Answer questions by reading articles and chapters

lni

David A. Garvin Competing
on the

eight dimensions
of quahty

U.S. managers know that they have to
improve the quality of their products hecause, alas,
U.S. consumers have told them so. A survey in 1981 re-
ported that nearly 50% of U.S. consumers helieved that
the quality of U.S. products had dropped during the
previous five years; more recent surveys have found
that a quarter of consumers are “not at all” confident
that U.S. industry can he depended on to deliver reli-
ahle products. Many companies have tried to upgrade
their quality, adopting programs that have heen staples
of the quality movement for a generation: cost of qual-
ity calculations, interfunctional teams, reliahility engi-
neering, or statistical quality control. Few companies,
however, have leamed to compete on quality. Why?

U.S. consumers doubt that
U.S. companies can

deliver quality.

Part of the prohlem, of course, is that un-
til Japanese and European competition intensified, not
many companies seriously tried to make quality pro-
grams work even as they implemented them. But even
if companies had implemented the traditional princi-
ples of quality control more rigorously, it is douhtful
that U.S. consumers would be satisfied today. In my

David A. Garvin is an associate professor
of business administration at the Harvard School.
He has published numerous articles on quahty in HBR and
other iouinals and is the recipient of McKinsey Awards for
best HBR article in 1982 and 1983. This article draws from
his book. Managing Quality, to be pubhshed by Free Press.

view, most of those principles were narrow in scope;
they were designed as purely defensive measures to
preempt failures or eliminate “defects.” What man-
agers need now is an aggressive strategy to gain and hold
markets, with high quality as a competitive linchpin.

Quality control

To get a hetter grasp of the defensive
character of traditional quality control, we should un-
derstand what the quality movement in the United
States has achieved so far. How much expense on qual-
ity was tolerahle? How much “quality” was enough?
In 1951, Joseph Juran tackled these questions in the
first edition of his Quahty Control Handbook, a publi-
cation that became the quality movement’s bible. Juran
observed that quality could be understood in terms of
avoidable and unavoidable costs: the former resulted
from defects and product failures like scrapped materi-
als or labor hours required for rework, repair, and com-
plaint processing; the latter were associated with pre-
vention, i.e., inspection, sampling, sorting, and other
quahty control initiatives. Juran regarded failure costs
as “gold in the mine” because they could be reduced
sharply by investing in quality improvement. He esti-
mated that avoidable quality losses typically ranged
from $500 to $ 1,000 per productive operator per year-
big money back in the 1950s.

Rcadingjuran’s hook, executives inferred
roughly how much to invest in quality improvement:
expenditures on prevention were justified if they were
lower than the costs of product failure. A corollary
principle was that decisions made early in the produc-
tion chain (e.g., when engineers first sketched out a
product’s design) have implications for the level of

102 Harvard Review November-December 1987

“Ispoke to my attorney today, Wendell, and I’m thinking of
putting you intopiay.”

quality costs incurred later, hoth in the factory and the
field.

In 1956, Armand Feigenbaum took
Juran’s ideas a step further by proposing “total quality
control” (TQC). Companies would never make high-
quality products, he argued, if the manufacturing de-
partment were forced to pursue quality in isolation.
TQC called for “interfunctional teams” from market-
ing, engineering, purchasing, and manufacturing.
These teams would share responsihility for all phases
of design and manufacturing and would disband only
when they had placed a product in the hands of a satis-
fied customer-who remained satisfied.

Feigenbaum noted that all new prod-
ucts moved through three stages of activity: design con-
trol, incoming material control, and product or shop-
floor control. This was a step in the right direction. But
Feigenhaum did not really consider how quality was
first of all a strategic question for any business; how,
for instance, quality might govern the development of
a design and the choice of features or options. Rather,
design control meant for Feigenbaum mainly prepro-
duction assessments of a new design’s manufacturabil-
ity, or that projected manufacturing techniques should
be debugged through pilot runs. Materials control in-
cluded vendor evaluations and incoming inspection
procedures.

In TQC, quality was a kind of burden to
be shared-no single department shouldered all the re-
sponsibility. Top management was ultimately account-
able for the effectiveness of the system; Feigenbaum,
like Juran, proposed careful reporting of the costs of

quality to senior executives in order to
ensure their commitment. The two also
stressed statistical approaches to qual-
ity, including process control charts that
set limits to acceptable variations in
key variables affecting a product’s pro-
duction. Tbey endorsed sampling proce-
dures that allowed managers to draw
inferences about the quality of entire
batches of products from the condition
of items in a small, randomly selected
sample.

Despite their attention to
these techniques, furan, Feigenbaum,
and other experts like W. Edwards Dem-
ing were trying to get managers to see
beyond purely statistical controls on
quality. Meanwhile, another branch of
the quality movement emerged, relying
even more heavily on probability theory
and statistics. This was “reliability en-
gineering,” which originated in the aero-
space and electronics industries.

In 1950, only one-third of the
U.S. Navy’s electronic devices worked

properly A subsequent study by the Rand Corporation
estimated that every vacuum tube the military used
had to be backed by nine others in warehouses or on
order. Reliability engineering addressed these problems
by adapting the laws of probability to the challenge of
predicting equipment stress.

Reliability engineering measures led to;

Techniques for reducing failure rates
while products were still in the design
stage.

Failure mode and effect analysis, which
systematically reviewed how altema-
tive designs could fail.

Individual component analysis, which
computed the failure probability of key
components and aimed to eliminate or
strengthen the weakest links.

Derating, which required that parts be
used below their specified stress levels.

Redundancy, which called for a parallel
system to back up an important compo-
nent or subsystem in case it failed.

Naturally, an effective reliability pro-
gram required managers to monitor field failures close-
ly to give company engineers the information needed
to plan new designs. Effective field failure reporting

Quality dimensions 103

also demanded the development of systems of data col-
lection, including return of failed parts to the labora-
tory for testing and analysis.

Now, the proponents of all these ap-
proaches to quality control might well have denied
that their views of quality were purely defensive. But
what else was implied by the solutions they stressed-
material controls, outgoing batch inspections, stress
tests? Perhaps the best way to see the implications of
their logic is in traditional quality control’s most ex-
treme form, a program called “Zero Defects.” No other
program defined quality so stringently as an absence of
failures-and no wonder, since it emerged from the de-
fense industries where the product was a missile whose
flawless operation was, for obvious reasons, imperative.

In 1961, the Martin Company was build-
ing Pershing missiles for the U.S. Army. The design of
the missile was sound, but Martin found that it could
maintain high quality only through a massive program
of inspection. It decided to offer workers incentives to
lower the defect rate, and in December 1961, delivered
a Pershing missile to Cape Canaveral with “zero dis-
crepancies.” Buoyed by this success, Martin’s general
manager in Orlando, Florida accepted a challenge, is-
sued by the U.S. Army’s missile command, to deliver
the first field Pershing one month ahead of schedule.
But he went even further. He promised that the missile
would be perfect, with no hardware problems or docu-
ment errors, and that all equipment would be fully op-
erational 10 days after delivery (the norm was 90 days
or more).

Quality means
pleasing consumers,

not just protecting them
from annoyances.

Tvo months of feverish activity fol-
lowed; Martin asked all employees to contribute to
building the missile exactly right the first time since
there would be virtually no time for the usual inspec-
tions. Management worked hard to maintain enthusi-
asm on the plant floor. In February 1962, Martin deliv-
ered on time a perfect missile that was fully operational
in less than 24 hours.

This experience was eye-opening for
both Martin and the rest of the aerospace industry After
careful review, management concluded that, in effect,
its own changed attitude had assured the project’s suc-
cess. In the words of one close observer: “The one time
management demanded perfection, it happened!”‘

Martin management thereafter told employees that
the only acceptable quality standard was “zero de-
fects.” It instilled this principle in the work force
through training, special events, and by posting quality
results. It set goals for workers and put great effort into
giving each worker positive criticism. Formal tech-
niques for problem solving, however, remained lim-
ited. For the most part, the program focused on
motivation-on changing the attitudes of employees.

Strategic quality
management

On the whole, U.S. corporations did not
keep pace with quality control innovations the way a
number of overseas competitors did. Particularly after
World War II, U.S. corporations expanded rapidly and
many became complacent. Managers knew that con-
sumers wouldn’t drive a VW Beetle, indestructible as it
was, if they could afford a fancier car-even if this
meant more visits to the repair shop.

But if U.S. car manufacturers had gotten
their products to outlast Beetles, U.S. quality managers
still would not have been prepared for Toyota Corollas
– o r Sony televisions. Indeed, there was nothing in the
principles of quality control to disabuse them of the
idea that quality was merely something that could
hurt a company if ignored; that added quality was the
designer’s business-a matter, perhaps, of chrome and
push buttons.

The beginnings of strategic quality
management cannot be dated precisely because no sin-
gle book or article marks its inception. But even more
than in consumer electronics and cars, the volatile
market in semiconductors provides a telling example
of change. In March 1980, Richard W. Anderson, gen-
eral manager of Hewlett-Packard’s Data Systems Divi-
sion, reported that after testing 300,000 16K RAM
chips from three U.S. and three Japanese manufactur-
ers, Hewlett-Packard had discovered wide disparities
in quality. At incoming inspection, the Japanese chips
had a failure rate of zero; the comparable rate for the
three U.S. manufacturers was between 11 and 19 fail-
ures per 1,000. After 1,000 hours of use, the failure rate
of the Japanese chips was between 1 and 2 per 1,000;
usable U.S. chips failed up to 27 times per thousand.

Several U.S. semiconductor companies
reacted to the news impulsively, complaining that the
Japanese were sending only their best components to

1 lames EHalpin,
Zero Defects
(New York:
McGraw-Hill, 19661, p. 15.

104 Harvard Review November-December 1987

the all-important U.S. market. Others disputed the
basic data. The most perceptive market analysts, how-
ever, noted how differences in quahty coineided with
the rapid ascendancy of Japanese chip manufacturers.
In a few years the Japanese had gone from a standing
start to significant market shares in both the 16K and
64K chip markets. Their message-intentional or n o t –
was that quality could be a potent strategic weapon.

U.S. semiconductor manufacturers got
the message. In 16K chips the quality gap soon closed.
And in industries as diverse as machine tools and ra-
dial tires, each of which had seen its position erode in
the face of Japanese competition, there has been a new
seriousness about quality too. But how to translate
seriousness into action? Managers who are now deter-
mined to compete on quality have been thrown back
on the old questions: How much quality is enough?
What does it take to look at quality from the custom-
er’s vantage point? These are still hard questions today.

Some consumer preferences
should be treated as absolute

performance standards.

To achieve quality gains, I believe, man-
agers need a new way of thinking, a conceptual bridge
to the consumer’s vantage point. Obviously, market
studies acquire a new importance in this context, as
does a careful review of competitors’ products. One
thing is certain: high quality means pleasing consum-
ers, not just protecting them from armoyances. Product
designers, in tum, should shift their attention from
prices at the time of purchase to life cycle costs that in-
clude expenditures on service and maintenance-the
customer’s total costs. Even consumer complaints play
a new role hecause they provide a valuable source of
product infonnation.

But managers have to take a more pre-
liminary step-a crucial one, however obvious it may
appear. They must first develop a clear vocahulary with
which to discuss quality as strategy. They must break
down the word quality into manageable parts. Only
then can they define the quality niches in which to
compete.

I propose eight critical dimensions or
categories of quality that can serve as a framework for
strategic analysis: performance, features, reliability,
conformance, durability, serviceabihty, aesthetics, and
perceived quality- Some of these are always mutually
reinforcing; some are not. A product or service can
rank high on one dimension of quality and low on an-
other-indeed, an improvement in one may be achieved

only at the expense of another. It is precisely this inter-
play that makes strategic quality management possi-
ble; the challenge to managers is to compete on select-
ed dimensions.

1 Performance

Of course, perfonnance refers to a prod-
uct’s primary operating characteristics. For an auto-
mobile, performance would include traits like acceler-
ation, handling, cruising speed, and comfort; for a
television set, performance means sound and picture
clarity, color, and the abihty to receive distant stations.
In service businesses – say, fast food and airlines-
performanee often means prompt service.

Because this dimension of quality in-
volves measurable attributes, brands can usually be
ranked objectively on individual aspects of perfor-
mance. Overall performance rankings, however, are
more difficult to develop, especially when they involve
benefits that not every consumer needs. A power shov-
el with a capacity of 100 cubic yards per hour will “out-
perform” one with a capacity of 10 cubic yards per
hour. Suppose, however, that the two shovels possessed
the identical capacity-60 cubic yards per h o u r – b u t
achieved it differently: one with a 1-cubic-yard bucket
operating at 60 cyeles per hour, the other with a 2-
cubic-yard bucket operating at 30 cycles per hour. The
capacities of the shovels would then be the same, but
the shovel with the larger bucket could handle mas-
sive boulders while the shovel with the smaller bucket
eould perform precision work. The “superior per-
former” depends entirely on the task.

Some cosmetics wearers judge quality
by a product’s resistance to smudging; others, with
more sensitive skin, assess it by how well it leaves skin
ini tat ion-free. A 100-watt light bulb provides greater
eandlepower than a 60-watt bulb, yet few customers
would regard the difference as a measure of quality.
The bulbs simply belong to different performanee
classes. So the question of whether performanee differ-
ences are quality differences may depend on circum-
stantial preferences-but preferences based on func-
tional requirements, not taste.

Some performance standards are based
on subjective preferences, but the preferences are so
universal that they have the force of an objective stan-
dard. The quietness of an automobile’s ride is usually
viewed as a direct reflection of its quality. Some people
like a dimmer room, but who wants a noisy car?

2 This framework firs I appeared,
in a preliminary form,
in my ariiele

“Whal Dues’Product Quality’ Really Mean?”
Slaiin Management Review, Fall 19S4.

Quality dimensions 105

2 Features

Similar thinking can he applied to fea-
tures, a second dimension of quality that is often a sec-
ondary aspect of performance. Features are the “bells
and whistles” of products and services, those charac-
teristics that supplement their basic functioning. Ex-
amples include free drinks on a plane, permanent-press
cycles on a washing machine, and automatic tuners on
a color television set. The line separating primary
performance characteristics from secondary features is
often difficult to draw. What is crucial, again, is that
features involve objective and measurable attributes;
objective individual needs, not prejudices, affect their
translation into quality differences.

To many customers, of course, superior
quality is less a reflection of the availability of particu-
lar features than of the total number of options avail-
able. Often, choice is quality: buyers may wish to cus-
tomize or personalize tbeir purchases. Fidelity Invest-
ments and other mutual fund operators bave pursued
this more “flexible” approach. By offering their clients
a wide range of funds covering such diverse fields as
health care, technology, and energy-and by then en-
couraging clients to sbift savings among these-tbey
bave virtually tailored investment portfolios.

Employing the latest in flexible manu-
facturing tecbnology, Allen-Bradley customizes starter
motors for its buyers without having to price its prod-
ucts prohibitively. Eine furniture stores offer their cus-
tomers countless variations in fabric and color. Sucb
strategies impose heavy demands on operating manag-
ers; tbey are an aspect of quality likely to grow in im-
portance witb the perfection of flexible manufacturing
tecbnology.

3 Reliability

This dimension reflects tbe probability
of a product malfunctioning or failing within a speci-
fied time period. Among tbe most common measures
of reliability are the mean time to first failure, tbe
mean time between failures, and the failure rate per
unit time. Because these measures require a product to
be in use for a specified period, they are more relevant
to durable goods than to products and services tbat are
consumed instantly.

Reliability normally becomes more im-
portant to consumers as downtime and maintenance
become more expensive. Farmers, for example, are es-
pecially sensitive to downtime during the short harvest
season. Reliable equipment can mean tbe difference
between a good year and spoiled crops. But consumers

in other markets are more attuned than ever to prod-
uct reliability too. Computers and copying machines
certainly compete on tbis basis. And recent market
research sbows that, especially for young women, reli-
ability has become an automobile’s most desired attri-
bute. Nor is the govemment, our biggest single con-
sumer, immune. After seeing its expenditures for
major weapons repair jump from $ 7.4 billion in fiscal
year 1980 to $ 14.9 billion in fiscal year 1985, the
Department of Defense has begun cracking down on
contractors whose weapons fail frequently in tbe field.

4 Confonnance

A related dimension of quality is con-
formance, or the degree to wbich a product’s design
and operating cbaracteristics meet establisbed stan-
dards. Tbis dimension owes tbe most to the traditional
approaches to quality pioneered by experts like Juran.

All products and services involve speci-
fications of some sort. When new designs or models
are developed, dimensions are set for parts and purity
standards for materials. Tbese specifications are nor-
mally expressed as a target or “center”; deviance from
the center is permitted within a specified range. Be-
cause tbis approach to conformance equates good qual-
ity with operating inside a tolerance band, there is lit-
tle interest in wbether specifications have been met
exactly. Eor the most part, dispersion witbin specifica-
tion limits is ignored.

One drawback of this approach is the
problem of “tolerance stack-up”: when two or more
parts are to be fit together, tbe size of their tolerances
often determines bow well they will match. Should
one part fall at a lower limit of its specification, and a
matching part at its upper limit, a tight fit is unlikely.
Even if tbe parts are rated acceptable initially, the link
between them is likely to wear more quickly than one
made from parts whose dimensions have been cen-
tered more exactly.

To address this problem, a more imagi-
native approach to conformance bas emerged. It is
closely associated with Japanese manufacturers and
the work of Genichi Taguchi, a prizewinning Japanese
statistician. Tagucbi begins with tbe idea of “loss func-
tion,” a measure of losses from the time a product is
shipped. (These losses include warranty costs, nome-
peating customers, and otber problems resulting from
performance failure.) Tagucbi then compares sucb
losses to two altemative approacbes to quality: on the
one hand, simple confonnance to specifications, and
on tbe other, a measure of tbe degree to whicb parts or
products diverge from tbe ideal target or center.

He demonstrates that “tolerance stack-
up” will be worse-more costly-wben the dimensions

iO6 Harvard Review November-December 1987

Exhibit Two approaches to conformance

In the following graphs, shaded areas under the
curves indicate items whose measurements meet
specifications. White areas indicate items not
meeting specifications.

Production process 1

Target Specification
limit

t.45

Iri production process 1 (favored by Taguchi), items dis-
tribute closely around the target, although some items
fall outside specifications.

Production process 2

Target Specification
limit

1.45

in production process 2 (favored in traditional ‘ ‘
approaches), items ah distribute within specifications,
but not tightly around the target.

Sourcfl: L.P. Sullivan, “Reducing Variability: A New Approach to
Duality.” Quality Progress. July T984, p. 16.

of parts are more distant from the center than when
they cluster around it, even if some parts fall outside
the tolerance band entirely. According to Taguchi’s ap-
proach, production process 1 in the Exhibit is hetter
even though some items fall heyond specification lim-
its. Traditional approaches favor production process 2.
The challenge for quality managers is obvious.

Incidentally, the two most common
measures of failure in conformance-for Taguchi and
everyone else-are defect rates in the factory and, once
a product is in the hands of the customer, the incidence
of service calls. But these measures neglect other devi-

ations from standard, like misspelled lahels or shoddy
construction, that do not lead to service or repair. In
service husinesses, measures of conformance normally
focus on accuracy and timeliness and include counts of
processing errors, unanticipated delays, and other fre-
quent mistakes.

5 Durability

A measure of product life, durability has
both economic and technical dimensions. Technically,
durability can be defined as the amount of use one gets
from a product before it deteriorates. After so many
hours of use, the filament of a light bulb bums up and
the bulb must be replaced. Repair is impossible. Econo-
mists call such products “one-hoss shays” (after the
carriage in the Oliver Wendell Holmes poem that was
designed hy the deacon to last a hundred years, and
whose parts broke down simultaneously at the end of
the century).

In other cases, consumers must weigh
the expected cost, in both dollars and personal incon-
venience, of future repairs against the investment and
operating expenses of a newer, more reliable model.
Durability, then, may be defined as the amount of use
one gets from a product before it breaks down and re-
placement is preferable to continued repair.

This approach to durability has two im-
portant implications. First, it suggests that durability
and reliability are closely linked. A product that often
fails is likely to be scrapped earlier than one that is
more reliable; repair costs will be correspondingly high-
er and the purchase of a competitive brand will look
that much more desirable. Because of this linkage, com-
panies sometimes try to reassure customers by offering
lifetime guarantees on their products, as 3M has done
with its videocassettes. Second, this approach implies
that durability figures sbould be interpreted with care.
An increase in product life may not be the result of
technical improvements or the use of longer-lived ma-
terials. Rather, the underlying economic environment
simply may have changed.

For example, the expected life of an auto-
mobile rose during the last decade-it now averages
14 years-mainly because rising gasoline prices and a
weak economy reduced the average number of miles
driven per year. Still, durability varies widely among
brands. In 1981, estimated product lives for major home
appliances ranged from 9.9 years (Westinghouse) to 13.2
years (Frigidaire) for refrigerators, 5.8 years (Gibson) to
18 years (Maytag) for clothes washers, 6.6 years (Mont-
gomery Ward) to 13.5 years (Maytag) for dryers, and 6
years (Sears) to 17 years (Kirby) for vacuum cleaners.’
This wide dispersion suggests that durability is a po-
tentially fertile area for further quality differentiation.

Quality dimensions 107

6 Serviceability

A sixth dimension of quality is service-
ability, or the speed, courtesy, competence, and ease of
repair. Consumers are concemed not only about a prod-
uct breaking down but also about the time before ser-
vice is restored, the timeliness with which service
appointments are kept, the nature of dealings with ser-
vice personnel, and the frequency with which service
ealls or repairs fail to correct outstanding prohlems. In
those cases where problems are not immediately re-
solved and complaints are filed, a company’s complaint-
handling procedures are also likely to affect customers’
ultimate evaluation of product and service quality

Some of these variables reflect differing
personal standards of acceptahle service. Others can be
measured quite objectively Responsiveness is typically
measured by the mean time to repair, while technical
competence is reflected in the incidence of multiple
service calls required to correct a particular problem.
Because most consumers equate rapid repair and re-
duced downtime with higher quality, these elements of
serviceability are less subject to personal interpreta-
tion than are those involving evaluations of courtesy
or standards of professional behavior.

Even reactions to downtime, however,
can be quite complex. In certain environments, rapid
response becomes critical only after certain thresholds
have heen reached. During harvest season, farmers gen-
erally accept downtime of one to six hours on harvest-
ing equipment, such as combines, with little resistance.
As downtime increases, they become anxious; beyond
eight hours of downtime they become frantic and fre-
quently go to great lengths to continue harvesting even
if it means purchasing or leasing additional equipment.
In markets like this, superior service can be a power-
ful selling tool. Caterpillar guarantees delivery of repair
parts anywhere in the world within 48 hours; a com-
petitor offers the free loan of farm equipment during
critical periods should its customers’ machines break
down.

Customers may remain dissatisfied even
after completion of repairs. How these complaints are
handled is important to a company’s reputation for
quality and service. Eventually, profitability is likely to
be affected as well. A 1976 consumer survey found that
among households that initiated complaints to resolve

.1 Roger B. Ycpscn. If., ed.,
The Diitabilily Factor
(Emmaus, Pcnn:
RcidalePress, l9H2|,p.|yO.

4 TARR Consumer Complaint
Hamilinxin America: Final Report
(Spnnniield, Va,:
National Technical Infonnation Service,
U.S. Department of Conunerce, 1979].

5 E Gieg Bonntr and Rjchard Nelson,
“Product Attributes and
Perceived Quality. FooJs/’m
Perceived Quality,
ed. Jacob Jauoby and lerry C. Olson
[Lexington, Mass.:
Lexington Books, D.C, Heath, l9S5),p, 71.

problems, more than 40% were not satisfied with the
results. Understandably, the degree of satisfaction with
complaint resolution closely correlated with consum-
ers’ willingness to repurchase the offending brands.’

Companies differ widely in their ap-
proaches to complaint handling and in the importance
they attach to this element of serviceability. Some do
their best to resolve complaints; others use legal gim-
micks, the silent treatment, and similar ploys to rebuff
dissatisfied customers. Recently, General Electric,
Pillsbury, Procter & Gamble, Polaroid, Whirlpool, John-
son & Johnson, and other companies have sought …

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