Method for Analysis of Front-End
Technology Development Effectivity
by
Thomas P. Courtney
M.S. Mechanical Engineering
Santa Clara University
B.S. Mechanical Engineering
Rochester Institute of Technology
AT THE
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
JANUARY, 2001
@ 2001 Thomas P. Courtney, All rights reserved
The author hereby grants to MIT permission to reproduce and distribute publicly paper
and electronic copies of this thesis document in whole or in part.
Signature of Author
A
J
/Thomas P. Courtney
System Design and Maqagement, January 2001
Certified by
Cliff Whitcomb
Associate Professor Ocean Engineering
Thesis Advisor
Accepted by
Steven C. Graves
LFM/SDM Co-Director
Abraham Sieael Professor of Management
Accepted by
--
Paul A Lagace
M/SDM Co-Director
Professor of Aeronautics & Astronautics and Engineering Systems
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
AUG 0 1 2002
LIBRARIES
BARKER
This thesis presents a method for analyzing the effectivity of an organization's
fuzzy front-end processes. Several technology development frameworks were
considered as the foundation of the proposed analysis method. Don Clausing's
"An embedded process framework for Total Technology Development" was
selected as the basis for the assessment. From this framework, a behavior
driven questionnaire was developed. The interview format was selected as the
method for obtaining data from the organization. The interview format specified
and detailed questionnaire were developed to be generally applicable to any
organization. The proposed assessment method was applied to one
organization within Xerox Corp. Over 800 data points were gathered,
summarized, sorted and discussed. Xerox uses the TTM (Time to Market)
development process. The proposed assessment method focuses on assessing
the actual processes implemented within the local organization. These
processes may be different than the corporate documented TTM processes. Ten
senior managers at Xerox were interviewed. Data from the interviews was
summarized and sorted. Weaknesses and strengths of the organization were
obtained from the sorted data. Initiatives may then be developed to improve
upon the weaknesses. Strengths are highlighted and communicated to foster a
learning organization. An example is given demonstrating the use of Monte
Carlo analysis to improve upon one of the weaknesses obtained from the Xerox
assessment. Further research into web-based assessment methods is
proposed.
Author:
Advisor:
Title:
Date:
Thomas P. Courtney
Professor Cliff Whitcomb
Method for Analysis of Front-End Technology Effectivity
January 29, 2001
2
I am filled with gratitude to all those who have helped me on this invigorating journey at
MIT these past three years. Through all the ups and downs, so many people have given
so freely of their time, energy, ideas, and spirit. I am so thankful.
First, I would like to thank my dearest companion Karen for her constant love and
support. Her encouragement means so much to me. A warm hug and a loving prayer
from her gave me the enthusiasm and stamina to be the best I could be.
My SDM friends have taught me so much. Much of my learning came from each of you.
I am thrilled to have been in the presence of so many dedicated, creative, energetic,
brilliant and fun individuals.
I would like to thank my incredible parents, Lucille and Richard Courtney, for all the
lessons in life they have taught me. Their examples of dedication to excellence,
compassion for what they do, and a thirst for continuous growth has shaped me into who
I have become.
God is the source of my strength. My travels to MIT provided me much more than an
education. My travels to MIT placed people in my path that profoundly changed my life
forever.
My thanks goes out to all those who participated in the interviews. Thanks to Ken
Altfather, Bob Burkett, Bill Hawkins, Juan Becerra, Terry Coggeshall, Mel Croucher,
Mariano Freire, Louis Isganitus, and Dale Ims. Their candid discussions greatly added to
the quality of this work.
Thanks to my thesis advisor, Cliff Whitcomb. Cliff helped keep my thesis properly
focused and provided valuable advice that greatly improved the quality of this thesis.
Last, but not least, I would like to thank my children Aaron, Robert and Andrew. Your
bright smiles and witty humor helped me over many bumps in the road. I am so pleased
with the growth I have seen in each of you over these past years. Your youthful spirit and
playfulness helped me to learn how to let the youthful child inside of me come out and
play.
3
Table of Contents
Chapter 1 Introduction................................................................................................6
Background ................................
.................................................................................
6
Objectives of this Thesis.............................................................................................
6
The Problem Statement....................................................................................................7
Research M ethod ........................................................................................................
8
Term inology .....................................................................................................................
9
Chapter 2 Total Technology Development Framework
....................
11
Total Technology Development Framework Selection .............................................
11
TTD Framework Overview.........................................................................................
12
Framework Phase 1 - Technology Strategy ...............................................................
12
Framework Phase 2 - Concept Generation and Enhancement
.................
13
Framework Phase 3 - Robustness Development and Analysis .................................
14
Framework Phase 4 - Technology Selection, Transfer, and Integration.................... 15
Comparison to Xerox Time To M arket Process ........................................................
16
Chapter 3 How to Analyze Upstream Technology Development Effectivity.....24
Introduction....................................................................................................................
24
Process used to create the methodology. ...................................................................
24
Applicability to other companies...............................................................................
25
Generation of behavior driven questions ....................................................................
25
Selection of Interviewees...........................................................................................
26
How interviews were conducted................................................................................
27
Chapter 4 Data Summaries and Key Points ..........................................................
28
Introduction ....................................................................................................................
28
Discussion of Lowest scoring behaviors....................................................................
29
Discussion of Highest scoring behaviors....................................................................36
Discussion of behaviors having high standard deviations ........................................
40
Chapter 5 Application of Results.............................................................................43
Chapter 6 Conclusions and Recommendations ......................................................
57
Bibliography and References......................................................................................60
A ppend ix ..........................................................................................................................
62
Appendix 1: Phase 1 Process Steps ..........................................................................
62
Appendix 2: Phase 2 Process Steps ..........................................................................
65
Appendix 3: Phase 3 Process Steps ..........................................................................
69
Appendix 4: Phase 4 Process Steps ..........................................................................
71
Appendix 5 Source Code for Install W ater Loss M onte Carlo Analysis....................72
Appendix 6. Detailed Questionairre Responses.........................................................73
Appendix 7 Questionnaire........................................................................................
75
4
Table of Figures
Figure 1 TTD Framework ..............................................................................................
12
Figure 2 Xerox Business Model.....................................................................................
16
Figure 3 TTD Bubble Portfolio.....................................................................................
18
Figure 4 Market Strategy Allocation Model ..................................................................
19
Figure 5 Newness and Complexity vs Program Configuration..................
22
Figure 6 Total Response Distribution ...........................................................................
28
Figure 7 Market Pull vs Technology Push....................................................................
33
Figure 8 Truncated Normal Distribution.......................................................................
44
Figure 9 Quality Loss Function.....................................................................................
45
Figure 10 Monte Carlo Analysis Example....................................................................
46
Figure 11 Useful Ink Histogram. Monte Carlo Output ................................................
47
Figure 12 Factory % Water Normal Distribution..............................................................
48
Figure 13 Transport LogNormal Distribution................................................................48
Figure 14 Evaporation Rate Emperical Table Distribution............................................
48
Figure 15 Storage LogNormal Distribution ..................................................................
49
Figure 16 Rate at Environmental Storage ....................................................................
49
Figure 17 Installation Temperature Emperical Distribution .........................................
49
Figure 18 Humidity Normal Distribution.......................................................................50
Figure 19 Pages/Day LogNormal Distribution .............................................................
50
Figure 20 Sensitivity to Temperature Noise .................................................................
52
Figure 21 Sensitivity to Humidity Noise.......................................................................
53
Figure 22 Sensitivity to Pages printed per day..............................................................
54
Figure 23 Water Evaporation Rate Sensitivity..............................................................
55
5
Chapter 1
Introduction
Background
How does one prosper in this high tech world? There is great leverage in the
Front-End of the product development process. This fertile time is often called the
Technology development phase, or Advanced Development phase. (Clausing, 1998).
This thesis will refer to this process as the Fuzzy Front-End. (Khurana, 1997). This is a
time of great uncertainty. Where is the market going? Which Technologies will become
dominant in the future? Where are our competitors going? How will we make money?
How should we be organized? What is more appropriate, Technology Push or Market
pull? Several heuristics passed down over the centuries capture the importance of this
phase. "The beginning is the most important part of the work." (Plato,
4 th
Century B.C.).
"All the serious mistakes are made in the first day." (Robert Spinrad, 1988). This early
process is often confusing and chaotic. It is an artistic time. No one has the answers.
Some organizations are fortunate to have a great system's thinker.
These system's
thinkers have the uncanny ability to merge and meld a plethora of disjointed and often
confounding issues to create a set of technology elements which when integrated bring
bountiful success to the organization. Most organizations however, do not possess such
an individual. Somehow, ordinary people in ordinary organizations must navigate these
waters and take their best guesses. This thesis suggests a better way.
Objectives of this Thesis
The goal of this thesis is to develop a method for assessing the strengths and
weaknesses of an organization's implemented Front-End Technology Development
process. Carefully note the word 'implemented' in the prior sentence. Many companies
have documented processes and procedures, yet there can be significant differences
between the corporate documented processes and the processes actually implemented
within an organization. This thesis focuses on those processes actually implemented and
practiced within an organization. The process will generate a list of areas for
improvement. Once a list of weaknesses are derived using this method, the organization
can create initiates targeted at improving their actual fuzzy front end processes. Where
would one start to try to improve their actual processes? This thesis provides a
6
methodology for systematically understanding the strengths and weaknesses of an
organization's Fuzzy Front-End Technology Development process. It is NOT the
objective of this thesis to make specific prescriptions, although many prescriptive
solutions are easily inferred from the proposed method. An example showing how the
results can be used to create an initiative is given. Individuals inside or outside the
organization may use the methodology proposed. The main objective is to get focus on
the right problems. Management consultants may find this methodology extremely
beneficial to help them pinpoint dysfunctional or absent processes for their clients.
Different companies use different terminology and practices, therefore, an interview
format for data collection was selected. Details of the interview procedure are given.
Ultimately, people and organizations will use this material to make major changes within
their organizations and reap significant success in their chosen markets.
The Problem Statement
Introduction of immature technologies is a leading source of schedule uncertainty.
(Clausing, 1994). A distinct technology development phase can greatly reduce schedule
uncertainty. (Clausing, 1994). Weak technologies even induce additional problems in
product development programs. (Clausing, 1994) and (Altshuller, 1984). The lack of
technology robustness has to be fixed in elaborate rework cycles during the production
preparation phase and thus quality and time to market become uncertain. (Clausing,
1998). Cooper and Kleinschmidt's research indicated that successful projects spent twice
the amount of money and almost twice the amount in man-days in the front end than did
projects that failed. (Cooper and Kleinschmidt, 1988). Hence, there are many important
reasons for seeking improvement in the fuzzy front end. There are many issues to
consider. Technology Push or Market Pull? Technologists have a notion of what's
possible. Business planners have a notion of what will sell in the marketplace. There
should always be a comfortable tension between these two fields. Often, however, they
live in two separate worlds. Their languages are different. Their motivations are
different. Technologists want to see their latest invention incorporated because they
believe it's the best thing since sliced bread. Product planners, on the other hand, are not
impressed with under the hood wizardry. They are simply looking for features to delight
customers at or below competitor's prices. The proposed methodology seeks to discover
7
and illuminate the most important areas in need of improvement in the fuzzy front end.
How are we to spend this important time and money?
Research Method
An interview/questionnaire was developed to identify areas in need of
improvement in the fuzzy front end. The questionnaire was developed based upon the
Total Technology Development framework proposed by Clausing. (Clausing, 1998). I
will refer to Clausing's Total Technology Development process as the TTD process.
Several frameworks were considered. Other frameworks considered include Xerox's
Time to Market Process, Michael Frauens "Improved Selection of Technically attractive
projects using knowledge management and Net Interactive tools, (Fraeuns, 2000) and
Robert Wirthlin's "Best practices in user needs/requirements generation." (Wirthlin,
2000). A discussion of the selection of Clausing's TTD process is included. Interviews
were conducted with ten senior managers from one organization's division. The interview
consisted of 82 questions. Respondent's scores were collected for each question.
Subjective comments regarding each question were also recorded. Averages and
Standard Deviations were calculated for each question. (Appendix XX). The average
scores were sorted. A discussion of the lowest scored questions and highest standard
deviation questions is given in section XX. Once a list of weaknesses are derived using
this method, the organizaton can create initiates targeted at improving their actual fuzzy
front end processes.
8
Terminology
The following words or phrases show up throughout the thesis. They are given to
help to reader interpret the thesis.
System's Thinking
"A way of thinking about, and a language for describing and understanding, the
forces and interrelationships that shape the behavior of systems. This discipline helps us
see how to change systems more effectively, and to act more in tune with the larger
professes of the natural economic world." (Peter Senge, pp. 6-7).
Technology Push
Technology push can lead to great technical concepts, but they can dismally fail
to meet some important customer needs. (Clausing, 1994).
Market Pull
The opposite of Technology push is market pull. Here, there are major customer
needs and technologists attempt to deliver technologies which lack robustness, leading to
disastrous results. (Clausing, 1994).
Technology
The word Technology derives from the Greek word technologia, meaning
'systematic treatment'. (Websters, 1996) Within this thesis, technology will be defined
as:
'Technology is the structured application of scientific principles and knowledge to
enhance the functional performance of a system. It has an overall structure and
classification. A particular technology contains a body of formalized, transmittable
scientific knowledge and has distinct attributes such as specialist techniques for
investigation, measurement, and application.' (Clausing, 1998).
Technology Readiness
9
Technology Readiness is the point in time in a program when the launch schedule,
product quality and product cost can be estimated with reasonable confidence. It
represents the point in time when a corporation makes a firm commitment of resources
and money to develop and deliver a product. (Xerox TTM Process).
Total Technology Development Phase
For this thesis, this phase includes all development activities leading up to the
point of Technology Readiness.
I exclude basic research from this phase.
Independence Axiom
An acceptable design is achieved when the design parameters and functional
requirements are related in a way that a certain design parameter can be adjusted to
satisfy its corresponding requirement without affecting other functional requirements.
(Suh, 1990).
10
Chapter 2
Total Technology Development Framework
This chapter provides an overview of several frameworks that were considered for
the foundation of this thesis. The rationale for selecting the Clausing TTD framework is
discussed. The remainder of this section discusses some of the major differences
between these frameworks and Clausing's TTD framework.
New technologies are the life-blood of thriving companies. Generating and
selecting winning technologies is a very difficult process. A process is needed to
generate and assign these winning technologies to products.
The process of generating and selecting these winning technologies is a very complex
process. A.D. Wheelon stated it nicely: (Rechtin, E. Systems Architecting):
"A System is successful when the natural intersection of technology, politics, and
economics are found."
How does one deal with these layers of complexity? The primary method for dealing
with complexity is to decompose the larger problem into smaller manageable pieces.
Hence, a framework is needed to decompose these activities down to manageable pieces.
Total Technology Development Framework Selection
Several frameworks were considered as the basis of the questionnaire.
Frameworks considered include Clausing's "An embedding process framework for Total
Technology Development" (TTD), (Clausing, 1998), Xerox's Time to Market Process,
Michael Frauens "Improved Selection of Technically attractive projects using knowledge
management and Net Interactive tools, (Fraeuns, 2000) and Robert Wirthlin's "Best
practices in user needs/requirements generation." (Wirthlin, 2000). The Framework
selected is titled, "An Embedding Process Framework For Total Technology
Development," by Armin P. Schulz and Professor Don P. Clausing. They completed this
work at the Center for Innovation in Product Development at MIT during 1998.
Members from the Center for Innovation in Product Development, MIT and the Institute
of Astronautics, Technical University of Munich cooperated on this work. Professor
Clausing is the Xerox Fellow in Competitive Product Development at the Center for
11
Innovation if Product Development at MIT. This work is an enhancement of Clausing's
earlier work in his book Total Quality Development (Clausing, 1994). There are several
advantages for selecting this framework over the others:
1.
The framework is comprehensive, incorporating all-important upstream and
downstream influences.
2.
The framework identifies many tools and techniques and their applications. This
makes the framework very practical and useful.
3.
The framework is flexible. Nearly any technology can benefit from these
practices.
4.
The framework encompasses aspects of human behavior.
5.
The framework seeks to integrate the Voice of the Market with the Voice of
Technology.
6.
The concepts and tools are consistent with the training incorporated within MIT's
System Design and Management curriculum.
TTD Framework Overview
The framework is subdivided into four Phases.
Phase I
Integrated
Technology
Strategy
Phase II
Concept
Generation
and
Enhancement
Z>
Figure
Phase III
Robustness
Development
and Analysis
Phase IV
Technology
Selection,
Transfer and
Integration
1 TTD Framework
12
Framework Phase 1 - Technology Strategy
Phase 1 Overview
Phase 1 systematically builds a solid foundation upon which superior Concepts
are generated. This phase seeks to blend the Voice to the Market with the Voice of
Technology. Phase 1 activities illuminate market and technology trends. Specific tools
help translate market needs into technology parameters. This parameterization is
essential. The parameterization speaks to the technologists in a language they can more
easily understand. This phase also sheds light on the basic technology strengths that will
be required to develop the new technology. One must determine whether these strengths
are present in the company, need to be developed further, or whether outside partners
should be considered. The success of this phase depends heavily on interactions between
the technologists and business planners. (Phase 1 steps are described in Appendix 1)
Framework Phase 2 - Concept Generation and Enhancement
Phase 2 Overview
Phase 2 is comprised of 4 main themes. The first is System Decomposition. This
phase begins with the most important functional outputs determined from Phase 1.
Functions are decomposed in solution neutral space. Triz concepts are applied to select
functional solutions having high ideality. The second step is system re-integration. This
is accomplished using a design structure matrix to aggregate related functions. This is
the step where function is transformed into the form of potential solutions. The third step
is concept enhancement. This is accomplished by defining critical failure modes and
critical system conflicts. This important step uses breadboard testing to assess the
significance of related failure modes. The 4th step is concept evaluation and selection.
The goal of this step is to select the most promising solutions in terms of superiority and
pre-robustness. (Phase 2 steps are described in Appendix 2)
13
Framework Phase 3 - Robustness Development and Analysis
Phase 3 Overview
Once several concepts are selected from Phase 2, the concepts now pass through
robustness development. This phase is composed of two major steps. The first is
robustness analysis and evaluation. The second is robustness design. Robustness
analysis consists of defining metrics to measure robustness, selecting appropriate signalto-noise ratios, identifying critical parameter sets, identifying noise sources, establishing
orthogonal array experiments and performing the experiments. Noises should be loud
enough to cause the system to fail. "Make early prototypes Fail", (Courtney, 1998). It is
only though observations of failures we gain a keen awareness of the system's
robustness.
The second step is robustness design. This phase involves calculating signal-tonoise ratios and selecting the best parameter settings. One major concern during this
phase is how to handle interactions. If certain interactions are expected, a suitable
orthogonal matrix should be used to capture the interaction. Preferably, the concept
selected for robustness development will obey the independence axiom. (Suh, 1990).
This will lead to an independent set of control factors. Independent control factors lead
to independent design factors. This will eliminate the interactions among the control
factors and is crucial for applying the additive model. (Clausing, 1998).
(Phase 3 steps are described in Appendix 3)
14
Framework Phase 4 - Technology Selection, Transfer, and Integration
Phase 4 Overview
Winning technologies must meet four general aspects:
1.
They must be Superior
2.
They must be Robust
3.
They must be Flexible
4.
They must be Mature
Superiority
Superiority implies the satisfaction to cost ratio is higher. Satisfaction is viewed in
light of both the market and technology based requirements defined in Phase 1.
Robustness and Maturity
A superior technology by itself won't guarantee success. A robust technology
will be able to be productized through engineering with less rework cycles. Hence, the
ability to predict schedules of robust technologies is greatly enhanced.
Flexible
Flexible technologies are able to easily adapt to variant products. Robustness
development helps to make the technology more flexible.
This selection criteria is similar to concept selection discussed in Phase 2.
However, there is one distinguishing difference. Concept selection and enhancement
seeks to enhance the concepts rather than to rule them out. Selecting winning
technologies for incorporation into product programs is more heavily constrained in order
to meet all the product program requirements.
(Phase 4 steps are described in Appendix 4)
15
Comparison to Xerox Time To Market Process
The Xerox Business Model is shown below.
Xerox
Management
Model
Xerox
Business
Architecture
Tim*e
Ch
2.
eT
IntrastrUCtur6
Time To Market Core Process
-~
Define
MarketAttackt
Dsg
'Define
ein
DeiePrdcProduct Producf Product Customens
e osrt
Dmntae
Deliver
Delight
Teechnnlogy
Figure 2 Xerox Business Model
Xerox's Time to Market Core process is subdivided into 7 Phases.
1.
Market and Product Strategy and Vision
2.
Phase 3.1 Define Market attack Plan and Technology
3.
Phase 3.2 Define Product and Deliver Technology
4.
Phase 3.3 Design Product
5.
Phase 3.4 Demonstrate Product
6.
Phase 3.5 Deliver Product
7.
Phase 3.6 Delight Customers.
This process encompasses all aspects of product and technology creation,
delivery, and service. This thesis focuses on only one aspect of this end to end process,
that being the front end technology development process. Hence, the portions of the
Xerox process that relate to this thesis are only the first three, Market and Product
16
Strategy and Vision, Phase 3.1 Define Market Attack Plan and Technology, and Phase
3.2 Define Product and Deliver Technology. There are many similarities and differences
between the Xerox process and the process proposed by Clausing's TTD process.
Following are descriptions of the first three phases of the Xerox process followed by a
description of the similarities and differences between the Xerox TTM (Time to Market)
process and the processes proposed by Clausing's TTD process.
Many corporations have documented processes. However, this doesn't mean they are
used throughout the company. Whether a company implements its documented processes
depends heavily on the amount of training and management support.
Xerox Market and Product Strategy and Vision
The output of this phase is a document referred to as the MPSV (Market Portfolio
Strategy Vision document.) This document describes the current state of the market,
defines the strategic market opportunities, and identifies vectors of differentiation that
distinguish Xerox from competitors in the mind of the customer. Technology and value
chain capabilities and strategies are identified and a risk assessment is provided. The
details of this process are beyond the scope of this thesis.
Similarities to Clausing's TTD process
Both processes use various charts and graphs to capture the essential business and
technical risks and opportunities. For example, Figure 2 shows Clausing's TTD proposed
Bubble Portfolio Analysis of Market segments and products. Figure 3 shows Xerox's
TTM Market Strategy Allocation Model. They share many similarities. Both indicate
the market or business strength of each product offering. Both also indicate a notion of
the market attractiveness or market growth potential. Both indicate the predicted future
movement of each product. The Clausing TTD graph goes one step further by indicating
the degree of competition for each product.
17
A k
"
*
P3
40
0
*
I-
*
0
Pi: Product i
Size of Circle
represents revenue
contribution.
Arrow indicates
trajectory.
Shading indicates
degree of
competition
0
Weak
below
Avg
Avg above
Avg
Strong
Market Strength
Figure 3 TTD Bubble Portfolio
Figure 4 below describes Xerox's market strategy allocation model. Note the similarity
to Clausing's TTD method.
18
2
4
Weak
Medium
Strong
Business Strength
Figure 4 Market Strategy Allocation Model
In addition to the charts shown above, both Clausing's TTD and Xerox's TTM
process propose similar charts for plotting risk-reward trade-offs. When selecting a new
technology, one must be highly cognizant of the technology risks and they must be
carefully weighed with the potential return on investment. When the technology is very
new or the degree of innovation is new, Utterback suggests completely separating out the
technology development from the organization. (Utterbach, 1991). Clausing also
suggests cycling individuals from mainstream product development teams back into
advanced technology development teams. (Clausing, Total Quality Development, 1994).
This can ease the difficult of NIH, (Not Invented Here) syndrome so common when other
people develop technology and throw it over the wall.
Lowell Steele stated the following misconception:
Misconception: The power of a new technology determines its success.
Reality: The infrastructure required to support it is often the determining factor.
(Steele, Managing Technology, p. 62)
Many of the processes in Phase 3.0 seek to identify technologies and the
underlying infrastructure required to enable the technology to be successful.
19
Management must be highly cognizant of this fact. The technology by itself is useless
without the supporting infrastructure.
Xerox Phase 3.1M
The output of this phase is the Market Attack Plan (MAP). The MAP defines the
market opportunities, defines market driven standards and coherence requirements,
identifies a vector of differentiation, identifies value proposition and family products,
creates a life cycle management plan and again performs risk assessment. Essential to
this phase it the definition of a platform strategy to support a family of products over
time.
The Xerox phase goes into significantly more detail than Clausing's TTD process.
For example, the Xerox process requires documenting where and how customers buy,
and how customers decide to buy.
One common theme is the identification of a Vector of Differentiation (Xerox
Terminology) and identifying Superior technologies (Clausing Terminology.). Each
process seeks to identify the superior technology in customer terms. This is important to
assure technologies are selected for their market strength, not just their technological
strength. This can be problematic, however. Some technologies are so new it is difficult
to obtain accurate market research data simply because the customer is unable to express
or relate to new discontinuous technologies. In these cases, Geoffrey Moore suggests a
need to identify and target niche markets initially. He refers to this as the 'Bowling
Alley.' (Moore, 1995mado). Pins in the bowling alley represent specific niche markets.
As a company is successful knocking down a few of the pins, the others begin to drop as
they hear and learn from the earlier successes. This can be very difficult for large
corporations who tend to listen only to their closest customers. Their closest customers
may NOT represent the best market for the company's new technologies. The disk drive
industry is a good example of how listening to your closest customers can be bad advice.
(Christensen, 1997). Both the Xerox TTM process and Clausing's TTD process should
look carefully at their market definitions to assure they have focused on the best market
segment.
20
There are many similarities between the two processes of this phase. Market
trends are plotted, customer satisfaction targets are established, new technology trends
are assessed, resource requirements are identified, reuse strategy created, cost
assumptions accounted, value chain partners identified, make-buy decisions assessed,
QFD matrix created, Failure modes are predicted. The Xerox process incorporates a
technique known as Input-Output-Constraint charts. The IOC charts clearly define
relationships between the subsystem modules. Clausing's TTD process does not
explicitly define IOC charts, however, he does mention defining constraints and
understanding subsystem dependencies through the interrelations matrix in the QFD
House of Quality.
Xerox Phase 3.1 P
This output of this phase are specific Product proposals, a program economic
case, value chain and channels plans for the program and a team is now chartered to
begin development work.
The elements of this phase are very synergistic with the
Clausing TTD proposal. Some highlights of this phase include technology capability
demonstration for all unproven elements. This is accomplished by charting the trajectory
of critical parameters (Clausing refers to them as Design Parameters). This phase does
NOT guarantee the technologies are Technology Ready. Technology readiness occurs at
the completion of Phase 3.2. One significant difference between Xerox' and Clausing's
TTD process is that Xerox defines newness and complexity ratings to the program.
Depending upon the newness and complexity, the program is categorized as short, midlength, or long. Figure 5 below defines the Xerox newness and complexity configuration
matrix.
21
Platform
Mid-length
Long
Long
Major
Mid-length
Mid-Length
Long
Minor
Short
Mid-Length
Mid-length
e0
Low
Medium
High
Complexity
Figure 5 Newness and Complexity vs Program Configuration
Depending upon the assigned length of the program, benchmarks are defined and
used to assign a time-table to the program. The assignment of program configuration
also determines the number of review cycles required. For example, the Long program
requires a total of 7 reviews while the short program only requires 5 reviews.
Xerox Phase 3.2
There are 5 outputs from this important stage.
1.
Specifications are complete, validated with customers, and under change control.
2.
Value chain and channels plans are complete. Working agreements and contracts
as appropriate have been signed.
3.
The integrated program plan is complete and agreed to by all parties
4.
Program business case is complete, agreed by all participants.
5.
Technology and value chain readiness demonstration is complete and has verified
readiness of the platform architecture and platform system elements for the
program using the unproven elements.
22
Everything above is also included in Clausing's TTD process. Again, both Xerox
and Clausing rely heavily on the use of the QFD House of Quality to track customer
requirements directly to technology requirements. There is great similarity in one
particular aspect, and that is the significance and importance of Technology Readiness.
Both Xerox and Clausing state no Technology should be placed into a Product
Development program until it has been proven, via simulation, experimental rigs, to be at
a significant level of maturity. Clausing states, "The traditional lack of emphasis on
robustness creates great schedule uncertainty during production preparation. The erratic
performance that is caused by lack of robustness leads to many rounds of build-test-fix
rework of product design." (Clausing, Total Quality Development, p 319). Therefore,
Clausing strongly recommends only selecting robust technologies to move into product
programs. Therefore, Clausing emphasizes Robust Design principles (Taguchi methods)
much earlier than the Xerox process. Xerox views robustness development as something
which occurs after Technology Readiness. Clausing believes this is too late.
The Design Structure Matrix is proposed by both Xerox and Clausing to cluster
subsystems based upon their degree of interactions. The Design Structure Matrix also
acts to define the informal network of communications needed within the organization.
In summary, several frameworks for fuzzy front end technology development
have been studied. Clausing's TTD framework was selected for its completeness,
flexibility and inclusion of the latest System Engineering tools. Clausing's TTD
framework provides an excellent basis upon which to build an assessment methodology.
23
Chapter 3
How to Analyze Upstream Technology
Development Effectivity
Introduction
This chapter provides a complete discussion of the thought processes that went
into creating the assessment method. One of the goals of the thesis was to select a
method that would be generic enough to apply to different companies or organizations.
This goal has many implications on the development of this assessment tool. These
issues and their bearing on the proposed assessment method are discussed.
Process used to create the methodology.
First, I researched various Technology development frameworks. I was looking
for a framework with great flexibility. I wanted this work to be applicable to any
company. I also wanted a framework that employed the latest tools and techniques in
System Engineering. Clausing's paper "An embedding process framework for total
technology development" (Clausing, 1998) met these two criteria very well. After
selecting a framework, I needed a method to extract data from an organization seeking to
improve its fuzzy front-end processes. I considered using a written form that could be
mailed to each respondent. This method has the following shortcomings. First and
foremost, the language used within different companies may be different. For example,
one company may call a critical parameter a design parameter. Since the questions are
asking whether or not specific behaviors were present or not present, I was concerned
that respondents might answer they never perform a behavior, simply because they did
not recognize the word or phrase. Second, written questionnaires do not generate any
dialog. Without dialog, it is difficult, if not impossible, to ascertain the motives behind
why a corporate process is not being followed. Hence, a written questionnaire would
have been a poor method for obtaining data. Another method I considered was a
roundtable discussion with all the respondents present. This method would have
generated a great deal of dialog, but has one important shortfall. In a group environment,
individuals may be reluctant to openly share their thoughts and feelings, especially in the
presence of upper management. Hence, this method lacked the ability to get accurate
24
feedback from each individual. The method selected was the interview. This method
overcomes the limitations of the above mentioned methods. The interviews consisted of
82 behavior driven questions. (see Appendix 7).
Applicabilityto other companies
Can this process be used by other companies? Clausing's TTD framework
includes techniques which may not be familiar to all respondents. For example, DSM
(Design Structure Matrix) method was not known by any of the Xerox respondents.
However, the concept of the Design Structure Matrix is easily explained during the
course of the interview. The respondent is asked when they employ any related processes
that achieve the same end result. For example, when creating a task list DSM, some
companies use a Gantt chart to understand the dependencies between tasks. In this case,
the Gantt chart provides for some elements of the task list DSM. Here's another
example. Some companies may not practice the principles of Robust Design. During the
interview, if it clear the respondents are unfamiliar with Robust Design principles, a short
overview of the method, its applicability and the potential benefits can be discussed.
During the interview, the person giving the interview must be knowledgeable about
Robust Design in order to give an overview of its value. This dialog is concluded by
asking the respondent if they see any utility in the method. Positive responses from the
respondents are noted. The value of this dialog is that awareness of the latest System's
Engineering techniques are communicated to the respondents. If the respondents
favorably respond to the techniques, this becomes an excellent starting point for bringing
new initiatives and techniques into the organization. During my interviews with Xerox,
this pattern became obvious. For example, when discussing DSM, all the respondents
said they felt the DSM process was highly valuable and that the organization should try it
out on select projects.
Generation of behavior driven questions
The questionnaire was developed a list of behaviors. The set of questions was
developed with a one to one correspondence to Clausing's TTD process. For tools
unknown to the respondents, I added verbiage to make the process more generic. For
25
example, the behavior surrounding TRIZ I said: TRIZ (or related methods) of conflict
elimination methodology applied. This verbiage seeks to discover if the company utilizes
some other process or technique which embodies the TRIZ principles. Again, the person
conducting the interviews must be well versed in each of the tools and techniques in
order to generate meaningful dialog during the interviews.
The 5 possible responses for each question are:
N- Never
R- Rarely
S - Sometimes
F- Frequently
A- Always
These words were carefully chosen to span the maximum range of behavior space.
Selection of Interviewees
How were the respondents selected? The Xerox organization is a light-weight
matrix organization. Respondents were selected from both the product side and the
functional sides of the matrix. Furthermore, individuals were selected from each of the
functional management teams in order to obtain a good cross section of the entire
organization. One selected individual was not a member of a product team or a member
of a functional department. This individual had a staff job as Technology Strategist. The
ten respondents comprised one Vice President, one Product Manager, one Technology
Strategy manager, four functional department managers, and three Principal technical
contributors.
Selection of individuals from other types of organizations should embody these
principles.
1.
Select managers representing each major subsystem of the product under
development. This assures good homogeneity of the responses across the
organization.
2.
Select managers closest to the market. These individuals may have various titles
such as Product planners, Product managers, Marketing managers.
26
3.
Select a Technology Strategist, if one exists in the organization.
4.
Include the most senior technical individuals. These individuals may have titles
such as Principle Scientist, or Principle Engineer.
How interviews were conducted
I contacted each respondent and set up a two hour window. We met either at my
office or at the respondent's office. I began the interview by explaining why I was
conducting the interview, and the goal of the interview was to generate a list of issues
upon which initiatives could be generated to improve the organizations fuzzy front end. I
had a blank copy of the questionnaire available for the respondent to look at. I had
second copy in front of me where I kept the scores. I also jotted interesting comments
next to each question. For behaviors having low scores I would ask the respondents
whether or not they thought the organization could improve its fuzzy front end by
increasing a particular behavior. If the respondent said yes, I made an additional
annotation next to that question. (Future improvements of the questionnaire should
include this directly on the form). The average length of time was 1
interview.
hours per
I also had additional materials with me. For example, when discussing DSM, I
had an simple DSM example with me to show to the respondent if they were unfamiliar
with the method. I also had materials for TRIZ, House of Quality, and Robust Design
available if the respondents were unfamiliar with the methods.
In summary, an interview format for data collection was developed. Specific
recommendations are given to make the process as generic as possible such that the
assessment method could be applicable across many companies and organizations.
27
Chapter 4
Data Summaries and Key Points
Introduction
This chapter provides detailed data summaries of the most relevant findings from
the interviews. First, the cumulative distribution of scores are presented and discussed.
This is followed by discussions of the lowest ranking scores, followed by the highest
ranking scores, followed by the scores having the highest standard deviation.
Figure 6 below is the cumulative distribution of all answers from all respondents.
Total Response Distribution
250
200
*E 150
50
C
\
Figure 6 Total Response Distribution
From Figure 6 above, approximately 4 % of the responses were Never, 26% of the
responses were Rarely, 32% of the responses were Sometimes, 36% of the responses
were Frequently, and 2% of the responses were Always. This result clearly indicates this
organization does not fully embody the behaviors/processes outlined by Clausing, since
only 30% of the responses were Never or Rarely. Assuming the behaviors/processes in
Clausing's model are valid and have benefit, the data indicates there is substantial room
for improvement within this organizations Front-end Technology development.
28
In order to improve the front-end technology development process for this
organization, the following process is employed.
Step 1: Calculate the average response for each question
Step 2: Sort the responses from lowest average to highest average.
Step 3: Eliminate any behaviors having less than 4 responses.
Step 4: Critically assess the respondents verbal responses
Step 5: Discuss the value of implementing the proposed behaviors.
It is beyond the scope of this thesis to discuss all the ramifications of
implementing process changes within an organization. This thesis presents the first step
in that process, to identify beneficial behaviors lacking within the organization.
Discussion of Lowest scoring behaviors.
Lowest Score Behavior #1
PhaseiStep IQ IlndexlRi
21!
61
44A
1R2
1
1R3
1R4
11
1R5
2
1R6
2
1R
3r
R8
1
1R9
2
IR10 I9
1,
1
.6
Apply Design Structure Matrix to re-allocate
system elements and theirfunctions into
modules, that is, highly interrelatedfunctions
allocated into individual modules and work
teams.
Oddly, none of the respondents had ever even heard of or seen a Design Structure Matrix.
During the interviews, the Design Structure Matrix concept was shown to each
individual. Each respondent easily grasped the concept and felt it was an excellent
methodology for mapping the interdependencies within the organization.
One respondent noted the Design Structure Matrix can be utilized to assess the
degree of risk in making certain decisions, or the risk to other subsystems if a decision is
later modified.
29
One respondent commented how some individuals are located in separate
buildings and that the Design Structure Matrix could highlight those groups or
individuals that should be collocated.
Lowest Score Behavior #2
Phs
tpQldx R1R2
1
41 11
221
21
1R3 1R4 1R5
21
21
21
1R6 1R7 1R8 1R9 IR1 0 Avg
21
11
21
11
21
11
1.71
House of Quality builtfor each technology
The respondents all answered this question consistently low. Again, this is a Xerox tool
that is clearly documented in the TTM guide books. Why isn't this organization using
House of Quality? House of Quality has gotten a culturally bad name for itself within
this organization. The reason is because most managers have had to create a House of
Quality to fulfill Xerox Phase gate criteria and have not obtained commensurate value.
The reason is because they are creating the House of Quality too late in the process. The
House of Quality has value during the Concept Phases, not at the completion of a phase.
The House of Quality can be used as a communication vehicle between marketing and
engineering. The cultural stigma from being forced to create a House of Quality to fulfill
the TTM policing function has made it very difficult for anyone to sincerely practice
using this tool.
Another barrier has been the lack of a good House of Quality software tool for the
creation and maintenance of the House. This is now changing. Recently a tool has been
made available from QFD Designer from Qualisoft (see www.Qualisoft.com). This tool
has a good user interface and can be learned quickly.
Lowest Score Behavior #3
Phase Step Q Index R1
R2
2
9 2
58
2
2
8 3
56
2
2
9 1
57
2
R3
R4
2
3
R5
3
4
3
R6
2
1
2
R7
2
R8
2
2
2
R9
R10 Avg
1
1
1.9
2.2
1
1 2.0
30
TRIZ or related methods of conflict
elimination methodology applied.
Inventive problem solving methods such as
ARIZ are applied to break system conflicts.
Conflicts are identified to be eliminated.
These two questions are highly related. At least fifteen individuals in this organization
went through a one week TRIZ training workshop last year. Yet, evidence of TRIZ
usage is nowhere to be found! What went wrong? It appears there was no management
support for TRIZ, other than financing the training. What I found most disturbing
however, is that the concepts embodied within TRIZ have not yet permeated this
organization. This organization focuses greatly on Compromise rather than Conflict
Elimination. Conflict elimination is a way of thinking. It is especially important during
the Concept generation phase. Yet, this organization has not embraced this manner of
thinking. This was highly evident from comments from respondents.
Overall, most respondents agreed Conflict Elimination thinking would be
beneficial to this organization. Their concern was the amount of time necessary to
explore the alternative paths generated.
Lowest Score Behavior #4
IPhaseiStep
2 -621 IQIJndexIRl
451
31
1R2-
1R3 JR4
I-
31
2
1R5
1
1R6
-
JR7
31
1R8
21
3
IR10 JAvg
1R9
-21
I
1 2.21
Great care taken to assure the architecture
has minimal interrelationsbetween modules.
There was greater variance to this behavior from the respondents. Two of the
respondents said the organization Never did this behavior. Four of the respondents said
the organization Sometimes did this behavior. This issue has caused schedule problems
for this organization. The firmware development for the inkjet printer was handed off to
an outside firm. The firmware touches practically every subsystem within the printer.
The interrelations between firmware and other modules is complex. The information
31
transfer requirements between firmware and the modules is high. The information
conduit passed through one individual who tried to keep the firmware and testing
requirements in order. It didn't work. The firmware became the critical path and caused
the program to slip. The quality of the firmware also was in question. The architecture
simply could not handle the two directional information pathways required between the
modules and the firmware. A Design Structure Matrix would have made this obvious.
32
Lowest Score Behavior #5
Phase Step
1
1
1
4
Index R 1Q R2
R3
R4
R5
R6
R7
R8
R9
R10 Avg
1
4
2
3
3
3
3
2
2
2
22.6
23
2
3
2
2
2.3
Market Pull requirements clearly defined.
Technologists and ProductMarketing work
well together defining the best mix of
technologies and markets.
This organization makes decisions primarily based on Technology Push and less
on Market Pull. Respondents were asked to place an 'X' where they thought we were on
the Market Pull vs Technology Push continuum. And to place an '0' where they thought
we should be. The results were unanimous.
Market
0
X
Pull
Technology
Push
Figure 7 Market Pull vs Technology Push
All respondents felt there needed to be more Market Pull and less Technology
Push in decision making. There was fear of creating technologies the market wouldn't
accept. The House of Quality can act as a speaking tool between these two forces. The
left side (Rows) being the 'What' (Market Pull) and the vertical colurns being the 'How'
(Technology Push).
One manager felt having more technical people in the marketing function could
help bridge this gap.
The other major difficulty occurred when partnering with companies having
different views of the market. This creates great confusion and chaos, resulting in
delayed decision making and sometimes reverting decisions later in time. These political
hurdles must be dealt with very early. If the differences in markets being served by the
partners are too vast, highly flexible technology must be developed for the partnership to
survive.
33
Lowest Score Behavior #6
IPhaseiStep IQ indexIJR1
21
61
11
351
1R2
31
1R3
21
1R4
31
IR5 1R6 1R7
21
21
21
1R8
21
IRio tAvg
1R9
21
31
21
2.31
Functions decomposed into sub-functions in
solution-neutralspace, that is, without regard
to any design concept.
The respondents, who responded with 3- Sometimes, said this behavior occurs implicitly
within the minds of the engineer. It isn't an explicit, written down process as suggested
by Clausing. Most respondents were unsure of the value of explicitly performing this
behavior. This process is the backbone of System' s Engineering. The value resides in
the ability to decompose the function down to the essential functional elements prior to
deriving a concept to map function to form. When an individual prematurely establishes
a design concept, the brain tends to take hold of this idea and great energy is required to
move the brain onto other concepts. The value of breaking down the functions to
subfunctions in design neutral space is proposed to prevent the brain from adopting
premature concept selections.
Lowest Score Behavior #7
IPhase-Step IQI~ndexIR1
41741
82
1R2
1R4
jR3
2
jR5
3
1R6 1R7
3
1R8 1R9
31
21
JR10 IAvg
2
2
Promisingtechnologiesnot yet readyfor a
productprogram areplaced back into
robustness development.
Many of the respondents indicated that promising technologies that are not yet ready for
product programs are typically killed, rather than placed back into Robustness
development. This organization does not actively staff resources to enable promising
technologies to cultivate. The organization is so fixated on getting the next product out
that managers are reluctant to place any resources on longer term, potential high gain,
projects. This approach is short sighted. The organization needs to achieve a balance
between getting products out the door, and maintaining a steady technology stream. This
34
is very difficult to achieve, because culturally, Xerox has a tendency to throw resources at
problems. Managers feel constantly in a state of fire fighting. In this mode, all resources
are thrown at the problem of the week to keep the fires from raging out of control. At
this point, a senior manager, or VP needs to step in, assess the total picture, and make an
appropriate judgement regarding allocation of resources.
Lowest Score Behavior #8
IPhase Step IQ In-dex Ri
1
1 131
131
1R2
21
1R3
41
R4 IR5
3
31
R7
R6
2
21
1R8 1R9
2
31
R10 IAvg
2
2 2.5,
Business Impact of technology assessed.
This question generated lots of discussion. Because there is a lack of Market pull
in this organization, technologists feel unsure of the value of their technical
achievements. The business cases for recent product programs had not been shared with
many of the senior managers interviewed. Hence, there was a lack of trust between
technical managers and business planners. Business planners need to openly share their
business models with the technical community. A sound business model can give the
organization the needed motivation and personal security to know their efforts will bear
fruit.
Lowest Score Behavior #9
JRi 3 1R2 3 1R3 4 1R4 2 IR5 2 R6 1R7 1R8 1R9 JR10 IAvgI
I1ndex
PhaseiStep
1
2 IQ5
18
1
4
3
2
1 2.5
Reasonable timeline estimates created.
Most managers agreed that unrealistic schedules are created. It is not clear
whether this is good or bad for the organization. Many managers believe that creating
realistic schedules is a poor idea because it takes the pressure off the people. They argue
aggressive schedules drive and motivate individuals. There is a flip side to this issue. If
schedule pressure is too great, individuals begin making poor decisions. They don't take
35
the time to properly gather the appropriate data for the decision. Excessive schedule
pressure over prolonged periods of time can lead to individual bum-out. This
organization is approaching burn-out stage as it continues to drive multiple parallel
projects, each under aggressive schedule pressure.
Lowest Score Behavior #10
IPhaseiStep IQolindexiR1
2
6
31
461
1R2
21
1R3 1R4
1
31
1R5 1R6 1R7
21
21 -31
1R8
21
1R9
IR1 0IAvg
31
21
42.61
Multiple System Architectures proposed,
rather than keying in early on a single
solution.
Rarely is the first idea the best idea. Yet, respondents said very little time is spent
developing multiple concepts! Pugh concept enhancement is a method proposed by
Clausing which leverages the strengths of each concept to build new concepts. This
behavior is grossly deficient in this organization. Most respondents agreed the
organization should foster a more active concept generation phase.
Discussionof Highest scoring behaviors.
Highest Score Behavior #1
Phase
Step Q Index R1
R2
3
123
69
4
3
122
68
4
R3
R4
4
R5
R7
R6
R8
4
3
2
4
4
4
R9
1
R10 Avg
4
4
Stdev
43.6
0.8
44.0
0.0
Design of Experiments. Environmental noises
selected.
Design of Experiments. Tolerance noises
selected.
36
Most respondents indicated this organization does a good job defining
environmental and tolerance noises. They indicated frequent testing at high and low
temperatures, high and low humidities, and high altitude testing. Tolerance noises were
also selected. This organization has painfully learned from past projects what happens
when a product moves into production and production processes are not able to meet the
tolerances specified. Because of this prior experience, the organization has become
sensitized to discovering tolerance sensitivities early in the development process. There
was one individual who did not agree tolerance noises were selected. This individual felt
tolerance noises were selected, however, they were selected too late in the development
process. Tolerance noises were considered something that could be worked out at a later
stage in the program. Also, note that several respondents did not answer this question.
This was because these individuals were at a higher level in the organization and did not
understand this level of detail within their organization. Is this an indication that upper
management isn't aware of what people lower in the organization are doing? Are these
managers out of touch with the processes being used in their organization? Should these
managers know whether or not environmental and tolerance noises are applied? Upon
further probing in the interview, the respondents indicated they believed these noises
were being applied, they simply didn't know the details of what specific noises were
being applied.
Highest Score Behavior #2
R2
Phase Step Q Index R1
1
1 1
1
1 8
R3
R4
R5
R6
R7
R8
R10 Avg
R9
Stdev
10
4
4
5
3
4
4
2
4
3
4
3.7
0.8
8
3
3
4
4
4
4
4
4
4
43.8
0.4
Provide a technology perspective for a
decision on which technologies to focus on.
Technology Trends plotted.
The respondents unanimously agreed that a very thorough technology perspective
is used for decision making. Technology perspectives include benchmarking of
37
competitive technologies, studying patent literature, and in-depth technology risk
assessment. However, the respondents felt that decision making was too focused on the
technology perspective, and too weak on the market perspective, as discussed earlier
(ref.Questionnaire Index #1). This organization is too heavily focused on technology
push and lacks the market pull factors in decision making.
Highest Score Behavior #3
Phase Step Q Index R1
R2
R3 R4 R5 R6 R7 R8 R9 R10 Avg Stdev
2
6 1
37
4
4
4
4
3
4
4
3
3
4 3.7
0.5
2
6 6
42
4
4
4
4
5
4
3
3
4 3.9
0.6
Target values establishedfor each design
parameter.
Appropriate design parametersdetermined for
each subfunction.
This question required some clarification during the interview. Xerox refers to
Clausing's design parameters as critical parameters. This Xerox organization has been
trained to apply Critical parameters to the design process. Management has supported
and fostered the deployment of critical parameters throughout this organization. Note the
consistent high scores across the organization. This is a good indication that training and
management support has been effective at instilling the critical parameter design process.
One of the lower scores came from an individual who worked in an area where it has
simply been too difficult to define appropriate critical parameters. Many of the design
practices in this group are driven by heuristics rather than strict critical parameter
determination for each function. Attempts have been made to seek out the critical
parameters and link them to function, yet the technology itself has been too difficult, even
for senior level scientists, to extract the relevant critical parameters. Because of the lack
of scientific knowledge linking critical parameters to function, they have had to rely on
lots and lots of empirical testing to assure the design functions could be met.
Highest Score Behavior #4
38
MPhase1 Step11 IQI11ndexIJRl
31
31
5
1R2
4
1R3
1R44
IR5
R6
4
1R7
4
1R8
1R9
51
IRl
41
ivg3. Idev09
21
Each competitor is well characterizedin the
market.
The scores were very high on this question, with only one major dissenter. Charts
and graphs are frequently created showing the competitive strengths of each competitor.
A competitive lab has even been established. This is a room dedicated exclusively to
competitive products. The room was created to raise the awareness of the competition.
Individuals within the organization are encouraged to visit the room and actually use the
competitive products. Individuals may also "check out" competitive products for several
weeks to use at their desktops. A great deal of analytic data is also collected from the
competitive products. The one dissenter commented that he believe competitive
information was collected, however, he felt it was not disseminated throughout the
organization, and that only select individuals actually had access to the data. This
individual happened to be located in another building. It appeared this was an example of
how geographic location had left this individual out the mainstream flow of information.
Again, the interview format was necessary to bring out this level of understanding. A
strict questionnaire would not have elucidated this important insight.
Highest Score Behavior #5
R2
Phase Step Q Index R1
4
54
1
8
2
4
48
8 1
2
4
4
4
4
3
3
R8
R7
R6
R5
R4
R3
4
4
3
3
R10
R9
4
4
4
4
Avg Stdev
0.5
3.8
0.5
3.8
FailureModes predicted.
Lab experiments performed to assess failure
mode impacts on System Performance.
These scores were consistently high. Why? When this organization first builds a
prototype, they have a test called the FMIT. This stands for Failure Mode Identification
Test. The name itself assures failure modes will be found! This organization has
39
delivered two generations or products from their core technology set. They have learned
through experience what important failure modes are necessary to evaluate. The
organization does a good job of looking at failure modes both at a subsystem level and at
the system level.
Discussion of behaviors having high standard deviations
Highest Standard Deviation Behavior #1
IPhase Step IQ Index Ri 1R2 1R3 1R4 IR5 1R6 1R7
1
241
171
51
41
31
41
4
5
1R8 1R9
41
R1 0 Avg IStdev
2
2
3.71
1.1
Resource Requirements determined.
Very interesting results. The two lowest scores came from the technical function
management level, where the two highest scores came from the managers responsible for
resource planning! This implies the people responsible for resource planning feel like it's
being done, yet the people who carry out the plans (the functional managers) don't feel
like it's done, or they don't feel it is done well. During the interview, the functional
managers asked whether the question meant whether resource requirements were
'accurately' determined. They believed resources were determined, however, they felt
the resource requirements were not accurate, implying they are asked to do more with
less people.
Highest Standard Deviation Behavior #2
Phase Step Q Index R1
R2 R3
R4 R5 R6 R7 R8 R9 R10 Avg Stdev
1
2 6
19
4
4
4
2
2
4
4
4
2
2 3.2
1.0
1
2 5
18
3
3
4
2
2
1
4
3
2
1 2.5
1.1
Timeline estimates created.
Budget requirements created.
Each respondent asked this question. "Do you mean 'realistic' timelines are
estimated?" The cynical tone of their voices indicated they believed timeline estimates
40
are created, however, most of the respondents indicated the estimates were not realistic.
For consistency sake, I appended the word realistic to this question for each interviewee.
During the interview two points of view on schedule creation emerged. One point of
view was that schedules should be created more realistically, that is, add more time to the
proposed schedules. They felt the organization had a better chance of hitting the
schedule if was created more realistically. The other point of view was to create
schedules that are more aggressive. They felt the same amount of slip would occur with
either schedule! They felt a certain amount of schedule pressure was necessary to keep
the organization pressured to deliver. This organization hadn't directly felt the impact of
schedule slips in the past, so a cultural norm exists within the organization that tolerates
schedule slips. Responses to budget requirements were similar to schedule requirements.
A large portion of this organization's budget is engineering labor, therefore, schedule and
budget estimates are linked.
Highest Standard Deviation Behavior #3
Phase Step
1
1
1R2
indexiR1
4
4
3
1R3
3
IR5
1R4
2
4
1R6
2
1R7
3
1R8
4
R10 Avg Stdev
1R9
5
3
2
1.0
3.1
Key customer satisfactionparametersare
identified for each market segment.
The respondents giving low scores say management gives diverse answers as to
what the markets are and what will succeed in each market. Why is there so much
diversity of opinion? This organization has an alliance with another company. This
partner is from another country and often has different opinions of the market and what
the appropriate satisfaction parameters are for those markets. Having a partner with a
different view of the market has destabilized this organization. They lack a consistent
focus on which market they are attacking. This has created confusion as evidenced by
the wide range of responses from Rarely to Always.
In summary, 820 data points have been summarized, sorted and discussed. From
these summaries, the organization has obtained a list of it's weaknesses and strengths.
41
These lists provide the bedrock upon which initiatives can be built to improve this
organization's fuzzy front end technology development processes.
42
Chapter 5
Application of Results
The previous chapter brought forward weaknesses within one organizations fuzzy
front end processes. Now that a list of weaknesses has been created, initiatives can be put
in place to create improvements. This chapter takes a look at one weakness found and
proposes a method and technique to improve the shortfall.
Question #13, 'Business impact of technology assessed', was one of the lower
scoring questions. The organization lacked a method for translating technology
variations to implications within the field. Monte Carlo Analysis is proposed as a
technique this organization could incorporate to translate real world issues into business
results.
This section presents a Monte Carlo Analysis applied to the life cycle of an inkjet
ink tank. Ink tanks represent the primary source of profits for inkjet printer vendors.
Customer usage patterns determine how often they will purchase new ink tanks. Also,
ink evaporates from ink tanks. Excessive evaporation of the water from the ink will
cause the remaining ink in the ink tank to go bad. The Monte Carlo Analysis considers
all these factors to obtain key information for business planners.
Phase 3 Robustness Development and Analysis is lacking one important step.
The proposed steps do not include a method for determining the system impact of
normally distributed noises. Phase 3 Robustness Development and Analysis consists of a
stepwise sequence for selecting appropriate control parameters to achieve the intended
system functions AND to achieve the least sensitivity to noise factors. After optimum
control factors are found it is desirable to determine the system sensitivity to the noise
factors. However, these noises are almost always normally distributed and their
contributions to system performance can not be assessed with a very high degree of
accuracy using the proposed steps.
Monte Carlo Analysis is proposed as an additional step to Phase 3. Monte Carlo
Analysis will aid the system designer in understanding and quantifying the impact of
noise distributions on system performance. The noise distributions may be of any shape.
Most noises are normally distributed. However, some distributions are truncated normal
43
distributions. Truncated normal distributions occur when parts are screened on the
production floor. Figure 8 below is an example of a truncated normal distribution.
Inkjet Drop Mass Distribution
0.25
0.2
0.15
o
I-
0.1
0.05
0
25
30
35
40
45
Drop Mass
Figure 8 Truncated Normal Distribution
In the above example, the production process is incapable of producing parts with a
nominal drop mass of 35 ngrams and a maximum drop mass of 38 ngrams. Printheads
having a drop mass greater than 38 ngrams place too much ink on the page and creates
two failure modes. One, excess ink causes the ink drying time to increase, causing
smearing of ink on the customer's hands. Second, excess ink causes ink to bleed through
to the back side. Thus, production must suffer scrap costs. One must carefully weigh the
scrap costs versus the cost of shipping an inferior product to the customer. This can be
quantified integrating Phadke's Quality loss function. (Phadke,1989).
44
A typical Quality Loss function is shown in Figure 9 below.
I
Quality Loss Function
120
100
80
e
+ Seriesi
60
40
20
0
25
30
35
40
45
Drop Mass
Figure 9 Quality Loss Function
The Quality Loss Function relates the Total Cost to society. This may include
service costs, market loss due to word of mouth from irate customers, customer down
time costs, etc. This function can be extremely difficult to quantify. When entering a
new market with excellent competitors, managers are very cautious about shipping
inferior products, fearing repercussions in the marketplace. Hence, it is all too common
for products to be launched into the market from truncated normal distributions. Robust
design practices as described by Clausing, (Clausing, 1993), Phadke (Phadke, 1989), and
Taguchi (Taguchi, 1993), seek to reduce the sensitivity to noise factors to allow for wider
tolerances. Therefore, Robust design practices are essential to assure products are
producible with acceptable tolerance latitude.
Monte Carlo Analysis is best explained by an example. Consider the following
system. The system is an inkjet inktank filled with color ink. The ink is comprised
mostly of water (90%). During the life of an inktank, ink will evaporate from the
inktank. If the amount of evaporation of water is too great, the concentration of the dye
and co-solvents in the ink will increase. Printhead operation will become poor when the
increase in concentration of non-aqueous components exceeds a certain limit. This
45
results in poor print quality which customers would judge as unacceptable. Therefore,
the water concentration in the ink must remain above a certain threshold.
Extend Software from Image That Inc. was used to create the Monte Carlo
Analysis described below. Refer to Figure 10 below.
OUTPUT
%Useful Ink
Factory% Water
Wate rout
Rate
Transp or
Transport Day
Water
ss
Storage
Water oss
Rate at Env iron
Inst
Wat
Install Pgs/Day
S S
te
Storage Days
A
=A (Tem ,rH)
Temp.
Temp
Install Te mp.
Rate i
xP
rHRate at Environ
rH
Pages/Day printed
Install rH
Rate
Figure 10 Monte Carlo Analysis Example
Overview of Model
An inktank ships with a fixed volume of ink. It is desirable that 100% of the ink
in the tank remain at an acceptable water concentration over the life of the ink tank. The
46
simulation is set to simulate the life of 1000 ink tanks. The Monte Carlo analysis will
calculate the percent of useful ink for each ink tank and display the results as a histogram.
Each of the 1000 inktank simulations will be different and will experience different noise
conditions according to the normal distribution noise factors. Figure 11 below is a
sample histogram output of useful ink percent for 1000 ink tanks.
Useful Ink Histogram
322
281.75
241.5
201.25
161
120.75
80.5
40.25
0
-
Data
Data
0.25
-
0.5
Usef ul Ink percent
Data
0.75
1
Data
Figure 11 Useful Ink Histogram. Monte Carlo Output
The peak at 100% indicates 322 out of 1000 ink tanks had an acceptable level of
evaporation over the installed life of those ink tanks. The bar at Useful ink = 50% and a
count of 80 indicates that 80 out of 1000 tanks only had 50% useful ink over the life of
those tanks. In this case, we expect those 80 customers would experience some print
quality shortfalls after their tanks become half empty. The bar at Useful ink = 27% and a
count of 10 indicates that 10 out of 1000 tanks only had 27% useful ink over the life of
those tanks. In this case, those 10 customers would expect to see print quality defects
after only 27% of the ink was used from their inktanks. This is clearly unacceptable.
47
What are the sources of noise in the Monte Carlo Analysis?
There are 8 noise factors in the model. Different types of noise distributions are used.
U
Noise #1: Factory %Water.
1 2 3
Factory% Water
This is a Normal Distributionof
Distribution Plottr
6.
the percent of water by weight in
4.1
the ink at the time the tanks are
3.
____
0.565
Member Value
0.5475
0 .53
-smm%
filled with ink. It has a very tight
.I
1. 3
0.6
0.5825
distribution.
Members
Figure 12 Factory % Water Normal Distribution
Noise #2: Transport Days in Truck
Transport Days
This is a LogNormal Distribution.
Distribution Plotter
9.28 c-I
This distribution represents the
6.9637 5
amount of time the tanks spend in
4.642
2.3212 5
transit in shipping.
2.2 63744
-mmm%
7.606081
12.94842
Member Value
23.63309
18.29075
Members
Figure 13 Transport LogNormal Distribution
Noise #3: Evaporation Rate in transit distribution
,--.::---.-.--. ---. -.- - ,
-... - -...---
Rate at Env iron
.
19bb1b'
This is a Empirical Table
-
14713411
986896.7
-
Distribution.The table is based
502452.4
18008.07
0.00 019
a
0.0009675
1mm inma
0.0025225
0.001745
Bin Range
upon experimental rate loss lab
0.0033
experimental data.
Den sity
Figure 14 Evaporation Rate Emperical Table Distribution
48
Noise #4: Storage Days Distribution
17.655
.-m.--
Storage Days
Plotter
Distribution
~-~
p~
-~-
This is a Log Normal
13.24125
Distribution.The distribution
8.8275
indicates the number of days a
4.41375,
.
tank may sit idle in a warehouse.
1739.258
1307.781
876.3026
444.8246
13.34662
Member Value
% Members
Figure 15 Storage LogNormal Distribution
Noise #5: Rate at Environment. Storage
Rate at Env iron
-
F
.
I
.
.
P
I
.
-
193939k-
This is a EmpiricalTable
1456034
Distribution.The table is based
972673.2[--
upon experimental rate loss lab
experimental data.
489312.8[
5952.38100
0.00019
0.0009675
0.0033
0.0025225
0.001745
Bin Range
Density
Figure 16 Rate at Environmental Storage
Noise #6: Installation Temperature
Install Temp.
0.015
This is a EmpiricalTable
0.01127638
I ~KJ
0.007552761
Distribution.The table is an
I
estimate of the temperature
0.003829142-
-'
0.0001055223
5
.
Density
15
25
Bin Range
J
~
35
mm
45
distribution at the customer's site
in deg C.
Figure 17 Installation Temperature Emperical Distribution
Noise #7: Installation Humidity
49
Install rH
This is a Normal Distribution.
Distribution Plotter
6.7
The distribution is an estimate of
5.032 5
the humidity distribution at the
3.35
1.677 5-
customer's site.
0.04890791
0.6867333
0.8993418
% Members
Figure 18 Humidity Normal Distribution
Noise #8: Installation Payes/dav
Install Pgs/Day
677
Distribution Plotter
8.
6.47 25
4.3 15
Distribution.The distribution
--
--
This is a Log Normal
indicates the number of pages a
-
-
0.4741248
Member Value
0.2615164
2.15 75
customer is likely to print per day.
2.363713
0.8969545
-
3.830471
5.29723
6.763988
Member Value
% Members
Figure 19 Pages/Day LogNormal Distribution
There are three Calculation Blocks representing the three different modes of evaporation
experienced by the tanks over their life cycle.
Calculation Block #1: Transport Water Loss
E Water
K
Days
Rate
WaterOut
Transport
Water Loss
During each of the 1000 tank simulations, this block
receives WaterIn, Days and Rate data points from the three
Noise inputs. The block calculates the new water
concentration and passes that information to the next block.
50
WaterOut=((GramsInkInTank*Watern)(Rateln*Daysln))/( Gramslnk~nTank -(RateIn*DaysIn));
Calculation Block #2: StorageWater Loss
During each of the 1000 tank simulations, this block
receives WaterIn data from the previous block, Days and
Rate data points from the other two Noise inputs. The
block calculates the new water concentration and passes
Days
Rate
WaerOut
I
that information to the next block.
WaterOut=((GramsInkInTank*Watern)-
Storage
(Rateln*Daysln))/( GramslnklnTank -(RateIn*DaysIn));
Water Loss
Calculation Block #3: StorageWater Loss
This block does more than the other blocks. Depending
C
waterin
upon the customer's usage rate (Pages/Day), this block
WaterOut
pete
calculates the estimated days to empty. It then calculates
the water loss each day and determines whether the ink is
7
C page/Day
n
%sfu
Daystill
J
good ink or bad ink.
Appendix 5 lists the source code for this block.
Installed
Water Loss
Auxilliary Calculation Block: Rate = f(Temperature and Humidity)
This is a very important block. This block calculates the
Rate
=f(Temp,rH)
Temp
EU
rate of evaporation as a function of temperature and
humidity.
k=6.3501;
Rate 0
I.Pv
= 0.098* exp(0.0603*TempIn);
RateOut=k *( 0.9 - rHIn ) * ( Pv / (Templn+273.0));
51
Sensitivity to Noise Factors.
Once the Monte Carlo simulation is built, sensitivity to noise factors can easily be
performed. This is in contrast to Robust design methodologies which can not predict the
system response to real world distributions such as those described in the example above.
Sensitivity Analysis #1: Temperature Noise impact on System Response.
Plotter XY
*
Ma.
0.9 846597
0.9 193193
0. 853979
4
a
0.7 886387
a
0.7 232984
0. 657958
Mot
0.5 926177272774
nr
.i
0.4619371
0.3965967
----
-A
l
N
0.3312564
0.2659161
-
%
*
a
-no
a
a
0.2005758
0.1352354
0.06989512
0.004554796
5.757476
~
*.
15.54281
*
--
25.32814
Temperature (C)
'
35.11347
___
44.8988
Figure 20 Sensitivity to Temperature Noise
There is a strong dependence of temperature on Useful Ink Percentage.
52
Sensitivity Analysis #2: Humidity Noise impact on System Response.
Plotter XY
1.05
0. 9848369
10
---
u~t~l~
now
NON
NIMV ass( x am
IF
-
Post
i
I
IC 0- N.%jL J a
-
0. 8545106
s"o
0. 7893475 --
-
0. 7241844
--
*
0. 9196737
U'
U a
--
aa
M
*
......
0. 6590212
0. 5938581-
aW
-
a
0 .528695 0. 4635318
1-
0
~
..
.n o
a -a.
-
0. 3983687
a
0. 3332056
-
0. 2680424
0. 1377162
-
U
0.0 7255306
nnf7q'
QOgW
0.2083549
4-
-
-
I
I
0.3116003
0.4148457
-
-
a
*
I
0.5180911
rH
I
-
0. 2028793
I
0.6213365
I
0.724582
I
0.8278274
Figure 21 Sensitivity to Humidity Noise
There is a strong dependence of Humidity on Useful Ink Percentage, but not as strong as
temperature.
53
Sensitivity Analysis #3: Pages printed per day Noise impact on System Response.
Plotter XY
1.05
0.9847014
I'm
U
I
I"
0.7888055
-
Eu0 Ito
0.7235069
F m
an
writ,
, a
I
quo
U
ma
%"U
Ib n a"BW
as
0.3317152
0.26641657 -0.2011179
0.1358193I-
qL
VI
U
U
10i
a
Im
a
0a
MEN
a
-
-0
I a
'mm
MEN
a
0
s
-
U
p.
I.
U
0.4623124
0
aU
-
-
U
-
m16U
*--
0.5929096
5--
WO-
WE
-
0
0
a
IV- IIII I
of ml
0.6582083
- -
- -
---
-
-
-
0.9606214
-- ~^-
I
0.07052067
0 00522205
U
-
U
U
p~iI
,
U
0.8541041
0.3970138
I
-w 0mm
a
0.9194028
0.527611
1--
I
1.609049
2.257478
2.905906
Pages/Day Printed
3.554334
4.202762
4.85119
Figure 22 Sensitivity to Pages printed per day
Useful ink percentage is function of pages printed per day up to about 4 pages per day.
Above four pages per day there is no sensitivity to pages printed per day.
54
Sensitivity Analysis #4: Temperature Noise impact on System Response
Plotter XY
1.05
r
0. 9849293
N
0. 9198586
0. 7897172
-N
0. 7246465-
No 0
a
0. 6595758
- ~-
0. 5945051
-
as
0. 8547879
~
.
I
a
0. 5294344
0. 4643637
a
~.399293
W0
0. 3342223
0. 2691516
a
'iEU
a
a
~
-
0. 2040809
0. 1390102
-
[it
~
N
0.0 7393953
0.0
0.0007690582
0.00282206
0.0 08981064
0.006928063
0.004875061
WaterEv apRate grams/day
0.01103407
0.01308707
Figure 23 Water Evaporation Rate Sensitivity
The water evaporation rate sensitivity is very strong, as one would expect.
Usefulness of Monte Carlo Simulation
The example above shows how Monte Carlo Analysis can be utilized to more
fully understand how real world distributions affect customer satisfaction. The model
allows the organization to understand the business impacts associated with technology
and market place variations.
Monte Carlo Analysis is a practical tool. It has an intuitive
appeal. It allows modeling of almost any input distribution. The software tool Extend,
from Image That, Inc. is quite simple and easy to use. It has a complete library of the
most common tasks. In addition, they provide tools for creating your own blocks, such as
the calculation blocks shown in the above example.
Understanding the business impact of technology requires a method for
systematically translating technology inputs into market place outputs which directly
55
impact the business results. Monte Carlo analysis can be a useful tool for systematically
mapping technology inputs and their sources of variation into business results.
56
Chapter 6
Conclusions and Recommendations
An appropriate framework for total technology development was selected from
the literature. A questionnaire was developed from this framework. The questionnaire
was developed in a manner to make it generically applicable. The questionnaire was
administered to ten individuals within one organization using an interview format. 820
data points were extracted from the interviews. The data was summarized, sorted, and
discussed. The summarized data provided a list of the strengths and weaknesses within
this organization. From the weaknesses, this organization can now begin to develop
initiatives to improve it's fuzzy front end. An example is provided showing how Monte
Carlo Analysis could be used to improve upon one of the lowest scoring questions.
Many other conclusions and interesting observations were obtained during the
course of this work. It is important to understand the difference between a corporation's
documented processes and the processes actually implemented within an organization.
Studying the corporation's documented processes would have been of limited value,
because I found many discrepancies between the documented processes and the processes
actually implemented at a local level. This is true of many organizations. The military
has an acquisition process, however, implementation to the process is quite difficult.
Why is this important to understand? When a company is faced with great competitive
pressures, management may look to modify its processes in hopes of reaping significant
returns. Management may look at the documented processes and try to build upon what
is already in place. Yet, during the course of this work, I came to understand there can be
great differences in what is actually implemented. Management first needs to determine
what people are actually doing. For example, Xerox lists the Design Structure Matrix as
one of the TTM tools. However, not a single individual I interviewed has even heard of
the Design Structure Matrix. This strongly implies the need to understand what is
happening locally before even beginning to overhaul a corporate process.
Reacquainting the organization with existing corporate methods may be one way
to improve upon defined weaknesses. For example, in the Xerox case the House of
Quality is rarely used in this one organization, yet it is a standard corporate method. The
57
interview may create a new awareness of the value of the House of Quality as a
communications vehicle, rather than documentation required to pass a phase gate. The
interview is key to understanding the cultural dimensions associated with negative
feelings toward a particular tool or technique. Given the cultural attitudes toward the
House of Quality, I suggest locating someone new in the organization to act as a niche
House of Quality activator. Once others see the value to be extracted, perhaps the tool
will be pulled from the rest of the organization rather than pushed upon them.
How applicable is this assessment method to other companies? Would this
assessment method be effective within other companies? What difficulties might arise? I
think there are two major difficulties which may limit the effectiveness of the proposed
assessment method. First, language or nomenclature differences may hamper clear
communication. If this occurs, additional time may be required for each interview.
Second, if the organization already has a deeply engrained process, or the general feeling
is that change is somehow bad, there may be negative reactions from management to 'fix'
the organization. In this case, it is essential to find an upper management supporter. This
supporter should have enough visibility and respect within the organization to foster an
environment conducive to change.
What difficulties were encountered during the interviews? How can they be
improved? Several questions were duplicates of earlier questions, causing confusion.
For example, the behavior 'Timeline estimates created', and 'Schedules estimated' are
essentially the same. The subtle difference is that they refer to slightly different phases of
the TTD process. The subtle distinction was difficult to clarify. Having knowledge of
the companies process may make it easier to relate the questions to the respondents in
their language. Therefore, it would be beneficial for the interviewer to understand the
companies basic process prior to the interviews such that the interviewer could more
easily relate the questions to the respondents.
Another improvement to the process would be to add a check box next to each
question. This check box would be checked when the respondent felt strongly the
behavior was lacking and was important to the organization. Adding this to the interview
sheet and data analysis would provide a list of 'low hanging fruit.' Low hanging fruit are
58
those actions that are easy to implement and typically yield quick improvements. When a
group of managers all agree a behavior is lacking and that it is important, it will be much
easier to get support for this initiative.
A web-based questionnaire may be a viable method to perform an initial scoping
of the issues facing the organization. However, this must be approached very cautiously,
for many of the problems cited earlier regarding a written survey. A web-based
questionnaire may need to be tailored to each organization to use the nomenclature
consistent with the organization under study. Otherwise, the data obtained could be
worthless! The web-based method could include 'education' buttons. For example, if
the respondent was unfamiliar with DSM, a button could be pressed to take the
respondent to an overview of the DSM method. Thus, the web-based method could act to
educate as well as gather data. Low scores from the web-based survey should be
followed up with interviews. This is critical. The interview is essential for understanding
the social, political, and cultural dimensions to each behavior. High scores could be used
to establish role model divisions or individuals. Identifying role models is an important
element of learning organizations.
In summary, the objectives of this thesis have been met. Recommendations to
continue this work should focus on selecting and implementing initiatives to improve the
defined weaknesses. I strongly feel the fuzzy front-end is a critical phase for high tech
companies to master. I believe application of the techniques and methods proposed in
this thesis will enable companies to move one step closer to realizing significant rewards
in the marketplace.
59
Bibliography and References
Altshuller, G. S. (1984), 'Creativity as an Exact Science', New York, Gordan & Breach
Science Publishers.
Christensen, C. (1997), 'The Innovator's Dilemma', New York, NY, HarperCollins
Publisher.
Clausing, D. (1993), 'Total Quality Development', New York, NY, ASME Press.
Clausing, D. P. and Schulz, A (1998), 'An embedding process framework for total
technology Development', Cambridge, MA, Massachusetts Institute of Technology,
Center for Innovation in Product Development.
Cooper, R. G. and E. J. Kleinschmidt (1988), 'Resource-Allocation in the New Product
Process', Industrial Marketing Management 17(3): 249-262.
Courtney, T. (1998), 'System's Architecture Principles Journal', Cambridge, MA,
System's Architecture Class, Massachusetts Institute of Technology.
Frauens, M. (2000), 'Improved Selection of Technically Attractive Projects Using
Knowledge Management and Net Interactive Tools', Cambridge, MA, Massachusetts
Institute of Technology.
Hammer, M. and Champy, J. (1993), 'Reengineering the Corporation', New York, NY,
HarperCollins Publisher.
Khurana, A., and S. R. Rosenthal (Winter, 1997), "Integrating the Fuzzy Front End of
New Product Development", Sloan Management Review.
Moore, G. (1995), 'Inside the Tornado', New York, NY, HarperCollins Publisher.
Phadke, M. S. (1989), 'Quality Engineering using Robust Design', New Jersey, Prentice
Hall.
Rechtin, E. and Maier, M. (1997), 'The Art of Systems Architecting', Boca Raton, FL,
CRC Press.
Senge, P. M. and Kleiner, A. and Roberts, C. and Ross, R. and Smith, B. (1994), 'The
Fifth Discipline: The Art and Practice fo the Learning Organization', New York, NY,
Bantam Doubleday Dell Publishing Group.
Steele, L. W. (1989), 'Managing Technology', New York, NY, McGraw-Hill Book
Company.
Suh, N. P. (1990), 'The Principles of Design', New York, Oxford University Press.
60
Taguchi, G. (1993), 'Taguchi on Robust Design', ASME Press.
Utterback, J. (1996), 'Mastering the Dynamics of Innovation', Cambridge, MA, Harvard
Business School Press.
'Webster's New Universal unabridged Dictionary', (1996), New York, Barnes and
Nobles Books.
Wheelon, A. D. (1986), 'Collection of Student Heuristics in Systems Architecting', Los
Angeles, CA, USC School of Engineering.
Wirthlin, J. R. (2000), 'Best Practices in User Needs/Requirements Generation',
Cambridge, MA, Massachusetts Institute of Technology.
61
Appendix
Appendix 1: Phase 1 Process Steps
Step la - Market and Product Assessment
Inputs
Market and product program data
Outputs
Significance of market segments and product programs
Key Customer satisfaction parameters sets.
Decisions: none
Step lb - Technology and Technological Capability Assessment
Inputs
Technology and technological capabilities
Key customer satisfaction parameter sets
Outputs
Significance of Technologies for each product
Significance of Technological Capabilities and Technologies
Decisions: none
Step ic - Trend and Impact Assessment
Inputs
Market pull parameter set
Technology push parameter set
Outputs
Market based trend analysis
62
Technology based trend analysis
Gap Analysis
Impact Analysis
Decisions: none
Step 2 - Develop Integrated Technology Strategy
Inputs
Significance of each market and product
Significance of each technology and technological capability
Gaps among market based trend and technology based trend
Technological and economical impact of each technology
Required target values for key parameter sets, derived from a market and technology
perspective
Available resources, budget, timeline
Outputs
Integrated strategy map
Separate key parameter set for each product driven by market pull and technology push.
Decisions
Selection of technologies to be developed
Selection of technological capabilities to be strengthened and pursed
Selection of products programs to implement technologies
Step 3 - Strategy Review
Step 4 - Definition of needs for next generation technologies
Inputs
Integrated Strategy Map
Market based trend models
63
Outputs
Strategic House of Quality for each technology
System Constraints and environment for each technology
Selection Criteria
Decisions
Set target values for key parameter sets.
Voice of Market
Voice of Technology
Step 5 - Review and Confirm Needs
64
Appendix 2: Phase 2 Process Steps
Step 6a - Develop Functional Structure
Inputs
Parent Function and Criteria
Outputs
Subfunctions and subcriteria
Subfunctional interrelations
Decisions: none
Step 6b - Deploy Current Function level to Alternative Solution Concepts
Inputs
Subfunctions and criteria
Outputs
Complete set of system structure matrices for each functional level and each alternative
solution concept.
System structure tree for each alternative solution concept.
Decisions
Selection of alternative solution concepts on each functional level.
Step 6c - Deploy Initial Concept to System Architecture
Inputs
Set of system structure matrices for each alternative solution concept
System structure tree for each alternative solution concept
Outputs
System architectures for each alternative solution concept
65
Hardware concept
Decisions
Most appropriate architecture for each alternative solution concept.
Step 7a,b - Concept Evaluation and Selection
Step 8a - Concept Failure and Conflict Analysis
Inputs
Alternative system structure matrices
Alternative system structure trees
Atlernative system architectures
Alternative hardware concepts
Outputs
Failure modes and interrelations
Critcal parameter sets
Critical System functions
System Conflicts
Decisions
None.
Step 8b - Laboratory Work
Inputs
Failure modes and interrelations
Critical parameter sets
Critical System Functions
System Conflicts
Breadboard Model
Outputs
Significance of Failure modes
66
Significance of System Conflicts
Decisions
Select system conflicts to be eliminated
Select failure modes to be reduced.
Step 9 - Enhance Concepts
Inputs
Failure modes and their significance
Critical parameter sets and their impact on system conflicts
System conflicts and their significance
System structure matrices
System structure trees
System architecture
Hardware concept
Outputs
Enhanced alternative system architectures
Enhanced alternative system structure trees
Enhanced alternative hardware concepts
Critical parameter setting and critical system functions.
Decisions
Select functions to be changed, eliminated, introduced
Select solution concept to be changed, eliminated, introduced
Step 10 - Concept Evaluation and Selection
Inputs
Alternative system structure matrices
Alternative system structure trees
Alternative system architectures
Alternative hardware concepts
67
Outputs
Superior and pre-robust concepts
Decisions
Select concepts to be proceeded into the next step or phase
68
Appendix 3: Phase 3 Process Steps
Step 11 a - Define Functional Metric to Measure Robustness
Selection of the proper functional metric is critical. The metric should capture the
essential physics of the system function, incorporate the effects of noises, and should be
based on the quality loss function concept. Maximizing the signal to noise ratio is
equivalent to minimizing the sensitivity of the system to noises. (Taguchi, 1993).
Step 1 lb - Determine and Select Critical Parameter sets
Critical parameter are those parameters which when satisfied in the system will deliver
the intended function. They are meant to be scientific quantities such as force or pressure
as opposed to geometric quantities such as length or width. Many of these parameters
were made self evident during Failure mode analysis from the prior concept selection
phase.
Step 12a - Design of Experiments 1- Select Alternatives for Evaluation
Orthogonal arrays are utilized to structure an efficient experimental process for spanning
the space identified by the control factors. Orthogonal arrays are balanced, meaning the
equally distribute the effects of each control parameter equally against the other control
parameters. Great care must be taken to manage interactions between control factors.
Step 12b - Design of Experiments 2- Determine, Select and Impose Appropriate Noises
All systems are subjected to a wide array of noises. Robust systems continue to operate
properly even in the presence of these noises. Noises can be external such as temperature
and humidity. Noises can also be internal such as tolerances on critical dimensions.
Step 13 - Perform Experiments - Evaluate Performance of Selected Alternatives
Step 14a,b - Calculate Signal-to-Noise Ratios and Select Best Parameter Settings
Step 15 - Evaluate and Confirm Overall System Robust Performance
69
70
Appendix 4: Phase 4 Process Steps
Step 16a - Criteria for Winning Technologies
Four criteria are evaluated. Superiority, Robustness, Flexibility and Maturity.
Superiority implies the satisfaction-to-cost ratio of the new technology is higher.
Satisfaction is measured with respect to the market and technology based requirements
defined during Phase 1. Robustness or maturity implies the technology can be developed
on a schedule with reasonable accuracy and that all supporting manufacturing
technologies readily available. Robustness or maturity also imply all legal or patent
issues have been cleared through legal counsel. Flexibility implies the technology is
adaptable to a wide range of applications. Flexibility links to Robustness. Robust
designs tend to be less sensitive to variation, hence, are more easily adaptable to new
environments.
Step 16b - Defining metrics to evaluate Selection Criteria
Criteria have been developed in the concept generation and enhancement phase. After
Robustness optimization these criteria may have changed based on the learning during
that phase.
Step 17 - Selecting Winning Technologies
Three outcomes are possible. One, the technology is selected for transfer into a product
program, having met the requirements for Superiority, Robustness, Flexibility and
Maturity. Two, the technology is rejected because of a lack in Superiority, Robustness,
Flexibility or Maturity. Third, the technology is placed back into robustness
development. This occurs when the technology is found to be superior, but lacks the
necessary robustness and maturity to be placed into a product program on a reliable
schedule.
71
Appendix 5 Source Code for Install Water Loss Monte Carlo Analysis
daystoEmpty = int(Globall/Pages-dayIn);
InkVolume = GlobalO;
WaterVolume = WaterIn*InkVolume;
PagestoFailOut = 350;
J= 1;
for i= 1 to days-toEmpty
{
WaterVolume = WaterVolume-RateIn(WaterVolume*Pages-dayin*0.0189/InkVolume); // second term is
water printed each day
InkVolume=InkVolume-RateIn-(Pages-dayIn*0.0189);!!- terms are
water evap grams and ink printed grams per day
if ((WaterVolume/InkVolume) > .5385)
{J=J+ 1;
}I/ add one good ink day.
if (WaterVolume <0)
{
WaterVolume = 0;
}
}/I for i = 1 to days_to_Empty
WaterOut=WaterVolume/InkVolume;
WaterVolumeOut=WaterVolume;
InkVolumeOut=InkVolume;
PagestoFailOut = J * Pages-dayIn;
UsefulInkOut = Pagesjto_FailOut / Global 1;
DaysToFailOut=J;
72
Appendix 6. Detailed Questionairre Responses
1- Never, 2-rarely, 3-Sometimes, 4-Fre uently, 5-Always
R2
Phase Step Q Index R1
4
1
1
1
1
2
2
1
12
5
1
1
3
3
14
4
3
1
4
5
5
1
1
1 6
6
4
7
3
1
17
3
18
8
1
9
4
1
9
10
4
1
1 10
111
11
1
4
1
112
12
13
2
1
113
4
1
14
1
2
3
1
22
15
5
23
16
1
17
5
1
2
2 5
18
3
1
19
4
1
26
1
2 7
20
31
21
1
2
1
4 1
22
4 2
23
1
1
4 3
24
1
4
1
44
25
26
4
1
4 5
4
1
4 6
27
28
1
1
47
29
1
48
30
1
51
5 2
31
4
1
32
2
1
53
4
1
54
33
34
3
1
5 5
2
6 1
35
3
2
6 2
36
3
6 1
37
4
2
38
4
2
6 2
2
6 3
39
4
6 4
40
2
2
4
4
3
2
2
3
3
4
4
4
3
4
3
2
2
4
3
4
4
2
2
R3
3
2
4
2
4
3
4
4
5
5
3
3
3
4
3
4
4
4
2
3
3
3
4
3
3
3
4
3
4
4
3
4
2
4
3
3
4
4
2
2
3
2
3
2
4
4
4
4
4
2
3
4
4
3
3
4
4
4
2
2
3
2
4
2
3
3
3
2
4
1
2
2
4
3
1
2
3
3
4
4
2
4
4
2
2
3
4
4
4
3
4
4
3
3
1
2
3
4
4
4
2
3
4
4
3
2
R9
R8
3
2
4
3
2
2
3
4
4
4
3
2
2
4
2
4
5
1
4
3
2
4
4
R7
R6
3
3
4
2
3
2
4
4
4
4
4
4
2
3
4
4
4
2
2
3
4
4
4
R5
R4
3
3
3
4
4
4
4
3 3
4
3
2
4
4
2
2
2
2
4
2
2
4
2
2
4
3
4
4
3
4
2
2
2
21
3
5
5
3
4
5
4
2
4
2
5
3
2
3
2
4
3
4
3
3
3
4
4
4
2
2
3
3
3
1
R10 Avg
2 2.6
3 2.7
2 3.9
2
3.1
33.0
2 2.9
2
3.4
4 3.8
3 3.5
4 3.7
3
1
2.8
2
4 3.5
2 2.5
2
2
3 3.1
3
3 2.8
4
4 3.6
2 3.7
2
1
2.5
2
2
2 3.2
3.3
3.4
3
2
1
1.7
2.3
3.5
2
4
3.3
3.8
4
4
4
4 3.7
2.0
3.8
4
3.5
2.8
4
1
3.0
3.7
2
2
4
3
3
3
2
4
3
3
3.4
3
3
3
2
2
2
4
4
4
3
2.3
3.2
3.7
3.4
2.9
1.7
73
Appendix 6 continued. Detailed Questionnaire Responses
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
6
6
6
6
6
6
7
8
8
8
8
8
8
8
8
8
9
9
9
10
10
10
11
11
11
12
12
12
12
12
13
14
14
15
16
16
16
16
17
17
417
4
17
5
6
7
1
2
3
1
1
2
3
4
5
6
1
2
3
1
2
3
1
2
3
1
2
1
1
1
2
3
4
1
1
2
1
1
2
3
4
1
2
3
4
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
2
4
4
2
2
2
4
4
1
3
3
4
3
1
3
2
4
2
2
1
2
2
5
2
3
3
3
2
4
2
1
2
2
4
4
2
3
2
3
3
3
3
2
3
3
3
2
2
2
2
4
3
2
3
2
3
3
2
4
2
3
3
2
2
2
3
2
2
3
3
3
2
3
1
3
3
2
3
3
2
3
3
1
2
2
1
1
4
3
2
4
3
4
4
2
4
4
4
3
2
2
2
3
2
_
2
4
3
3
3
3
4
3
4
41
4
4
4
4
4
3
3
4
3
3
3
3
4
1
1
3
4
_
2
4
3
3
4
3
3
4
4
4
3
3
4
4
3
3
4
3
3
3
4
4
3
4
3
3
4
2
4
3
4
4
3
3
3
3
2
3
3
1
2
2
4
2
2
4
4
4
2
3
3
2
4
3
2
2
2
4
4
2
3
2
4
3
3
4
3
4
3
2
4
1
1
3
3
21
2
3
4
3
2
1.8
3.9
3.0
1.6
2.2
2.6
##
3.8
4
3 3.3
4 3.0
4 3.6
3 2.5
4 3.2
4 3.8
3.0
2.2
2.0
1
1.9
1
3.0
4.0
3 3.1
2.5
4 3.4
2.3
3.0
4 3.4
3 2.9
4 4.0
4 3.6
4 3.1
4 3.3
3 2.6
4 3.1
4 3.4
2.5
3.0
2.5
3.0
2
3.3
3 3.2
2.8
2.4
2
4
4
1
1
4
4
4
4
4
4
3
1
2
2
4
2
74
Appendix 7 Questionnaire
The questions are intentionally 'behavior' driven. That is, the respondent reads the
behavior and decides whether that behavior is practiced:
Never
Rarely
Sometimes
Frequently Always
Wording was chosen to be reasonably unambiguous. Where there is ambiguity, I have
included descriptive words in the Terminology portion of this thesis.
Phase 1 Technology Strategy
Step 1
1. Technologists and Product Marketing work well together
defining the best mix of technologies and markets
2. Markets identified and well characterized.
3. Each competitor is well characterized in the market.
4. Key customer satisfaction parameters are identified for
each market segment.
5. Provide market-perspective for a decision on which
technologies to focus on.
6. Technologies identified which link directly to customer
satisfaction parameters.
7. Core resource capabilities required defined for each new
technology.
8. Provide technology perspective for a decision on which
technologies to focus on.
9. Market trends plotted.
10. Technology trends plotted.
11. Technology limits are established and compared to market
trends.
12. Technology Risk assessed.
13. Business Impact of technology assessed.
Step 2 - Develop Integrated Technology Strategy
1. Technology elements mapped into a product platform
strategy, identifying derivative products.
2. Reuse matrix developed showing which elements are
reused in each product derivative
3. Make or buy decisions based upon company's
technological ability and resource availability.
4. Resource requirements determined.
5. Timeline estimates created
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
75
6. Budget requirements estimated
7. Key parameters sets for each product are determined
which will meet projected market needs.
N
N
R
R
S
S
F
F
A
A
1. Integrated technology strategy is reviewed and consistent
with corporate strategy and vision
N
R
S
F
A
Step 4 - Definition of needs for next generation technologies
1. House of Quality built for each technology
2. Market Pull requirements clearly defined
3. Technology push requirements clearly defined
4. System constraints defined for each technology
5. Environmental constraints defined for each technology
6. Selection criteria defined for each technology.
7. Main function of each technology defined.
8. Target values for key parameter sets defined.
N
N
N
N
N
N
N
N
R
R
R
R
R
R
R
R
S
S
S
S
S
S
S
S
F
F
F
F
F
F
F
F
A
A
A
A
A
A
A
A
N
N
N
N
N
R
R
R
R
R
S
S
S
S
S
F
F
F
F
F
A
A
A
A
A
N
R
S
F
A
N
R
S
F
A
R
S
F
A
R
S
F
A
R
S
F
A
R
S
F
A
R
S
F
A
R
R
S
S
F
F
A
A
Step 3 - Strategy Review
Step 5 - Review and confirm needs
1.
2.
3.
4.
5.
Technology risks reviewed.
Market place risks reviewed.
Resource allocation confirmed
Budget requirements confirmed
Schedule estimated.
Phase 2 Concept Generation and Enhancement
Step 6a - Develop Functional Structure
1. Functions decomposed into subfunctions in solutionneutral space, that is, without regard to any design
concept.
2. Important interrelations between subfunctions highlighted
Step 6b - Deploy Current Function level to Alternative Solution Concepts
1. Appropriate design parameter determined for each
N
subfunction.
2. Design parameters checked against criteria and
N
constraints.
3. Likely System conflicts between design parameters
N
identified.
4. House of Quality or equivalent built to show linkage
N
between functional requirements and design parameters
N
5. House of Quality or equivalent built to show harmful and
useful interactions between design parameters
6. Target values established for each design parameter.
N
7. Tolerance Range established for each design parameter.
N
76
Step 6c - Deploy Initial Concept to System Architecture
1. Apply Design Structure Matrix to re-allocate system
elements and their functions into modules, that is, highly
interrelated functions allocated into individual modules
and work teams.
2. Great care taken to assure the architecture has minimal
interrelations between modules.
3. Multiple System Architectures proposed, rather than
keying in early on a single solution.
Step 7a,b - Concept Evaluation and Selection
1. See step
Step 8a - Concept Failure and Conflict Analysis
1. Failure modes predicted
2. Critical parameters identified for each failure mode
3. Noise factors identified which may cause failure modes
4. System Conflicts are identified
5. New concepts developed to break conflicts, rather than
compromise between conflicts.
6. Failure modes correlated to System Failures
Step 8b - Laboratory Work
1. Lab experiments performed to assess failure mode impacts
on System performance
2. Lab experiments performed to assess impact of system
conflicts on system performance
3. Conflicts are identified to be eliminated
Step 9 - Enhance Concepts
1. TRIZ (or related methods) conflict elimination
methodology applied.
2. Inventive problem solving methods (such as ARIZ) are
applied to break system conflicts.
3. Failure mode impacts reassessed for Enhanced concepts.
Step 10 - Concept evaluation and Selection
1. Criteria for Concept selection created
2. Superiority criteria derived from market and technology
based requirements.
3. Robustness and flexibility criteria included based upon
breadboard models.
Phase 3 Robustness Development and Analysis
Step 11 a - Define functional metric to measure robustness
N
R
S
F A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
N
N
N
N
R
R
R
R
R
S
S
S
S
S
F
F
F
F
F
A
A
A
A
A
N
R
S
F A
N
R
S
F
N
R
S
F A
N
R
S
F A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
N
R
R
S
S
F
F
A
A
N
R
S
F
A
N
R
S
F
A
A
77
N
R
S
F
A
N
R
S
F
A
Step 1 lb - Determine and select Critical Parameter sets
1. Critical parameters selected for each functional metric.
N
R
S
F
A
Step 12a - Design of Experiments 1 - Select Alternatives for
Evaluation
1. Orthogonal arrays constructed to span the critical
parameter space.
N
R
S
F
A
N
R
S
F
A
N
N
R
R
S
S
F
F
A
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
N
R
S
F
A
1. Functional metrics to optimize selected based upon their
ability to capture the essential physics of the system
function.
2. Signal- to- noise ratios are selected based upon the type of
quality loss function expected.
Step 12b - Design of Experiments 2 - Determine, select and
impose appropriate Noises
1. Noises selected broad enough to cause failure modes to
appear.
2. Environmental noises selected
3. Tolerance noises selected.
4. Customer usage noises selected.
Step 13 - Perform experiments - Evaluate Performance of
selected alternatives
1. Experiments run with combinations of noises and control
factors.
Step 14 - Calculate signal-to-noise ratios and select best
parameter settings
1. Signal-to-noise ratios are used to select best control factors
2. Adjustment control factors utilized to move the response
to target.
Step 15 - Evaluate and Confirm Overall System Robust
Performance
1. The system is set up and run with the selected best control
factors to verify performance.
Phase 4 Technology Selection, Transfer, and Integration
Step 16 - Criteria for Winning Technologies
1. Superiority criteria metrics defined based upon market and
technology requirements and independence axiom.
2. Robustness criteria metrics defined
3. Flexibility criteria metrics defined.
78
4. Maturity criteria metrics defined based upon producibility,
safety and legal issues.
Step 17 - Selecting Winning Technologies
1. Technologies selected meeting established Market Quality
goals.
2. Technologies selected meeting established cost criteria
3. Technologies selected meeting program schedule criteria.
4. Promising technologies not yet ready for a product
program are placed back into robustness development.
N
R
S
F
A
N
R
S
F
A
N
R
S
F
N
R
S
F
A
A
N
R
S
F
A
79