TRIZ Within the Context of The Kano Model or Adding the Third Dimension
to Quality
Steve Ungvari, SPI, Inc.
810-220-8440
sufield@aol.com
Purpose:
The purpose of this paper is to link the evolution of quality with the
emerging body of knowledge contained in the TRIZ methodology. Understanding how
TRIZ integrates with quality will arm the reader with a more potent approach to
successfully competing in the marketplace. Author's Note: Writing this paper was
precipitated by Dr. Kano's expression of interest in TRIZ in his discussions
with Bou Bertsch of Ideation International in the Netherlands.
Introduction:
The notion of inherent quality, of products and services that
are deemed to be superior as opposed to inferior, has been discussed and debated
for centuries. Philosophers such as Aristotle, Rene Descartes and John Locke
have provided different facets of the definition of quality.
In the 1930s, Dr. Walter A. Shewhart began developing his
definition of quality through the use of statistics and what is now termed
"Statistical Quality Control." During and after World War II, the
statistical variations on the meaning of quality continued in the United States
and Japan with the work of W.E. Deming, Joseph Juran and Armand V. Feigenbaum.
In Japan, the work of Kaoru Ishikawa, Shigeru Mizuno, Shoji Shiba, Yoji Akao and
Genechi Taguchi provided additional perspectives and a much larger context in
which quality is germane, e.g., "Total Quality Management (TQM)" and
"Loss to Society."
The Kano Model
In the late 1970s Dr. Noriaki Kano of Tokyo Rika University
further refined the notion of quality derived partially from his study of
Herzberg's "Motivator-Hygiene Theory." Whereas many of the previous
definitions of quality were linear and one dimensional in nature, i.e., good or
bad, small versus large loss to society, Dr. Kano integrated quality along two
dimensions. The two dimensions were: 1) The degree to which a product or service
performs, and 2) The degree to which the user is satisfied. See Figure 1.

Figure 1.
The juxtaposing of the quality parameters of performance and
user satisfaction in a two-axis plot created the ability to define quality in a
more sophisticated and holistic manner. The correlation of quality on two axes
led Dr. Kano to three unique definitions of quality, namely: Basic Quality,
Performance Quality and Excitement Quality. See Figure 2.

Figure 2.
The Three Types of Quality
The Kano Model is very useful in providing a level of
sophistication not available in a one-dimensional model of quality. If the level
of customer satisfaction is plotted on a vertical axis, and the degree that the
product or service has achieved a given performance attribute on the horizontal
axis, different types of customer wants and needs can be shown to cause widely
different responses. The model shows that the customer's responses can be
classified into three types as shown in Figure 2 above, i.e., Basic, Performance
and Excitement.
Basic Quality
The dynamics of Basic Quality indicate that some customer
requirements, if not achieved. cause high dissatisfaction, and, if they are
achieved, have only a limited effect on causing customer satisfaction. The
reason for this is that this quality type is expected by the customer.
For example, when going into a restaurant for a meal, the customer expects there
to be a place setting. If there isn't one, the customer will be dissatisfied. If
there is a place setting, no credit will be given because there is supposed to
be one. On the other hand, having many place settings does not create any
additional satisfaction.
In the Automotive world, the customer expects a vehicle to
start easily, provide a safe driving environment, and be free of squeaks,
rattles and wind noise. Satisfaction is not created if a vehicle does these
things. However, if these "basic" needs are not met, the result is
devastating to the reputation and business of the Original Equipment
Manufacturer. Basic quality provides "down-side risk" with very little
"up-side potential" for customer satisfaction.
Customers will express violation of basic quality attributes
by complaining. In industry, basic quality is typically measured by customer
complaints, warranty data, product recalls, number of lawsuits,
things-gone-wrong (TGW) and other failure reports.
Performance Quality
A second type of customer requirement generates satisfaction
proportional to the performance of the product. This quality type is referred to
as Performance Quality. Performance quality attributes generally cause a linear
response. Increased levels of satisfaction are caused by increased levels of
achievement. The customer in a restaurant expects his/her order to be taken
promptly and accurately and the food delivered in a reasonable period of time.
The better the restaurant meets these needs, the more satisfied he/she is.
Customers freely express their desires relative to
performance quality when they are asked. This type of information is often
called the Voice of the Customer, because these are the types of things that
customers like to talk about. They want the car to perform one way or another,
and have this or that feature. We measure them using customer research tools,
feature rating surveys and ride/drive evaluations, asking how well a product
performs relative to a graduated scale.
An automotive customer expects a vehicle to have good engine
performance, but performance is gauged relative to expectations. Someone that is
buying a small economy car will not expect the same raw performance as they
would in a "muscle" car. Generally speaking, however, the better the
performance, the greater the satisfaction.
Excitement Quality
The third quality type generates positive satisfaction at any
level of execution. This is referred to as Excitement Quality. Excitement is
generated because the customer received some feature or attribute that they did
not expect, ask for, or even think was possible. For example, if the restaurant
provides a glass of champagne "on the house," the customer will be
pleasantly surprised. Likewise, the customer of a vehicle may not expect a car
to have a built-in global positioning system, a maintenance-free battery, heated
seats, etc., but will be pleased when they are discovered during the ownership
experience.
Customers generally do not articulate excitement attributes
in customer surveys, because they do not know that they want them. In order to
generate customer excitement and brand loyalty, companies must leverage their
creative resources to identify ideas and innovations that cause customer
excitement. Excitement quality becomes the special reason why customers will
make a specific company the default choice over the competition and return to
buy again and again.
Excitement attributes cause an exponential response. Small
improvements in providing excitement items cause relatively large increases in
satisfaction. Several small excitement features may accumulate and generate
sheer delight on the part of customers.
The Kano model is useful for providing a two-dimensional
model of quality. In actual application, requirements do not always fall neatly
into one of the three categories. Very high levels of performance relative to
expectations can act like excitement attributes and provide real reasons to
choose a particular product over its competitor. Likewise, an intended
excitement feature executed badly will cause dissatisfaction.
Customer Requirements Over Time
It has also been observed that customers’ requirements
change over time. Sources of excitement when they were first introduced tend to
become expected as the market becomes familiar and saturated with them. In time,
excitement quality will become a performance item, and, with the passage of
time, quite possibly a basic requirement.
Automatic transmissions which initially provided excitement
because they made cars much easier to drive are classified today as a basic
quality item. For a time, customers made comparisons because some designs
performed better than others, but, in today's vehicles, customers demand that
automatic transmissions perform flawlessly. Customers talk about them only if
there is a problem. Figure 3 shows the dynamic of time.

Figure 3.
Kano Summary
There is no doubt that to be competitive, products or
services must flawlessly execute all three quality types. Meeting customers’
basic quality needs provides the foundation for the elimination of
dissatisfaction and complaints. Exceeding customers’ performance expectations
creates a competitive advantage, and innovations differentiating the product and
the organization creates an excited customer.
TRIZ and the Archeological Analog
TRIZ, the Russian language acronym for the Theory of
Inventive Problem Solving, is the product of an exhaustive analysis of the
world's most creative inventions as described primarily in patent literature.
The analysis of some three million inventions over the past fifty years can be
compared to an archeological reconstruction of life forms as recorded in the
fossil record. In a sense, one can think of TRIZ as an encapsulation of the
historical record of the evolution of product quality. TRIZ theory, as in
archeology, is a product of the cataloguing and analysis of empirical data. As
an archeologist probes the remains of the fossil record, they seek to understand
what natural phenomena led to the emergence of newer and better (higher-quality)
life forms. In a similar fashion, Genrich Altshuller observing the
"natural" quality progression of products, discovered a series of
repeatable patterns he called The Laws of Technological Systems Evolution.
In other words, just as natural forces have been discovered to produce
higher-quality life forms, the analog of how technological systems evolve was
uncovered by the extensive analytical work of Altshuller and his colleagues.
There are several significant differences between
archeological reconstruction and TRIZ. In archeology, much of the record is not
complete enough to allow for unassailable conclusions. The archeological records
also contain large chronological gaps making it impossible to extrapolate
vectors of evolution. This is clearly not the case with TRIZ. In TRIZ, there is
a complete record making reconstruction of systems evolution clear to the point
of predictability.
Adding the Third Dimension to Quality
The two dimensional model of quality, as described by Kano,
is itself proof of how systems (any system) evolves. One of the laws of systems
evolution is the Law of Dynamicity. This law states that any system will become
more flexible and dynamic over time. Another law states that single (mono)
systems will combine with other mono systems to form new "bi-systems."
The conjoining of Quality and TRIZ is an example of this law.
The advantage of a bi-system is that it provides additional
functionality with increased efficiency and less consumption of resources as
opposed to separate mono systems. This is precisely the rationale for combining
Quality, as expressed in the Kano Model, and TRIZ into a powerful three
dimensional bi-system as shown in Figure 4.

Figure 4.
Just as the Kano Model is composed of three elements, the
TRIZ interface is likewise composed of three separate but complementary subsets
including: 1) Anticipatory Failure Determination1 (AFD),
2) Classical TRIZ Problem-Solving Tools, and Directed Evolution2
(DE). Anticipatory Failure Determination and Directed Evolution are the latest
additions to the TRIZ "toolbox." Both AFD and DE have been developed
through the Kishinev School under the leadership of Boris Zlotin and Alla Zusman.
The classical tools of TRIZ are the product of Altshuller's patent work from
1946 to 1985.
The third dimension to quality made possible by TRIZ provides
organizations with powerful tools to fully leverage each of the three quality
types. As important as it is to understand each of the three quality types, it
is equally important to be able to take specific actions on the unique
challenges posed be each type. The three TRIZ tools provide the quality
professionals with the ability to explore, improve and optimize the full
technological solution space for each quality type.
Basic Quality and AFD
The Basic Quality dimension on the Kano Model addresses
features or functions that are "demanded," yet unspoken. While this
may sound contradictory, it is because basic quality is deemed to be so obvious
that articulation of it seems pointless. Basic Quality, however, is a disaster
waiting to happen. A customer of an automobile would not specify that they want
fuel tanks that do not explode. An engineer would never deliberately design a
fuel tank to explode. Recent history, however, from the Ford Pinto, the GM Light
Truck side-saddle fuel tanks to the Chevrolet Malibu rear-end $4.9
billion-dollar judgment vividly exemplify that Basic Quality is repeatedly
violated and the consequences that follow when it is.
How can engineers, within the context of product development,
do a better job of designing out these devastatingly inherent flaws?
Paradoxically, violations of Basic Quality can be prevented by proactively
exploring every conceivable method to create such failures. It is this bit of
logic that makes AFD fundamentally different in approaching the elimination of
failure modes.
Traditional failure prediction tools such as Failure Mode
& Effects Analysis (FMEA), Fault Tree Analysis (FTA) and Hazards and
Operations Analysis (HAZOP) are predicated on answering the question: "What
can go wrong?" In these traditional methods, since the point of departure
is a conceptualized articulation of the current system, the process follows
traditional failure scenarios. This logic is lacking structural validity because
it is subject to Psychological Inertia (PI). An engineer will analyze a
situation only from his or her known paradigm. The constraints of the engineers
paradigm will limit the failure analysis to something less than 100% of the
available catastrophe space.
AFD, on the other hand, inverts the situation by asking the
question: "How can I destroy the system?" This question presents an
"inverted" problem as well as an "inventive" one. There are
two distinct benefits from this inverted approach. First, viewing the system
with the intent to destroy it provides a fresh analytical perspective, and
second, it makes the problem "inventive," thereby bringing to bear the
full arsenal of TRIZ tools and techniques. The application of all of the TRIZ
tools eliminates Psychological Inertia ensuring a thorough rigorous analysis of
potential violations of Basic Quality.
Performance Quality and Classical TRIZ
As the name implies, Performance Quality is characterized by
the ability of the product to meet desired levels of achievement. Performance
Quality is also characterized by the fact that the user defines the level of
"goodness" that is desired. The advantage to the quality professional
in dealing with performance issues is that a series of metrics can be
established to keep score.
Given the linear nature of performance quality, it is
axiomatic that achieving higher levels of performance, especially in a cost
effective way, will create product differentiation and competitive advantage.
Understanding how to overcome the barriers to low-cost performance increases is
the key to moving the performance index ahead of the competition.
Product performance is limited, to a great extent, by
inherent system conflicts that act as barriers to increasing performance levels.
A typical conflict, for example, is weight versus strength. In TRIZ terms, this
is called a Technical Contradiction. The essence of the contradiction is that to
increase strength, the typical way of accomplishing that is to increase the
weight of the object. Increased weight, however, is undesirable as is reduced
strength. These conflicts are usually resolved by meeting the conflicting
parameters "halfway," vis a' vis, a compromise solution.
The classical tools of TRIZ, including the 40 Inventive
Principles, the Contradiction Matrix, Substance-Field Modeling, Standard
Solutions, the Algorithm for Inventive Problem Solving (ARIZ), and Effects
(physical chemical and geometrical) plus the modern tools developed since 1985
including Problem Formulation3 and the System of
Operators4 are uniquely designed to tackle the issue
of elimination of system conflicts. To return to the previously mentioned
conflict, it is obvious that if strength can be increased without paying a
weight penalty, the product would possess advantages over competitive
alternatives. This has been accomplished by use of composite materials,
honeycomb structures, etc.
It is beyond the scope of this short article to explain all
of the TRIZ tools mentioned above as there are volumes of printed matter written
to accomplish that. Suffice it to say that the classical TRIZ problem-solving
tools will enable the quality, engineering and product development professional
with the elimination of inherent system conflicts in a cost-effective way. When
this is accomplished, the result is increased cost-effective performance and
greater customer satisfaction.
Excitement Quality and Directed Evolution
Excitement Quality addresses what are termed as
"latent" or unmet user needs. These needs are latent because users are
not consciously aware of their need. Users will oftentimes resort to
"workarounds," oblivious to the fact that the product does not fully
meet all of their needs. When a user discovers an excitement feature, they are
pleasantly surprised and even delighted. Within the context of the Kano Model,
excitement features provide the greatest opportunity to differentiate the
product.
The TRIZ interface to produce dimensional depth to Excitement
Quality is Directed Evolution. Directed Evolution is itself the latest
derivative of Technological Forecasting. Technological Forecasting is a TRIZ
capability because of Altshuller's discovery of the Laws of Technological
Evolution. These eight laws represent repeatable patterns depicting the natural
progression of products through Life Cycle "S-curves." Through the
efforts of Zlotin, Zusman and others, additional gradations to these laws have
been provided called "lines of evolution." For each major law, there
are a number of lines that refine and pinpoint the understanding of the
evolutionary life cycle progression. The lines of evolution allow organizations
insights into future product derivatives. These derivatives will occur
"naturally" over time or they can be "directed" to appear as
a part of an organization’s product development strategy.
For example, the law of Dynamicity indicates that systems
will become flexible and dynamic over time. A well-known example of this law is
the Snake Lightää introduced several years ago by Black & Decker. The
Snake Lightää proved so popular that Black & Decker couldn't produce them
fast enough. This product derivative was totally predictable well before it was
ever conceptualized. Had a competitor known about Directed Evolution and
introduced the product before it was naturally conceived by Black & Decker,
they, and not Black & Decker, would have reaped the goodwill and financial
benefits.
The power of Directed Evolution is the ability of an
organization to predict the full spectrum of future product scenarios and then
to select the most promising one. Having done that, it is possible to create a
technological roadmap and establish patent fences to protect a company’s
intellectual property and future income stream.
Summary
The understanding of Quality has progressed over the years
into a more sophisticated model integrating product performance with customer
satisfaction. This two-dimensional model provides the foundation for a
three-dimensional model making it possible to utilize powerful invention-based
tools to explore, understand and exploit the entire product possibility space.
TRIZ, like the archeological record, provides an encapsulated
view of how and why products evolve into more robust derivatives. Competency in
the complete TRIZ tool-set makes it possible to foresee potential catastrophic
failures, be able to eliminate inherent system contradictions, and direct future
new product derivatives to address latent requirements.
The Kano Model, coupled with the TRIZ interface, represents
the most complete and powerful conceptualization of the quality dynamic and the
scientific ability to exploit it.
Acknowledgements
The author wishes to acknowledge the invaluable contribution
of the following individuals:
-
Mr. Zion Bar-El, President and CEO of Ideation
International for challenging me to write this article
-
Ms. Alla Zusman, Ms. Karen Pike, Mr. Boris Zlotin, Mr.
Dana Clarke, and Dr. Stan Kaplan for their editorial comments
Endnotes
1, 2 Anticipatory Failure
Determination and Directed Evolution are Trademarks of Ideation International,
Inc.
3, 4 Problem Formulation and
System of Operators are Trademarks of Ideation International, Inc.