Graduate School ETD Form 9 (Revised 12/07) PURDUE UNIVERSITY GRADUATE SCHOOL Thesis/Dissertation Acceptance This is to certify that the thesis/dissertation prepared By Entitled For the degree of Is approved by the final examining committee: Chair To the best of my knowledge and as understood by the student in the Research Integrity and Copyright Disclaimer (Graduate School Form 20), this thesis/dissertation adheres to the provisions of Purdue University’s “Policy on Integrity in Research” and the use of copyrighted material. Approved by Major Professor(s): ____________________________________ ____________________________________ Approved by: Head of the Graduate Program Date Brian Scott Glassman IMPROVING IDEA GENERATION AND IDEA MANAGEMENT IN-ORDER TO BETTER MANAGE THE FUZZY FRONT END OF INNOVATION Doctor of Philosophy Dr. Linda Naimi Dr. Michael Menefee Rodney Vandeveer William Krug Dr. Linda Naimi Dr. Gary Bertoline 4/19/09
This seminal work is a comprehensive review of the fuzzy front end of innovation, idea generation, and idea management, and provides a clear means of managing the idea generation process. This dissertation was published by Purdue University in 2009 and was written by Dr. Brian Glassman
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Graduate School ETD Form 9 (Revised 12/07)
PURDUE UNIVERSITY GRADUATE SCHOOL
Thesis/Dissertation Acceptance
This is to certify that the thesis/dissertation prepared
By
Entitled
For the degree of
Is approved by the final examining committee:
Chair
To the best of my knowledge and as understood by the student in the Research Integrity and Copyright Disclaimer (Graduate School Form 20), this thesis/dissertation adheres to the provisions of Purdue University’s “Policy on Integrity in Research” and the use of copyrighted material.
Approved by Major Professor(s): ____________________________________
____________________________________
Approved by: Head of the Graduate Program Date
Brian Scott Glassman
IMPROVING IDEA GENERATION AND IDEA MANAGEMENT IN-ORDER TO BETTERMANAGE THE FUZZY FRONT END OF INNOVATION
Doctor of Philosophy
Dr. Linda Naimi
Dr. Michael Menefee
Rodney Vandeveer
William Krug
Dr. Linda Naimi
Dr. Gary Bertoline 4/19/09
Graduate School Form 20 (Revised 10/07)
PURDUE UNIVERSITY GRADUATE SCHOOL
Research Integrity and Copyright Disclaimer
Title of Thesis/Dissertation:
For the degree of ________________________________________________________________
I certify that in the preparation of this thesis, I have observed the provisions of Purdue University Executive Memorandum No. C-22, September 6, 1991, Policy on Integrity in Research.*
Further, I certify that this work is free of plagiarism and all materials appearing in this thesis/dissertation have been properly quoted and attributed.
I certify that all copyrighted material incorporated into this thesis/dissertation is in compliance with the United States’ copyright law and that I have received written permission from the copyright owners for my use of their work, which is beyond the scope of the law. I agree to indemnify and save harmless Purdue University from any and all claims that may be asserted or that may arise from any copyright violation.
________________________________Signature of Candidate
________________________________Date
*Located at http://www.purdue.edu/policies/pages/teach_res_outreach/c_22.html
IMPROVING IDEA GENERATION AND IDEA MANAGEMENTIN-ORDER TO BETTER MANAGE THE FUZZY FRONT END OF INNOVATION
Doctor of Philosophy
April-20-2009
Brian Glassman
Graduate School Form 16 (Revised 7/02)
Copies to: Thesis/Dissertation Office, Candidate, Graduate School
PURDUE UNIVERSITY GRADUATE SCHOOL
Thesis/Dissertation Receipt
Date of Deposit: 4/27/09
Received from: Glassman, Brian Scott Student ID No. 00168-37682
Major Professor: L. Naimi Department Head: G. Bertoline
Department: Technology (Organizational Leadership and Supervision) TECH
Official Degree Title Expected: Doctor of Philosophy
Date Degree Expected: May 2009
Subject Heading∗ Business Administration, Marketing; Business Administration, Management; Business Administration, General
The final approved deposit copy of a thesis entitled: Improving Idea Generation and Idea Management In Order to Better Manage the Fuzzy Front End of Innovation
______________________________________________________ Graduate School Committee on Theses and Publication
∗ Choose subject category from ProQuest
For Thesis Format Office use Only:
Thesis No.
Pagination . xv; 329p.
Notes .
IMPROVING IDEA GENERATION AND IDEA MANAGEMENT IN ORDER TO BETTER MANAGE THE FUZZY FRONT END OF INNOVATION
A Dissertation
Submitted to the Faculty of
Purdue University by
Brian Scott Glassman
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy
May 2009
Purdue University
West Lafayette Indiana
ii
I dedicate my thesis to my mother and father, Linda and Andy whose patience,
nurturing and regard for education held me on a steady course. I want to
express my appreciation to my sister Stephanie whose antics always kept me
thinking of ways to outsmart her. I also want to thank my Grandmother Irene
and Grandma Sally for their unconditional love and emotional support. I want to
acknowledge my Aunt Nancy for her wise encouragement and advice. Finally, I
want to remember my Poppa Frank whose love and enthusiasm for engineering
was passed down to me with unending patience at his basement workbench.
iii
ACKNOWLEDGMENTS
I would like to thank my committee members - Linda Naimi, Michael Menefee,
Rodney Vandeveer and William Krug - for their help and support throughout the
dissertation process. And I would like to thank Kenneth Kahn for his advice and
encouragement.
I would especially like to thank my major advisor, Dr. Linda Naimi, for her
support, encouragement, and understanding. She truly is an inspiration to me!
Select Quotes
“In the hustle and bustle of everyday life, one can get caught up in life’s many
problems. When that happens, remember life is beautiful. Stop and take some
time to appreciate how beautiful and precious it is. It will surely make you feel
better.” - Dr. M.T. Naimi
“Life is not hard any more, it is just a whole lot more complicated.”
- Brian Glassman
“The brain is a wonderful organ. It starts working the moment you get up in the
morning and does not stop until you get to the office.” - Robert Frost
iv
PREFACE
During my management studies at Duke University, Dr. Jeff Glass, a great
leader, and always an inspiration to me, was the first to formally introduce me to
the topic of the fuzzy front end. I remember it vividly, because he said the fuzzy
front end was a major challenge for management because its inner workings
were relatively unknown. From that point on, I was hooked on the topic and the
major challenges associated with it, and I felt a compelling need to help solve this
vital piece of the innovation puzzle. Hopefully, I have shed some light on it with
this research and model.
v
TABLE OF CONTENTS
Page LIST OF TABLES ................................................................................................. x LIST OF FIGURES .............................................................................................. xi LIST OF ABBREVIATIONS ............................................................................... xiv ABSTRACT ......................................................................................................... xv CHAPTER 1. INTRODUCTION ............................................................................ 1 1.1. Statement of Research Problem, Background, and Context ....................... 1 1.2. Importance and Significant of the Study ..................................................... 4 1.3. Research Questions ................................................................................... 5 1.4. Assumptions ............................................................................................... 6 1.5. Delimitations and Limitations ...................................................................... 8
CHAPTER 2. A COMPREHENSIVE REVIEW OF THE LITERATURE................. 9 2.1. Literature Review of Ideas .......................................................................... 9 2.1.1. Why does the Innovation Process Need Ideas? ................................... 9 2.1.2. Value of Ideas ..................................................................................... 10 2.1.3. Defining an Idea .................................................................................. 11 2.1.4. Narrowing the Definition of Ideas ........................................................ 12 2.1.5. Terminology ........................................................................................ 14 2.1.6. New and Old Ideas ............................................................................. 16 2.1.7. Summary of Literature Review on Idea ............................................... 17
2.2. The Evolution of the Innovation Process ................................................... 18 2.2.1. The Importance of Innovation ............................................................. 18 2.2.2. A Quick History of Innovation and R&D: A Process Perspective ........ 19
2.3. Research on the Fuzzy Front End ............................................................ 26 2.3.1. Intro to Section on Fuzzy Front End .................................................... 26 2.3.2. Terminology for the Fuzzy Front End .................................................. 27 2.3.3. Activities in the Front End of Innovation .............................................. 29 2.3.4. Importance of the FFE ........................................................................ 30 2.3.5. Deliverable at the End of the Fuzzy Front End ................................... 32 2.3.6. Structured vs. Unstructured Fuzzy Front End ..................................... 33 2.3.7. Quick Review of Research on the Fuzzy Front End............................ 34 2.3.8. Summary of Research on the FFE...................................................... 36
2.4. Review of Process Models for the Fuzzy Front End ................................. 37 2.4.1. Intro to Section .................................................................................... 37 2.4.2. Review of FFE Process Models .......................................................... 37 2.4.3. Innovation Value Chain ....................................................................... 38
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Page 2.4.4. Cooper’s Stage-Gate Process Model .................................................. 40 2.4.5. Downsides of the Stage-Gate Model .................................................. 45 2.4.6. Khurana & Rosenthal FFE Model ....................................................... 46 2.4.7. Deloitte’s Spiral Model ........................................................................ 48 2.4.8. Downsides of the Deloitte Spiral Model .............................................. 51 2.4.9. Koen’s NCD Model ............................................................................. 52 2.4.10. Downsides and Conclusion on Koen’s Model ................................... 54 2.4.11. Husig, Kohn, and Poskela 2003 ........................................................ 55 2.4.12. Montoya-Weiss & O’Driscoll ............................................................. 56 2.4.13. General Problems and Issues with Fuzzy Front End Models ............ 57
2.5. Literature Review of Activities in the Fuzzy Front End .............................. 62 2.5.1. List of Activities in the Fuzzy Front End .............................................. 62 2.5.2. Quick Categorization of Activities in the Fuzzy Front End ................... 68 2.5.3. Proposed Organization of Activities for the Fuzzy Front End .............. 68 2.5.4. Summary of Section ............................................................................ 69
2.6. Literature Review of Idea Generation ....................................................... 69 2.6.1. Why is Idea Generation Important? .................................................... 70 2.6.2. What is Idea Generation? ................................................................... 71 2.6.3. A Review of Idea Generation Research .............................................. 72 2.6.4. Creativity and Idea Generation ........................................................... 74 2.6.5. Environmental Scanning and Idea Generation ................................... 75 2.6.6. Seeding Ideas ..................................................................................... 77 2.6.7. Opportunity Identifications .................................................................. 78 2.6.8. Issues and Problems with Idea Generation ........................................ 79 2.6.9. Summary of Section ............................................................................ 81
2.7. Highly Detailed Review of Sources of Ideas, and Idea Generation Techniques, Activities, and Processes ............................................................ 81 2.7.1. People are the Only Source of Ideas .................................................. 81 2.7.2. Techniques, Activities, and Full Processes for Idea Generation ......... 84 2.7.3. Review of top idea generation processes ........................................... 90 2.7.4. Detailed Examination of Sources of Ideas ........................................ 101 2.7.5. Issues with External Sources of Ideas .............................................. 112 2.7.6. Which Source of Ideas is the Best? .................................................. 112 2.7.7. Major Issue with Idea Generation (Lack of Control Models) ............. 113 2.7.8. Summary of Section 2.7 .................................................................... 113
2.8. Literature Review of Idea Management and Idea Banks ........................ 114 2.8.1. Introduction to Section ...................................................................... 114 2.8.2. What is Idea Management and What are Idea Banks? ..................... 114 2.8.3. Need for Idea Management and Idea Banks .................................... 115 2.8.4. Terminology for Idea Banks .............................................................. 116 2.8.5. A Review of the Literature on Idea Management and Idea Banks .... 117 2.8.6. Problems and Issues with Idea Management and Idea Banks ......... 126 2.8.7. Summary of Section .......................................................................... 127
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Page CHAPTER 3. DEVELOPMENT OF CONTROL MODELS ................................ 128 3.1. Review and Selection of a Control Theory .............................................. 128 3.2. Development of a Control Model for Idea Generation ............................. 132 3.2.1. Continuous Idea Generation vs. Event Based Idea Generation ........ 132 3.2.2. Supporting Evidence for Ideation Events .......................................... 133 3.2.3. Controlling External and Internal Events ........................................... 135 3.2.4. Controlling the Source ...................................................................... 138 3.2.5. Internal vs. External Source and Methods of Control ........................ 140 3.2.6. Controlling Idea Generation Activities ............................................... 141 3.2.7. Internal and External Idea Generation and Control ........................... 144 3.2.8. Screening and Filtering Before Being Captured ................................ 145 3.2.9. Quick Review on Areas of Control .................................................... 147 3.2.10. Strategy and Idea Generation ......................................................... 148 3.2.11. Idea Generation’s Process Check Analysis .................................... 153 3.2.12. Characteristics of Created Ideas ..................................................... 154 3.2.13. A Practical example of managing the idea generation process ...... 155 3.2.14. Summary of Section ........................................................................ 157
3.3. Development of a Control Model for Idea Banks and Idea Management 158 3.3.1. Major Functions of Idea Management ............................................... 158 3.3.2. Capturing Ideas................................................................................. 161 3.3.3. Tagging ............................................................................................. 166 3.3.4. Storage and Categorizing ................................................................. 173 3.3.5. Process Check and Feedback .......................................................... 182 3.3.6. Diffusing and Routing ........................................................................ 184 3.3.7. Routing ............................................................................................. 189
3.4. Linking Idea Banks to Portfolio Management .......................................... 190 CHAPTER 4. RESEARCH METHODOLOGY ................................................... 193 4.1. Purpose of Study .................................................................................... 193 4.2. Limitations Effecting the Selection of the Type of Study ......................... 193 4.2.1. Lack of Metrics for Success in Idea Generation ................................ 193
4.3. Study Type Which Will Not Be Used ....................................................... 195 4.3.1. Observational Based Support Studies .............................................. 195 4.3.2. Application Based Support Study...................................................... 195 4.3.3. Laboratory Testing Base Support Study ........................................... 196 4.3.4. Analysis of Secondary Research ...................................................... 196 4.3.5. Interview Based Support ................................................................... 196 4.3.6. Electronic Survey Study .................................................................... 197
4.4. Parts to the Study ................................................................................... 198 4.5. Study Part One ....................................................................................... 198 4.6. Study Part Two ....................................................................................... 199 4.6.1. Description of Part Two ..................................................................... 199 4.6.2. Description of Survey Tool ................................................................ 200 4.6.3. Description of the Respondent Pool.................................................. 202 4.6.4. Data Analysis .................................................................................... 202
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Page CHAPTER 5. RESEARCH RESULTS .............................................................. 204 5.1. Summary of Case Study Results ............................................................ 204 5.1.1. Benefits of the Case Studies ............................................................. 205 5.1.2. Analysis of the Company .................................................................. 205 5.1.3. Brief Summary of Each Case Study .................................................. 206
5.2. Case Study 1: Company Alpha ............................................................... 208 5.2.1. Background on the Company ........................................................... 208 5.2.2. Sources of Ideas for Idea Generation ............................................... 208 5.2.3. Events and Activities Used to Generate Ideas .................................. 209 5.2.4. Screening Ideas upon First Submission ............................................ 211 5.2.5. Capturing Ideas from Internal and External Sources ........................ 211 5.2.6. Sources Tapped for Ideas ................................................................. 213 5.2.7. Tagging Ideas during Capture .......................................................... 214 5.2.8. Storing and Categorizing Ideas ......................................................... 214 5.2.9. Process Check Used to Improve the Idea Generation Process ........ 215 5.2.10. Diffusing Ideas to Employees inside the Company ......................... 215 5.2.11. Comparison with Measures of Satisfaction ..................................... 216 5.2.12. Late Front End Activities at Company Alpha ................................... 217 5.2.13. Recommendations for Late Front End Activities ............................. 218
5.3. Case Study 2: Fairbanks Scales ............................................................. 218 5.3.1. Background on the Company ........................................................... 218 5.3.2. Overall Situation & Broader Strategic View ....................................... 219 5.3.3. Adopting a Broader View of Their Core Business ............................. 221 5.3.4. A Broader Understanding of How their Products Fit into the Job Process ....................................................................................................... 222 5.3.5. Idea Generation ................................................................................ 223 5.3.6. Recommendations for Idea Generation ............................................ 224 5.3.7. Screening of Ideas ............................................................................ 227 5.3.8. Capturing Ideas from Internal and External Sources ........................ 228 5.3.9. Tagging Ideas during Capture .......................................................... 228 5.3.10. Storage and Categorization ............................................................ 229 5.3.11. Process Check Used to Improve the Idea Generation Process ...... 229 5.3.12. Diffusing Ideas to Employees inside the Company ......................... 229 5.3.13. Late Front End Activities ................................................................. 230 5.3.14. Skunk Works Team ......................................................................... 232 5.3.15. Comparison with Measures of Satisfaction ..................................... 233
5.4. Case Study 3: CartêGraph ...................................................................... 235 5.4.1. Background on the Company ........................................................... 235 5.4.2. Idea Generation ................................................................................ 235 5.4.3. Technology Adoption ........................................................................ 236 5.4.4. Types of Idea Generation Activities .................................................. 238 5.4.5. Idea Management ............................................................................. 238 5.4.6. First Screen of ideas ......................................................................... 239 5.4.7. Capturing Ideas from Internal and External Sources ........................ 239
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Page 5.4.8. Recommendations for Capturing Ideas ............................................. 240 5.4.9. Tagging Ideas during Capture .......................................................... 241 5.4.10. Storage & Categorization ................................................................ 241 5.4.11. Process Check Used to Improve the Idea Generation Process ...... 242 5.4.12. Diffusing Ideas to Employees Inside the Company ......................... 242 5.4.13. Late Front End Activities ................................................................. 243 5.4.14. Comparison with Measures of Satisfaction ..................................... 244
5.5. Case Study: Discussion of 2nd Research Question Based on Case Study Evidence ........................................................................................................ 245 5.6. Case Study: Major Lessons Learned ...................................................... 247 5.6.1. Structure of Idea Management ......................................................... 248 5.6.2. Situational Dependence on Idea Generation or Idea Management .. 249 5.6.3. Assigned Idea Manager .................................................................... 249 5.6.4. Expertise is Needed .......................................................................... 249
5.7. Survey: Method of Cleaning the Data and Analysis ................................ 250 5.8. Survey: General Demographic Statistics for the Sample ........................ 252 5.8.1. Sample’s Relation to the Greater Population .................................... 255
5.9. Survey: Correlations between Satisfaction Variables.............................. 256 5.9.1. Idea Generation ................................................................................ 256 5.9.2. Idea Capture ..................................................................................... 258 5.9.3. Development Outcomes ................................................................... 260
5.10. Survey: Discussion of Correlations Between Satisfaction Variables and Measures of Activities .................................................................................... 261 5.10.1. Correlations for the Idea Management Process .............................. 264
5.11. Survey: Discussion of Support for Proposed Model .............................. 274 5.12. Survey: Discussion of Normative Results ............................................. 275 5.12.1. Normative Results for Satisfaction Questions ................................. 275 5.12.2. Normative Results for Activity Questions ........................................ 276
5.13. Survey: Major Lessons Learned ........................................................... 278 CHAPTER 6. UPDATED CONTROL MODELS ................................................ 279 6.1. Screening Moved into Idea Management ............................................... 279 6.2. Strategic Alignment Activities .................................................................. 280 6.3. Final Version of the Glassman Control Model ......................................... 283
BIBLIOGRAPHY ............................................................................................... 284 APPENDICES Appendix A. Concept Life Cycle .................................................................... 301 Appendix B. Details of Stage Gate Process ................................................... 302 Appendix C. Survey Instrument ..................................................................... 303 Appendix D. Normative Survey Results ......................................................... 311
VITA ................................................................................................................. 329
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LIST OF TABLES
Table Page Table 2.1. Koen et al. Activities in the Front End of Innovation ........................... 28 Table 2.2. Koen et al. Factors and Characteristics of the Front End of Innovation
...................................................................................................................... 29 Table 2.3. Specific Activities and Decisions for Each Stage and Gate ............... 43 Table 2.4. List of Activities Which Can Occur in the Front End of Innovation ..... 62 Table 2.5. Categorization of Front End Activities ................................................ 68 Table 2.6. Techniques which Aid in Idea Generation .......................................... 86 Table 2.7. Activities which Specifically Trigger Creativity.................................... 87 Table 2.8. Activities which Seed Individuals with Ideas ...................................... 88 Table 2.9. Activities Which Use Analysis to Spawn Creativity and Ideas ............ 89 Table 2.10. Full Idea Generation Processes ....................................................... 90 Table 2.11. Major Categories for Source of Ideas ............................................ 102 Table 2.12. Employee Based Sources of Ideas ................................................ 103 Table 2.13. Customer Sources Which Can Result in Ideas .............................. 104 Table 2.14. Non-for-profit Organizational Based Sources of Ideas ................... 106 Table 2.15. Supplier Sources ............................................................................ 109 Table 2.16. Competitor sources ........................................................................ 110 Table 2.17. Sources of Ideas From Other Companies ...................................... 111 Table 3.1. Example of Idea from the Company’s First Attempt ......................... 156 Table 3.2. Example of Improved Set of Idea Resulting from Second Attempt .. 157 Table 3.3. Diffusion Methods, Forced, and Sought Diffusion ............................ 187 Table 5.1. Attributes of the Three Companies .................................................. 205 Table 5.2. Idea Generation Satisfaction Variable Results for Alpha ................. 216 Table 5.3. Idea Management Satisfaction Results Variables for Alpha ............ 217 Table 5.4. Recommended Idea Generation Techniques and Activities ............ 226 Table 5.5. Idea Generation Satisfaction Variable Results for Fairbanks ........... 233 Table 5.6. Idea Management Satisfaction Results Variables for Fairbanks ...... 234 Table 5.7. Correlation for Diffusion Activities .................................................... 271 Table 5.8. Correlations for Idea Management Software ................................... 272 Table 5.9. Support Found for the Author’s Proposed Model ............................. 274
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LIST OF FIGURES
Figure Page Figure 1.1. Koen’s breakup of the new product innovation processes .................. 2 Figure 2.1. Concept Life Cycle Model ................................................................. 16 Figure 2.2. Early R&D process ........................................................................... 20 Figure 2.3. R&D Funnel ...................................................................................... 21 Figure 2.4. R&D Funnel and New Product and Commercialization Processes ... 21 Figure 2.5. Addition of the Fuzzy Front End ........................................................ 22 Figure 2.6. State-Gate Process in the Overall Development Process and a Map
of Project Costs as the Project Progresses ................................................... 23 Figure 2.7. Innovation Value Chain ..................................................................... 25 Figure 2.8. Visual Depiction of the Innovation Value Chain Model ..................... 38 Figure 2.9. Visual Depiction of the a Stage in the Stage-Gate Model ................. 41 Figure 2.10. Full Stage-Gate Process Model ...................................................... 41 Figure 2.11. Options for Sage Gate Process ...................................................... 44 Figure 2.12. Pie Charts Depicting Activities in Each Stages ............................... 45 Figure 2.13. Khurana & Rosenthal FFE model ................................................... 47 Figure 2.14. Visual Depiction of the Delottie’s Spiral Model ................................ 49 Figure 2.15. Visual Depiction of Koen’s NCD Model ........................................... 52 Figure 2.16. Visual Depiction of Husig, Kohn, and Poskela Model ..................... 55 Figure 2.17. Montoya-Weiss & O’Driscoll’s Funnel Model .................................. 56 Figure 2.18. Idea Creation in a Person’s Mind .................................................... 83 Figure 2.19. Activities Leading to the Creation of Ideas ...................................... 83 Figure 2.20. Unknown Activities which Lead to the Creation of an Idea ............. 84 Figure 2.21. Illustration of How Techniques are Embedded in Activities,............ 85 Figure 2.22. Illustration of the Contextual Research Process ............................. 92 Figure 2.23. Illustration of the Outcome-Based Innovation Process ................... 93 Figure 2.24. Illustration of the IDEO’s Idea Generation Process ......................... 96 Figure 2.25. The Strategic Canvas from Blue Oceans Strategy with
Three Plotted Value Curves .......................................................................... 97 Figure 2.26. Illustration of a Blue Ocean Strategy Idea Generation Process ...... 98 Figure 2.27. Illustration of Flynn’s Idea Generation Process ............................. 100 Figure 2.28. Modification of Flynn’s Idea Generation Process .......................... 101 Figure 2.29. Montoya-Weiss & O’Driscoll’s Idea Generation Process .............. 121 Figure 2.30. Bakker, Boersma, & Oreel Idea Storage Processes ..................... 124 Figure 3.1. Process Control Model ................................................................... 131 Figure 3.2. Process Control Model with formal input and process controls....... 131
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Figure Page Figure 3.3. Continuous Idea Generation vs. Event Driven Idea Generation ..... 132 Figure 3.4. Idea Generation Triggered by Formal Events ................................. 134 Figure 3.5. Controlling Both Internally Idea Events an External Idea Events .... 136 Figure 3.6. Ideation Events Influence on Idea Generation ................................ 137 Figure 3.7. Controls over Sources of Ideas ....................................................... 141 Figure 3.8. Controls over External and Internal Idea Generation ...................... 144 Figure 3.9. Screening and Filtering Located After Idea Generation Activities ... 145 Figure 3.10. Screening and Filtering in and After Idea Generation Activities .... 146 Figure 3.11. Points of Control in the Full Idea Generation Process .................. 147 Figure 3.12. Statistical Results from Adams-Bigelow Showing How Idea Were
Generated ................................................................................................... 149 Figure 3.13. Strategy’s Possible Influence on the Idea Generation Processes . 151 Figure 3.14. Strategic Idea Continuum ............................................................. 152 Figure 3.15. Control model for Idea Generation ................................................ 153 Figure 3.16. Initial version of Glassman Model ................................................. 160 Figure 3.17. An Example of a Company’s Receptiveness to Outside Ideas at
Respective Levels of Concept Development .............................................. 165 Figure 3.18. An Example of a Company’s Receptiveness to Outside Ideas in
Different Innovation Categories .................................................................. 166 Figure 3.19. Illustration of the Idea Cloud, Idea Bank,
and Company Idea Bank ............................................................................ 174 Figure 3.20. Illustration of the Continuum of Idea Formality .............................. 175 Figure 3.21. Illustration of the Diversity of Idea Banks ...................................... 176 Figure 3.22. Illustration of Idea Bank Organized by Incremental
and Radical Ideas ....................................................................................... 177 Figure 3.23. Illustration of Idea Bank Organized by Innovation Category ......... 177 Figure 3.24. Idea Management Feeding Idea Back into Idea Generation to
Stimulate more ideas .................................................................................. 184 Figure 3.25. Diffusion Power Spectrum ............................................................ 185 Figure 3.26. How Portfolio Management Determines Options for New Projects
.................................................................................................................... 191 Figure 3.27. How Assessment of Idea Banks can be Used by Portfolio Managers
.................................................................................................................... 191 Figure 3.28. Late FFE Activities Linking to Screening and Filtering .................. 192 Figure 5.1. Vertical Packaging Machine with Integrated Scales ....................... 222 Figure 5.2. Conversion of Answers from Likert to Ordinal Scales ..................... 251 Figure 5.3. Distribution of Respondents’ Companies amongst their Respective
Industries .................................................................................................... 253 Figure 5.4. Distribution of Respondent’s Companies by Revenues and Number of
Employees .................................................................................................. 253 Figure 5.5. Distribution of Respondent’s Companies by Locations ................... 254 Figure 5.6. Respondents Organized by their Roles .......................................... 255 Figure 5.7. Correlations of the Satisfaction Variables ....................................... 256
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Figure Page Figure 5.8. Correlation for Overall Satisfactions with the Idea Generation Process
.................................................................................................................... 257 Figure 5.9. Correlation of V48 Ability to Fill Front End Portfolio ........................ 258 Figure 5.10. Correlation of 51S Ability to Capture Ideas from Employees ........ 259 Figure 5.11. Correlations of 52S Ability to Capture Ideas from Outside Sources
.................................................................................................................... 259 Figure 5.12. Correlation of Dependent Development Variables ........................ 260 Figure 5.13. Correlations with Company Resources ......................................... 260 Figure 5.14. Correlations of Activities to Quality of Ideas Generated ................ 261 Figure 5.15. Correlation 0.851 Comparison with Model .................................... 263 Figure 5.16. Weak Correlation for Capturing Ideas from Employees ................ 264 Figure 5.17. Strong Correlation for Capturing Ideas from Employees .............. 265 Figure 5.18. Correlation for Capturing Ideas from Outsides Sources ............... 267 Figure 5.19. Correlation for Storing and Capturing Ideas.................................. 269 Figure 5.20. Correlation for Process Improvement ........................................... 269 Figure 5.21. Correlation for Development Activities .......................................... 272 Figure 6.1. Updated Glassman Model .............................................................. 283
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LIST OF ABBREVIATIONS
FFE - fuzzy front end of the innovation process
PDMA - product development and management association
NPD - new product development process
CAP - Capitalization which defines the market value of the company
xv
ABSTRACT
Glassman, Brian Scott. Ph.D, Purdue University, May 2009. Managing Idea Generation and Idea Management In Order to Better Manage The Fuzzy Front End of the Innovation Process. Major Professors: Linda Naimi and Michael Menefee.
An expansive review of the literature on the fuzzy front end of innovation, idea
generation, and idea management was conducted and is shown. Based on a
depth of understanding, a control model was developed to aid innovation
practitioners in effectively controlling the idea generation and idea management
processes.
This control model, named the Glassman Model for Managing Idea Generation,
was then validated in two studies. The first was the application of the control
model via analyzing, diagnosing, and making recommendations for three
companies outlined in three individual case studies. The second study used an
online survey to develop normative data and correlations on the idea generation
and idea management processes. Improvements were made to the model based
on lessons learned from the two studies. Both studies supported and validated
the model as containing the factors needed to manage these processes
effectively.
1
CHAPTER 1. INTRODUCTION
1.1. Statement of Research Problem, Background, and Context
The popular management of trends in the twentieth century towards improving
innovation is well founded because it is based on a company’s un-deniable need
to improve itself for the future (Collins, & Porras, 2002; Berkun 2007;
Christensen, & Raynor, 2003; Christensen, 2000; Drucker, 1985). Thousands, if
not hundreds of thousands, of articles, books, and publications, along with
conferences on the topic of innovation and the hundreds of innovation consulting
firms stress this point.
Out of the innovation literature, new product development has condensed
as a distinct field of research (Kahn, 2005; Belliveau, Griffen, Somermeyer, 2002;
Griffen, Somermeyer, 2007; Belliveau, 2004). Hallmark books on this subject by
authors such as Kahn (2005), Belliveau (2004), and Griffen & Somermeyer
(2007) reveal a large breadth of knowledge in this subject and cover areas
including management, processes, tools, resources, people, organizational
culture, and best practices for new product development.
On the process side, Koen (2005) breaks the innovation process “into
three areas: the Fuzzy front end (FFE), the New Product Development Portion
(NPD), and Commercialization” (Koen, 2005, p. 3).
2
Figure 1.1. Koen’s breakup of the new product innovation processes
Of these areas, the fuzzy front end (coined by Smith & Reinerten in 1991)
according to Kahn is “an important issue in future research on product
development (Verwon, Herstatt, & Nagahira, 2008). Further, authors like
Backman, Borjesson, and Setterberg (2007) say, “the greatest opportunities for
improving the overall innovation process lie in the very early phases of NPD”
process being the fuzzy front end (p. 321). Hence, Zhan and Doll (2001) states,
“managers and researchers claim the benefits resulting from improvements in the
front [end] are likely to far exceed those that result from improvements aimed
directly at the design engineering process” (Koen, et al. 2001, p. 2).
Process models for the fuzzy front end highlight idea generation as being
The following examples illustrate that the front end can be improved
through improvements in the idea generation processes. MIT Technology’s
Review 2003 R&D scorecard survey of the top 318 companies in the world in ten
different industry showed that they cumulatively spent $274 billion on R&D with
$4.13 trillion in revenues. Increasing their R&D efficiency by 1% could
cumulatively save $2.7 billion. Conversely, increasing their return on their R&D
dollars by even 1% could cumulatively easily produce hundreds of billions in
additional revenue. Given this, one can see that even a small improvement to the
innovation process can produce tremendous results.
Additionally, the value of this study can be in the creation of new
knowledge and the aid it may offer practitioners. First, this research developed
and tested a viable control model (referred to within this study as the Glassman
5
Model for Idea Generation Management) to fill the gap in the literature on
managing idea generation and idea management. Second, the creation of new
knowledge will occur from developing, testing and supporting this model. Third,
the model is expected to aid practitioners in more effectively managing ideas and
idea generation. In addition, given research on previous front end models, it is
expected that the proposed Glassman model could be applicable in companies
of any country and any industry, and thus may have a global impact on
innovation practices.
In terms of research, this model may provide future researchers with a
model to study the effect of particular factors on the outcome of the idea
generation processes. Additionally, this model explains and contributes to other
works on innovation by tying together previously disparate activities and topics
like knowledge brokering (Hardagon, & Sutton, 2000), environmental scanning,
seeding ideas, and opportunity identification. Additionally, it may bring together a
more coherent view of the front end of innovation and its inter-workings.
As well, it will address randomness and the chaotic nature of the fuzzy
front end by giving innovation practitioners a means to turn idea generation into
and on demand activity.
Ideally, a properly designed control model for idea generation and idea
management could become another best practice model for innovation, which
will lead to greater recognition of the importance of managing innovation,
efficiency in the idea generation process and opportunities for further research
and funding.
1.3. Research Questions
A review of current practices suggests a lack of suitable control models for idea
generation and idea management. Further, the literature illustrates the lack of a
conceptual understanding of how to manage either idea generation or idea
6
management. Interestingly, both idea generation and idea management are
linked through front end processes (Alam, 2003; Montoya-Weiss & O’Driscoll,
2006; Flynn, Dooley, O’Sullivan, and Cormican’s, 2003). Hence, the following
study addressed these research questions:
1.) Based on a review of the literature, can a control model be developed to
aid in the conceptual understanding and management of idea generation and
idea management?
2) Can the developed control model be supported as capturing the required
factors needed to manage and control idea generation and idea management
effectively?
1.4. Assumptions
A number of assumptions have been made for the purpose of this research study
and are broken up into the major areas assumptions related to: 1) company’s
motives, strategies, and limitations, 2) communication and information, 3)
supporting the proposed model, and finally assumptions related to 4) behavior of
the employees.
The first set of assumptions are related to the company’s motives,
strategies, and limitations and start with the assumption that the company would
like to improve its’ innovation process and has access to people which can be
trained to manage the innovation process.
Next, it is assumed that innovation practitioners want to manage the front
end to achieve a specific set of business related goals to benefit the
shareholders (growth, profitability, competitive advantage, and so on). Thus they
do not innovate because it is entertaining and they enjoy experiments for the
sake of experimenting. For example Bose Company knowingly wastes millions of
dollars in R&D because the CEO enjoys playing with basic research. Next, it is
assumed that companies have a general strategy for innovation (grow offering,
7
develop a competitive edge, and so on) and that innovation practioners are
working towards and aligned with their company’s goals based on a general
innovation strategy.
Finally, it is assumed that companies have some sort of preference toward
certain types of ideas because of limitations in resources, capabilities, and
people. Thus, they do not have the ability to develop every idea that comes along
nor have the desire to do so.
The second set of assumptions relate to communication and information
sharing in the company. This starts with the assumption that a company may not
share particular ideas all their idea with employees for reasons of intellectual
property or trade secrets. Next, it is assumed innovation practitioners, in the front
end, are not restricted from accessing any information related to those processes
or ideas (total free communication), and that the product portfolio accurately
shows the current projects in the development pipeline.
The third set of assumptions relates to supporting the proposed model and
are innovation practitioners can: (1) promote events; (2) have control over the
execution of activities in the front end; (3) have the freedom to select employees
they choose; (4) have reasonable discretion over the use of resources given to
them for front end activities; (5) have a general understanding of their business
environment and companies strategy and needs; (6) are competent enough to
manage; (7) have limited control over people outside their company; (8) they
cannot control the company’s culture; and (9) finally are aligned with company
goals.
The final set of assumptions relates to behaviors of employees in the
company. It is assumed that innovation practitioners do not behave maliciously
and that they do not conduct front end activities their own benefits or for
malicious intents. Also it is assumed that employees and innovation practitioners
do not exercise their decisions based on irrational biases or determinable
psychological conditions.
8
1.5. Delimitations and Limitations
For the purposes of this study, the following delimitations are to be applied. First,
the following model will be directly applicable to companies in any country or
those which have formalized innovation process for creating new products and
service industry. Also the study supporting the proposed model may be applied
to companies which conduct innovation with a heavy emphasis on process-
based management.
Several limitations apply to this study. Since this study will require self-
reporting by respondents, the reported results may not be representative of the
respondent company’s actual behaviors or practices. In other words, the
respondents may knowingly or unknowingly falsify their responses.
Given the sample size, it is not reasonable to conduct on site visits to
validate the respondent’s answers; however, check questions will be put in place
to determine discrepancies and help indicate if respondents are being consistent.
Second, the proposed control model and supporting study will not take
into account company culture, or national culture because those factors cannot
be accurately gather through a survey and almost always require primary
research to accurately obtain.
9
CHAPTER 2. A COMPREHENSIVE REVIEW OF THE LITERATURE
2.1. Literature Review of Ideas
“Man can live without air for a few minutes, without water for about five days, without food for about two weeks, and ….without a new thought for years on end.” – Kent Ruth
2.1.1. Why does the Innovation Process Need Ideas?
The goal of a company’s innovation process is to create new products and
services, or improve operations, brand, customer’s experience, supply chain
operation, and so on. Yet, every one of the mentioned concepts starts as an
idea. Ideas are a core part of the innovation process. Vandenbosch, Saatcioglu,
& Fay (2006) states “each innovation begins with an idea”, and Jack Foster
(1996) asserts “new ideas are the wheel of progress” and Linda Rochford (1991)
ideas are the raw material for product development.” Logic says, all the current
products and services were once an idea in someone’s mind. Steven Covey
(2004) calls an idea the “first act of creation” where the second act of creation is
the deed of putting an idea into a physical form.”
Obviously, ideas are vital in the innovation process, and the following
references support this point (Verworn & Herstatt, 2001; Boeddrich, 2004; Hüsig
2) Strategy – how the company plans future actions
3) Employees – attracting, acquiring, retaining, training, socializing, and
motivating employees
4) Products & Services – similar to above
5) Processes – similar to above
6) Tool – the gear, machinery, models, theories, practices used by the
company
7) Technologies – the technology used and created by the firm or for the
customer
8) Suppliers – finding, selecting, leveraging, enhancing suppliers to the
company
9) Market distribution – methods of finding, distributing, delivering, supplying
the customers and
10) Brand – similar to above.
There are visible differences between the above two categorizations;
however, both demonstrate ideas create value in a variety of forms. In later
discussions on new product development it may be helpful for the reader to
restrict the scope of ideas to those which relate to new offerings. Ideas related to
offerings can be anything from a minor tweak of a product (like its color) all the
way to a release of a new product technology which creates a new market.
2.1.5. Terminology
In reviewing the literature, this researcher has noticed many articles on idea
generation may not use the word “idea”. Subsequently there are several words
which have been interchanged with the word idea such as: invention, concept,
innovation which in essence mean the same thing. Some articles prefer to use
15
the term “concept” (Backman, Borjesson, & Setterberg, 2007; Wagener &
Hayashi, 1994). Some prefer “innovation”. Some prefer the word “opportunity”.
The term, “concept”, is often interchanged with the word “idea”, but it has
a slightly different meaning. Concept generally refers to “a set of proposed
solutions complying with a set of fixed constraints” (Backman, Borjesson, &
Setterberg, 2007, p. 86). Articles like Backman, et al. (2007) and (Crawford, Di
Benedetto, 2003) use the term concept instead of the term idea.
Similarly the term “opportunity” is interchanged with the word “idea”.
Vandenbosch, et al. (2006) state that “ideas and opportunities are intertwined.
Recognizing or creating an opportunity is an occasion for generating or testing an
idea; an idea may lead to an opportunity and it may require an idea to capitalize
on an opportunity” (Vandenbosch et al, 2006, 371). Researchers should note that
in the literature, the use of the term “idea” can be spotty in relation to methods for
generation of ideas for new products or services.
To help refine the terminology associated with a project in the new product
development process Merle Crawford, and Anthony Di Benedetto (2003)
proposed the “concept life cycle model” in the figure below. This model showed
the evolution of the terms associated with a project as it met given requirements.
This strict model for the terminology associated with a project show the
terminology for an idea changes as the idea is developed. Appendix A described
each of the twelve terms in this model.
16
Figure 2.1. Concept Life Cycle Model
It is questionable whether new product development practioners will
adhere to any strict terminology. Further, the concept life cycle model may not be
followed linearly by practitioners. For example some R&D labs are known for
having prototype concepts, being a tentative physical product, including feature
and benefits, prior to having protocol concept, being a statement of the intended
market user, the problem perceived, and the user benefit.
Nonetheless, for this thesis the word ‘idea’ was chosen over the word
‘concept.’ This way the reader will not have to memorize the terms shown in the
above figure 2.1. Further, the level of an idea’s development will be clarified. For
example, an idea may be in the commercialization phase or be successfully
launched by a competitor. This should also remind the readers of the value that
ideas have in the innovation process.
2.1.6. New and Old Ideas
Another way one can look at an idea is “if the idea is new or old.” It is often
thought that a company needs to come up with new ideas, but one should not
forget old ideas may work just as well. For example, say a manager was
Market Value
Clarity
High
Opportunity concept Idea concept
Stated concept
Defined concept
Protocol concept
Batch concept Processes concept
Pilot concept
Market concept
Successful
Prototype concept
Test concept
High
17
generating ideas about how to motivate his employees. Old ideas like ‘paying
more’ or ‘conducting moral surveys’ work just as well, or even better, than a new
idea like building ‘a in house gym.’ Vandenbosch, Saatcioglu, and Fay (2006)
observe that “not all ideas are creative, nor do they have to be. In fact, successful
managers often rely on old, ordinary ideas or new, but imperfect one to cope with
the challenges they face” (p. 95).
In new product development there is an often unsaid assumption that all
newly release products should be based on new ideas. This assumption is based
on the view that customers want new things. But what often is disputed is the
meaning of new. Is the product idea new to the market, new to the world, or new
to a company? Rochford discusses this in some detail. A product can be “new”
in the sense it is either: (1) new to the firm, taking the company into new markets,
new technologies, or new production methods; (2) new to the market, the first of
its kind, what some call an innovation; or (3) new in the sense it is better for the
customer with the product yielding some net benefit to the customer. For the
intentions of this study, a new product will be defined as a product not previously
manufactured by the firm. In other words, a product is new to the firm (Rochford,
1991).
This researcher has selected new to the firm as the definition of new ideas
for this thesis. This was chosen for the three following reasons: 1) managers
often mistakenly think the product idea is new, 2) managers apply the word new
to their project to improve their social image inside the company 3) because
companies’ often increase the attractiveness of their products and services to
customer by promoting it as new.
2.1.7. Summary of Literature Review on Idea
In summary, there is a strong need for ideas so a company can grow and
develop. This requires the innovation processes to generate or obtain ideas,
where the innovation will then use these ideas to grow the company’s offering,
improve operations, improve the brand image, improve the customer experience
18
and ensure sustainability. We have defined an idea as the result of the brain’s
activities in which previous knowledge or ideas are recombined in a way forming
a new concept. The definition was further specified to describe an idea as
creating value for a company. And in specific instances of new product
development, an idea is any changes to or new product or services offered by
the company.
This section also alerts future researchers to the fact that the word “idea”
may be interchangeable with words like innovation, concept, opportunity,
technology, offerings, and other. Thus future research on things like idea
generation should take these keywords into account in their searches. Finally,
this researcher discusses new and old idea, and fell on his definition of a new
idea as being “an idea which is new to the firm.”
2.2. The Evolution of the Innovation Process
2.2.1. The Importance of Innovation
The study of innovation has gained much notoriety since the 1980s, for good
reason. Companies now realize more than ever that their ability to innovate so
strongly affects their company’s future. Books with titles like “Innovate or Die” by
Jack & Matson (1996) and quotes by greats like Drucker (1985a) ‘company have
two functions innovation and marketing everything else is just expenses’ are just
a few of the messages in the popular media which blasts that innovation is vital.
Almost all articles or books on innovation open with statistics on the value
of innovation, or logic of how innovation creates tomorrow, or even strong winded
stories of innovative companies perpetuating throughout the decades while their
competitors die off. As well, conferences around the world on the topic of
innovation, and hundreds of top management consulting firms with department
19
specializing in innovation attest to innovation’s vital function in the businesses of
today. Magazines like MIT’s Technology Review (2003) even track and rate
yearly the top R&D spenders an achiever in each industry.
Hence it would be trivial and even redundant to open with a couple
paragraphs restating the value of innovation. Funny enough, this researcher has
yet to see an article asserting that innovation is not all as important as the
popular management trends makes it out to be. Nonetheless, this researcher
must say “innovation is important and must not be ignored.”
2.2.2. A Quick History of Innovation and R&D: A Process Perspective
It is amazing how fast and how far society has advanced over the last two
centuries from the horse and carriage to landing on mars, from living in dark
candle lit wooden houses to the luminous glamour of New York’s time square
skyscrapers. With all these advances it is funny to think that the formal study of
management did not even exist until Frederick Talyor launched the movement of
scientific management in 1911. So looking back, it is amazing that the first and
second industrial revolutions (1st from 1760 to 1850 and 2nd 1860 to 1900) were
achieved without any formal knowledge of management or innovation (Ashton
1997).
Similarly, the study of R&D management is relatively young since it was
started around 1920s or 1930s. The first accounts of a true R&D lab mentioned
in the literature are that of Thomas Edison’s in Menlo Park, New Jersey. As
Andrew Hargadon (2000) posit:
From 1876 to 1881, Thomas Edison in his Menlo Park, New Jersey laboratory produced one innovation after another: high-speed, automatic, and repeating telegraphs; telephones; phonographs; generators; light bulbs and vacuum pumps. Edison built the laboratory, in his own words, for the “rapid and cheap development of an invention” and promised “a minor invention every ten days and a big thing every six months or so.” And he delivered. In a
20
single six-year period the laboratory generated over 400 patents and became known worldwide as an invention factory. - The Menlo Park laboratory was one of the first dedicated research and development facilities. Over a century later, it remains the model for R&D in modern firms (Hargadon, 2000, p. 3).
Figure 2.2. Early R&D process
The early innovation process is depicted in the figure above and it
includes generating the ideas, testing the ideas, developing the ideas, and even
launching the ideas to market. It is thought the process was managed by a
primary stake holder (like Thomas Edison) where they eliminate poor project, and
decide how to advance others (Axelrod, 2008).
As one can see, much of the process was not formalized and depended
highly upon a knowledgeable stakeholder. Hargadon mentions in his articles on
knowledge brokering that the Menlo Park lab was a room full of bright inventors
and engineers from many disciplines who talked a lot about inventions and
technology, were close, constantly experimenting, prototyping, and working
towards making world altering technologies, which they did.
At some point later, possibly in the 1930 or 1940s, companies started
adopting the concept of a funnel in their R&D process. The funnel helped
manage cost and control risk while opening up the option for evaluating and
developing many ideas. Think of it as a literal funnel where the front end catches
many ideas, and eventually through the R&D process is funneled down to a few
preferable ideas.
21
Figure 2.3. R&D Funnel
This concept greatly allows companies to explore their options while
managing risk and cost. Remember as an idea progresses through the R&D
process it accumulates greater and greater expenses. Thus, using the funnel
concept to weed out less preferable ideas helped manage cost and reduce new
product risk.
Later yet, around the 1930s or 1940s the above process was split up into
two parts 1) R&D process and 2) new product development and
commercialization processes. The R&D process was a highly random process of
discovery where the new product development processes’ was a controlled way
of developed products and services for the market. The first processes opened
up options for the company where the second analyzed, selected, and developed
the best options.
Figure 2.4. R&D Funnel and New Product and Commercialization Processes
R&D funnel Output: Discovery in
knowledge, Inventions,
New ideas for product or
services New product
development Commercialization
Market launch
Idea for new
product &
Services
Input:
Research
Decision point
R&D funnel Input:
Ideas Output: Market
22
For the most part, these were different processes, with the R&D funnel
focusing on creating discoveries in understanding, creating new knowledge,
generating novel inventions, generating new product ideas, and figuring out
where to look next. The ideas from the R&D process along with other were then
feed into the new product development processes. Again the new product
development processes function similarly to the R&D funnel described above.
Companies like IBM, Xerox, and Bell Labs were famous for having their
R&D divisions filled with geniuses and brainiacs which came up with new far-out
inventions and discoveries. Some discoveries were so great that many
researchers were awarded Nobel prizes. Figure 2.4 shows the second process
divided into new product development and commercialization. The line between
those processes represents a formal point of evaluation so that projects can be
stopped before they enter the commercialization phase. This keeps poor projects
from advancing to the commercialization phase where expenses increase
considerably. Many companies do not have the resources to support a research
division and thus typically use a new product development and commercialization
process for innovation.
The next major change in the process was the addition of the “fuzzy front
end (FFE)” by Smith and Reinertsen in 1991 and is illustrated in Figure 2.5.
Figure 2.5. Addition of the Fuzzy Front End
Murphy & Kumar (1997) state the fuzzy front end “ranges from the
generation of an idea to either it approval for development or its termination”, and
is “often chaotic, unpredictable, and unstructured” (p. 32).
New product
development
Commercialization processes Market launch
Ideas for new
product &
Services Decision
FFE
23
The goal of the fuzzy front end is to reduce uncertainty about an idea and
develop it into a concept which could be entered into the new product
development process (see definition of a concept in Appendix A). The fuzzy front
end will be mentioned at length in Sections 2.3, 2.4, and 2.5 of this thesis.
The next major development was the introduction of the stage-gate
process by Robert Cooper (2008). The stage-gate process split the new product
development process up into multiple stages where at the end of each stage
there was a formal decision point being a gate. Each gate provided the stake
holders an opportunity to evaluate a project, and then make a decision to either
end/kill the project, or advance the project to the next stage. Killing a project was
accomplished by denying funding or removing resource.
The stage-gate process served as both a guide, by requiring specific goals
to be met at the end of each stage, and a means of controlling risk, by eliminating
poor projects as more information emerged. Each stage had goals like, to have a
working prototype or proof of market demand.
Again, if the goals were not met the project would not move into the next
stage. The concepts of State-gate truly revolutionize the NPD process.
Figure 2.6. State-Gate Process in the Overall Development Process and a
Map of Project Costs as the Project Progresses
Market launch Process
Decision
FFE
Commercialization Stage Gate process for NPD
Stage in
Relative
Expenses associate
with a project
Expenses increase as project proceed
Idea for new product & Services
24
Figure 2.6 above represents the current best practices model for
developing product and services. Amazingly, according to research by Hsiao &
Chou (2004), 40% of the companies surveyed had no formalized product
development. This means that 60% of companies report having some type of
product development process. Further, it is not known what percentage is of
companies are utilizing the current best practice model, as shown above. Some
companies may include the R&D basic research process in their development
process, but most usually keep it separate from the process shown in Figure 2.6.
Typically only new product and service ideas move through the above
mentioned processes. Other ideas, like those for process or manufacturing
improvement, move through a separate process such as Kazian or total quality
management and other ideas, like branding or value capture, may be developed
through their own unique processes.
The market launch process shown in Figure 2.6 is depicted as an
expanding cone to denote the additional costs and activities associated with a
market launch. Further, the chart in Figure 2.6 shows generally how expenses
rise in each respective stage. Current development models try to reduce risk and
uncertainty while expanding options for a company.
A recent article in Harvard Business review, entitled the “Innovation Value
Chain” by Hansen & Birkinshaw (2007), shows the innovation process as a
series of linked processes, where if any link is weak the whole innovation
processes is negativity affected. They emphasize that there are “no universal
solutions for organizations wanting to improve their ability to generate, develop,
and disseminate new ideas” (p. 15). As well, they emphasize “managers need to
take an end-to-end view of their innovation efforts, to pinpoint their particular
weakness, and tailor their best practices appropriate to their deficiencies.”
25
Figure 2.7. Innovation Value Chain
Figure 2.7 shows the innovation value chain as being divided into the
three major areas of idea generation, conversion, and diffusion. Idea generation
is composed of generating ideas in-house; cross-pollination is getting different
divisions and units to collaborate to combined knowledge and insight; and
external sourcing is getting ideas from outside the organization.
Conversion is composed of selection and development. Selection is
screening idea, analysis idea, and initiating funding for given ideas. Development
is transforming an idea or concept into the required final form. Finally, diffusion
involves spreading the idea around the organization so that the crucial share
holders involved in the market launch and operational activities commit to the
idea.
The innovation value chain model is not so much a process model as a
model describing the vital goals in each phase. The innovation value chain can
also be used to analyze how the best practices models fit and is performing in a
company’s development process. For example, the stage-gate process can be
seen to fit in both the selection and development areas. Whereas the PAC
approach, in which a product approval committee is used to select and screen
projects, would only be applicable to the selection of projects and cannot be used
to guide development (Koen 2005). One can see the genius in leaving the model
broad because it allows a company to tune its innovation value chain to the most
effective processes instead of blindly following the best practices models.
26
Hansen & Birkinshaw (2007) focused on diagnosing a company’s
innovation value chain, which is very helpful because few articles offer any
diagnostics tools for innovation. They described different deficiencies in
companies as delineated below:
1) Idea-poor companies are company, which spends a lot of time and
money developing and diffusing mediocre ideas which result in
mediocre products and financial returns. The problem is in idea
generation, not execution.
2) Conversion-poor companies has lots of good ideas, but managers
don’t screen and develop them properly. Instead, ideas die in
budgeting processes which emphasize the incremental and the certain,
not the novel.
3) Diffusion-poor companies have trouble monetizing their good ideas.
Of course a company can be weak in any one or more of these areas, hence the
authors offer references to other articles which discuss solution to improving a
specific part of the innovation value chain. Finally, the article ends by stating that
companies should benchmark and record statistics on each part of their
innovation value chain, so they can monitor performance and make specific
improvements.
2.3. Research on the Fuzzy Front End
2.3.1. Intro to Section on Fuzzy Front End
The term the ‘fuzzy front end’ is ambiguous and may elicit many questions like,
“what does the term mean?”, “what take place in the fuzzy front end?”, “why is it
important to research?” or “why should innovation practitioners care about it?”
This chapter addresses many of these questions and attempts to clarify what the
fuzzy front end is, and what type of research has been done on it to date.
27
2.3.2. Terminology for the Fuzzy Front End
As mentioned, the beginning of the innovation process is the main focus of this
thesis; however it goes by many names. The term the fuzzy front end was
popularized by Smith and Reinertsen in 1991, and was used since the word
“fuzzy” describes how chaotic, unpredictable, and uncertain this part of the
innovation processes can be (Koen 2005). However, there are several other
terms which were applied to describe this phase of innovation such the ones
listed below.
Front end of innovation,(Nobelius, 2000; Front End of Innovation
Conference, 2008; Koen, 2005; Koen, 2001) Early stages of the product
development (Nobelius, 2000; Khurana and Rosenthal,1998), early phases of
innovation (REF C3), early innovation phases (Lichtenthaler, Savioz,
The fuzzy front end of innovation or, for the sake of brevity, ‘front end of
innovation or FFE’ has many definitions in the literature, most of which define it
by stating the type of activities which take place in it. Basically, FFE involves
“activities taking place prior to the formal, well-structured new product process
development” (Koen, 2005; Koen et al., 2001, p. 3). Other similar definitions are
Reid & Brentani’s (2004) where the FFE “is considered to be the earliest stage of
the new product development (NPD) process and roughly is meant to denote all
the time and activities spent on an idea prior to the first official group meeting to
discuss it or what they call ‘the start date for team alignment” p. 5). Others
define it in terms of the activities which take place. Murphy & Kumar (1997)
define the front end as ranging “from the generation of an idea to either its
approval for development or its termination” (Verworn & Herstatt, 2001, p. 53).
A lengthier definition by Crawford and Di Benedetto (2000) is the fuzzy
front end’s “early activities are broad and include opportunity identification and
exploration, while later activities consist of information collection and concept
28
development preparing it for the transfer into the NPD process” (Backman,
Borjesson, & Setterberg, 2007). Yet, Khurana & Rosenthal define the front end
“to include product strategy formulation and communication, opportunity
identification and assessment, idea generation, product definition, project
planning, and executive reviews” (Verworn & Herstatt, 2001, p. 83). As well, Kim
& Wilemon (2002) define the FFE as “when an opportunity is first considered
worthy of further ideation, exploration, an assessment, and ends when a firm
decides to invest in the idea, commit significant resources to its development,
and launch the project (Kim & Wilemon, 2002, p. 31). Finally, Hüsig and Kohn
(2003) and have the most elaborate activity based definition of the FFE which
has lists of both exclusive and inclusive activities. Yet a comparison of the fuzzy
front end to the NPD process in table form seems to be one of the best ways to
understand what the fuzzy front end is, see Tables 2.1 & 2.2 below.
Table 2.1. Koen et al. Activities in the Front End of Innovation
and New Product Development Processes
Table 2.2. Koen et al. Factors and
and New Product Development Processes
2.3.3.
The activity-based definitions can give one a slight understanding for the
activities which take place in the FFE; however, further
According to Verworn & Herstatt
strategy formulation, communication, opportunity identification and assessment,
idea generation, product definition, pro
(Verworn & Herstatt, 2001,
activities are generation of ideas, initial screening, preliminary evaluation, and
concept evaluation” (p.11)
phases for the FFE being “1) idea phase 2) feasibility and potential phase and 3)
concept development phase. Interestingly, thi
state:
Activities do not occur in a specific order: It is important to note that these three different phases and gates differ from the normal stagegate process in some extent. First of all they are not a sequential order of activities that are followed through development process. This can happen, but in general the teams
Factors and Characteristics of the Front End of Innovation
and New Product Development Processes
2.3.3. Activities in the Front End of Innovation
based definitions can give one a slight understanding for the
place in the FFE; however, further clarification is needed.
Verworn & Herstatt (2001), the tasks in the FFE are, “product
strategy formulation, communication, opportunity identification and assessment,
idea generation, product definition, project planning, and executive review
Verworn & Herstatt, 2001, p. 383). Cooper’s (1988) article concludes the main
activities are generation of ideas, initial screening, preliminary evaluation, and
(p.11). Similarly, Hüsig and Kohn (2003) states
phases for the FFE being “1) idea phase 2) feasibility and potential phase and 3)
concept development phase. Interestingly, this Husig, Kohn, & Poskela
Activities do not occur in a specific order: It is important to note that these three different phases and gates differ from the normal stagegate process in some extent. First of all they are not a sequential order of activities that are followed through like in the following development process. This can happen, but in general the teams
29
the Front End of Innovation
based definitions can give one a slight understanding for the
clarification is needed.
the tasks in the FFE are, “product
strategy formulation, communication, opportunity identification and assessment,
planning, and executive review”
article concludes the main
activities are generation of ideas, initial screening, preliminary evaluation, and
states general
phases for the FFE being “1) idea phase 2) feasibility and potential phase and 3)
s Husig, Kohn, & Poskela (2005)
Activities do not occur in a specific order: It is important to note that these three different phases and gates differ from the normal stage-gate process in some extent. First of all they are not a sequential
like in the following development process. This can happen, but in general the teams
30
working in the front-end works on several parallel projects, and redirects ideas and concepts from one stage to another. While in the development stage-gate process the redirection of projects is more an exception, it is more the rule in the front-end (Hüsig and Kohn, 2003, p. 11).
Furthermore,
Concept and ideas merge, and activities are continuous in nature: for each opportunity that seems worth pursuing several ideas will be developed. Those ideas will be combined to one or more concepts. This implies that the subject of analysis keeps changing over the process. Therefore this process model is rather a representation of continuous activities that permanently go on in order to fill the NPD pipeline (Hüsig and Kohn, 2003, p. 14).
This researcher strongly agrees that the activities of the FFE do not occur
in a specific order, partially because of the work of Koen et. al. (2001) but also
because of the large observed variation in activities noted in case studies on the
FFE. This researcher also strongly agrees with the continuous nature of the FFE,
which is also represented in Koen et al’s model.
2.3.4. Importance of the FFE
One might ask what is the importance of the fuzzy front end in the innovation
process. Kahn the editor of PDMA handbook (2003) and an authority on
innovation and new product development states that he “sees the front end as an
important issue in future research on product development 2003” (Verwon,
Herstatt, & Nagahira, 2008). Also, “Rice calls the fuzzy front end ‘the root of
success’ for discontinuous product innovation” (Verwon et al., 2008, p. 32). More
importantly, an extensive empirical study by Cooper & Kleinschmidt (1994)
showed, “the greatest differences between winners and losers were found in the
quality of execution of pre-development activities” (Verworn & Herstatt, 2001, p.
43).
31
Furthermore, Backman, Borjesson, and Setterberg (2007) posit that “the
greatest opportunities for improving the overall innovation process lie in the very
early phases of NPD” process (Backman, Borjesson, and Setterberg, 2007, p.
52). Hence, Zhan and Doll (2001) states, “managers and researchers claim the
benefits resulting from improvement in the front are likely to far exceed those that
result from improvements aimed directly at the design engineering process”
(Zhan & Doll, 2001, p. 73).
Kim and Wilemon (2002) state “the importance of the FFE lies in the fact
that effectively performing front-end activities can contribute directly to the
success of a new product” (p. 32, Cooper 1988, 1998; Dwyer & Mellor 1991;
McGuiness & Conway 1989). As well they state, “one can find several low cost
opportunities to achiever large improvement in time-to-market” (Kim & Wilemon,
2002, p. 33).
However, only a few references state why it is so important. To prove the
value of the FFE Cooper and Kleinschmidt (1994) found that pre-development
activities received the least amount of attention (only at 6% of dollars and 16% of
man-days of the total) when compared to the product development and
commercialization stages. Interestingly, when they compared successes to
failures they found about twice as much money and time is spend for the front
end stages. Although the importance of the early development phase is
recognized, researchers and practitioners still focus on the later phases of the
innovation process, where information is more reliable (Verworn & Herstatt,
2001). It seems there are some concerns related to failure rates of projects in the
FFE as alluded to by Khurana & Rosenthal (1998) who commented that “most
projects do not fail at the end; they fail at the beginning” (Khurana & Rosentha,
1998, p. 1).
Unfortunately, a review of the literature failed to produce a list of
compelling reasons which support the importance of the FFE. Thus, this study
begins with developing categories that reasonably capture the importance of the
FFE. The first category of reasons concerns the costs involved in the innovation
32
processes. As mentioned above, a single idea may be cheap to develop and
analyze in the FFE but as Cooper and Kleinschmidt state cumulatively
developing and analyzing many ideas over time may show the FFE is a larger
expense than previously thought.
Second, the fuzzy front end is directly responsible for getting valuable
ideas into the innovation value chain or new product development (NPD)
processes. The old adage ‘trash in trash out’ applies well to the innovation
processes. The value and quality of the ideas going into the new product
development process is a major limiting factor affecting the quality of products
and services ready for market launch. Thus, researching the FFE to determine
how to get a high quality stream of ideas into the NPD processes is a creditable
research goal.
Third, it is clear that in reducing the amount of uncertainty through the FFE
activities, we achieve better results in terms of concepts, project plans, and
selections of tasks for the project as it moves into the new product development
process. In other words, the more information a new product team knows, and
the less uncertainty they have, the better they can optimize costs and plans for
subsequent new product development activities.
Lastly, the organizational fit and organization’s commitment to a new idea
is the final category of importance for FFE. Having a deep understanding of the
fuzzy front end will allow companies to generate ideas, then select or screen
ideas and concepts which fit with the company’s capabilities and strategies. As
well, it will allow companies to put in place the people, management, teams,
culture, incentives, and other mechanisms which are considered vital to obtained
ideas and pushing them through to market launch.
2.3.5. Deliverable at the End of the Fuzzy Front End
One might move on to ask, “What are the deliverables at the end of the fuzzy
front end?” And it is unfortunate, but this question has not been answered in
much detail in the literature. Cooper (1993) says, “one goal of the FFE is the
33
creation of a well defined product concepts prior to development” which seem
obvious given the NPD process requires a clear concept to proceed (p. 13). This
All of these activities build a large amount of knowledge about the
customer, their behavior, and their environment which are then used to locate
opportunities and generate ideas. For example, contextual research studies
usually are delivered in video and written form which is directly used to generate
ideas (Conley, 2002).
Amazingly, the valuable knowledge generated during these intensive
research studies may be re-used to fuel future idea generation activities;
however, the documents containing them may be forgotten about or even worst
60
lost in a company’s database. Why, can’t these documents be built upon
resulting in a richer record of information to help spawn idea, and locate unseen
opportunities? Note: idea management and knowledge management overlap to
a degree because ideas are considered a form of knowledge (Bakker, Boersma,
& Oreel, 2006).
Remarkably, the front end processes and FFE process models have no
link to knowledge management. Additionally, building the capabilities to execute
a project in the NPD also requires knowledge management, to insure the product
team has obtained the needed knowledge, or know how to get the information to
execute effectively. Even the business plan is considered a knowledge document
which must be built, developed, and managed.
Hardagon & Sutton (2000) article on knowledge brokering at IDEO is
probably the best evidences that knowledge management should be integrated
into FFE processes. They learned “the best innovators systematically use old
ideas as the raw material for one new idea after another” (p. 6). In the highly
innovative companies they studied, they found individuals: 1) captured good
ideas from things they researched for customers, observed from other great
inventions, or collected, and 2) kept ideas alive in product archive rooms,
databases, idea fairs, and pictures which is very similar to knowledge storage
and 3) applied old ideas in a new way by allowing individuals to communicate
problem through expert phonebook databases and disseminate good ideas
amongst their organization.
For example, IDEO offices are very open allowing for hundreds of unplanned
interactions per day.
Hence, a link to knowledge management could benefit idea generation,
opportunity identification, as well as, other activities of the fuzzy front end, and
should be integrated into future process models for the fuzzy front end. If
anything the process of knowledge brokering some how should be integrated into
the processes for the FFE especially for firms with large amounts of design work.
61
2.4.13.6. Poor Link to Creativity Management
Creativity management is not mentioned in articles on the fuzzy front end,
but it however, has been mentioned greatly in the literature on idea generation
and opportunity identification. Steven, Burley, & Divine show individuals with
higher creativity which are coached in the NPD process and business basics out
perform individuals with normal creativity by up 5-to-12 times. This result was
obtained from a single long term study in one company but seems very
promising. This leads one to think that creativity management should concentrate
on placing individuals with high creativity into the FFE processes and train them
to practice discipline business.
As well, journals like ‘creativity and innovation’ among others attest to the
importance of creativity management. In the literature, creativity management
has gained much importance in FFE processes of companies (like marketing
firms, advertising, design firms and so on) where design task are prevalent
(McAdam & McClelland, 2002). Majaro (1991), state creativity can be divided
into three categories, depending on how it originates. These are A) normative
creativity, which is creativity in problem solving, B) exploratory creativity which is
creativity not related to a particular demand, and C) creativity by serendipity
which is luck or chance (Flynn, Dooley, & O’Sullivan, 2003). So tasks like
experimentation and prototyping can help increase creativity through both
normative and explorative means. Thus, activities which have high creativity
potential can be integrated into the FFE processes, and in this way, creativity
management can be knowingly integrated into FFE processes.
62
2.5. Literature Review of Activities in the Fuzzy Front End
As can be seen in section 2.4, each FFE model tends to highlight some
activities over others; as well, some models may not mention an activity which
another model says is vital. Hence, this researcher feels it would be valuable to
create a comprehensive list of formally named activities which may take place in
the fuzzy front end, and then quickly describe how each functions.
2.5.1. List of Activities in the Fuzzy Front End
Table 2.4 below shows all of the activities mentioned in the FFE literature
which can or should occur in the front end of innovation. Note the table was split
into to columns so the information can be placed all on one page.
Table 2.4. List of Activities Which Can Occur in the Front End of Innovation
Knowledge management Idea GenerationConcept refinement Idea SelectionTesting (trial) Idea ScreeningMarket testing Diffusing IdeaFunctionality testing Knowledge Management Analysis Diffusing ideas
Idea and concept Analysis Idea ManagementMarket analysis Prototyping Competitive analysis Environmental Scanning
Building a business case Opportunity IdentificationPlanning for the NPD Opportunity AnalysisReview Review Development Research Strategy planning Market Research Application Exploration Customer research Partnering Technical ResearchPortfolio planning Commitment building
At first glance, one notices that many activities can occur in the front end
of innovation. Table 2.4 highlights the major activities which are referred to in the
literature. Table 2.4 places them in similar categories, so, for instance, concept
testing and market testing both fall under the major category of testing.
63
The first set of tasks is concept refinement and includes selecting or
developing a concept definition. Concept refinement is a very broad activity
which can include many if not all of the activities mentioned below. In many
instances concept refinement means specifically, narrowing a definition of the
product or service into a short narrative or illustrated form.
Testing is a vital activity in the front end and includes concept testing,
market testing, technical testing, functionality testing, and manufacturing testing
among others. Concept testing usually pertains to testing the concept with
customers and users, where market testing is more looking at the demand and
receptiveness of the market to the product or idea. Functionality and technical
testing are self-explanatory.
The term “testing” may be inter-changed with the word “analysis.” For
example, concept analysis looks at the strengths and weaknesses of a concept
where concept testing could also be done the same way. The goals of testing are
typically understanding and the confirmation of assumptions. So something like
concept testing seeks to understand how customers feel about an idea and tries
to confirm the assumed value of that idea. Please note, the word ‘trial’ can be
inter-changed with the word ‘testing.’
Analysis is a very broad term and can be activities like idea analysis,
opportunity analysis, competitor analysis, or even functionality analysis.
Consequently, the term “analysis” alone is not very guiding as an activity and
must be combined with another term to really be made into an activity. For
example, market analysis can be anything from looking at the size of the market
and its revenues, to a detailed examination of trends, price-elasticity, and
impending market events.
The goal of an analysis is typically understanding and the building of
knowledge. For example the goals of a competitor analysis mainly are to
understand the competitive landscape which aids in judging the risk of the
competition. The words analysis and assessment can be inter-changed.
64
Opportunity identification is a commonly cited activity and is the act of
locating favorable circumstances or situations in the marketplace. Opportunity
identification examines in the marketplace for: 1) a solution is needed or, 2) there
are un-filled customer needs, or 3) there is a chance to create new customer
needs, or even 4) there is some type of change in the market which creates a
chance for new business offerings. Opportunity analysis is the activity of
examining the opportunity to determine if it has validity and value. Opportunity
analysis seems to overlap to some degree with customer needs analysis. As
well, opportunities screening is the act of eliminating opportunities from further
consideration.
Planning or project planning is a typical activity which involves creating
project plans, with lists of: activities, milestone, objectivities, and deliverables.
The project plan is typically used to guide tasks in the new product development
process, but can also guide tasks for the FFE process.
Building a business case is a fairly comprehensive set of activities,
which includes many types of analysis, testing, planning, and development. Most
importantly a clear understanding of the risks, benefits, requirements, and
required resources should be clarified and presented to upper management.
Typically, building a business case results in a defendable business plan.
However, as an activity alone ‘building a business case’ is a bit too broad and
should not be used to guide specific activities. Importantly this term does
emphasize the need to prove the value of the idea, while minimizing the
downside. Hence, this researcher really prefers ‘building a business case’ to be a
goal more than a specific activity.
Reviews are also a highly cited front end activities. Reviews may be tasks
like a legal review, technical review, business case review, and so on. Reviews
are typically an activity where either upper management, stake holders, or parties
controlling resources have the opportunity to, examine, evaluate, and judge a
particular item. For example, a legal review is an activity where a company’s
lawyers can assess the legal impact a particular idea would have on a company.
65
Reviews are an integral activity which may also include making particular
decisions, like the gates in the stage-gate process. The word ‘evaluations’ can
also be inter-changed with reviews.
Development is another broad word which can include anything from:
environmental scanning, among others. The term research is associated with
activities such as learning, knowledge building, and testing, and may be
combined with another term to serve as a focused activity, like market research
or customer research.
Commitment building activities relate to getting devotion or dedication to
an idea and can include activities like idea selling which typically are performed
by product champions, product teams, or upper management (Hansen &
Birkinshaw, 2007). Again this discussion of activities in the front end was not
meant to be comprehensive but more of an overview of general activities which
can take place.
Application exploration activities related to finding, and exploring
applications and potential markets for a new radical or disruptive technology.
Interesting, Thongpapnal, O’Connor, & Sarin (2008) argue that application
exploration for radical & disruptive innovation is vita and if done poorly may
“result in serious repercussions on the perceived viability and business potential
of the proposed major innovation” (Thongpapnal, O’Connor, & Sarin, 2008, p. 4).
Application exploration is rarely mentioned in the FFE literature. However,
Thongpapnal, O’Connor, & Sarin’s (2008) study makes a strong argument that
application exploration should be a formal activity in the FFE, especially for
radical & disruptive innovations.
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2.5.2. Quick Categorization of Activities in the Fuzzy Front End
In reviewing activities which take place in the front end, it was observed that
some activities related to (a) improving and evaluating a concept, or the (b)
alignment and management activities, while others were general activities for (c)
coming up with ideas. Table 2.5 shows a rough categorization placed into these
three areas. One should notice that many activities overlap between areas.
2.5.3. Proposed Organization of Activities for the Fuzzy Front End
It seems from conducting this rough categorization that there is a big division
between front end activities related to developing a particular idea, and front end
activities for getting ideas. However, it was also observed that some activities
benefited both areas, such as analysis, idea diffusion, research, and testing.
Table 2.5. Categorization of Front End Activities
A) Activities related to a developing a particular idea
C) Activities related to generation of ideas
Analysis AnalysisBusiness case building Diffusing ideasCommitment building Environmental screeningConcept refinement Idea capture & storingDevelopment Idea diffusionIdea diffusion Idea generationKnowledge creation, storage, & diffusion
There are hundreds of different ways to display information
Scenario games Create scenarios and try to play them out to their logical end.
* Jack Foster "How to Get Ideas" pg 117, * Rochford Linda 2001
Aggregation , Combination Combining characteristics of a product, service, offering, processes, into a single thing
* Rochford Linda 2001
Metaphors & Analogies Compare a problem, solution, or thing to a person, place, thing, concept, time, or experiences to draw out relationships
* PDMA handbook 2005 chapter 17, * Jack Foster "How to Get Ideas" 110
Our truck is tough like a ram, why not make it look more like ar ram
Though experiment Measure, tests, validate, explore, through thought by deductive or inductive reasoning and proceed through to the logical results to gain an insight
* PDMA handbook 2005 chapter 17, * Rochford Linda 2001
Redefining question Re-wording the question to change the perspective on the problem
* Jack Foster "How to Get Ideas"
How do I work harder to "how to I get more work done" (improve work efficiency)
Think like a child Being open to re-questioning base assumptions, look at the world with extreme curiously to find new relationships
* Jack Foster "How to Get Ideas" pg 55
Why do refrigerators have to have doors?
Lateral thinking The shifting of thinking patterns, away from entrenched or predictable thinking patterns to new or unexpected ideas
* Edward de Bono The Use of Lateral Thinking, published in 1967. * Jack Foster
Remove boundaries, and base assumptions
Remove boundaries, and retest base assumptions, do not assume restriction unless strictly told
* Jack Foster "How to Get Ideas" pg 102
Set strict limits Set limitations, remove typical options * Jack Foster "How to Get Ideas" pg 106
Find solutions within limitations
Purposefully break the rules
purposefully violate base assumptions, and rules * Jack Foster "How to Get Ideas" pg 115
Re-define the problem Change the format of the question, * Jack Foster "How to Get Ideas" pg 131
Abstraction Make the problem or situation more abstract * Rochford Linda 2001 Increase company revenue changed to better the company
Adaptation Adapting a solution, offering, process to suit a companies need by modifying it
* Rochford Linda 2001, * Hardagon 1997 & 2000
Reduction Reducing the amount, functionality, or features of a particular thing
* Blue Ocean Strategy 2005
Elimination Eliminating a particular, feature, attribute * Blue Ocean Strategy 2005
Raise or increase Increasing a particular feature, attribute or factor above the norm in that industry
* Blue Ocean Strategy 2005 Large button telephones, calculators and remotes
Creation Creating new features, attributes, factors, which an industry has not seen
* Blue Ocean Strategy 2005
Division of part Breaking up the whole in to smaller and smaller features, functions, or pieces
* Rochford Linda 2001
Iteration Repeating a process or set of actions with the goal of narrowing them down to a set of solutions
* Rochford Linda 2001
Devil's Advocate or methodical doubt
A method of exposing every weak point, while letting others quickly find solutions
* Rochford Linda 2001
Detailed observation Looking closely at something, trying to understand every facet and function
* Hardagon 1997 & 2000 * Tom Kelley 2001 & 2005
87
Table 2.7. Activities which Specifically Trigger Creativity
Activities Description References
Brainstorming Creating ideas in open discussion, (typically many techniques are applied)
*Chapter 17 PDMA handbook 2005, Rochford, Ref Tom Kelley, Ref Hardagon, Hsiao, S. -., & Chou, J. -. (2004
Method "6-3-5" "6 participants write 3 ideas within 5 mins on paper, then pass ideas to next person till one full rotation is made
* Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc
Problem inventory analysis
generating a list of negatives of a offering then finding solution to eliminate those negatives
(2007) The PDMA ToolBook
Visualization exercises Same as techniques just proceed as a formal activity
(2007) The PDMA ToolBook
Experimentation activities
Measure, tests, validate, explore, via physical, virtual, or thought experimentation
* 2005 PDMA hand book chap 17, Tom Kelly, Ref 30, Hardago, Stefan Thomke 2001
Scenario activities Instead of the technique, this a full activity where scenarios for marketing strategy, business unit strategy, tech strategy, were feasible scenarios are thought out
* Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers, San Francisco163 * Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296.
Six thinking hats role based brainstorming activities where each individual plays a different role, Facts, optimism, judgment, feeling, creativity, control
* DeBono Group http://www.debonogroup.com/6hats.htm
Focus group activities A collected group of individual focusing on giving feedback on a particular, product, service, and process
* Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296.Incubation &
relaxation
Relaxing and thinking lightly or not at all about the problem to be solved (sleeping) letting the mind sub-consciously work on the problem
* Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers, San Francisco163
Activities that are Specifically Creative
88
Table 2.8. Activities which Seed Individuals with Ideas
Activities Description References
Environmental scanning
Scanning the outside environment in the areas mentioned in (environmental scanning)
Drucker 1985, Auster & Choo 1993, REF 27
Systematic search of a field
researching all direction starting from fixed starting point
* Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296.
Conferences and trade shows
Industry conferences to aid in learning about new knowledge, technologies, developments,
Reviewing idea databanks
Reviewing the ideas in an idea bank *Hardagon, A. and Sutton, R.I (2000) Building and innovation factory. Harvard Business Review, 78 May-June 157-166 Link
Technology fairs same as conferences but held internally just for employees
*Hardagon, A. and Sutton, R.I (2000) Building and innovation factory. Harvard Business Review, 78 May-June 157-166 Link
Suggestion & improvement capture
Capturing ideas and issues from internal and external individuals
Deep questioning Question with the goal of deeply understand all aspects of a offering, service, industry
* Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers, San Francisco pg 146.
Tech boxes Maintaining a archive of products, materials, pictures and other things that can seed ideas
*Hardagon, A. and Sutton, R.I (2000) Building and innovation factory. Harvard Business Review, 78 May-June 157-166 Link *Kelley, T., & Littman, J., & Peters (2001). The Art of innovation, Lessons in Creativity from IDEO, America's Le
Company get togethers
Meeting where employees can talk informally like at bars, restaurants, or parties
Seeding activities
89
Table 2.9. Activities Which Use Analysis to Spawn Creativity and Ideas
Activities Description References
Opportunity identification Locating unmet needs or gaps in the market place that can present opportunities
* Flynn, M., Dooley, L., O'Sullivan, D., & Cormican, K. (2003). Idea management for organizational innovation. International Journal of Innovation Management, 7(4), 417-442.
Opportunity analysis Analyzing to see if a opportunity possess real value, and looking for potential problem and issue that can be solved to realize that opportunity * Flynn, M., Dooley, See above.
Customer needs analysis The customer needs are determined via surveying, interviewing, or feedback mechanisms. Feedback then is analyzed to determine customer needs
Wasted base analysis Looking for sources of waste tangible and in-tangible and finding ideas to utilize that waste
Competitive mapping Mapping competitor via, offering, pricing, branding, or other means to extract gaps and understanding
Analysis of customer feedback Examining customer feedback to determin unmet needs, or opportunities
Ethnographic research Researching customer behaviors and cultural aspects across different cultures to gain insight and understanding
Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc
Application Examining possibilities and results by application (2007) The PDMA ToolBook
Attributes based discriminant analysis (PREMAP)
Develop by performing a discriminant analysis from brand's effective attributes, then mapping and analyzing them
* Rochford, L. (1991). Generating and screening new product ideas. Industrial Marketing Management, 20(4), 287-296. * Foster, J. (1996). How to Get Ideas, Berret-Koehler Publishers,
SWOT analysis Looking at the strengths, weakness, opportunities, & threats to a competitor or offering
Morphological analysis/ Matrix
"Splitting up problem into parts and look for partial solutions to each, leading to generation of ideas"
* Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc.
Graphically representing activities their duration and finding gaps and problems with their flow
Dimensional investigation Mathematical equation used to relate functions, and economic properties of the product
* Belliveau, P., Griffen. A., & Somermeyer, S. (2007) The PDMA ToolBook 1 for New Product Development, Hoboken, New Jersey: John Wiley & Sons. Inc.
Porters analysis Using porter's analysis to understand an industry and gain insight into power relationship
Portfolio analysis Looking at the portfolio of offerings to find new possibilities, gaps, or weakness in the offerings
Gap analysis Comparing where a specific performance metric should be against where it is
Patent scanning Reviewing new or expired patents to see new product or service opportunities
Whole product solution analysis
Analyzing the offerings of an emerging market and determining which offering must be made to complete the whole product solution
* Moore, Geoffrey, (2004). Crossing the Chasm, HarperCollins Publishers, New York, New York,
Marketing research Researching the market, competitors, and market condition to determine trends, changes, and gain insight
Forecasting Predicting trends, and forecasting future developments in an industry, then trying to predict customer needs and requirements
* Kahn, K. B., Castellion, G., Griffin, A. (2005). The PDMA Handbook of New Product Development: 2nd (228-248). Hoboken, New Jersey: John Wiley & Sons. Inc.
Root Cause Analysis Looking for root causes of: failure, issues, and problems in the process of trying to diagnosis a system, behavior, or processes
Analysis based idea generating activities
90
Table 2.10. Full Idea Generation Processes
Processes Description References
1 Full Contextual research process
Detailed studies of customer unmentioned needs and situation
* Conley, C.V. (2005). Chapter 15: Contextual Research for New Product Development. In A. Kahn, K. B., Castellion, G., Griffin, A. (2005). The PDMA Handbook of New Product Development: 2nd (228-248). Hoboken, New Jersey: John Wiley & Sons. Inc. Link to
2 Outcome based innovation Uncovers desired user outcomes then generates ideas to fill those outcomes
*Ulwick, A. W. (2007, Fall). Turn customer input into innovation. Harvard Business Review, 80(1), 91-97. *Sutton, N. (2007). Outcome-driven innovation®: A critical review. Masters thesis, Cranfield CERES
Ulwick's Job Mapping Define the job process then use a set of techniques to add, remove, combined, or split the jobs into parts, use that understand to generate ideas
* Bettencourt, L., & Ulwick A., The customer centered Innovation Map, Harvard business Review, May 2008 109-114
3 Deep Dive by IDEO Similar to contextual research but heavier on idea generation
* Kelley, T., & Littman, J. (2001). The Art of innovation, Lessons in Creativity from IDEO, America's Leading Design Firm, New York, New York: Doubleday publishers* Kelley, T., & Littman, J. (2005). The Ten Faces of Innovation: IDEO's Strategies for Bea
4 Blue Ocean strategy Heavy on new ways to analyze market to find gaps to generate new sub-markets with very little immediate competition
* Kim, W. C., & Mauborgne, R. (2005). Blue Ocean Strategy How to Create Uncontested Market Space and Make the Competition Irrelevant. Boston, Massachusetts: Harvard Business School Press
5 TRIZ based innovation A russian idea generation technique combined with strategy
* Hart M. book review of Fey, V., & Rivin,. E Innovation on Demand: New Product Development Using TRIZ, New York, New York, Cambridge University Press
6 Flynn's idea generation process
Utilizes environmental scanning, opportunity identification, and ends with idea generation
* Flynn, M., Dooley, L., O'Sullivan, D., & Cormican, K. (2003). Idea management for organizational innovation. International Journal of Innovation Management, 7(4), 417-442.
7 Lead User innovation Following and working with lead users to generate leading edge ideas
* Von Hippel, E., Thomke, S., & Sonnack, M. (1999). Creating breakthroughs at 3M. Harvard Business Review, 77(5), 47-57, 183.
8 Multi-day ideation retreats A fully structured retreat design to run through many idea generation activities over a series of days
* Miller, C.W. (2005). Chapter 17: Getting Lighting to Strike: Ideation and Concept Generation, In A. Kahn, K. B., Castellion, G., Griffin, A. (2005). The PDMA Handbook of New Product Development: 2nd (228-248). Hoboken, New Jersey: John Wiley & Sons. In
Full Idea generating processes
2.7.3. Review of top idea generation processes
Many of these techniques and activities are well known in business practices
while others are not. For the goal of brevity this study does not discuss any of the
techniques or activities in detail, and instead will concentrate on elaborating on
idea generation processes. These idea generation processes are consider
extremely valuable because they have been tested to be effective in generating
valuable ideas and again tie together a set of activities, which utilize multiple
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techniques to produce ideas. There seems to be few full idea generation
processes which have been proven to be effective in creating valuable ideas. An
individual could slap together a set of activities from the tables above and label it
an idea generation processes. But creating an effective idea generation process
is much more difficult. Hence, this research views proven idea generation
processes as gems, because of their rarity and difficulty in refining.
Consequently, the following section discusses the top idea generation processes
in detail.
2.7.3.1. The Contextual Research Idea Generation Process
Chapter fifteen of the 2005 PDMA handbook written by Conley (2005) reviews
contextual research for new product development. Contextual research can be
thought of as indepth customer research, where one looks for information about
what people do, rather than what they think and say. The context is the every day
situation of the customer, their environment; their behavior, the situation they are
in, and their local environment (Conley, 2005).
Typically, customer feedback leads to minor changes or incremental
innovations in the product, whereas, contextual research looks at the bigger
picture to determine unseen opportunities for innovation by looking at the
environment, interaction, processes, activities, and customer types. As Von
Hippel puts it, this information is “sticky” because it is very difficult for the user to
convey this detailed information” (Von Hippel, Tomke, & Sonnack, 1999).
The power of contextual research is its ability to communicate this “sticky”
information and use it to spot unmet needs or simulate new innovative ideas. The
process of contextual research involves: (1) designing the study, (2) selecting the
research team, (3) gathering required research tools like cameras, (4) selecting
the customers to observe, and (5) creating a topic guide for interviews.
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Figure 2.22. Illustration of the Contextual Research Process
The research is based on a vigilant observation of users in their
environment. This is commonly done by job shadowing or observation from a
distance. Also it is recommended that users verbalize their actions by talking
about them out loud. Activities should be captured on rich media like video,
photographs, and audio tape, as well as more traditional lead mediums like note
pads. It is recommended that this take place over several observation sessions.
After the research info is gathered it is analyzed to determine the goals of each
activity and then coded into bite-size chunks. Coding is used to identify patterns
of issues. “In analyzing data, one must avoid simply responding to problems
seen in the field, because many problems are symptoms of a larger systematic
issues” (Conley, 2005, p. 98).
The coded information is then used by the new product development
teams to extract insight and simulate ideas. Next, several brainstorm meetings
are performed with each concentrating on a different issues or patterns
discovered during coding. The generated ideas should be recorded, sorted, and
voted on, then documented. Reporting the contextual research to the larger
organization is a vital step, and helps seed other individuals outside the NPD
group with idea and information. Report of the research can be displayed by
videotaped examples, diagrams, illustrations, photographs, and in the traditional
written form. This process produces the largest benefit in that it develops a deep
understanding of customer needs which has been said to develop the most
Deep market research; contextual research; problem analysis; Customer Gap Analysis; satisfaction surveys , many others
Ref 18,21,27,23,
2 Core customer groups
Customer groups that provide the bulk of the revenue or profit for the company.
same as 1 same as 1 Ref 54, 32, 30, 58, REF Neal & Corkindale 1998,
3 Lead User Highly advanced user has needs way in advance of the bulk of the market place, because they are visionaries and try an advances quiker to get a competitive edge
Direct customer request, interviews, lead user processes, focus groups, customer projects
See lead users innnovation process by von Hippel
Ref von Hippel HBR 1999, Urban & von Hippel 1986
4 Possible new customer group
Customers the company is not yet serving but would like to. same as 1 same as 1
5 Dis-satisfied customers
Customer that are dissatisfied and are still with your company, or have switched to a competitor. May also include dissatisfied customer of a competitor.
Customer interviews, customer feedback surveys, dissatisfaction survey, focus groups
same as 1
Ref 58, Wharton: How to turn customer ideas into innovation HBR Companies and the customer who hate them McGovern & Moon
6 User, inflencer, buyer customer groups
The individuals buying, using, and influencing the purchase may be very different. Each group should be considered differently for ideas, to better satisfy all groups.
same as 1 same as 1Ref Blue ocean strategy, Ref Harvard Business Review on Innovation 2001 Chan Kim & Mauborgne
7 Anonymous Customer who submit ideas annoymously or been recorded as annoymous
Received though annoymous submittion or direct contact but not recorded
Idea contests, suggestion systems
Ref 40
Customer Sources
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woman who was very dissatisfied with Nabisco Oreo packaging which could not
be easily closed, told customer service the company should change the
packaging immediately. The result? Nabisco (Oreo) released a simple resealable
flap that has since increased the freshness and consumption rates of their Oreos.
Users, influencers, and buyers are different customer groupings even
though they are often referred to as a single unit. For example, a user of a
construction tool may be a construction worker, the influencer may be a foreman,
and the buyer may be the owner of the construction company - each of which
have their own specific needs. Finally, customers may sometimes anonymously
submit ideas to a company. Unfortunately, follow-up feedback or additional
information cannot be obtained (Perk, Cooper, & Jones, 2005).
2.7.4.2. Non-for-profit Organizational as Sources of Ideas
NASA is well known to be a source of inventions and ideas, and has been
credited with many well known inventions like the microchip. National
laboratories are a government funded way of inducing innovations in US
companies by creating new knowledge and spreading novel concepts. There are
a number of national laboratories each having their own licensing and technology
transfer departments. Keeping up with the invention and discovery of all of these
can be a daunting task. National labs are very similar to NASA in that they all
have formal licensing departments and continually market their achievements.
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Table 2.14. Non-for-profit Organizational Based Sources of Ideas
National organizations are primarily non-for-profit organizations. Every country
has a list of national organization most of which are not funded by the country.
Examples would include NSF, boy scouts, and so on. The largest problem with
organizational sources is there are so many. It is difficult to know which ones
Source Description Direct way to
get ideas
In-direct ways to generate
ideas References
1 NASA NASA openly lists inventions that can be licensed and tries activity to seek placements for the promising technologies
Visit website, talk to licensing officer, scanning new technology releases
Scanning new technology releases at there website; scanning SBIR, STTR awards; Open innovation network
technology.jsc.nasa.gov/
2 National Lab National laboratory of the US and other country produce many technology related ideas
Visiting respective website, talking to licensing officers at each lab, solicing national labs, scanning new technology releases
scanning published literature, open innovation network
Limited by design, R&D laboratories in the US national innovation system Crow, Bozeman 2001 , www.lanl.gov, www.anl.gov, www.sandia.gov, www.jlab.org, www.bnl.gov, www.inel.gov,www.inl.gov, www.lbl.gov, www.nrel.gov, www.llnl.gov
3 National Org These are typically non-for profit national organization of all types.
Same as 1 Same as 2
4 University University are known for transferring inventions and discoveries to the private sectors, include professors, researcher, & students
Same as 1+idea competitions, + idea awards
Same as 2
5 Research Parks These are groups of research companies, where the research park promotes their technologies, and ides
Same as 1 + Open Innovation network
Same as 2
6 Groups of practices
This are organization dedicated to aiding a professional group, like the national society of professional engineers and the National lawyers guild
Same as 1 + conferences, meetings, networking, solicitations
scanning published literature, referral, search and find
6.1 Professional Same as 1 + Conferences, trade shows, meetings, talking to members
conference proceedings,
6.2 Consumer6.3 Economy Looks at general region
or nations 6.4 Religious/race
6.5 Interest/hobbies Hobby and interest groups.
Same as 6.1
7 Media sources Speaking with editors Searching media
Groups of practices and be organized into professional (like the lawyers
guild), consumer (like association for consumer research), economy (social
venture network), religious/races, special interest, or hobbies (like Nascar or
aircraft owners & pilots associations). These groups of practice can be valuable
points of ideas. Again because there are so many, it may require more energy to
locate and solicit relevant groups of practices. One should also note that groups
of practice outside of a company’s core business area may hold sources of new
ideas. For instance, a boater’s conferences may hold valuable ideas for home
builders looking for water proofing ideas. Unfortunately, it can be time consuming
to join and scan groups of practices to far outside ones core business area.
2.7.4.3. Suppliers as Sources of Ideas
Suppliers are great sources of ideas and they can also help integrate those
ideas to one’s business. Suppliers were loosely structured to include any
organization which supplies a company with anything from work to actual goods,
and includes current and possible suppliers, consultants, idea consultants, and
research firms. Robert tucker states: “If you ask a supplier if they have any ideas
or new technologies they usually provide none, whereas, if you bring a problem
or opportunity to them and ask them to help solve it they are delighted and
provide many ideas” (Tucker, 2003, p. 2).
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Table 2.15. Supplier Sources
Amazingly, research firms were never mentioned as sources of ideas
before. Firms like Forester research which identifies trends in the market place
have an excellent sense of the opportunities which exist and often state such in
their publications. Also they can be contacted directly for ideas. Partners and
alliances were put under supplier sources because they supply resources,
knowledge, and capabilities to a company.
Source Description Direct way to
get ideas
In-direct ways to
generate ideas References
1 Current suppliers The current suppliers to a company could provide ideas
Solicitation, problem statement, direct contact, part of contract requirements,
Scan for news from suppliers, locate best practice suppliers, Open innovation networks
Ref 27, 54,
2 Possible suppliers These are possible supplier which may be activity or in-activity biding for business
Solicitation, direct contact, part of bid requirements,
same as 1
3 Consultants Consultants of all types may provide ideas.
contracting with consultants, solicitations, direct contact,
solicitation, open innovation networks
Ref 18*, 30
4 Idea consultants Using companies like IDEO, design firms,
requirements for contract
solicitation, open innovation networks Ref Tom Kelly,
5 Research firms Marketing, consumer, industry, and economic research firms can be sources of ideas
same as 1 solicitation, open innovation networks
Ref 59
6 Partners / Alliances Partners and Alliances which supply resources, knowledge, capabilities
Contractional agreements, + same as 1
solicitation, open innovation networks
Supplier Sources
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2.7.4.4. Competition as Sources of Ideas
Competitors could be great sources of ideas, as NPD handbook showed
many businesses are fast follower of the best in class competitor. Best in class
competitors are often cited in popular media as pioneering a new process,
releasing new products, and so forth. Ignoring best in class competitors can be a
large mistake because they are often rich sources of ideas.
Direct competitors are all the companies in direct competition to ones
business, which may include best in class competitors. While, indirect
competitors are companies which are in a similar business and are servicing
customers outside of markets which your business is concerned with. For
example, a car dealer in Indianapolis selling Jeeps is in indirect competition with
a car dealer selling Jaguars in the same area. Whereas a friendly competitor
may be a Jeep dealership in Denver Colorado who is willing to share helpful tips
and ideas.
Table 2.16. Competitor sources
Source Description Direct way to get
ideas In-direct ways to generate ideas References
1 Best in class competitors Best in class competitor are often looked toward for sources of new ideas
Direct communications with competitors, competitative intellegence, direct observation
Market research firms, best in class practice reports, GAP analysis of competitors, SWOT analysis of competitors, competitive mapping, porters analysis, market research
REF 3, 18
2 Direct competitors Direct competitors to the business
Same as 1 Same as 1REF 3, 18
3 Indirect competitors Competitors in market outside of the companies given competivite area,
Friendly communication, + same as 1
Same as 1
4 Friendly competitors Friendly competitor that are not in real competition with one's company
Direct solicitaion, Friendly communication, + same as 1
Same as 1
5 Substitute sources As Porter defines markets that could be substitutes to ones market
Same as 1 + industry trends reports Same as 1
6 New potential entrance sources
As Porter defines markets that could be threats to enter ones market
Same as 1 + industry trends reports Same as 1
Sources from competitors
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Substitutes are, as Michael Porter defines it, products and services which
can be substituted for ones which your company is selling. For instance, cereal
companies look at substitutes like breakfast bars, fast food restaurants, and
others cereal substitutes for changes and new ideas.
Finally, potential new entrances are companies treating to enter the
industry. For example, the core US airline market close observed the launch of
JetBlue and closely examined all of JetBlue new innovative like in seat TV
systems.
2.7.4.5. Other Companies as Sources of Ideas
Unfortunately the category of direct competitors and non-for-profit organization,
do not account for the millions of for-profit companies which exist that can be
used as potential sources of ideas. Most notably, media sources are great
sources of ideas.
Media sources include publications like: journals, magazines, patents,
article databases, books, articles, and new publication; as well as, media like
radio programs, television shows, and movies.
Table 2.17. Sources of Ideas From Other Companies
Keep in mind the original author is the source of the idea and the
publishers, being the media companies, are the means of distribution. If one
considers the publishers a group of individuals then they would be a formal
Source Description Direct way to get
ideas In-direct ways to generate ideas
References
1 Other companies All other companies around the world
All All
7 Media sources Books, magazines, articles, patents, newspaper,
Speak with editors, Searching media
3 Inventors Indepent inventors direct solicitation, scanning new invention disclosure
Sources from other companies
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source of ideas, even though they are re-distributors. For instance, a magazine
like Harvard business review are great source of ideas for improving
management even though the new source of the idea may be Michael Porter.
Media sources may be great sources of ideas which should not be
neglected. Formal scanning mechanism for new ideas should include relevant
media sources because of their targeted nature and breadth of coverage.
Independent inventors are also valuable sources of ideas however they
are difficult to locate, contact, and solicit. Nonetheless, having one or two highly
talented inventors which can be called upon for idea can be of great value.
2.7.5. Issues with External Sources of Ideas
Of course there are many issues with obtaining ideas from outsides sources.
Some companies believe receiving outside ideas may jeopardize internal
development efforts. For example, this researcher contacted Arm-hammer to
submit an idea but was sadly informed they will not listen to outside ideas.
There are hundreds of issues in setting up and receiving ideas from
external sources. One should consider the benefits and downsides carefully. If
possible the downsides should be reduced or eliminated via creative problem
solving, because there are greater benefits than risk in sourcing external ideas.
Also, one should remember their own company may be afflicted with the not-
invented-here syndrome, which may severely limit their ability to innovate.
2.7.6. Which Source of Ideas is the Best?
Given the detailed review of the sources of ideas, one might ask: “which sources
of ideas are the best?” The answer is: “it depends.” It would be ludicrous to state
one group is the best sources of ideas. There are too many factors affecting the
production of ideas from a single source to make any kind of reasonable
conclusions across sources. For example, things like: culture, management,
leadership, and incentives vary greatly between even similar sources of ideas.
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Additionally, the typical sources of high quality ideas in one industry may be
different than another industry. So given those variations and the large number of
affecting factors, concluding one source is the best source of ideas is absurd.
The question should instead be: “what sources can this company turn into
great sources of ideas?” This would suggest things can be done to improve the
quality of ideas coming from internal and external sources. The following sections
will dive into and explore the feasibility of this suggestion.
2.7.7. Major Issue with Idea Generation (Lack of Control Models)
Unfortunately, even after this detailed review of idea generation and its
respective literature; no models were uncovered which could be used to manage
the whole idea generation process. This represents a massive gap in the
literature. Further, a conceptual understanding of how to manage the idea
generation process has not been developed in the literature. This constitutes a
severe limitation in the literature which must be rectified.
2.7.8. Summary of Section 2.7
To summarize, a detailed series of tables respectively showing idea generation
techniques, idea generation activities, and idea generation processes were
created to fill the gap in the literature. Following this discussion, the top idea
generation processes were described and critiqued.
The next section described how companies may react differently to
outside ideas based on their innovation category and level of concept
development. This was followed by a detailed series of tables showing the
sources of ideas, which was offered to fill a gap in the literature.
Finally, this section concludes with the question “what can be done to
improve the quality of the ideas generated?” This question will be addressed in
the Chapter 3.
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2.8. Literature Review of Idea Management and Idea Banks
2.8.1. Introduction to Section
The following section will review idea management and idea banks with the goal
of fleshing out the knowledge required to manage the fuzzy front end of
innovation.
The following section begins by explaining what idea management and
idea banks are and then go into why they are so important and valuable. Then
this section will move into a detailed review of several key articles on this topic.
Finally the section ends by stating several problems and issues with the
knowledge in this area.
2.8.2. What is Idea Management and What are Idea Banks?
Unlike the Fuzzy front end, there are very few definitions for idea management.
Drawing from other papers on idea management, this thesis defines idea
management as the process of capturing, storing, and organizing ideas can
be used in other processes, like the late FFE processes (Flynn, Dooley, &
To remedy these natural biases, companies initially have to become
aware they have a natural bias. This can be first achieved through education by
books like Christensen’s (2003) The Innovator’s Dilemma and second be
achieved through making the innovation process more transparent. Again, the
proposed solution of tagging was hypothesized to help make the innovation
process more transparent. One proposed way to deal with the bias toward
certain types of ideas in the innovation process is by tagging an idea with
information. By initially tagging ideas one can track the progress of particular
ideas through the innovation processes and visibly see the bias of a company.
For example, you can compare how many ideas are tagged as being customer-
driven in the idea bank, then compare how many were selected for development
in the FFE, and NPD processes.
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50 of 150 (1/3) are customer-driven in the idea bank
10 of 50 (1/5) projects are developed in the FFE
1 of 20 (1/10) were developed in the NPD
1 of 12 (1/12) made it to market launch
The list above shows an example of a company’s innovation process and
the number of customer-driven ideas being pushed through to market launch. By
quickly reviewing the tags associated with projects in the portfolio an innovation
practitioner can quickly generate these numbers. One quickly sees that the
number of customer-driven ideas drops in the NPD, which might indicate a bias
of the NPD process against customer-driven ideas.
3.3.3.3. Controlling tagging
Tagging can be controlled rather easily by the input conditions: (1) the method of
tagging, (2) the attributes of the tag and (3) by the way tagging is executed.
3.3.3.4. Controlling via method of tagging
The method of capture also dictates the method in which the idea can be tagged.
So for example, if ideas are captured orally over the phone and then memorized,
one must also ask the submitter how the idea was created, what event triggered
its creation, and so on. If the idea is submitted in to a suggestion box the act of
tagging becomes much more difficult. However, if a standardized forum is used
along with a suggestion box, the required tag info can be integrated into the
forum.
Idea management software allows the greatest flexibility in terms of
tagging because they can ask follow up questions and then formally store that
information with the idea, and be recalled very quickly. Whatever form the tag
takes - written, computer based, or oral - it is just important that the information
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capture in the tag stays with the idea so it can be traced. So if the idea is
accepted as a project and then passes on into the development, management
should be able to quickly pull up the idea tag info associated with the project to
see what conditions lead to the ideas creations. Again, the innovation process is
a value chain, and tracking items as they proceed through the process is just vital
to improving the links in that chain.
3.3.3.5. Controlling via Attributes of the Tag
Again, the amount of detail captured for the tag must be balance against the
energy in obtaining it. Not every piece of information is vital, only a few are. Thus,
asking a submitter what time and day he had the idea is much less relevant than
what event triggered him to create the idea. Thus, this research concludes there
are a few required items which should be captured along with an idea. These
items are listed on the following page, and are broken up into process related
tags and idea related tags.
Collecting information related to the idea like financial potential, feasibility,
and so on is not required by the tag, because the tagging function is more
concerned with tracing the idea creation back through the process. Additionally,
capturing information like financial potential, required resources and so on at the
time of submission is a bit premature because, (1) you cannot estimate them
without having done a fair bit of analysis, and (2) because you want to take time
and develop the idea further to increase the financial potential and or lower the
required resources.
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Source Tag Info
• Who or what group of people generated the idea?
• What motivated the source to generate this ideas?
Event Tag Info
• What event triggered them to create the idea? (formal or informal)
• Was the event a formal event held by the company or dictated by
management?
• What incentive motivated them to generate the idea?
• When did the event occur?
Activities Tag Info
• What activities did they formally do to come up with the idea?
• What activates did they informally do to come up with the idea?
• What was the order of the activities?
• What tools or resources did they use during idea generation?
• Where or how was the environment for idea generation?
• Who managed the idea generation activities?
Screen and Filter Tag Info
• What screens did the idea pass through?
• Who told you not to submit the idea?
• Who managed the screening?
Capture Tag Info
• Who was the idea submitted to?
• How was the idea submitted?
• Who encouraged them to submit the idea?
• Was it hard to submit the idea?
Tags Related to the Idea
• Is this idea (technology, customer, market, value) driven?
• What category is this idea (product, service, process, marketing, ..)?
• Is this a disruptive or incremental idea?
• Is anyone committed to this idea? If so who?
• Who else is aware of this idea?
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3.3.3.6. Controlling via the Execution of Tagging
Tagging is highly linked to capture, because tag information is taken at the time
of capture. Hence managing the capture function can also include managing
tagging. Again, the execution of tagging is important. For example, if a secretary
captures an idea and fails to write down the associated tag information because
they were short on time, the benefits of tagging are forfeit. Hence, managers
much ensure that employees and others submitting ideas are capturing and
tagging ideas appropriately.
Interestingly, properly selecting the method of capture can reduce the
need to manage tagging. For example, idea management softwares can require
the user to fill out related tag information prior to submitting the idea, whereas,
the good old paper submission system can not. Yet, idea management softwares
cannot probe a submitter like a trained manager who can extract accurate tag
information. Hence, extra attention should be paid to the selection of the capture
method because it may greatly reduce the need to actively manage tagging.
3.3.4. Storage and Categorizing
The first part of this section presents a review of how the ideas and opportunities
are stored and how they can be categorized. This is followed by the second part
showing how to control storage and categorization.
3.3.4.1. Formal vs. Informal Storage of Ideas and the Concepts of the Idea Cloud
The following paragraphs will review several obvious attributes which This
researcher deems useful for the innovation process. The first is the form in which
the idea is recorded, being highly formal or informal.
Many ideas exist solely in the minds’ of the employees and have not been
recorded to paper. So to account for these ideas which exist in the larger
organizational consciousness the term “idea cloud” is being used. To help in the
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differentiation, the term “idea bank” is being used strictly as ideas recorded
formally on a fixed media (paper, computer disk, audio tape).
Figure 3.19. Illustration of the Idea Cloud, Idea Bank,
and Company Idea Bank
Figure 3.19 illustrates the idea cloud with two idea banks embedded in it.
Hence, an idea in a person’s mind would be contained in the idea cloud,
whereas, if it was written on paper (say in a lab notebook) it would exist in the
idea bank, and if it was submitted it would then exist in the company’s idea bank.
The value gained from splitting up storage this way is it highlights that
many ideas are kept in peoples minds’ and there are barriers which those ideas
must move across to become more formalized.
So given this, one can view ideas in the organization on a continuum of
formality as shown by Figure 3.20 below. Figure 3.18 shows informal ideas which
may exist in only a person’s mind whereas highly formal ideas may exist on
paper and computer, with fully detailed written descriptions with prototype
pictures and so on.
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Figure 3.20. Illustration of the Continuum of Idea Formality
Interestingly, some companies like IDEO store some of their ideas in a
Tech box which just keeps a physical sample of the idea with a short written
description (Hardagon & Sutton, 2000; Kelley & Littman, 2005). While other
companies may require ideas to be recorded in highly formalized forms (like
several written descriptions, with detailed summaries of the idea, technical
feasibility, required resources and so). An example of idea banks requiring highly
formalized idea submission may be Nortel’s “Galileo” idea management system
described by Montoya-Weiss & O’Driscoll (2006).
Evidently, having ideas in a more formal fashion helps later FFE activities,
but one must keep in mind that requirements for formality may stop individuals
from submitting their ideas. Thus, one must carefully balance the formality
requirements for the idea bank against the need to collect more ideas.
3.3.4.2. Categorization of the Idea Bank
Unfortunately, none of the literature on idea banks or idea management
highlights the diversity of ideas which exists in a formal idea bank. To quickly
illustrate how convoluted an idea bank can become, Figure 3.16 was created.
Figure 3.14 shows a huge diversity of ideas from new to old; analyzed or
unanalyzed; technology or customer driven; product or supply chain; and so on.
Of course, Figure 3.14 does not show the overlap among categories, so an idea
can be new, customer driven, and radical while another can be old, customer
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driven, and incremental. With this dizzying array of categorizations, it may seem
daunting to organize an idea bank. Yet these categorizations give one an
increased ability to search through and select ideas, and use their understanding
of the ideas in the idea bank to improve the innovation process.
For example, if one purely categorized the ideas in an idea bank by
incremental or radical ideas one might see what is illustrated in Figure 3.17.
Instantly, one can deduce that the company is not effectively capturing or
generating radical ideas and should place more effort on these tasks. Similarly,
by organizing ideas by their innovation category (as illustrated in Figure 3.18)
one would see the need for more service ideas.
Figure 3.21. Illustration of the Diversity of Idea Banks
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Figure 3.22. Illustration of Idea Bank Organized by Incremental and Radical Ideas
Figure 3.23. Illustration of Idea Bank Organized by Innovation Category
Of course, one can organize the ideas in an idea bank by almost any
factors like ideas with the shortest time to market, or lowest amount of required
resources. However, one must be careful not to use factors which in themselves
are useless, irrelevant, or can not be accurately determined. For example, one
should not sort new unanalyzed ideas in an idea bank according to those which
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are most appealing to customers or by total possible revenues, because those
factors will not be determined with a reasonable level of certainty until after they
are analyzed in later FFE activities.
Hence, one can see that ideas may have obvious attributes (like new or
old, or product or service) which can be easily determined even for new un-
analyzed ideas, and conversely, un-obvious attributes (like possible revenues,
required resources, competitive advantage, and so on) which require analysis
and work to uncover.
3.3.4.3. Examined vs. Un-Examined Ideas
It may not be directly obvious, but a quick review with the NPD or FFE team will
uncover which ideas have been formally examined verses which have not been
examined. Knowing this allows one to better organize their efforts in the late FFE
processes. For example, the FFE team may decide to spend three months
evaluating un-examined ideas in the idea bank to see if any great ideas can be
uncovered. Plus, keeping records of the number of examined versus
unexamined ideas in the idea bank will show if the FFE teams are effectively
examining ideas, or if there are too many ideas in the bank.
3.3.4.4. Temporary vs. Permanently Stored Ideas
IDEO’s idea generation process has shown that ideas can be created and stored
temporarily (Kelley, Littman, & Peters, 2001). Again, in IDEO’s process, ideas are
presented to the group, often in a very informal written form, and then used as
bases for the next evolution of the concepts. Ideas which do not make the final
cut are then trashed. The output of the IDEO process again is one or two well
developed ideas.
In companies like IDEO, which have so many diverse client projects, it
really does not make sense to permanently record ideas because, (1) the
chances of getting a similar client project are remote; and (2) the chances of
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using those ideas again are very remote. Thus, the benefit for permanently
recording ideas into the bank does not justify the required energy and time.
However, in other companies there is a much greater benefit to permanently
storing ideas. Hence companies should take note, that there can be cases where
either temporarily storing ideas or permanently storing ideas may be beneficial.
3.3.4.5. Awareness Continuum
Some ideas are known to many inside a company while others may be unknown.
For example, practically every employee in Apple’s competitors being Sony,
Nokia, and Motorola are aware of Apple’s touch screen Iphone; while many less
employees are aware of new ideas like new OLED displays for cell phones.
Obviously, some ideas may have higher levels of awareness than others.
Ideas which have higher levels of awareness may be more easily backed
by their organization and pushed through the new product development and
commercialization process. Having many more people, especially decision
makers like key executives, being aware of an idea may be very helpful in getting
a project noticed and funded. Hence companies should also consider the levels
of awareness associated with an idea (Conley, 2002; Flynn, Dooley, &
O’Sullivan, 2003).
3.3.4.6. Ideas and their Level of Development
Differentiating ideas by their level of development may also prove to be a useful
factor. Ideas which are undeveloped, in development, or developed have
radically different amounts of information associated with them, and may have
firm support which can help spread useful ideas across the organization. For
example, having a team which is currently developing a new process talk and
spread their process may provide the useful energy needed to jumpstart the
implementation of those ideas (like process improvements) in other areas of the
business.
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3.3.4.7. Commitment to Ideas
Ideas which have a high level of commitment behind them are greatly different
than similar ideas with low levels of commitment. For example, an ideas which
has the backing and commitment of the executives and upper management
stands a far greater chance of passing through the NPD process than those
ideas which do not have this support. Also, the employee-driven idea system
mentioned by Gorski, & Heinekamp, (2002) where employees became
committed to their ideas, showed to have substantially better rates of
implementation than those of ideas placed into suggestion box systems.
Thus, the FFE team should strongly consider the level of commitment and who is
committed to an idea when selecting ideas for development (Montoya-Weiss &
O’Driscoll, 2006).
3.3.4.8. Newness of the Ideas
Some companies are biased toward new ideas, but old ideas are also useful and
still hold great value (Vandenbosch, Saatcioglu, & Fay, 2006). Again a new idea
was defined as one which is new to the company as a whole. For example, in
organizing the idea banks by newness of ideas, one may uncover there is a lack
of old ideas being proposed and being analyzed. Or conversely, one may find out
that idea generation activities are producing old similar ideas and not enough
new ideas. Hence, having a map of the newness of ideas in the idea bank can
show front end practitioners where extra work is needed.
3.3.4.9. Controlling Storage and Categorization
There are two hypothesized ways to control storage and categorization: (1) the
method of storage and categorization, and 2) being the execution of storage and
categorization. There are several ways to store ideas as mentioned above, some
are formal and some are informal. Regardless of the method chosen or what is
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stored one must look at the main functions of the idea storage, which is a) to
store idea and opportunities, and b) to retrieve ideas and opportunities.
Viewing it in that light, one can see it is important to quickly store and
retrieve idea and opportunities. But this must be balanced against the need for
formality, and how much detail should be captured. So again, if the idea is for
and mechanical device much more info may be required than and idea for a new
customer group.
Interestingly, the quickest way to retrieve stored idea is through idea
management software programs; whereas, some of the quicker ways to store
idea can be via paper documentation methods. The benefits of idea management
software are that ideas can be easily appended to, and modified, as they
processed through development.
Categorization does take some energy especially if ideas are stored in a
paper form. Again, idea management software have major benefits because
categorizations can be quickly drawn up, edited, compared, and reviewed, on
many systems at once. When selecting the method of categorization one should
keep at minimum a few consistent categories so the results of the idea stored in
the bank can be compared overtime.
Again, the selection of the proper categories depends upon the business
but in general the categories which should be used are: level of development,
newness of the ideas, innovation category, disruptive versus incremental, and
idea driver.
3.3.4.10. Control the Execution of Storage and Categorization
Yet again, the system being used makes a huge difference in the amount of
management effort spent on storage and categorization. Computer software
systems can quickly store and retrieve ideas, but must be managed for uptime.
Conversely, paper systems may require a secretary to fetch the documents, and
management may have to take time to train and monitor the performance for
these tasks.
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Similarly, computer systems can perform categorization according to their
programming, and may provide resulting maps of ideas by category in the idea
bank very quickly. However, categorization in paper based system may be much
more tedious, and require much management to insure ideas are correctly
categorized. The amount of management required for any idea storage and
categorization system should be known at the time of implementation or
purchase.
3.3.5. Process Check and Feedback
As mentioned in the section on controlling idea generation, feedback on the
generated ideas is critical to improving the idea generation process, and idea
capture. Hence, the process check is a quick analysis to see if a) the ideas being
created by the ideas generation process are meeting their preset goals or b)
the ideas being captured from external sources are meeting the preset goals
set for capture of external sources.
For example, if the chief innovation officer (CIO) sets an objective of
generating twenty plus disruptive ideas and capturing twenty plus disruptive
ideas from outside sources. The company then goes off and generates ideas and
captures ideas from outside sources. The feedback from these activities shows
the company has created four disruptive ideas and captured twenty plus
disruptive ideas from outside source. The CIO then knows they need to rework
their current internal idea generation process.
As shown in the Section 3.2 “control model for idea generation”, the
process check “feedback” was placed at the end of that process. However,
because in this model, idea generation and idea management are combined, it
makes perfect sense to combine the process check into idea management
section. Hence, the process check function was placed after the storage and
categorizing not before it because, (1) the ideas are in a more permanent form
for a process check; and (2) one does not have to worry about the process check
blocking the storing of ideas.
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Controlling the process check to some degree depends on the systems
being used. Software idea management systems allow quicker access to ideas,
and analysis results can be tagged to a group of ideas which were created
through a particular set of idea generation activities. Hence, it make be quicker
and easier to use and idea management software for large groups of ideas.
Paper based process checks are still imagined to be effective, as long as the
individuals managing idea generation understand how their strategies are
affecting the outputted ideas.
3.3.5.1. Controlling the Process Check via the Selection of People
The people performing the analyses were shown to be a major factor in the
quality of the analysis performed. Steven, Burley, & Divine (1999) uncovered that
certain personality types enjoyed analyzing and distributing new ideas while
others quickly tired of this task. Their insight was that certain people are really
pre-disposed to this task and they would resemble a person like a technologists
who loves looking at new technologies, analyzing them, and talking about them,
or the business analysis guy who loves looking at and talking about new
business ideas. Hence, one should look for these personality types when
selecting individuals for the process check task.
3.3.5.2. Controlling the Execution of the Process Check
Like any process, the process check analysis must be monitored and feedback
must be given to the appropriate parties. Accountability can be created by
allowing the individuals who manage the idea generation process to hold those
individuals performing analysis and providing feedback accountable for their
reports and their quality.
Again, the process check analysis is not supposed to be detailed, it is a
quick overview to see if the ideas being generated by the idea generation
process are meeting their pre-set targets. Hence, if the initial goal is to create five
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disruptive product ideas, and it actually produces five incremental service ideas
the individuals managing idea generation can be informed quickly over the
phone, a detail report is not needed. One should not over complicate the
analysis, just get the rough info to the idea generation manager quickly, so they
can learn and refine their processes.
3.3.6. Diffusing and Routing
Diffusion is the act of spreading the ideas and opportunities through the
organization, and routing is sending a particular idea or opportunity to the most
relevant individuals. Diffusion was highlighted in the innovation value chain
model; however, diffusion in is this model is slightly difference. Diffusion here is
the act of taking anything from a rough idea to a developed concept and
spreading it around the organization so that a) future development projects can
be created from it or b) current or future development projects can be aided by it.
Again, to reiterate, ideas can be a) used directly with little or no
modification, and or b) can be modified to suit the needs of the company, and or
c) can be used to seed people inside the company with stimulus (see Figure
3.24).
Figure 3.24. Idea Management Feeding Idea Back into Idea Generation to Stimulate more ideas
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With this view, diffusing ideas does not only have to be about getting an
idea accepted as a project as mentioned by Hardagon, & Sutton (2000). As well,
there is value to having non-perfect ideas in the idea banks. To illustrate, that
ideas can be used to seed individuals in idea generation activities, this model
had a link linking diffusion to idea generation. However, before going into detail
about how to control diffusion, we discuss theories of diffusion. This research
views two distinct types of diffusion one being a) forced diffusion, where an
individual or group (internal or external) is pushing the idea through the
organization, and b) sought diffusion, where individual activity seeks new ideas.
The best example of forced diffusion is the executive product champion,
who uses every means possible to spread his idea through the organization. This
individual uses memos, speeches, conferences, meetings, emails, and face-to-
face communication to get his idea out to individuals in his organization. There
are other means of forced diffusion, like companywide memos, idea fairs, idea
discussions, promo video of idea, posters of new ideas, and so on. The many
ways they differ from each other is the amount of power they have to diffuse and
idea. Hence, to demonstrate this better the researcher has created a diffusion
power spectrum, Figure 3.25.
Figure 3.25. Diffusion Power Spectrum
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Note that ideas can be diffused by internal or external sources, so a large
competitor launching a new product has a lot of power to diffuse that idea to
other companies. Sought diffusion is different than forced diffusion because, here
an individual is seeking out the idea, not having it forced on them. This can entail
anything from and individual requesting ideas of others, scanning periodicals or
media, or searching databases or the internet for ideas or opportunities. Sought
diffusion is a different mindset than forced diffusion because of its structure.
Sought diffusion is allowing access to tools and resource which would
enable an individual to seek and find ideas relevant to their needs. The fields of
knowledge management and Informatics have shed much light on the way to
enable individuals to seek and find information. For example, GE and Mckinsey
both have elaborate knowledge management systems which would allow
individuals to access an expert, find relevant knowledge, or get solutions to
particular problems.
Hence, a company can create systems, tools, and resources which would
allow individuals to more quickly find ideas. It is hypothesized that company
culture has some effect on sought diffusion. This is because it requires a different
mindset, “I will find an idea”, instead of, “I will wait till an idea comes to me.”
Regardless of culture, structures and systems can be put in place to enable
sought diffusion.
For example, expert directories allow employees to search out relevant
experts and ask for new ideas which are relevant to their needs. Also, idea
management software enable employees to search the idea banks for ideas
relevant to their needs. IDEO’s Tech box, allow employees to physically search
for materials and products which could seed their idea generation activities. Idea
conferences allow individuals to talk about ideas and opportunities.
Unfortunately, no data exists on which types of diffusion are taking place
in companies or if sought or forced diffusion is more prevalent. Nonetheless, the
best strategy is to enable both forced and sought diffusion to occur.
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3.3.6.1. Controlling via Methods of Diffusion
There is great value in forcing the diffusion of select ideas in the organization,
and enabling systems and tools so sought diffusion can occur. To aid
practitioners in selecting methods which could be applied to their company, this
research offers a rough table of possible methods of diffusion.
Table 3.3. Diffusion Methods, Forced, and Sought Diffusion
3.3.6.2. Controlling Diffusion and Routing via Selection of People
Networking theory has shown that some people inherently like to distribute
information (Facilitators). In addition, some people like to distribute ideas. The
point can be quickly made, if one imagines the archetype technologist talking
relentlessly about the newest inventions, technologies, and product ideas.
Diffusion method ReferanceInternal Force Diffusion
Executive product championproduct champion Idea fairs & conference (3M) Hardagon & Sutton (2000) & (1997) Weekly new idea sessionIdea promo video Hardagon & Sutton (2000) & (1997) Idea posters Internal Idea blog Idea newslettersIdea booklets, cataloguesIdea memos, emails, calls, mailIdea retreats
Passive Forced diffusion methodsWork space design Kelley & Littman, (2005)Community areas (free coffee bars) Kelley & Littman, (2005)After work get together Kelley & Littman, (2005)Online idea forums or news groups Kelley & Littman, (2005)
Internal sought diffusionExpert networksIdea management softwareIdea databanksRecommended list of databasesRecommended list of search resourcesIdea booklets, catalogues
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Kelley, & Littman (2005) explained in detail that some individuals like
discussing new ideas and things they learned. They termed these people,
“Cross-Pollinators” and dedicated an entire chapter to them. They also assert
that not everyone likes this role.
Hence, it is easy to see that some people are much more inclined to be
good at distributing ideas and opportunities around the organization. Formally
assigning this task and providing them with the power to execute it can greatly
increase the degree to which ideas are distributed through the organization.
Allowing these individuals to select and conducted via any of the diffusion
methods from above will also help diffuse ideas across the organization.
A sign of an individual great at diffusion is that they can name off relevant
products, technologies, inventions, ideas, and show you were to go to learn more
about them, and they enjoy talking about this to others.
3.3.6.3. Controlling the Execution of Diffusion
Again, one must differentiate among forced and sought diffusion. Not everyone
needs to know about every idea in the idea bank; they only need to know about
the ones which are relevant to them at that particular time. As Hardagon & Sutton
(2000) showed their “idea brokers” distributed ideas in a just-in-time means to
solve problems relevant to the individuals they were helping.
However, Kelley, & Littman (2005) stressed that “Cross-Pollinators”
should spread ideas regardless of whether or not there was a need. Hence, one
can measure the effectiveness of forced diffusion by looking at the effectives of
a) getting idea solutions to people who have problems, b) spreading new or
useful ideas around the organization to the relevant individuals.
Opinions and metrics can be used to manage diffusion. If the development
team members feel they are not getting exposed to enough new ideas, then
possibly forced diffusion maybe failing to work. In addiction, measuring the
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number of events where new ideas are forced out and the number of people they
are distributed too can also give an indication of the effectiveness of forced
diffusion.
For sought diffusion, opinions and metrics can also be used. If employees’
feel they do not have access to easy methods of finding new ideas, then possibly
sought diffusion maybe failing-to-work. Also, if metrics on items like searches in
the idea banks, or use of expert networks are low, then sought diffusion may not
be used effectively.
3.3.7. Routing
Routing ideas is also an affective way to deal with this bias. Christensen
and Raynor (2003) proposed that disruptive ideas should be developed in
separate organizations. Similarly, Lockheed Martin is famous for their use of
skunk works to develop radical airplane concepts. By using idea management to
route disruptive idea to proper development groups like skunk works, internal
incubators, or spin-of-companies the company’s internal bias toward disruptive
ideas can be avoided. Similarly, by having market-driven ideas routed to the
marketing department for development can again overcome another company
bias.
The concept of routing ideas to the appropriate parties based on tagged
information is especially powerful for ideas of different innovation categories. For
example, a customer experience idea possibly should be routed to the customer
service department; whereas, a branding idea should be routed to the marketing
department.
Having a routing system also allows each particular department to have
their own idea bank, which can be linked to a company-wide idea bank. It is
imagine this could be rather easy, for example an employee may notice a
competitor using a new branding technique. That employee would then write-up
the idea, tags it, and then it is automatically routed to the marketing department
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by the idea management team. Additionally, tagging and routing also allows for
accountability in the front end of innovation because of the increase visibility
associated with the process.
3.3.7.1. Controlling via the Method and Execution of Routing
There are several methods of routing ideas, and they resemble the methods of
routing information. First, ideas and information can be routed to a particular
individual, group, or department. Second, ideas can be routed via email, memo,
document, meeting, or any other method of conveying information.
Additionally, Hardagon & Sutton (1999) suggest that “idea-brokers” route
ideas to the relevant individuals. Hence, the act of routing could be a formal task
assigned to a group of individuals. Interestingly, idea management software
could also be programmed to automatically route ideas to particular individuals in
a company. However, there is a benefit to having a personal idea-broker who
knows your needs and present the most relevant ideas at appropriate times.
As mentioned for diffusion, opinions and metrics can be used to manage
the execution of routing.
3.4. Linking Idea Banks to Portfolio Management
Similarly, idea banks and idea management can be linked to early portfolio
management. Typically companies determine their current portfolio of projects by
assessing the projects in the NPD process and commercialization process. Also
they determine their options for projects, by assessing the projects in the FFE
ready to move into the NPD process as shown by Figure 3.26.
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Figure 3.26. How Portfolio Management Determines Options for New Projects
Interestingly, by assessing the ideas in the idea bank product portfolio
managers can get an earlier understanding of options for their portfolio (Figure
3.27). As well, by analyzing the ideas in the idea bank, portfolio managers can
get a better understanding of the weakness in their company’s innovation
processes. Finally, portfolio managers can also selectively force fuzzy front end
processes to develop ideas particular for gaps in their portfolio.
Figure 3.27. How Assessment of Idea Banks can be Used by Portfolio Managers
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Figure 3.28. Late FFE Activities Linking to Screening and Filtering
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CHAPTER 4. RESEARCH METHODOLOGY
4.1. Purpose of Study
The purpose of this study is to answer the research questions as follows. First,
can the proposed control model aid in a conceptual understanding of idea
generation and idea management and, second can this control model be
supported as capturing the required factors needed to manage and control idea
generation and idea management?
4.2. Limitations Effecting the Selection of the Type of Study
Prior to discussing the study the factors limiting the study must be elaborated on.
This will greatly help in the selection of the appropriate study type and
methodology.
4.2.1. Lack of Metrics for Success in Idea Generation
Unfortunately, the lack of understanding of successful outcomes for idea
generation and idea management limits the number studies that can be perform
to support the research questions. The recent article by Hüsig & Kohn (2003),
had to go to great efforts to develop a set of criteria which they could measure
the success of front end activities. Unfortunately, neither idea generation nor idea
management has any metrics defining successful outcomes. As mentioned in the
previous chapter the output of the idea generation process can be generally
measured in: 1) the quality of ideas, 2) the quantity of ideas, and 3) the attributes
of ideas.
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Unfortunately, one company’s definition of successful idea generation can
vary greatly from another’s, and often vary based on that company’s needs and
situation. This researcher’s primary research has show that Siemens’ Power
Generation Division goals for idea generation are based on a quantity metric;
whereas, design firms like IDEO considers quality of generated ideas as being
most important (Kelley & Littman 2005). Finally, some companies consider
creating ideas of a very specific set of attributes (financial potential, feasibility,
required resources, and so on) as being a successful outcome of idea
generation.
Now, one way to test a control model is through the application of controls
and the monitoring of outputs. If the given control produces the required
successful output then the model is supported as useful. In a process, like
manufacturing, where quality is the main output this is a relatively straight
forward. However, for a process like idea generation where the outputs are so
variable and dependent upon a huge variation of needs, testing the impact a
control has on the output is tremendously more complicated, and may be to a
large degree futile because of the large interdependency amongst the control
variables.
Hence, the standard approach of testing control variables against their
outputs may help support this control model for a small set of instances, but will
not provide the needed evidence to support it broadly as a means of controlling
idea generation.
As for idea management, the process is so poorly understood that besides
not having models to describe its basic functions, there again is no metrics
describing successful idea management. Hence, a similar argument can be
made against doing causal studies to support specific control variables for idea
management.
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4.3. Study Type Which Will Not Be Used
The goal of this section is to make a rational argument for the selection of the
survey and interview based studies, by showing that the other optional studies
are inadequate.
4.3.1. Observational Based Support Studies
There are more limitations and downsides to conducting an observational study
than benefits. Observational studies are not going to be chosen for this research
because it:
• Is not economical and can be inefficient
• Will not allow the author to obtain a large enough sample size
• Requires extensive time to conduct
Additionally, because there are no particular behaviors which are trying to be
uncovered, examined, or validated, there is little need for an observational study.
Additionally, practitioners will accurately self-identify their current management
practices through tools like interviews or surveys. As a result, verifying this via
observations is redundant and inefficient.
4.3.2. Application Based Support Study
Testing this model was excluded from the research options because to truly test
a control model it must be applied in practice. This would require a company to
use the model to control their idea generation activities. Several companies have
expressed a willingness to implement this model; however, due to the time
required to gather results it will not fit within This researchers expected
graduation dates. Finally, application to a small set of companies will not provide
the evidence needed to support this model across industries. For these reasons,
an application based study will not appropriate.
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4.3.3. Laboratory Testing Base Support Study
Although, laboratory base tests are a common means to supporting a control
model, the author does not feel it would provide the needed support for this
study. First, practitioners will not see a laboratory reproduction of the idea
generation process as being an accurate representation of idea generation in
their companies, and often they scoff at laboratory studies. Again this is because
of the large disconnection between the complex worlds of actual business and
the idealized laboratory environment.
Finally, it is extremely difficult to reproduce the specific and changing
needs of a company, and the pre-set conditions of the business environment in a
laboratory setting. For example, asking a group of random individuals in a lab to
generate ideas for new cell phone technology will not accurately reflect a group
of telecommunication engineers with years of design experience producing ideas
in their own company environment. Hence for these reasons, laboratory tests will
not be performed.
4.3.4. Analysis of Secondary Research
Unfortunately, a secondary research study cannot be conducted because there is
no existing quantitative data on companies’ idea generation processes, practices,
or behaviors. Only, a few case studies on a company’s idea generation process
exist. Thus, the data must be generated through primary research.
4.3.5. Interview Based Support
Interviews will be used to support this model, however due to the limitation in
sample size they cannot be the only means of support. Additionally, interviews
can give detailed case examples of how companies manage idea generation and
idea management. However, interviewing requires substantial time and
resources if done over a large sample. Thus, interviews can be used in this study
but must be augmented with data from other supporting studies.
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4.3.6. Electronic Survey Study
A survey based study was chosen as the primary research design for this study.
This research design is appropriate because:
o It is economical and efficient
o Can capture a wide target population
o Can generate quantitative and qualitative data on practices, perceptions,
and needs.
There are several additional reasons why a survey was chosen as the primary
study instrument. First, the survey will be able to determine the practices and
satisfaction of the respondents with respect to idea generation and idea
management processes over a large sample size. Second, a large set of data
showing other companies best practices will be viewed a creditable and provide
the supporting evidence needed to develop broad acceptance of this model.
Third, surveying of practices, perceptions, and needs will show
weaknesses in current practices which may need to be addressed. Hence, solid
data on these weaknesses will help raise awareness of a problem area, and will
aid in the adoption of new practices.
Finally, by having the large pool of supporting evidence across several
industries will help the board acceptance of this control model. None, the less
surveying alone has weaknesses which are it:
1. Will not show if additional points of control can be used
2. Will not show if the model produces understanding
3. Will not show if the model accurately represent the idea generation
process?
To eliminate these weaknesses, this study will be combined with interviewing. In
particular, additional missed points of control may be uncovered through
interviewing with practitioners and researchers. Supporting evidence that this
control model generates understanding can also be obtained through
interviewing of a small sample. Finally, the weakness of accurate representation
cannot be solved through this study, and must be addressed in future research.
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4.4. Parts to the Study
To strengthen the support evidence for the research questions this study has
been split into two separate studies.
1. A series of case studies based on three very different companies
2. A normative and correlative study using an electronic survey with over
thirty respondents
4.5. Study Part One
The case studies consist of three companies with mature product development
processes in different industries. First, the company’s sponsors were asked to
identify the top three individuals in the company responsible for or most
knowledgeable about idea generation and idea management practices.
These individuals were sent an online survey (see Appendix C) of which
they collaboratively answered. The surveys answers were reviewed by This
researcher and sets of questions were formulated for the individual interviews.
Interview questions were based partially on areas of strength and weakness
determined from the survey responses. Each of the respondents was interviewed
for 1 hour, in which pre-determined questions were asked as well as follow-up
questions. Other interview questions revolved around the following topics:
A) Current company situation and strategy
B) Market served by the company
B) Current practices for idea generation and idea management,
C) Current needs for the early front end of innovation
D) Level of satisfaction with their current idea generation and idea
management practices
E) Detailed examples for use of each point of control.
All information captured from the interviews and online surveys were analyzed
and transformed into three case studies with recommendations for
improvements. The information was analyzed with the help of this researcher’s
proposed model.
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As compensation for their participation the companies’ sponsors will
receive the case studies and associated recommendations in a written report and
is considered a pro-bono consulting job.
Case study companies were selected from a pre-known batch of large
mature companies which was already personally contacted, and selected to
show diversity of size, situation, and industry.
4.6. Study Part Two
4.6.1. Description of Part Two
The second part of this study was structured into three elements. First the study
consisted of a (1) small number of interviewees, and then move to a (2) small
pilot survey study, and then towards a (3) full survey study. This format is a
variation on the total design study recommended by (Dillman, 1978). The
interviews will be conducted for the following purposes:
1. Test to see if the control model develops understanding and satisfies
the first research question.
2. Obtain case examples of points of control at specific companies.
3. Uncover points of control which should be included in the model, hence
further developing the model.
The interviews were first conducted with two expert researchers (Michael
Menefee and Kenneth Kahn) who were shown the model, and asked about the
overall setup of the questionnaire. The recommendations were integrated into the
survey instrument. This helped refine the structure of the survey and reduce
possible measurement errors.
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Next, the survey was sent out in a small pilot study to four or five company
respondents. The purpose of the pilot study was:
• To uncover confusion in the survey’s questions
• To get a rough estimate of measurement error
• Do a preliminary analysis of the data to see if the obtained data categories
provided the needed information for supporting the model
This preliminary pilot study obtained 5 respondents, and the data obtained
showed of 0.6 Cronbach which is good reliability for such a small number of
respondents. Further, post interviews with respondents showed no confusion
from the survey’s questions.
Finally, the full survey was sent out and data was received over a two
month period. This researcher used two web seminars to develop interest in the
survey. The web seminars were hosted by RYMA technologies and discussed
the idea generation and idea management process in a one hour long web
presentation during which one minute was devoted to promoting This
researchers survey. The attendees were primarily managers with product
development responsibilities. The attendees (122 individuals) were then emailed
an invitation to take the online survey which resulted in the highest completion
rate.
Additionally, web posts inviting individuals ‘to take the survey’ were posted
on Linkedin.com’s “front end of innovation group” and “product development
group”. These had very low completion rates.
4.6.2. Description of Survey Tool
The survey tool will have three main parts: a) identification questions, b)
satisfaction questions, and c) current practice questions.
Identification questions will be: who they are, how much knowledge they
have of their companies practices, the company they work for, industry,
revenues, number of employees, and so on. This will help qualify the
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respondents as a reputable source of data, and provide data to compare
respondents and their companies. All published data will be de-identified from the
company’s and respondent’s names.
Unfortunately, the best dependent variable which could be selected was
the satisfaction based variable. Many research studies have shown satisfaction
to have a strong correlation with output and results because respondents innately
have a sense of what works and what does not and correlate their satisfaction
respectively.
Dependent quantitative variables such as number of ideas, revenues
generated per ideas, number of ideas captured from the employees, number of
ideas captured from outsides sources, average revenues per idea were noted in
the case studies to vary greatly between industries and company size. Further,
respondent’s accounts of these numbers were found to be totally un-reliable
because they did not keep track of these numbers.
Other dependent qualitative variables such as: quality of ideas generated
quality of ideas captured from employees, and quality of ideas in the idea bank,
were found to be highly objective and mostly unknown amongst interviewees of
the case studies, and hence were deemed totally un-reliable.
Unfortunately, amongst all the reviewed literature no articles were noted to
measure output of the idea generation or the idea management process, or even
link idea generation to development output such as: revenues, or new product
releases. Consequently, there were no dependent variables to build upon. Only
one article was found to have a correlation linking idea generation to marketing
information (Husig, Kohn, & Poskela, 2005). Due to these problems, the only
logical and halfway reliable dependent variable was that of “satisfaction.”
The respondent’s level of satisfaction was split up with respect to the
outcomes of their companies, a) idea generation processes, b) idea management
processes, and c) development process. This allowed one to draw valuable
correlations between levels of satisfaction and actual practices.
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Questions regarding current practices looked for points of control which
are currently in use in their business. This will develop the needed support for
each control point mentioned in the model. More interestingly, this will give a
general understanding of how much control is placed on a particular activity.
Current practice questions were broken up into amount, and frequencies and all
used a five-point Likert scale (never, rarely, some-times, most-of-the-time,
always, don’t know, NA). The survey can be seen in Appendix C.
4.6.3. Description of the Respondent Pool
RYMA solution community consisted of 50,000 members of which 90% product
development managers from companies all over the world. On average, 100
members read the blog daily, and over 150 members on average attend their
web seminars.
4.6.4. Data Analysis
This survey tool output all responses in an excel file format. Exported data from
the survey was automatically organized by the survey tool by respondent. The
analysis of the data was rather straight forward, and required comparing data by
respondent companies, industries, satisfaction, and so on. Graphs were created
showing results of the data, and all data were de-identified from the
respondent companies. Comparison and correlations were drawn, and
examined to determine statistical significances.
Normative data, graphs, and charts were created showing the current
practices and methods controlling the idea generation and idea management
process. Finally, this research shows the practices most associated with
satisfactory outcomes for idea management and idea generation. The resulting
data gave a strong base for future researchers to attack and make great strides
in idea generation and idea management.
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4.7. Human Subjects
For the purposes of this research, human subjects’ approval was sought and
obtained prior to the study’s commencements, as required by the Purdue
University, and consistent with current research standards. The study’s reference
number is 0808007117.
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CHAPTER 5. RESEARCH RESULTS
The following chapter presents the research findings for both the case studies
and the qualitative survey. The research findings are broken up into two sections
being: (1) case study results, and (2) quantitative survey findings, which each
section including a respective discussion and conclusion. The duel research
study approach would lend more support for the proposed model and help in
answering the second research question. The first research question was
answered in Chapter 3.
5.1. Summary of Case Study Results
These three case studies show distinctly different companies and their respective
idea generation and idea management processes. These companies provided an
adequate diversity, with the first company being a multinational large cap
company with products in every geographic market. The second being a small
cap company with products mainly in the US, and the third being a small
company marketing a new software technology to a pre-adoption marketplace.
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Table 5.1. Attributes of the Three Companies Company Name Alpha Company Fairbank's Scales Cartêgraph
Company size Large Cap Mid cap SmallEmployees 125,000 500 80Revenues $5 billion + $100 mill + $30 to $50 mil
Product area Consumer Food products Scales - machinery Software managementMarket Age Highly Mature Highly Mature Pre-adoption
Business ModelSells products to food retail chains Product manufacturer
Subscription based business model
SituationLack of capturing ideas from outside sources Need disruptive ideas Needs help crossing chasm
Major Recommendation Reorganization of process
Broader perspective of their business
Have idea generation create ideas to help cross the chasm
5.1.1. Benefits of the Case Studies
There was a great benefit to conducting these detailed case studies. First, the
detailed analysis allowed this researcher to probe deeper into the situation than
the simple online survey would have allowed. This probing uncovered company
situation and market age played a large role in all case studies. Further, the case
studies uncovered motivations and underlining issues which would not have
been picked up by the survey. Simply put the detailed analysis through
interviewing allowed for much more detailed analysis and a rich learning
opportunity.
5.1.2. Analysis of the Company
To aid in this analysis, company Alpha’s idea generation and idea management
practices were compared to this researcher’s idealized (Glassman Model) idea
management model. It was found that these comparisons allow the author to
quickly identify areas of weakness & strength and in detail and see how the
minor differences in their practices affected the overall process.
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5.1.3. Brief Summary of Each Case Study
In order to highlight the lessons learned, each case study will be summarized
and it’s associated lessons will be briefly discussed. Again, each detailed case
study is listed in the following section. Please note that each case study contain
recommendations made to the company’s sponsor which are interwoven into
body of each study. As mentioned previously, all companies were analyzed with
the assistance of the Glassman model.
5.1.3.1. Summary of Company Alpha
Company Alpha (de-identified) presented an interesting case of a large multi-
national with multiple dedicated research facilities. This case study focused only
on one of their research facilities located in Europe which concentrated on
developing food products: hot drinks, chocolates, coffees and employed 500
researchers. This R&D center had a 2007 $110 million R&D budget.
This research center had great difficulties in capturing, storing, and
diffusing ideas generated by their large number of employees. Unfortunately,
researchers did not use the idea management software offered by the company
because it was cumbersome and lacked major features. The main lesson learned
here was that an effective idea management software system is needed for idea
management inside of large companies which handle large number of ideas.
Second, the company only practiced a limited range of idea generation
activities and did not conduct any more beneficial idea generation activities
involving customer research. This major error was found to limit the number and
quality of the generated ideas.
Third, the company did not capture or accept ideas from outside sources
being: partners, suppliers, customers, inventors, or universities. Because of the
size and visibility of the company they could easily receive many dozens of ideas
per day. Not the having means to capture ideas from these sources was an
error.
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5.1.3.2. Summary of Fairbanks Scales
Fairbanks Scales is a small capitalization company with revenues around $100
million, and 500 employees, of which only 16 are involved in R&D. Fairbanks
Scales strictly produces scales and weighting equipment.
Interestingly, their strict adherence to the “scale” concept seemed to have
stalled their idea generation process. Their multiple markets for scale products
are highly mature and attempts by Fairbanks to generate “scale” ideas for these
very saturated markets resulted in fruitless ends. As a result, Fairbanks Scales
rely interiorly on capturing ideas from a multitude of sources: partners, lead
users, customers, suppliers, universities, and on.
To avoid stalling the idea generation process, this researcher
recommended (based on Levitt’s Marketing Myopia article) that they broaden
their strategic view to “being in the business of providing assurance and
information on any physical attributed” instead of “being in the business of
making scales.” In addition, this research recommended that they look at the
whole job process of their customers so they can generate product ideas which
integrate other functions and functionalities in addition to weighing. For example,
a potato chip bagger can also integrate a scale into one machine to assure the
proper product weight.
Associated idea generation activities were recommended based on this
larger strategic view and they should bring about many fruitful ideas.
5.1.3.3. Summary of CartêGraph
CartêGraph is the smallest company studied at $50 million in revenues and 100
employees and produces software management tools for local governments to
manage maintenance on items like: roads, streetlights, sewage pipes, and so on.
Interestingly, only 1% of local governments use software to aid in managing their
infrastructure, hence this technology can be considered a pre-adoption market.
Given the pre-adoption status of their market and that the bulk of their future
profits lie in the mass market adoption of this technology, this researcher thought
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it best if the idea generation activities focused exclusively on creating ideas
which specifically helped the mass market in adopting this technology. As well,
this researcher highly recommended integrating “crossing the chasm strategy” by
Moore into the strategy and development decision processes of the company
(Moore, 2003).
CartêGraph’s idea management process was very haphazard and many
recommendations were made for improvement. In all, it was interesting to see
how important it was to tie idea generation into the larger company strategy.
5.2. Case Study 1: Company Alpha
5.2.1. Background on the Company
Company Alpha (cover name) is a large company with consumer food products
in every major geographic market. Company Alpha’s R&D divisions are spread
out into individual R&D centers around the world. Because of the R&D center
approach, innovation efforts are decentralized which allow the company to
specialize in particular markets/country preferences. This study concentrated
only on one R&D center located in Europe, employing more than 250 workers
and with a R&D budget larger than 50 million.
5.2.2. Sources of Ideas for Idea Generation
Company Alpha always uses employees in idea generation activities.
employee), opportunity area, reviewed or not-reviewed, technical feasibility, and
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developed or not-developed. More categories help employees in quickly
reviewing ideas prior to participating in future idea generation activities, and help
the innovation directors to see where the gaps are in the idea database.
5.2.9. Process Check Used to Improve the Idea Generation Process
Luckily this company’s research center has at least three individuals dedicated to
refining and improving the idea generation and idea management process. The
interviewees were mentioned to sometimes review the process based on the
outputted ideas. Ideally the open innovation director should review ideas
submitted during a period of time to see if the past changes had the desired
effect and if the idea generation activities are having a positive ROI. These
reviews would be best made every 4 or 6 months.
5.2.10. Diffusing Ideas to Employees inside the Company
Again there are two reasons for diffusing ideas being: (1) to get ideas to turn into
new product development projects, and (2) to use the ideas to seed employees
brains so they are more able to generate new ideas. At Company Alpha, much
work needs to be done in diffusing idea to employees. Sought diffusion (allowing
employee to freely scan the idea database) is mentioned by interviewee not be
effective since very few access the database. Employees in particular groups like
chocolates or hot beverages should be made aware of newly submitted ideas in
their area via forced diffusion. Force diffusion can be performed by email
notification of best ideas every week or month, or newly submitted ideas can be
diffused to employees in batches a mandatory bi-weekly meeting.
Further, a culture should be developed where ideas are sought from
internal and external sources and discuss frequently, the best way to start this is
to force lots of ideas on employees till they get used to discussing ideas on a
regular bases. The fifteen individuals responsible for receiving ideas in this
research center should be also responsible for distributing these idea emails or
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idea memos to respective employees. Routing of ideas is being performed
correctly by the idea coordinator and seems to be the only way which ideas are
currently being distributed.
5.2.11. Comparison with Measures of Satisfaction
The satisfaction variables in the survey were compared across the three
interviewees and it was found that their opinions differed. The minor differences
were mainly due to the responsibility areas of the interviewee and knowledge in
that area, for example the open innovation officer was dissatisfied with their
ability to capture ideas from outside the company, whereas, the idea coordinator
had a neutral opinion on this matter. The results for the satisfaction variables are
shown in tables 5.2 and 5.3 below. Note number 1, 2, 3, are the number of
interviews which responded at that particular level of satisfaction for the given
question.
Table 5.2. Idea Generation Satisfaction Variable Results for Alpha
Satisfaction Variables Very
Dissatisfied
Dissatisfied Neutral Satisfied Very
Satisfied
1. Quality of ideas 3
2. Number of ideas 1 2
3. Generating idea with a
specific set of attributes
1 2
4. Time for generating ideas 2 1
5. Ability to fill frontend portfolio 3
6. Overall idea generation
process
3
Interestingly, overall satisfaction with the idea generation process (being
dissatisfied) was much lower than the dependent satisfaction factors mentioned
above. This initially led the author to believe the first five factors are not
substantial factors in determining overall satisfaction.
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Table 5.3. Idea Management Satisfaction Results Variables for Alpha
Satisfaction Variables Very
Dissatisfied
Dissatisfied Neutral Satisfied Very
Satisfied
7. Capturing ideas from
employees
3
8. Capturing ideas from outside
sources
3
9. Storing & capturing ideas 3
10. Amount, quality, & type of
ideas
3
11. Ability to distribute and route
ideas
3
12. Ability of ideas bank to fill
frontend portfolio
3
Interestingly, interviewees seem dissatisfied with three out of the five
activities in the idea management process. This researcher hypothesizes that the
interviewee’s satisfaction with the overall idea generation process is taking into
account factors which are associated with idea management. Since both idea
generation and idea management are very new areas of research with very new
terminology, it is reasonable to suppose that the interviewees consider idea
generation to include the factors 1 to 5 & 7 to 12. Hence, one can hypothesize
that above satisfaction factors can, in sum, correlate to overall satisfaction with
idea generation.
5.2.12. Late Front End Activities at Company Alpha
Through out the interviews, additional insights were gain into Company Alpha
Late Front End activities which are note worthy. Interviewees noted that after an
idea is captured and screened, the ideas are usually rushed to a second screen.
This researcher feels this is an error, because the ideas need time to be
developed before being placed in the second screen. Coopers Stage gate
process demonstrates this well. By looking at the Figure 2.9 and Appendix B one
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can see that ideas are scoped before the second screen, then have a business
case build for them and then proceed to a third screen. This insures that work is
put into the ideas to develop them and that proper kill/proceed decision are
made.
5.2.13. Recommendations for Late Front End Activities
To avoid ideas from being rushed into a second screen, this researcher
recommends some initial work be performed on raw ideas to turn them into more
refined concepts. This can be done by assigning a batch of ideas to a group of
researcher and requesting that 2 to 3 concept ideas be developed, regardless of
the quality of the ideas in the batch. This will force researchers to be more
creative and seek out better ideas from the idea database if their batch is full of
poor ideas.
5.3. Case Study 2: Fairbanks Scales
5.3.1. Background on the Company
Fairbanks Scales was established more than 150+ years ago has 500 employees
and creates scales of all types. Their scales range from small doctors scales all
the way to large truck scales, and they have 5000 product model variations and
over 100 scale product lines with all product lines being strictly scales or
weighting equipment.
The company has a typical centralized organizational structure, with sales,
service, manufacturing, development, and admin/finance departments all located
at the US headquarters. The development department has 16 engineers with 10
of those individuals involved in R&D, and a R&D budget of less than $2 million.
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Fairbanks Scales’ has a manufacture/sales business model and generates
additional revenues via servicing scales and 2007 revenues were $100 million +.
Technical details of their products will not be discussed because they were not
found to be relevant to the analysis of Fairbanks Scales’ innovation process.
The VP of development stated that Fairbanks Scales, as well as, the rest
of the scale industry has been waiting for the next major development in scales,
and consequently they have been actively looking for the next disruptive
technology, product, or major market application.’
Evidently, the scale markets are extremely mature. Case study evidence
and market theory shows that extreme segmentation only occurs in highly mature
markets. Evidence of market maturity is Fairbanks Scales’ highly segmented
product portfolio and the general age of the product markets many of which are
more than 50 years old.
5.3.2. Overall Situation & Broader Strategic View
Prior to discussing the details of the idea generation and idea management
process this researcher would like to discuss a larger and more urgent issue
which affects the greater innovation process at Fairbanks Scales. This section is
of interest to the CEO and board because it suggests a broader view of the
company’s strategy.
Research on Fairbanks Scales’ current markets and offerings and
interviews with the VP of engineering/development and director of development
have lead this researcher to “question if Fairbanks Scales narrow view of “scales”
as their core business will provide them with the required future growth?”
Aside from entering new major geographic markets like Asia, or South
America, growth will come mostly from developing new products for their
currently served geographic markets. As the VP of engineering/development put
it “we are looking for the next big thing.”
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This researcher’s initial thoughts were that Fairbanks Scales was narrowly
concentrated on developing “scales” for a highly mature and highly saturated
scale markets which has limited innovation opportunities remaining. In other
words, Fairbanks Scales had taken the scale concept, to what seems to be, the
current limits of the technology and customer needs for their currently served
geographic markets. Again, their extreme segmentation (130+ product lines &
1,500 product variations) and the multitude of application areas were evidence of
this thought. Reaching the application limits of any market is, in itself, an
accomplishment any company should be proud of!
There are many companies, existing both currently and in the past, which
have reached the limits of their current business applications and for the most
part have stalled in developing new products in categories like: pens, tables,
doors, windows, silverware, to name a few. Some product categories like “trolley
cars and horse carriages” have even been superseded and no longer exist. The
trick to getting unstuck in these instances is viewing product innovation through a
larger view, instead of a narrower product based view.
For example, trolley car manufacturer throughout 1800’s and early 1900’s
made tremendous value for their shareholders; unfortunately, they did not see
they were in the “business of providing transportation” and with the advent of
cars, & trucks, lost market share and now are in total obscurity. Hence, thinking
in line with your current product category can limit the company’s ability to
expand as famously noted by Dr. Levitt in his Harvard Business Review article
Marketing Myopia (Levitt, 2006).
Again Fairbanks Scales should consider it a great accomplishment to
have fulfilled their customer’s needs with regards to scales. Unfortunately, it
seems that Fairbanks has limited their development thinking purely to the “scale
concept.” Their manufacturing, engineering, sales capabilities and their
distribution channels would definitely allow them to expand outside of the pure
“scale” concept, into related areas.
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The lessons learned from Levitt’s Marketing Myopia article (read this
article listed on page one before proceeding) can be directly applied to Fairbanks
Scales. However, recent discussions of Levitt work mentioned that he neglected
company resources and core competencies in his theories. For example Kodak
saw the arrival of digital camera technologies but was unable to make the
transition successfully due to their lack of electronics knowledge.
Applying Levitt’s lesson to Fairbanks Scales one would have two new
perspectives on their products which will help them generate new products being
(a) broader view of their core business and (b) a broader understanding of how
their products fit into the job process
5.3.3. Adopting a Broader View of Their Core Business
As for (a), Fairbanks should understand that they are not in the business of
providing “scales” but actually in the business of ‘providing assurance and
information on a physical item.’ Again people don’t buy drills; they are buying the
ability to make a hole. Following this logic, Fairbanks has been ‘providing
information and assurance on “weight’ for a multitude of physical items for more
than a century through their scales.
Remember weight is only one physical metric of an item which a customer
may want information or assurance on. Here is a list of other aspects of a
physical item:
1. Number of items
2. Volume
3. Dimensions
4. Density
5. Hardness
6. Color
7. Odors
8. Temperature
9. Pressure
10. Orientation
11. Integrity
12. Item information (serial #)
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Take for instance a food quality assurance lab, in testing their food
products they weigh them, measure density, and in many cases test hardness or
taste. A small scale that weighs, counts average number, and measure density
and weight simultaneously may be valuable especially if it can be integrated
directly into a production line.
Similarly scales that can automatically measure dimensions & weights
may be valuable to some customers who must determine shipping costs or figure
out how to effectively pack a semi-truck. Hence, one can use the above list, and
a broader view of ‘providing assurance and information on physical items’ in
formal idea generation activities to create many new product ideas which would
build on the core strengths and sales channels of Fairbanks.
5.3.4. A Broader Understanding of How their Products Fit into the Job Process
Fairbanks should adopt a broader view of how their products fit into the larger job
process when generating ideas for new products. For example, the vertical
bagging machines shown in figure 1 below weighs but also bags and seals items
like food. This machine provides assurance that the correct portion size (by
weight) is dispensed but also performs the next step in the job process which is
bagging the product. Performing this additional step greatly increases the value
of the machine, and it is no longer just a scale but a larger and more valuable
piece of equipment.
Figure 5.1. Vertical Packaging Machine with Integrated Scales
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Hence, looking at the steps before and after the weighing in the job
process will help one generate more new product ideas. For example, look at a
ranch hand that is tasked with weighing cattle. First the hand must round up the
cattle and bring them home. Then the hand must read the cattle’s ear tag
number, put it on the scale, write down the weight, compare the weight to the old
weight (to assure the cattle is growing properly), then calculate the weight
increase, and release the heifer if it is the appropriate weight. If it is sick they pull
it aside to quarantine it so the veterinarian can check it out.
Thinking more broadly one can integrate the scale forward and backwards
into this job process and hence create a more valuable product. For example the
cow’s ear tag could be scanned by the computerized scales by a simple RFID
chip embedded in the cow’s ear tag or bar code printed on the ear tag. The
scale’s memory would then pull up the cow’s old and new weights. With this
information in the memory the scale could print out metrics valuable to the
rancher like, pounds gained, average pounds gained over last 3 scans, average
pounds gain per month, and so on. The scale could even beep loudly or marked
a cow with spray paint if it lost weight, so the rancher can inspect them or
quarantine them.
There is great value in looking at the whole job process and seeing how
weighing fits in, and then using that understanding to generate ideas. Best of all
these new product ideas should fit into the sales channels and build on the
strengths of the company. With these two new perspectives discussed, this
thesis moves on to details of the idea generation and idea management process.
5.3.5. Idea Generation
It was found that Fairbank Scales’ did not have a process for, or conduct any
activities for idea generation. More specifically, they did not hold idea generation
activities, host idea generation events, or select individuals to generate ideas.
This finding was confirmed among both interviewees, where one interviewee
mentioned “we conducted several brainstorming activities and found that they
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produced very mediocre ideas which were already present in our idea bank.”
Thus they stopped all idea generation and rely presently on capturing ideas from
internal and external sources.
This researcher hypothesizes that many companies experience similar
frustrations from a lack of success in idea generation. It is thought this is partially
due to a lack of expertise in effectively conducting idea generation activities. This
is understandable given the large gap in the literature on how to effectively
conduct idea generation activities.
In the case of Fairbanks Scales, it is even more likely that frustrations and
fruitless results would arise using the narrow “scale” concept to direct idea
generation activities especially given the maturity and saturation of the scales
markets.
5.3.6. Recommendations for Idea Generation
Again, it is recommended that Fairbanks Scales take a broader view of their
business so they can venture into related products and grow successfully. Their
narrow view of producing just “scales” has stalled all idea generation activities,
and it strongly felt that shifting perspectives, as elaborated on, will reinvigorate
the company’s idea generation process and produce worthwhile new product
ideas.
To do this, the new perspectives must be discussed and infused within the
larger company, being sales, service, engineering, and development. As well, the
intent for these new perspectives must also be discussed.
Next the management inside of Fairbanks Scales namely the VP of
engineering and development and the product development director must
familiarize themselves with the recommendations for the idea generation
process, namely because they will be the parties managing and conducting this
process.
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To generate ideas, Fairbanks Scales should use formal idea generation
events where a set of employees are assigned and required to generate ideas,
obviously the most observant and creative employees are preferable for these
activities. The exact mix and number of employees is based upon the selected
idea generation activities.
The VP of development/engineering desires large revenue ideas, which
can be classified as A) disruptive ideas or B) new opportunity areas. Strictly
speaking disruptive products are those which are set to supersede a preceding
product and utilize some major shift in function, technology, or use. For example,
flat screen TVs were a disruptive product when compared to tube televisions. A
new major opportunity area maybe a new application for a product like
integrating scales into medical beds or GPS for cars, where previously no
product or technology was filling the need.
One should note that the idea generation activities used to generate
disruptive or new major opportunity areas are much different than the activities
used to generate incremental product ideas. Hence, this researcher is
recommending idea generation activities which will primarily generate disruptive
ideas or new opportunity areas.
Table 5.4 shows a list of idea generation activities which fill the prior
mentioned goals, remember each activity requires a moderator or director who is
trained (self-training possible) on how to properly conduct that activity. Further,
the company should not spare budget on particular idea generation activities, for
this will greatly affect their output. Note that idea generation techniques are used
inside of idea generation activities. For example, a scenario games can be used
to augment a brainstorming activity; whereas, problem inventory analysis is a 1
hour long activity in itself.
As well, the list above shows several idea generation activities, and the
cost and time associated with each activity will vary based on that activity. It is
recommended that at least 3 to 5 activities (with one of them being a large
budget activity) be conducted per month till a sufficient number of new ideas and
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opportunity areas are discovered. Remember an opportunity area only highlights
a particular customer need, and that further idea generation activities should be
used to generate specific new product ideas which can capitalize on that
opportunity. As a result, many more than three activities should be conducted per
month if a valuable new opportunity area is discovered.
Table 5.4. Recommended Idea Generation Techniques and Activities
The list above also focuses heavily on activities which require customer
visits or observation of customer activities. This is because the company is
looking for areas where (1) they can provide additional assurance and
Idea Generation Techniques Experimentation Measure, tests, validate, via physical, virtual, or thought experimentation
with the goal of confirming a hypothesis or gathering data
Charting and plotting Helps visualize unknown or un-seen relationships
Use this technique in problem inventory analysis
Scenario games Create scenarios and play them out to their logical end Adaption Adapting a solution, offering, or process to suit a companies need by
modifying it as needed
Reduction Reducing the amount, functionality, or features of a particular thing Elimination Eliminating a particular, feature, attribute Raise or increase Increasing a particular feature, attribute or factor above the norm Division of parts Breaking up the whole into smaller and smaller features, functions, or
pieces
Perspective shifts Using a perspective or view to aid in generating new ideas Removing boundaries Removing boundaries, and retesting base assumptions, do not assume
restriction unless strictly told
Detailed observation Looking closely at something, trying to understand every facet, function, and behavior
Idea Generation Activities
Brainstorming Creating ideas in open discussion, (typically many techniques are applied)
Use hybrid using each one of the above techniques
Contextual research See appendix B
IDEO process IDEO Idea Generation Process see appendix A
Job Mapping See the article “the customer centered Innovation map” on page 1
Hybrid-Brainstorming
Brainstorming using techniques above and using the two (2) suggested views on page 3 & 4
Customer Focus groups
A collected group of individuals (customers) focused on giving feedback on a particular product, service, or process
Problem Inventory Analysis
Generating a list of negatives or problems with an offering, product, or process, and then finding solutions to eliminate those negatives
Critical path mapping
Graphically representing activities their duration and fining gaps and problems with their flow
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information on physical items outside of weight, and (2) analyze the greater job
process to identify steps where they can add additional value. Not conducting
customer visits is a major error!
Innovation managers must keep in mind that employees are busy, and for
them to dedicate time to idea generation there must be an incentive in place.
Fairbanks’ did not have an incentive system for patents or new ideas; hence this
researcher recommends that using a $5K bonus for identifying a fruitful new
opportunity area, and $10K for new profitable products will help incentivize
employees. Additionally, having moneys awarded only after a new product hits
market launch will help motivate employees to do additional market research and
push possible wining products through the development process.
5.3.7. Screening of Ideas
Screening of ideas created from formal idea generation activities should be done
differently than ideas which are captured from internal and external sources.
Ideas created as a result of a formal activity should be submitted to one
individual inside the company, where a high level strategic and capability screen
is applied. For example, a contextual research activity may generate an idea for
integrating a dimension monitor into a production line weighing system, in which
case it would pass a strategic screen and a company capability screen. Note that
a feasibility screen was not applied.
Screening of ideas captured from internal and external sources should be
also done by one individual inside the company, but instead a capability screen
should be applied. One goal of capturing outside ideas is to identify new
opportunity areas, and using a strategic, or feasibility screen may inadvertently
throw away a valuable opportunity area.
As well, there is little harm in storing poor ideas, and turning down poor or
low quality ideas submitted by employees too promptly will make them less likely
to submit ideas in the future. For example, an employee may relay that a
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customer wants’ a very cheap scale for cooking. This may highlight a larger
opportunity which is integrating scales into kitchen appliances like microwaves.
5.3.8. Capturing Ideas from Internal and External Sources
Fairbanks Scales strength is capturing ideas from any source possible. The
survey shows that Fairbanks Scales always captures ideas from: employees,
customers, universities, external research labs, suppliers, consultants,
partners/alliances, in-direct competitors, independent inventors, & media
magazines by phone, email, in-person, or through the idea management
software. As well they monitor direct competitors for new product releases.
The large number of sources which they capture ideas from was confirmed to be
the result of a (1) strong need to obtain ideas for new applications, (2) the lacking
of an idea generation process, and (3) the lack of any one source providing an
adequate number of ideas.
One recommendation for improvement may be to further incentivize the
sources so that they can submit more ideas. This can be done with small royalty
agreements or bonuses to the submitters think of it as incentivizing someone
who refers you a customer. Additionally, the solutions group should advertise that
they can assist in developing ideas in-order to obtain more submissions.
5.3.9. Tagging Ideas during Capture
The company is tagging ideas by always recording upon capture “who created
them”, however, they sometimes record “when the ideas were created”, “who
else participated in their creation”, and “what activities lead to the ideas creation.”
Always recording this information is valuable because as more advance idea
generation activities are used, the ability to track which activities generated a
particular idea will be useful in selecting future idea generation activities and
recording ROI for a particular idea generation activity.
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5.3.10. Storage and Categorization
Fairbanks Scales refers to their idea database as an “Idea vault” and has a mix
of formal (software) and informal means (computer documents) for storing ideas.
Their idea management software is called “quick base” and can store images,
documents, and text. An interviewee noted that metrics and categories can be
added to help store and evaluate ideas.
This researcher recommended that Fairbanks Scales categorize ideas by:
supplier, employee), opportunity area, reviewed or not-reviewed, technical
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feasibility, developed or not-developed, and finally idea driver (technology,
market, customer, solution driven). More categories help employees in quickly
reviewing ideas prior to participating in future idea generation activities, and help
the innovation directors see where the gaps are in the idea database.
5.4.11. Process Check Used to Improve the Idea Generation Process
CartêGraph did not perform process checks on ideas or refined the idea
generation process as a result of these checks. It is recommended that an
“Innovation manager” knowledgeable in idea generation and idea management
be assigned and accountable for reviewing ideas captured by the company, and
ideas generated by the company. In doing so, they should check that the idea
generation activities are producing the desired ideas. For example, the
innovation manager should check that an idea generation activity such as “whole
product solution analysis” produced ideas which will help the company cross the
chasm.
5.4.12. Diffusing Ideas to Employees Inside the Company
CartêGraph also seems very poor at diffusing ideas across the company and it
was mentioned that ideas are not getting spread across the company. As well,
monthly development & sales progress meeting are being used to talk about new
ideas. It is hypothesizes that these new idea conversations must compete for
time against the more pressing sales and development conversations, and
inevitability lose priority.
Ideally, given the small size of the company (70 to 90 employees) there
should be a separate monthly or bi-monthly meeting dedicated to discussing new
ideas. A group of ideas should be selected and assigning ideas to individuals to
conduct preliminary market research. The result of their market research will be
used in the next idea meeting to select ideas. As well, meeting to discuss new
ideas should be combined with, and held right before idea generation activities.
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5.4.13. Late Front End Activities
This researcher noted that there were several issues with CartêGraph’s
Innovation process which need urgent attending to. These issues are:
a) The need for a portfolio management process, and
b) The need to integrate crossing the chasm strategy into the company’s
development process and company strategies.
Portfolio management is a vital process which is the act of selecting,
managing, and prioritizing the mix of development projects (a portfolio of
projects) so to manage the risk, returns, and strategic implication of the
company’s future product offerings. Metaphorically think of it, as managing a
portfolio of stocks & bonds that will mature anywhere from three months to five
years out. Having a detailed and sound process for selecting and managing the
portfolio will greatly increase returns when compared to a haphazard investing
strategy.
Currently, CartêGraph does not have a portfolio management process,
and all interviewees requested a process by which new products can
systematically be selected for development. Hence, this researcher recommends
that all executives should download and read the portfolio management articles
from the page. From those teaching the executives should structure their own
portfolio management process and communicate it to the boarder company so to
create alignment and understanding.
As previously mentioned the books Crossing the Chasm and Inside the
Tornado highlighted that companies in pre-adoption markets should integrate
company strategies towards forcing market adoption. In doing so they can force
themselves into market leadership for their emerging markets. This was true for
HP in the desktop printer market, Intuit for accounting software, Nikon for digital
cameras, and so on.
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This researcher recommends that the prior mentioned marketing research
project be carried out to determining the major 4 or 5 crossing the chasm factors.
The portfolio manager should then collaborate with the board and other
executives to push a part of their company’s product portfolio towards meeting
those factors, maybe 20% of next years products.
Again, sales will not be able to cross the chasm without a massive push to
do so, thus, preliminary sales and market responses for these products will, most
the time, be false indicators of their actual ability to cross the chasm without a
massive push to do so.
However, great efforts should be taken to uncover if these new products
are: a) lacking factors preventing pragmatic customers from adopting, or b) the
pragmatic customers are not adopting because they lack confidence in the
market and need to see their friends adopt it first.
If (a) is the case, more product development work needs to be done to
ready the products for chasm crossing. If (b) is the case, work must be done to
prove to the market that these products are ready and a small portion of the
pragmatic customer must be forced into adopting and providing references to the
greater market (i.e. running the market crossing battle mentioned in Moore
2006).
Again, no market research study is ever 100% correct, and hence pushing
the whole product portfolio towards the factors needed to cross the chasm is
risky. Hence some portion of the product portfolio should be dedicated to
crossing the chasm, while the remainder of the portfolio should generate
revenues from the current customer base.
5.4.14. Comparison with Measures of Satisfaction
The satisfaction variables in the survey were taken from only one interviewee
(marketing manager) and were found not to be reliable. After the survey was
completed, the respondent was interviewed, during which point he noted that the
levels of satisfaction were in retrospect much lower than that entered into the
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survey. For example, the levels of satisfaction with the overall idea generation
process was (satisfied; however, during the interview he mentioned to be very
dissatisfied because no process for idea generation existed. Hence this
researcher must discount all measure of satisfaction from CartêGraph from this
case study.
5.5. Case Study: Discussion of 2nd Research Question Based on Case Study
Evidence
The following section discusses the supporting evidence (obtained from the case
studies) that the model satisfies the second research question. Again, the second
research question is: “Can the developed control model be supported as
capturing the required factors needed to manage and control idea generation and
idea management effectively?”
This section supports the purpose model through evidence of its useful
application in analyzing and making recommendations for the case study
companies’ idea generation and idea management process. The supporting
evidence for this model is its: (1) aid in a quick analysis, (2) systematic analysis
of the information, (3) aid in performing a detailed analysis, (4) help in uncovering
major problem areas, (5) aid in making recommendations, and (6) aid in
comprehending the information. One major factor (strategy) was found to have
been missing from the model and will be discussed in the following “lessons”
section.
First, the proposed model aided in a rough analysis of the companies
processes. Again, the interviewees first answered the online survey which was
created directly from the proposed model. Then this researcher reviewed the
survey answer. From a 20 minute review of those answers, this researcher had a
very good understanding of areas of strength and weakness in their process.
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Second, the Glassman Model helped this researcher systematically
examine the vital points of the idea generation and idea management process
and according to the interviewee help create a very detailed set of
recommendations.
Third, it was found that the Glassman model resulted in a superior
analysis when compared to simple interviews conducted around general
activities such as generating ideas, screening ideas, capturing ideas, storing
ideas, and diffusing ideas.
The resolution offered by the Glassman model’s point of control for each
activity directly helped create many interview questions which uncovered a great
deal of valuable information which otherwise would not have been uncovered.
The Glassman model also guided interviewing questions to follow a logical flow.
Fourth, the model uncovered major and minor problem areas in the
companies’ idea generation and idea management processes. The model and
comprehensive list of factors and points of control helped in uncovering major
problem areas in their company’s process that otherwise may have been missed
during un-guided interviewing. The case studies highlight the many problems
uncovered for each company, and attest to the models value in these areas.
Fifth, the proposed model definitely aided in making recommendations.
The model’s comprehensive factors and points of control insured that a
comprehensive list of recommendations was made to each company. Without the
model, it would be very easy to forget to include a recommendation for a
particular part of the process.
Lastly, all information gathered from the interviews, both solicited and
unsolicited, could be fully understood in the context of the proposed model. This
is considered to be a major step because prior to this model interviewing often
uncovered information which did not result in an understanding of the process or
was information too difficult to piece together. The purposed model aided in
mapping and understanding of the companies processes which were previously
convoluted and difficult to comprehend.
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5.6. Case Study: Major Lessons Learned
The case studies again provided a rich learning opportunity, and from this many
major lessons were learned, the following section discusses the major lessons
being: (1) a need to integrate company strategy into idea generation, (2) the
structure of idea management, (3) process dependence and (4) the need for an
idea manager.
In all three of the case studies, this researcher used the structure of the
Glassman Model to recommend changes to the companies’ idea generation
process. But the specific options for each company varied based holy on their
strategic need.
For example, CartêGraph required an idea generation process which
assisted their major strategic goal of forcing market adoption of their technology
by generating ideas which assisted in market adoption. As well, Fairbanks
Scales strategically sought large opportunity areas, and hence had to change
their strategic scope and idea generation process to follow suit. Company Alpha
also required a process to better utilize their researchers in generating ideas.
All cases demonstrated that the idea generation process relies heavily on
company strategy. This is logical considering that the process can output a great
range of ideas. In-order to focus its’ output, the company strategy must be well
known and used to select the specific options for the idea generation process.
This lesson highlights a major weakness in the Glassman model which
must be addressed. The Glassman model does not contain the factors needed to
align the idea generation process with a company strategy. Hence, the model
must be appended to include activities for strategic alignment such as: 1)
reviewing the company strategy, 2) determining major areas which ideas should
be generated for based on the strategy, 3) confirming these areas, and 4)
aligning the process. Two examples will be used to explain these activities.
In the CartêGraph case study, this researcher was told the major strategic
goal was to gain market share, from their currently paltry 1%. Given the state of
their market it was obvious that they needed to force adoption of their
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technology. This contradicted their request to generate incremental ideas for their
current customer base. Consequently, this researcher recommended that they
shift toward generating ideas to aid market adoption and forgo generating idea
for their current customer base.
On the other hand, Fairbanks Scales strategy was to grow in scales, but in
confirming these areas (step 3) it was convincingly determined that the “scale”
concept would not provide adequate opportunity to generate the needed growth.
Consequently, this researcher recommended that broaden their company
strategy (step 1), and use this researcher’s suggested areas to generate idea
(step 2). In all, it is believed that the mentioned factors and activities can be
easily integrated to improve the Glassman model.
5.6.1. Structure of Idea Management
In reviewing the case studies, it was determined that the structure of the idea
management process did not depend upon company strategy, but rather it
depended upon the number of captured ideas.
One can imagine the idea management process as a logistical process
much like a post office, where ideas/packages are: captured, tagged, stored,
categorized/sorted and diffused/delivered to the appropriate people. In this view,
the particular options for each activity depend holy upon the number of ideas
going through the process.
For example, Fairbanks Scales which only required a few ideas could
feasible perform an idea management process conducted mostly on paper;
whereas, Company Alpha which received many thousands of ideas required an
elaborate idea management software system.
From this conclusion it should also be noted, that companies which
capture large numbers of ideas most likely will need an idea management
software to conduct this process effectively. This is because a paper system, or
email system cannot feasibly deal with a large number of ideas.
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5.6.2. Situational Dependence on Idea Generation or Idea Management
Fairbanks Scales had a highly evolved set of idea capture activities which tapped
every available source of ideas known to the company. This was a direct result of
a stalled internal idea generation process. Conversely, Company Alpha captured
very few ideas from outside sources and relied entirely on their R&D staff to
generate ideas. Both these cases highlight that a company can become
dependent upon either idea generation or capturing idea via idea management.
Nonetheless, this researcher believes that both processes can be fruitfully
utilized together regardless of the company situation.
5.6.3. Assigned Idea Manager
In all of the case, this researcher recommended an owner/manager of the idea
generation and idea management process. It is believed that having and single
or set of individuals responsible for obtaining ideas imparts needed internal
accountability on getting ideas into the pipeline. As noted by the literature, the
lack of clarity of this process and lack of accountability was responsible for many
problems. Given the proposed Glassman model and the review of material
presented in this dissertation, it is very reasonable that a manager could learn to
effectively manage these processes and be accountable for their results.
5.6.4. Expertise is Needed
Although the above information supports that the model contains the factors
needed to manage both processes, it was found that some expertise is required
to use this model to manage these processes. In particular, an innovation
practitioner requires the expertise to knowledgeably select amongst the options
presented for each point of control. For example, the selection of the appropriate
idea generation activity for Fairbank’s Scales required a general understanding of
all activities and the output for each activity. Only then could an innovation
practitioner effectively select the appropriate idea generation activities.
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5.7. Survey: Method of Cleaning the Data and Analysis
Several actions were taken to prepare the survey data for analysis. The first was
scanning the data to remove incomplete surveys. The survey had a completion
rate of 60%; however, this would have been higher if the survey links were not
put on online forums. Interestingly, an 85% completion rate was associated with
individuals who were invited to take the survey after watching this researcher’s
online presentation. Surveys which were 85% complete were left in the data set.
Next, the reliability of the data was checked for all the dependent
satisfaction variables and found to have a Cronbach Alpha of 0.91, the reliability
for the activity variables were found to have a Cronbach Alpha of 0.91.
All variables were measured on a single item scale so individual measures
of Cronbach could not be computed. Although this may reduce reliability, many of
the questions were thought to be so straight forward that repeating them would
annoy respondents, as well as, lengthen the survey time to an unreasonable 50 +
mins. The average time to complete this survey was 25 minutes with some
individuals taking up to 40 minutes. Nonetheless, the correlations in the following
section show some strong evidence of reliable data.
Next the respondent groups were compared amongst themselves using
Cronbach Alpha and some of the uncovered correlations. It was noted that
respondents who identified themselves solely as “support”, “researcher”, or
“advisors” introduced substantial error into the data set and greatly offset all of
the correlations, hence these groups were removed. If an individual selected any
of the following roles they were kept: project manager, division manager, R&D
manager, VP of R&D. Keep in mind an individual could be a “R&D manager” and
a “researcher” in which case their response was kept. This left 40 respondents
from the total sample of 60 completed surveys.
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It was determined that management responsibilities produced more
reliable responses than those individuals which were solely “support”,
“researcher”, or “advisors.” This is obviously due to the higher amount of
exposure and familiarity management has with the process when compared to a
line worker (like researchers, advisors, or support) who may be only exposed to
small parts of the process.
Unless otherwise noted all correlations in the following section were
found to have two tailed significances to 0.001, with the critical value for N=40
being 0.393. In most cases, the correlation R squared value was even above the
critical value of 0.393.
These author only considered correlations, of 0.6 or greater to be of
interest because, 1) 40 responses is a very small sample population of the
millions of businesses in existences, 2) this researcher wanted to avoid making
weak correlations which could lead to faulty conclusions, 3) many correlation
existed in the data between 0.4 to 0.6 and rationalizing each of these for such a
small sample size would be to cumbersome and most-likely unfruitful. This
researcher considered a correlation of 0.8 or above to be very strong, 0.64 to
0.8 to be strong, and 0.6 to 0.64 to be moderate.
A Pearson’s correlation calculation was used for all correlations.
Satisfaction items were converted to ordinal scales as shown in figure 5.2 and
denoted by a number followed by an S as such “#S.” Questions about the
frequency, amounts, or degree of an activity were converted to ordinal scales as
shown in figure 5.2 and denoted by a number preceded by a V as such “V#.”
Figure 5.2. Conversion of Answers from Likert to Ordinal Scales
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Please note many of the correlation sum one or more factors, this is a
simple procedure. For example, if a particular respondent answers “sometimes”
or 3 for V45 and “always” or 5 for V46, then the sum is 9. This calculation is then
computed for all respondents, and the resulting 1x40 matrix can be used in a
simple Pearson’s Correlation.
5.8. Survey: General Demographic Statistics for the Sample
The following section presents the demographics of the respondents who were
kept in the survey for analysis. IRB dictated that all companies and respondents
names be de-identified.
The respondent companies range greatly across several industries,
revenue size, employee size, but the vast majority seem to be located in the US,
with a majority in Ohio (see Figure 5.5). Figure 5.3 shows the distribution for the
respondents amongst their respective industries. Software and chemical seem to
have a large number, but the software & chemical companies varied greatly
within the sub-industry, hence, a very even distribution of company industries
was sampled.
Figure 5.4 shows respondent companies by both revenues and by number
of employees. The sample seems to bias larger revenue companies; whereas,
the number of employees seems to be bias toward companies larger than 501
and between 101-300 employees. Thus, this sample’s results should be strongly
applicable to large to mid size companies measured by number of employee and
revenues; however, it is unclear how applicable the results of the survey would
be to companies with less than 500K in revenue.
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Figure 5.3. Distribution of Respondents’ Companies amongst their Respective
Industries
Figure 5.4. Distribution of Respondent’s Companies by Revenues and Number of
Employees
Respondents' Industry Distribution N=40
1 1
6
1 1 1 12
12
1 1 1 1 1 1 1 1
6
21 1 1
2
01234567
Academic/university
Business Consulting
Chemicals
Consulting
Electronics
Energy
Finance
Healthcare
HVAC
Industrial Equipment
ITLaboratory Equipem
ent
Life Sciences
Manufacturing (Autom
otive, Aviation, Heavy Duty Construction eqpt.)
Marine
Office Products
Pow
er Generation
Publishing
Software
Software Consulting
Software Vendor
Telecom
Think Tank
Travel
Number of c
ompan
ies
sampled in
that in
dustry
Respondent Company Organized Revenues
1
2
3
4
5
6
7
8
0 2 4 6 8 10
less than $100K
$100K to $500K
$500K to $1M
$1M to $50 M
$50M to $500M
$500M to $1B
$1B to $5B
$5B +
# of Respondents
Respondent Company Organized # of Employees
5
4
1
9
2
4
3
9
0 2 4 6 8 10
1-20"
21-50
51-100
101-300
301-500
501-1000
1001-5000
5001+
# of Respondents
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Figure 5.5. Distribution of Respondent’s Companies by Locations
Aside from companies, the respondents were also analyzed on their
project responsibilities, company roles, and years of experience in that company.
Figure 5.6 shows the respondents organized by their roles, again the sample is
purposefully bias toward management.
Out of the respondents, 1 respondent managed one project, 24 managed
two or more projects, 14 managed one division, and 16 managed the whole
company (see appendix D). This again shows a purposeful bias toward
management responsibilities.
The average years of experience within their current company for
respondents were 6.03 years, with a standard deviation of 5.73 years, with one
respondent having 28 years experience. On the low end seven respondents had
2 years experience and six had 1 year of experience. Keep in mind this has no
relation to the actual years of experiences of the respondents.
Distribution of Respondents Country & States
21 1 1 1 1 1
32
3 3
7
1 1 1 1
3
1 1 1 12
1 1
012345678
Califorina
Idaho
Illinois
Iowa
Maryland
Massachusetts
Michigan
Missouri
New
Jersey
New
York
North Carolina
Ohio
Oregan
Texas
Virginia
Pennsylvania
UK
Spain
Norway
Italy
India
France
China
CanadaNumber of Compan
ies
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Figure 5.6. Respondents Organized by their Roles
5.8.1. Sample’s Relation to the Greater Population
No statistical tests have been conducted to determine this samples relation to the
greater population. Because the survey was promoted in conjunction with a web-
seminar on idea generation and idea management, it is thought that the vast
majority of the respondents were interested in this topic which may be due to: (1)
a need they see in their company for improvement in these areas, or (2) a
general interest in these subjects. Product development managers are typically
fairly busy and it is thought the first explanation may be the main reason for
taking this survey.
Hence, it is thought that the sample is bias toward respondents who see a
need for improvement in these given areas for their companies. However,
question 21S shows a normal distribution of satisfaction for respondents with
their overall idea generation process, suggesting no bias. But questions 51S to
56S suggest that respondents are more dissatisfied with their idea management
processes. Question V132 shows 85% of respondents are interested in learning
Respondent Roles for N = 40
1615
98 8
6 65
43 3 3
2
0 0 00
2
4
6
8
10
12
14
16
18
Project Manager
R&D manager
Advisor
Researcher
Chief Innovation Officer
VP of R&D
Consultant
Division Manager
Engineer
Developer
Supervisor
Assistance
Support
No Role
Technician
Minimal Role
Num
ber of Respondent w
ho selected that role
Note a respondents can select more than one Role. Also,respondents who solely selected "assistance", "support", or "Research" were removed from the data set.
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more about this topic. This researcher is unsure if this sample is representative of
the greater populations, and would lean toward it representing individuals who
see a need for improvement in these areas in their companies and have a
general interest in this subject area.
5.9. Survey: Correlations between Satisfaction Variables
It would be helpful to start the discussion of the data obtained from the survey
with an analysis and discussion of the satisfaction variables. In this section the
dependent satisfaction variables were compared with each other to see if any
logical correlations could be developed. Figure 5.7 below shows that out of the
sixteen variables only one (61S) could not be correlated with the others.
Figure 5.7. Correlations of the Satisfaction Variables
5.9.1. Idea Generation
The first most important correlation found in this group was the correlation that
49S (Overall Satisfaction with the Idea Generation process) had with the sum of
factors 44S, 45S, 46S, 48S, 54S, shown in Figure 5.8.
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The correlation in Figure 5.8 was found to have a Pearson 0.833
significant to 0.01, and is of extreme interest because it encompasses 70% of the
variation in an individual’s overall satisfaction with their companies idea
generation process.
Figure 5.8. Correlation for Overall Satisfactions with the Idea Generation Process
This is a logical correlation because the quality, number of ideas, time to
generate ideas, and ability to generate a specific set of ideas are in sum the
major outcomes of the idea generation activities and should obviously be tightly
correlated with overall satisfaction with the idea generation process. The factors
of 54 (quality and amount of ideas in the idea bank) and 48 (the ability of idea
generation process to fill the front end portfolio) are also the result of the output
of idea generation process, and should also be tightly correlated with overall
satisfaction.
The true importance of this correlation is that a consultant can use a single
question (What is your overall satisfaction with your company’s idea generation
process?) to fairly accurately gauge an individual’s sum satisfaction with
important outputs of their company’s idea generation process.
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Figure 5.9. Correlation of V48 Ability to Fill Front End Portfolio
Figure 5.9 shows the correlation between the satisfaction of 48S (ability of
your company’s idea generation process to fill the front end portfolio needs) and
56S (the ability of your company’s idea bank to fill the front end portfolio’s needs)
to be 0.678 significant to 0.01. A high correlation is logical given they both relate
to the front end portfolio needs. The variation can be primarily attributed to the
difference between the “ideas” created from the idea generation process and the
“ideas” located in the idea bank (which also included ideas captured from outside
sources).
5.9.2. Idea Capture
Another impressive relationship is the strong 0.728 Pearson correlation between
51S (the satisfaction with the company’s ability to capture ideas from employees
at all levels) and the sum of (53S the company’s ability to store and organize
captured ideas, and 55S the company’s ability to distribute or route ideas across
the company), show in figure 5.10. The following hypothesis is offered to explain
this relationship.
As shown in the initial version of Glassman’s model (Figure 3.16),
capturing ideas comes before storing, organizing, and distributing ideas, yet they
are all connected in a continuous linear process. If any one part of the process
(capture, storing, organizing, or distributing) is inefficient, obviously the whole
idea management process will be inefficient. This is further back by all three
variables having strong correlations between each other of 0.61 or greater.
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This correlation can be used as supporting evidence for this researcher’s
idea management process as being linear.
Figure 5.10. Correlation of 51S Ability to Capture Ideas from Employees
The next correlation, which seems to be less useful, relates satisfaction
variable 52S (company’s ability to capture ideas from outsides sources) to the
sum of 49S (overall satisfaction) and 54S (quality and amount of ideas in the idea
bank), shown in figure 5.11. This moderate correlation (R2 = 36%) is less obvious
and may be rationalize by an innovation director being satisfied with ideas in his
idea bank, and thus being satisfied with his idea generation process and by their
ability to capture ideas from outside sources. Remember some confusion still
exists in the term “idea generation process” where many innovation practitioners
also take it to include many activities in idea management like “capturing ideas.”
Figure 5.11. Correlations of 52S Ability to Capture Ideas from Outside Sources
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5.9.3. Development Outcomes
Satisfaction variables dealing with development outcomes (58S, 59S, 60S) were
compared and found to have a strong correlation as shown in Figure 5.12. This is
an obvious correlation and just verifies that the survey is acting correctly. The
variation in this correlation can be attributed to the difference between comparing
a ratio and the ability to convert a single idea.
Figure 5.12. Correlation of Dependent Development Variables
Interestingly two unexpected correlations were noted as shown in figure
5.13. Given these correlations are moderate ones, one explanation is that an
innovation director is more satisfied with their development department’s use of
resources when they see their department can create a number of quality ideas
with these given resources.
Figure 5.13. Correlations with Company Resources
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5.10. Survey: Discussion of Correlations Between Satisfaction Variables and
Measures of Activities
The following section will discuss the correlations found between the dependent
satisfaction variables and the independent activity variables. The section will be
arranged by the descending order of activities as shown in the author’s proposed
model.
Figure 5.14. Correlations of Activities to Quality of Ideas Generated
The strongest and most significant correlation uncovered in this study is
0.851 Pearson R correlation shown in figure 5.14. The sum of the variables in the
left side of this correlation can be thought of as the “quality of the output from the
idea generation process.” A high quality idea generation process produces large
numbers of quality ideas for a specific purpose. Obviously, high quality ideas are
going to be stored in the idea bank as shown by 54S in the left side of Figure
5.14.
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The right side of this correlation shows several things. First it shows that
selection of creative people (which equate to selection of the source in
Glassman’s model) is an important factor in generating a quality output. Alone
V73 (selection of creative people) had the highest correlation (0.61 moderate)
with 47S (time to generation ideas). Again, this supports the author’s model.
Next, having, hosting, and managing events are very important in
generating a quality output. Alone V75 (actively holding events) had a 0.67
(strong) correlation with quality of ideas (44S) and a 0.6 (moderate) correlation
with (49S) overall satisfaction with the idea generation process, and a 0.59
correlation for both V45 & V47. This shows the importance of having formal
events to generate ideas. Actively managing these events V76 had a moderate
0.45 to 0.48 individual correlation with factors 44S, 45S, 47S, and a high
correlation (0.58) with 54S the amount and quality of idea in the idea bank.
The idea generation activities V80, V81, V82 together showed the highest
correlations to satisfaction variables 44S, 45S, 46S, 47S, 54S. What this says is
that selecting, managing, and providing tools & resources for idea generation
activities is the most important thing one can do to generate a number of quality
ideas. This is logical considering that these activities are the ones which actually
create the ideas. All 12 internal correlations between these variables had
correlations above 0.49 with the average being 0.6.
Out of this group V81 had the highest correlation to 45S of 0.75. This says
that managing the idea generation activities accounts is require to obtain a
satisfactory number of ideas (accounts for R2=56% of the outcome).
The importance of selecting, managing, and providing tools for idea
generation activities cannot be understated and should be central in ones efforts
to generating a number of qualities of ideas quickly.
Together the variables on the right of figure 5.14 have a strong 0.695
correlations with (49S) the overall satisfaction with the idea generation process.
This greatly supports that these activities are vital additions to Glassman’s
proposed model.
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Figure 5.15. Correlation 0.851 Comparison with Model
The right hand side of Figure 5.14 shows that those activities are highly
interrelated. Thankfully, this strongly supports the author’s proposed model for
idea generation shown in Figure 5.15 as having these activities occurring in an
interrelated linear process. Again, the linear process is the only one which makes
sense as discussed in Chapter 3, development of a control model.
Unfortunately, several points of control shown in Figure 5.15 were not
tested for in the survey due to length requirements. Interestingly, providing
incentives for events showed no notable correlations, but providing a general
incentive for submitting ideas created a 0.53 correlation with 44S (satisfaction
with quality of ideas), and a weak 0.48 correlation with 45S (satisfaction with
number of ideas). This provides weak support, but support Nonetheless for
incentives in Glassman’s proposed model.
Amazingly, screening in Glassman’s model showed no notable
correlations with the variable on the left of Figure 5.15. Later in this section, one
will see that screening plays an important role in idea management. Hence, one
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can tentatively conclude that screening activities must be removed from idea
generation and placed in the idea management part of Glassman’s proposed
model.
Satisfaction with the ability of their company's idea generation process to
fill the front end portfolio's needs (48S) at best had a weak correlation 0.58 with
V75 the degree to which one actively holds events. The low correlations that
(48S) has to other satisfaction variables is weird and un-explained considering in
figure 5.9 it helps the correlation with overall satisfaction.
Again the resulting correlations developed from the survey, show strong
support for the points of control proposed in the author’s idea generation model.
5.10.1. Correlations for the Idea Management Process
5.10.1.1. Capturing and Screening Ideas
The next set of correlations are those dealing with the activities described under
idea management, starting with capturing of ideas from employees.
Figure 5.16. Weak Correlation for Capturing Ideas from Employees
It was thought that 51S, satisfaction with capturing ideas from employees,
would have correlated strongly with V88, the degree by which their company
accepts ideas submitted from, or by observing employees, see Figure 5.16. In
reviewing the data it was found that several activities combined together created
a very strong correlation with 51S, as shown in Figure 5.17.
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The correlation shown in Figure 5.17 displays a strong relationship
between 51S and the ten activities on the right which were clumped into similar
groups. The screening activities all had individual correlations of 0.5 with V85
having a 0.55 correlation with 51S. This says, that screening is important part of
capturing ideas from employees.
Next, the capturing activities, V88, V98, V104, V105, had correlations of
0.433, 0.59, 0.56, 0.60 with 51S, respectively. It was interesting that V98
(capturing ideas from media) correlated with 51S. Consider this, the only ways
ideas are captured from magazines or media source are if employees read or
watch them, then submit the ideas. Given this, one can deduce that to be better
at capturing ideas from media sources, they must be effective at capturing idea
from employees.
Figure 5.17. Strong Correlation for Capturing Ideas from Employees
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Interestingly, V105 (actively managing capture from outsides sources)
increased satisfaction with capturing ideas from employees. This may be
because companies which are effective at capturing ideas from employees are
also effective at capturing ideas from outside sources? Or this may be because,
the respondents considered many of the ideas captured from outsides sources
(like media sources) to be observed and submitted by employees. Nonetheless,
the strength of this correlation (0.60) suggests that companies should also
actively manage the capture of ideas from outsides sources in their efforts to
capture ideas from employees.
Finally, idea management activities being V114 (actively managing the
system for storing ideas), V115 (degree of formality of this system), and V116
(use of idea management software) have individual correlations with 51S of 0.58,
0.51, 0.64, respectively. Obviously, actively managing the system for storing
ideas is important. But it was surprising for V115 that a more formal system for
capturing ideas increased satisfaction. During the case studies, this researcher
learned that employees (especially at large companies) are often confused about
how to submit ideas, so clearly having a more formal system reduces this
confusion. In hindsight this is logical because the more formal the system is the
more employees would be aware, and knowledgeable in how to submit ideas.
As was mentioned in the conclusions of the case studies, the idea
management process is highly logistical and idea management software are
ideal for dealing with high volumes of ideas, and the strong 0.64 correlation
shows this. As well, idea management software are really tailored toward
capturing ideas from employees.
Most importantly, the strong correlations in figure 5.17 provide support for
the importance of the management activities described in Glassman’s model for
idea management. In particular the activities of: screening, capturing, storing,
and organizing ideas were shown to be interdependent. As mentioned in chapter
3, only a linear process makes sense for these activities.
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Figure 5.18. Correlation for Capturing Ideas from Outsides Sources
Figure 5.18 shows a very strong correlation for capturing ideas from
outside sources relating to the sum of the five variable V123, V125, V126, V127,
V128, having individual correlations of 0.62, 0.58, 0.63, 0.66, 0.71 with 52S,
respectively. This correlation validity is further backed by the correlations shown
in Figure 5.10.
It seems that refining the process using outputted ideas, is important in the
satisfaction with capturing ideas from outside source, this can be due to
companies needing to adjust the selection and method of capturing ideas from
outsides sources to optimize the process.
Interestingly, diffusion is vitally important in satisfaction with capturing
ideas from outsides sources. One idea for its importance is the innovation
director’s satisfaction when employees receive and proposed ideas from outside
sources. Obviously, employees would mainly receive ideas from the idea bank or
be routed the ideas. In fact, routing ideas had the highest individual correlation of
0.71 with 52S.
Another thought for its importance is because the innovation director, or
product development managers mainly see the end results of capturing ideas
from outside sources being the diffusion activities, and they attributed much
satisfaction to the quality of those visible activities, placing less weight on the
screening, capturing, and storing activities.
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Yet another explanation for this correlation may be this. In some
companies employees are responsible for capturing ideas from outsides sources,
and if they notice that higher quality ideas in the idea bank are coming from
outside sources they may be more inclined to tap those outside sources for ideas
in the future.
Regardless of these correlations, this researcher still feels that capturing
ideas from outside sources is only efficient when the whole idea management
process is effective. Further this researcher feels that variable 52S “satisfaction
with capturing ideas from outsides sources” as measured does not reflect
accurately the actual effectiveness of capturing ideas from outsides sources.
5.10.1.2. Tagging Ideas
Moving on, one correlation was found for tagging ideas of 51S (satisfaction with
capturing ideas from employees) and V107 (who submitted the idea) of 0.465.
Obviously innovation directors are going to be satisfied with capturing ideas from
employees when they no who submitted them. The fact that no other tagging
activities had correlation should not detract from the importance of this activity.
Again, when new practices are recommended they are usually not practiced and
this was very much the fact with tagging (see Section 5.12.2 for details on
tagging).
Very few companies practiced recording tag info other than who created
an idea. So it is no surprise that there was no correlation found for the tagging
activities. Nonetheless, this researcher still feels that tagging is a vital and easy
to perform activity, which gains great importance as process checks are
conducted.
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5.10.1.3. Storing & Categorizing Ideas
Figure 5.19. Correlation for Storing and Capturing Ideas
There were substantial correlations found for storing of ideas in figures
5.15. Outside of that, figure 5.19 shows a moderate correlation between 53S and
V114 and V122. Alone, V114 correlated to 53S with a 0.61 Pearson which can
be obviously explained by increase quality associated with increase management
activity. Interestingly, there was no notable correlation found between 53S and
V115 degree of formality of this system. This researcher thought there would be
a strong correlation, but in review this lack of correlation may be due to small
companies not needing a formal system for storage. A weak 0.5 correlation was
found for this correlation using only large companies (more than 500 employees),
thus this researcher is unsure how formality alone affects satisfaction with storing
and categorizing ideas.
5.10.1.4. Process Check Activities
Process check was found to be important in figure 5.19 as well, in figure
5.20 below. The rational for this correlation was already mentioned to be due to a
innovation director needing to review the ideas to see which outside sources are
producing ideas.
Figure 5.20. Correlation for Process Improvement
53S. Satisfaction with Storing & Categorizing Ideas V122. How often does your company
refine the idea generation process?
V114. To what degree does your company actively manage the system for storing ideas?
Pearson 0.648
R2=0.41
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5.10.1.5. Diffusion Activities
Satisfaction with diffusion was correlated to activities shown in table 5.7. Out of
these the V114 (degree to which a company actively manages the system for
storing ideas) had a weak 0.493 correlation, saying that 25% of the satisfaction is
due to this activity. Amazingly, all diffusion activities had poor or no correlations
with 55S; therefore, this result cannot be explained. Again Figure 5.18 shows the
diffusion activities related to satisfaction with capturing ideas from outsides
sources.
Otherwise, V127 (exposing employees to ideas from the idea bank)
showed the highest but weak correlation with 56S. Rationalizing this, one would
say that more new product projects can be made if employees are exposed more
to ideas from the idea bank.
The weak correlation developed for diffusion activities, except for that of
Figure 5.18, seem to understate the importance of these activities. Again, idea
management is a linear process and it makes very little sense to be efficient in
the rest of the process yet be poor in diffusion. As well, the literature review on
diffusion in this dissertation stresses the importance of these activities.
There seems to be some weak correlation between 54S (quality and
amount of ideas in idea bank) and V126 (staff referring to idea bank), V127
(exposing employees to ideas from idea bank), and V128 (routing ideas to
employees), as shown in Table 5.7. Again, the more employees are exposed to
ideas the higher the chance that ideas are created serendipitously. As well, many
idea generation activities (like IDEO process) recommends that employees to
review the idea bank prior to participating in idea generation activities. Hence,
these correlations follow predicted logic.
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Table 5.7. Correlation for Diffusion Activities
54S. The amount, quality, type of ideas in your company s idea bank or idea pool?
55S. How satisfied are you with your company s ability to distribute or route ideas across the organization?
56S. The ability of your company's idea bank to fill the front end portfolio's needs?
V114To what degree does your company actively manage the system for storing ideas? 0.400 0.493 0.351
V122How often does your company refine the idea generation process? 0.402 0.426 0.418
V123
How much does your company use the outputted ideas to refine the idea generation process? 0.382 0.188 0.349
V125
How frequently does your company’s employees search the idea bank when they need new ideas? 0.280 0.357 0.381
V126
How frequently does your product development staff refer to or search the idea bank during idea gene... 0.422 0.208 0.432
V127
To what degree does your company actively expose its’ employees to ideas from the idea bank? 0.519 0.354 0.523
V128
To what degree does your company actively route particular newly submitted ideas to the employees wh... 0.547 0.287 0.412
5.10.1.6. Development Activities
As an additional measure the survey tested satisfaction with respect to four
development activities. Out of these only one 60S (satisfaction with their
company’s ability to convert an idea into a marketable product) was found to
have a moderate correlation of 0.6 to V126 (a diffusion activity) as shown in
figure 5.21. It does not make sense that later development activities are
improved by referring to the idea bank. Instead, one can hypothesize those
employees which refer to the idea bank more, purposefully create ideas that are
more in line with the needs of the company and create ideas which have higher
chance making it to market launch. The other two correlations shown in figure
5.21 support this thought.
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Figure 5.21. Correlation for Development Activities
5.10.1.7. Idea Management Software
Idea management software is an upcoming tool to aid idea management, and
again, this researcher’s case studies concluded that idea management software
is almost necessary for companies with large number of employees. Table 5.8,
shows the correlation that the use of idea generation has to levels of satisfaction.
Table 5.8. Correlations for Idea Management Software
51S
How satisfied are you with:Your company s ability to capture ideas from employees at all levels? 0.643 strong correlation
52S
Your company s ability to capture ideas from outside sources like competitors, suppliers, consultant... 0.389 No correlation
53SYour company’s ability to store and organize captured ideas? 0.293 No correlation
54SThe amount, quality, type of ideas in your company s idea bank or idea pool? 0.268 No correlation
55SYour company s ability to distribute or route ideas across the organization? 0.203 No correlation
58S
How satisfied are you with: The development outcomes of ideas that enter into your pipeline? 0.105 No correlation
49SOverall idea generation process of your company? 0.092 No correlation
60SYour company s ability to convert an idea into a marketable product or service? 0.084 No correlation
56SThe ability of your company's idea bank to fill the front end portfolio's needs? 0.047 No correlation
61S
Your company s ability to use resources during development in an effective manner? -0.013 No correlation
59S
The ratio of ideas that make it through to market launch? -0.025 No correlation
V116. To what degree does your company: Use Idea management software for storage?
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Again, Idea management software’s main goal is to capture ideas from
employees and hence that correlation 0.643 supports that point.
Interestingly, the use of idea management software did not correlate with
any other activities. Now, this is by no means conclusive, because idea
management software is evolving greatly in effectiveness and functionality, even
over the last year (2008). It is totally reasonable not to see any correlations with
idea management software until they gain wider market acceptance, and have a
common level of functionality. Keep in mind not all idea management software
have the same functionality, some companies even used Microsoft SharePoint
which is a knowledge management program, and claim it to be their idea
management software, which in reality it is not! From this one can conclude that
the correlations in table 5.8 can be deemed totally inaccurate for future
reference.
This researcher sees much potential in the use of idea management
software to formalize and stream line the idea management process. But again,
one should understand the process before using a tool to manage it.
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5.11. Survey: Discussion of Support for Proposed Model
Table 5.9. Support Found for the Author’s Proposed Model
Level of Support Figures or Table location of supporting correlation
Supporting Activity Question
Screening ideasMethod of screening (input) Strong 5.15 84Attributes of the screen (input) Strong 5.15 85Execution of screening (process) Strong 5.15 86
Capturing IdeasMethod of Capture (input) Strong 5.15 116Sources of Capture (input) Strong 5.15 88,98,104Execution of capture (process) Strong 5.15 105
Tagging Method of Tagging (input) Not Tested for in surveyAttribute of the Tag (input) Weak 107Execution of Tagging (process) Weak 107
Storage and CategorizationMethod of Storage & Categorization (input) Strong 5.15 115, 116Execution of Storage & Categorization (process) Strong 5.15 114
Process Check Methods of Process Check (input) Strong 5.16, Table 5.7 122, 123People performing the Process Check (input) Not Tested for in surveyExecution of Process Check (process) Strong 5.17 122, 123
Diffusion Methods of Diffusion & Routing (input) Strong 5.16, Table 5.7 127People executing diffusion & routing (input) Not Tested for in surveyExecution of Diffusion & Routing Strong 5.16, Table 5.7 125,126,127,128
Support found for points of control in the author's proposed I-Gen model (Idea Management part of model only)
Table 5.9 compiles the support for the points of control in Glassman’s
model. One can see that all points of control but the tagging had strong support.
To reiterate, this researcher feels that the lack of proper tagging is a systemic
error in the practices of companies that will be remedied when these companies
start doing detailed process checks.
One can also see in table 5.9 that several points of control were not tested
in the survey. This was done because these questions were either too redundant
to ask, not important enough to be asked, or could not be formulated. Methods of
tagging seem not important enough to ask because it was based on the way
which idea were recorded. It was difficult to formulate a question regarding the
“people performing the process check” and “people performing diffusion or
routing” because this researcher was unclear if he wanted frequency, selection,
or the role of these individuals.
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In all the supporting correlations discussed in this section lend great
validity to the authors proposed idea management model. Combining this with
the support for the points of control listed in figure 5.15, the combined model of
idea generation and idea management is well supported.
5.12. Survey: Discussion of Normative Results
The results for all of the questions of the survey were summarized in graphic
form and are displayed in Appendix D, so please refer to it often while reading
this section.
For the satisfaction questions a higher “mean” resulted in higher
dissatisfaction and for the activity questions a higher “mean” resulted in higher
frequency, of amount of that activity occurring. Very few of the questions had
normal distribution of answers (44S, 47S, 54S, V115), the bulk of the questions
were double humped or skewed left or right with a few having flat distributions.
For the sake of brevity, the most interesting findings will be discussed below.
5.12.1. Normative Results for Satisfaction Questions
Out of all the questions dealing with satisfaction with idea generation outputs only
questions 46S had a high skew where 49% of the respondents were satisfied
with their company’s ability to generate a set of ideas with a specific set of
attributes. Most of the questions had slight double distributions with only 45S,
46S having right skews towards being more satisfied.
Three of the questions for dealing with satisfaction with idea
management’s outputs produced interesting results. Question 52S showed that
51% were satisfied or very satisfied with capturing ideas from outside sources.
Yet the activity questions V63-V72, & V87-V97, shows that most companies did a
poor job of tapping a variety of outside sources for ideas. One may hypothesize
that (1) respondents only need to tap a small number of sources to be satisfied,
or *2) respondents are not aware of the number of outside sources and outside
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ideas they are missing, and thus are content. The second hypotheses would also
explain why the activities associated with capturing ideas from outsides sources
are missing Figure 5.18.
Question 53S shows a hard skew to the left with 48% dissatisfied and
53% very dissatisfied or dissatisfied with their company’s ability to store and
organize captured ideas. Obviously, the respondents in this sample have a
systemic problem with storing and organizing ideas.
Question 55S shows a light skew to the left with 43% being very
dissatisfied or dissatisfied with their companies’ ability to distribute or route ideas
across the company. This may be part of the reason why no strong correlations
were found (outside of Figure 5.18) with diffusion activities.
Question 58S showed that 51% of respondents were satisfied or very
satisfied with the development outcomes of the ideas that enter their pipeline.
This shows that the sample is from companies which, on the majority, are
effective at developing products.
5.12.2. Normative Results for Activity Questions
Moving on to activities, question V75 showed that the bulk of the respondents
(79%) did not frequently hold events to generate ideas, where only 4
respondents (10%) always held events to generate ideas, and to that questions
V76 showed that 61% of the respondents undermanaged these events.
Not hosting and managing events is a systemic problem in this sample,
and should be improved upon because the correlations in Figures 5.12, showed
that holding and managing events is vital factor in generation a number of quality
ideas.
Another systemic problem was found in V77 and V78 in the lack of
incentives across all respondents. It seems companies go cheap, and expect
employees who often have other major responsibilities outside of generating
ideas, to take the time and generate and submit ideas. Incentive theory showed
that for employees to make something a priority they must be incentivized rightly.
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Questions V80, V81, V82 highlight that the bulk of the respondents do not
select the idea generation activities, manage them or provide adequate
resources and tools to these activities. Once more the correlation shown in
Figure 5.14 highlights that this is a major error!
Screening shown in question V84 is one of those simple activities which
every company seems to do, again this is only a minor part of the whole process.
Amazingly, there is a flat distribution in responses amongst V85 setting the
attributes for the first screen and V86 managing the first screens.
Questions V87 to V97, and V63 to V72 show that outside sources like:
customers, partners, and the media sources are often tapped for ideas; while,
universities, external research labs, suppliers, consultants, indirect competitors,
and independent inventors are much less frequently tapped for ideas. Open
innovation experts should take note of these graphs for these questions because
it lends them much support. Obviously, companies should be frequently tapping
all sources for ideas.
Question V100-V103 shows that an “individual” and “email” is the most
prevalent form of capturing ideas, followed by suggestion boxes and voice mail,
and lastly idea management software. Using an individual to capture ideas is
very acceptable as long as they are trained in how to apply the screens
appropriately.
Questions V107-V110 showed a systemic problem with tagging, that
although respondents are recording who submitted the ideas, they are failing to
record other via tag information. As mentioned, this researcher believes this will
change when more rigorous process checks are adopted, and responses in
question V122, V123 show that only 5 respondents frequently perform process
checks.
Diffusion of ideas seems to be practiced poorly amongst the respondent
companies as shown by questions V125, V126, V127. Out of these activities
routing V127 had the highest mean of 3.28 with 36% of the respondent “always”
or “most-of-the-time” routing ideas to employees. This hints at possible systemic
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problem with routing and diffusion which may be due to the lack of importance
placed on this activity in the literature. Nevertheless, the correlation in figure 5.18
and correlations in table 5.7 state the importance of diffusion activities.
5.13. Survey: Major Lessons Learned
There were several major lessons learned from conducting the survey research
study. The first and most important lesson was that most of the correlations and
normative data supported Glassman’s model for idea generation and idea
management. Once more, table 5.9 and figure 5.15 showed a summary of
support for the model. This helps to answer the second research question
further. Combined with the case studies there is substantial evidence that the
proposed model will be effective in managing and controlling the idea generation
and idea management processes.
The second major lesson was that screening activities are really
considered by respondents to be part of the idea management process. This
lesson is applied in the following chapter 5 Updated Control Models.
The third major lesson is the importance of people, events, and idea
generation activities in creating a number of quality ideas in a timely fashion. This
lesson was highlighted in detail in the discussion surrounding figure 5.14.
Unfortunately, the normative data in appendix D showed that a majority of the
respondents did not host or manage idea generation activities correctly.
The forth major lesson is how satisfaction with capturing ideas from
employees is greatly affected by the screening, capturing, and storing activities,
see the discussion surrounding figure 5.17. The fifth major lesson is how
satisfaction with capturing ideas from outside sources depended highly on
diffusion activities as shown by figures 5.18 and table 5.7.
The last major lesson was the systemic dissatisfaction with: capturing
ideas from outside sources, storing and categorizing of ideas, and diffusion and
routing of ideas, amongst the respondents. Yet again, this may hint at a larger
systemic issue with these items for the greater population.
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CHAPTER 6. UPDATED CONTROL MODELS
This very short chapter presents improvements made to the proposed Glassman
model based on lessons learned from the case studies and survey study.
Appending to this model is believed to strengthen it further, and lend it additional
creditability as being an effective means of controlling the idea generation and
idea management processes. The improvements to the model will be discussed
sequentially.
6.1. Screening Moved into Idea Management
The first improvement to this model was the movement of screening activities
into the idea management portion of the model. Section 3.28 discusses
screening in detail but fails to mention that most of the screening occurs during
the capturing of ideas, in addition, to screening occurring during idea generation.
The importance of screening as part of the idea management process was
established from the very strong correlation in Figure 5.17, in which all three acts
of screening V84 (degree to which a company does screening), V85 (setting the
attributes for the screen), and V86 (actively managing the screen) had 0.5 or
better correlations with 51S (satisfaction with capturing ideas from employees).
Screening is an activity which all respondents of the survey seemed to
understand and perform (V84), yet actively managing the screen (V86) and
setting the attributes for the first screen (V85) were not as well performed with
only 43% respondents “most-the-time” or “always” performing these activities.
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To keep an emphasize on screening activities they will be separated from
capturing activities, even though in practice they can be conducted at the same
instance. For example, an innovation director would capture an idea via a phone
call and be simultaneously screening it.
Screens can be applied before capturing, in which case it prevents certain
types of ideas from being submitted. Or screening can be practiced after
capturing in which case it prevents ideas from being stored. Out of the two
options, this researcher feels it is much worse to inhibit the capturing of ideas via
a pre-screen.
The rationality for this is simple; (1) there is very little harm in capturing a
poor idea then screening it out later, (2) it gives one the option to screen a
potentially valuable idea, and (3) it allows the employee or outside individual to
feel satisfied with their aid, and (4) it allows the screen to be malleable and post-
adjusted to allow potential great ideas (which may initially not meet the first
screen) to be captured.
The harm in having the screen before capture is (1) significant loss of
revenues and competitive advantage associated with screening out good or great
ideas, (2) it is difficult to tell if the screen is eliminating good or bad ideas, and (3)
the de-motivating effects a pre-screen would have on employee or outside
sources who would like to submit an idea.
For these reasons, screening was put after capturing in the updated
management model. Once more, individuals applying a screen should be trained
in how to apply it correctly and how to avoid de-motivate individuals while
screening ideas.
6.2. Strategic Alignment Activities
The case studies clearly demonstrated that the idea generation process requires
strategic alignment to focus its outputs; whereas, the idea management process
is purely logistical. Given this, the idea generation part of the model was
appended to include four activities designed to align the outputs of the idea
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generation process with the company’s strategic needs, and they are: (1)
reviewing the company strategy, (2) determining major areas which ideas should
be generated for based on the strategy, (3) confirming these areas, and (4)
aligning the process.
During strategic reviews companies often identify opportunity areas, areas
of strategic importance, or general areas to grow business. These strategic
initiatives are often dedicated much resources and are hopefully well thought out.
Focusing the outputs of the idea generation process toward meeting these
strategic needs is only smart. Having an idea generation process which
generates random ideas which may or may not meet strategic needs can be a
major waste of resources, and unfortunately produce great dissatisfaction with
the idea generation process.
The first activity (strategic review) should be performed by the innovation
director, VP of R&D, or chief innovation officer. Next these individuals should
determine the major areas which idea should be generated for, then these areas
should be confirmed.
The act of confirming an area can be the same as confirming an
opportunity area, but in many cases it is more high level. For example, say a
bedding company has selected bed liners to be an area to generate ideas for
because this is a major weakness of their competitors and this can be a way to
gain market share. The company would then look at that area and determine if
there is suitable room to generate ideas.
In the case of Fairbank’s Scales, one learned that their market of industrial
scales was highly mature, highly saturated, and contained limited number of new
product opportunities. Even the best idea generation activities would have had
much trouble generating ideas under these circumstances.
Interestingly, there seems to be this unspoken notion that smart
individuals or geniuses can create great ideas no matter how old or saturated the
market is, this is simply not true. This researcher has seen brilliant individuals
and even geniuses’ stall in their efforts to generate ideas for super saturated
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markets. Further, some markets just do not need new category of products, or
new functionality because the current offering, as segmented as they are, come
close to totally satisfying the needs of their customers, and short of creating a
blue ocean market nothing of real consequent can be introduce. Remember, the
purpose of a market is to satisfy the needs of that segment of customers, and
there is only so much one can do to create demand, outside of that additional
efforts would result in a waste of money.
So during the third step of confirming an area, one should take an honest
look and determine if the selected area has room to generate and introduce new
products or services. Remember, choosing incorrectly could completely stall the
idea generation process. Conversely; keep in mind that for some opportunity
areas, customers may be satisfied with the current product offerings until a new
disruptive product arrives and shows there is much room for improvement. An
example of this is the recent improvement in windshield wipers where they are
now one solid piece, and the advancement of tube televisions to LCD flat panel
televisions.
Once the areas are confirmed, the idea generation process can then be
aligned and adapted towards generating ideas for those areas. The
understanding of which areas to generate ideas for would then be used to select
amongst the many input controls to focus the process on which people, events,
idea generation activities, or screens to select. The process controls are used to
continually insure that the idea generation process is creating ideas for those
areas.
The appropriate employees must be selected for (1) reviewing the
company strategy, (2) selecting areas to generate ideas for, and (3) confirming
these areas. Most-likely a VP of R&D, innovation director, or Chief innovation
officer is appropriate for these tasks. A different set of people can be used to
perform the forth task of aligning the idea generation process. In addition, tasks 1
to 3 must be executed correctly (process control).
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6.3. Final Version of the Glassman Control Model
Idea Generation Processes (External or Internal)
Idea Management & Idea Banks (Internal)
Event
Source AKA
People
Ideas Ideas
Capture
Diffusion & Routing
Opportunity
Process Check
Tagging
Idea Generation Activities
The source
The Event
Idea GenerationActivities
Capture
Tagging
Storing & categorizing
Diffusion & Routing
Process Check
Selecting the sources (input) General incentive (input)