer Input . . . . . . . . . . . . . . . . . . . . . . . . 43
4.3 Data Sources that were Discovered . . . . . . . . . . . . . . . . . . . . . . . 44
4.4 Potential Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
5 Gap Assessment 46
5.1 Summary of Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.2 Design of Survey Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.3 Dem ographics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.4 Gap Assessment Survey Results . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.4.1 Comparison of Ratings and Rankings . . . . . . . . . . . . . . . . . . 56
5.4.2 Summary of the Findings . . . . . . . . . . . . . . . . . . . . . . . . 64
6 Text Analytics of Unstructured Survey Responses 65
6.1 Text Mining Open-Ended Responses . . . . . . . . . . . . . . . . . . . . . . 65
6.1.1 Word Count Analysis in Excel . . . . . . . . . . . . . . . . . . . . . . 66
6.2 Summary of Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
6.3 Potential Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
6.3.1 Sentiment Analysis Tool by Third-Party Vendor . . . . . . . . . . . . 73
6.3.2 Social Media Listening . . . . . . . . . . . . . . . . . . . . . . . . . . 75
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7 Organizational Assessment using the Three Lenses Framework 76
7.1 The Strategic Design Lens . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
7.2 The Political Lens. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
7.3 The Cultural Lens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
8 Conclusions 80
8.1 Summary of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
8.2 D iscussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
8.3 Recommendations for Future Initiatives . . . . . . . . . . . . . . . . . . . . . 83
9 Bibliography 85
A The Gap Assessment Survey 89
A.1 The Survey Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
A.2 The 22 Descriptors in the Survey . . . . . . . . . . . . . . . . . . . . . . . . 94
A.3 Consumers' Definitions of "High Quality" . ... ............ 95
A.4 Employees' Definitions of "High Quality" .. . . .. . . . . . . . . . . . . . . . 96
A.5 Consumers' Definitions of "Dependability" . . . . . . . . . . . . . . . . . 97
A.6 Employees' Definitions of "Dependability" . . . . . . . . . . . . . . . . . 98
A.7 Consumers: Adv. Tech. Not Sign of Qual/Depend . . . . . . . . . . . . . . . 99
A.8 Employees: Adv. Tech. Not Sign of Qual/Depend . . . . . . . . . . . . . . . 100
A.9 Consumers: Adv. Tech. Is Sign of Qual/Depend . . . . . . . . . . . . . . . 101
A.10 Employees: Adv. Tech. Is Sign of Qual/Depend . . . . . . . . . . . . . . . 102
A.11 Consumers' Definitions of "Advanced Technology" . . . . . . . . . . . . . . . 103
A.12 Employees' Definitions of "Advanced Technology" . . . . . . . . . . . . . . . 104
B Text Mining 105
B.1 Excel Macro Code for Word Parsing . . . . . . . . . 105
B.2 Verbatims on the Absence of Interior Trunk Latch . 108
B.3 Verbatims on Absence of Spare Tire . . . . . . . . . 110
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List of Figures
2-1 World production (by share) of passenger cars and commercial vehicles, 1961-
2013 ........... ........................................ 18
2-2 World production (in thousands of vehicles) of passenger cars and commercial
vehicles, 1961-2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2-3 Top 10 Manufacturers by Market Share: Rolling 12 months from March 2014-
Feb 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2-4 2013 World Production of Cars and Commercial Vehicles, by Country . . . . 20
2-5 Logos of GM's Ten Brands . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2-6 U.S. Market Share from 1961-2014 from Ward's Auto Data . . . . . . . . . . 22
2-7 The Classic Customer Purchase Funnel . . . . . . . . . . . . . . . . . . . . . 23
2-8 Customer-centric Customer Life Cycle . . . . . . . . . . . . . . . . . . . . . 23
2-9 The Kano Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4-1 Sources of Customer Input at GM . . . . . . . . . . . . . . . . . . . . . . . . 43
5-1 Gap Assessment: Respondent Demographics by Region . . . . . . . . . . . . 48
5-2 Gap Assessment: Respondent Demographics by Age . . . . . . . . . . . . . . 49
5-3 Gap Assessment: Demographics by Vehicle Segment . . . . . . . . . . . . . . 49
5-4 Gap Assessment: GM Employee Respondents' Years of Service . . . . . . . . 50
5-5 Gap Assessment: GM Employee Respondents' Job Functions . . . . . . . . . 50
5-6 Word Cloud of Consumers' Responses to the term 'High Quality' . . . . . . . 51
5-7 Word Cloud of Employees' Responses to the term 'High Quality' . . . . . . .. 52
5-8 Word Cloud of Consumers' Responses to the term 'Dependable' . . . . . . . . 52
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