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The challenges of six sigma in
improving service quality
Six sigma in
improving
service quality
Behnam Nakhai
Department of Business Administration, Millersville University of Pennsylvania,
Millersville, Pennsylvania, USA, and
Joao S. Neves
Department of Management, The College of New Jersey, Ewing,
New Jersey, USA
663
Received 10 June 2008
Revised 2 March 2009
Accepted 24 March 2009
Abstract
Purpose – The purpose of this paper is to critically evaluate the contributions of six sigma
methodology to the improvement of service quality. Since its development in the late 1980s, six sigma
has been extensively applied in manufacturing and quasi-manufacturing settings. This study aims to
explore the challenges of six sigma in reaching a much wider field of application.
Design/methodology/approach – Utilizing the service quality framework, the authors assess the
contributions of six sigma and explore its limitations when applied to services.
Findings – The relentless drive toward adopting six sigma to services has led both to a limited field
of applications and to unrealistic expectations as to what six sigma is truly capable of achieving,
particularly in knowledge-based environments.
Research limitations/implications – This research focuses on highlighting gaps in the six sigma
as applied to services; further work is necessary to identify and develop new methods and to study
their effectiveness.
Practical implications – The most immediate practical implication of this study is the call for the
redesign of the curricula of six sigma black belts training programs; training in service quality is vital
for the successful application of six sigma in service operations.
Originality/value – This study provides a fresh look into six sigma application to services by
combining a thorough analysis of the service quality model with the in-depth understanding of six
sigma statistical concepts.
Keywords Six sigma, Customer services quality, Consumer behaviour, Quality management
Paper type Research paper
Introduction
Service quality is an increasingly important priority for companies that wish to
differentiate their services in a highly competitive and often cutthroat environment.
Two trends are generally at work: in industrialized nations, the services have become
the dominant sector of the economy, and, at the same time, products are being offered
more and more as bundles of goods and services in response to a more comprehensive
understanding of customer needs. Aided by innovative and pervasive communication
technologies, even the old manufacturing facilities have largely turned into “service
factories” (Chase and Garvin, 1989).
From an academic perspective, service quality continues to be a stimulating topic in
contemporary management theory and practice. Researchers in the field of marketing
have contributed significantly to our understanding of the nature of services and of the
International Journal of Quality &
Reliability Management
Vol. 26 No. 7, 2009
pp. 663-684
q Emerald Group Publishing Limited
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DOI 10.1108/02656710910975741
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nature of customer satisfaction (Ghobadian et al., 1994; Grönroos, 1982, 1984). The
most consistent findings of three decades of service quality research are that:
.
service quality is more difficult for the consumer to evaluate than product quality;
.
service quality perceptions result from a comparison of consumer expectations
with actual service performance; and
.
quality evaluations are not based solely on the outcome of a service but also
involve evaluation of the delivery process.
The challenges of service quality management are well captured in the words of Berry
and Parasuraman (1997, p. 66):
The task of improving service in organizations is complex. It involves knowing what to do on
multiple fronts, such as technology, service systems, employee selection, training and education,
and reward systems. It involves knowing how to implement these actions and how to transform
activity into sustainable improvement. Genuine service improvement requires an integrated
strategy based on systematic listening. Unrelated, incomplete studies, outdated research, and
findings about customers that are not shared provide insufficient support for improving service.
In services, the meaning of quality can be elusive and is often defined as a measure of
how well the service level delivered meets customer expectations (Lewis and Booms,
1983). Rust et al. (1994) defined six levels of customer expectation as shown in Figure 1.
According to this hierarchical framework, the will expectation is the average level of
quality that is predicted based on all available information and represents the level of
quality most expected by the customer; the should expectation represents the level of
service the customer believes is deserving; and, the ideal expectation is what the
customer believes is the best of circumstances. The minimally acceptable expectation
is the threshold level of mere satisfaction, while the low-will expectation is the lowest
level of quality expected by the customer and the worst possible is the worst service
outcome that the customer can imagine.
Figure 1.
The hierarchy of customer
expectations
The concept of service quality is a technical term in the marketing literature that usually
embodies a particular model relating service performance, customer perceptions of
quality, customer expectations, and customer satisfaction. The seminal work in this area
was presented by Parasuraman and his colleagues who developed a framework for
assessing five dimensions of customer perceptions of service quality (Parasuraman et al.
1985, 1988, 1991, 1994; Zeithaml et al., 1988, 1996; Berry and Parasuraman, 1997). A
number of studies have criticized and expanded the early stream of research and have
proposed alternative models, which are reviewed in Seth et al. (2005).
Recently, a number of articles has focused on the importance of six sigma for
services and the challenges of applying this quality improvement methodology to
service operations (Biolos, 2002; Patton, 2005; Hensley and Dobie, 2005; Antony, 2006;
Chakrabarty and Tan, 2007; Antony et al. 2007; and Kumar et al., 2008). For example,
Kumar et al. (2008) debunk the seven most common myths about six sigma that:
(1) it is a fad;
(2) it is all about statistics;
(3) it is good only for manufacturing processes;
(4) it is effective in large organizations;
(5) it is the same as TQM;
(6) it requires strong infrastructure and massive training; and
(7) it is not cost effective.
Myth 3 is of special interest to us given the context of this study. What is the effectiveness
of the six sigma methodology in improving the quality of services? What can be learned
from the service quality literature that may inform the six sigma professionals and
contribute to the effectiveness and to the range of applications of six sigma?
This article first summarizes the growing literature of six-sigma applications in
services, highlighting the potential and possible limitations of six sigma applications in
service industry particularly in a knowledge-based environment. We then examine the
theoretical contributions of six sigma to the quality field and compare it to total quality
management (TQM). We present the main tenets of the service quality model, point to
some deficiencies in the application of six sigma to services, and discuss the implications
of those deficiencies to the continued expansion of this approach in service industries.
The six sigma wave in services
Since its development by Motorola in the late 1980s six sigma has gained considerable
attention, especially since its adoption by high profile companies such as General
Electric (GE) in the mid-1990s, six sigma has spread like “wildfire” (Caulcutt, 2001;
Goh, 2002; Chakrabarty and Tan, 2007). Many organizations in manufacturing and
services, public and private, large and small have joined the six sigma band wagon. In
addition to Motorola and GE, many other Fortune 500 companies such as American
Express, Boeing, Caterpillar, Fidelity Investments, Honeywell International, J.P.
Morgan Chase, Johnson and Johnson, Kodak, Lockheed Martin, Maytag, Northrop
Grumman, Sony, and Texas Instruments have applied six sigma to a myriad of
projects. The six sigma wave has spread from the US to the European Union, Japan,
Canada and is gradually becoming popular in India and other less developed countries
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in Asia, Middle East and Latin America (Thawani, 2004). Table I summarizes recent
studies that report six sigma applications broken down by specific service industry or
sectors. It includes examples from service industries as well as from service operations
of manufacturing companies.
There is a growing number of descriptive and prescriptive articles, mostly authored
by practitioners and consultants, that deal with six sigma applications in the service
industry (e.g. Biolos, 2002; Hensley and Dobie, 2005; Patton, 2005; Antony, 2006;
Chakrabarty and Tan, 2007; Antony et al., 2007). Some researchers employ conceptual
models to investigate the organizational requirements for effective six sigma
implementation. Hensley and Dobie (2005) propose a conceptual model for assessing
organizational readiness for six sigma and utilize the model to analyze the readiness of
a public transit company based on survey data. Chakrabarty and Tan (2007) examine
the current state of six sigma application in services based on quantitative and
qualitative analysis of the literature and identify critical success factors and key
performance indicators as management guidelines for effective applications of six
sigma in the service industry. Biolos (2002) prescribes ways how to effectively
implement six sigma in service organizations. Some studies have investigated the
success factors for implementing six sigma in world-class organizations (Eckes, 2000;
Antony and Banuelas, 2002; Antony, 2006; Antony et al., 2007). Antony (2006)
highlights the six sigma success factors: strong leadership and management
commitment, organizational culture change, aligning six sigma projects to corporate
business objectives, election of team members and teamwork, six sigma training,
understanding the DMAIC methodology, tools, techniques and key metrics, selection of
projects and project management skills, linking six sigma to customers, and
accountability (tying results in financial terms to the bottom line). Wessel and Burcher
(2004), Antony et al. (2005), and Fahmy (2006) discuss the application of six sigma in
small and medium enterprises and what can be done to help them succeed. Antony
et al.(2007) report on the benefits, challenges, and critical success factors of six sigma
projects in service organizations. While the majority of articles pertain to six sigma
applications in the USA, several studies focus on a variety of countries (Wessel and
Burcher, 2004 – Germany; Ho and Chuang, 2006 – Taiwan; Kumi and Morrow, 2006;
Antony et al., 2007 – UK; Kim, 2006 – S. Korea; Pheng and Hui, 2004 – Singapore).
While six sigma has been adopted by many organizations both in the United States
and around the world, the main areas in the service industry where six sigma has seen
the most work are banking and financial services, healthcare, construction, supply
chain management, accounting, customer relations, public utilities, material
procurement, education, libraries, order processing, the airline industry, safety and
even the government and non-for-profits. Antony (2006) describes some of the potential
areas in the service sector, which are prime for six sigma adoption. Edgeman et al.
(2005) describe how the US government is using six sigma in order to increase the
quality of service they are providing in this time of uncertainty. Furterer and
Elshennawy (2005) explain how municipal finance departments are trying to increase
their efficiency through lean six sigma initiatives. Reece (2006) describes how six
sigma is aiding the US Department of Defense in managing budgetary constraints.
Matchette (2006) on the other hand describes the various other ways that the
US Department of Defense benefits from six sigma. Jenicke et al. (2008) propose a
framework for applying six sigma in institutions of higher education.
Sector
Examples of applications
Sources
Financial services
Student Loan Marketing Association
(Sallie Mae), Bank of America, Citibank,
Fidelity Investments, J.P. Morgan
Chase, American Express, GE Capital
Corp., Sun Trust Banks, Inc., Credit
Unions
GE, Honeywell, Maytag, Lockheed
Martin, Northrop Grumman, Allied
Signal, Dow Chemical, Ford, Caterpillar,
DuPont, Raytheon, 3M, Polaroid
Supply chain management
Taghaboni-Dutta and Moreland, 2004;
Biolos, 2002; Roberts, 2004; Carlivati,
2007; Antony, 2006; Chakrabarty and
Tan, 2007; Hensley and Dobie, 2005
Non-manufacturing
processes
Human resource management
processes – Raytheon
Institute of Management and Admin,
2007
Accounting: Sarbanes-Oxley Act 404
Compliance
Customer relations
Innovation
Safety engineering
Government
Utilities and oil
companies:
Healthcare
Education
Organizational change
Office of the Chief Technology Officer
of the Government of the District of
Columbia
Municipal Services
US Department of Defense
Taiwan Government Agencies
ConocoPhillips, Dominion Energy,
Constellation Energy, Aquila Inc., BHP
Billiton, DuPont and Dow Chemical
Public Service Electric & Gas Co., Puget
Sound Energy
OSE Saint Francis Medical Center –
University of Illinois College of
Medicine
Commonwealth Health Corp., Bowling
Green, KY
Naval Medical Center, San Diego, CA
Wake Forest University Baptist
Medical Center, NC
Radiology Film Library
Newcastle University Library
Library Services, LibQUAL, South
Korea
Institutions of Higher Education
Construction
Housing and Development Board,
Singapore
Logistics and distribution R.R. Donnelley Logistics
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Fahmy, 2006; Antony, 2006; Biolos,
2002; Hensley and Dobie, 2005;
Chakrabarty and Tan, 2007;
Taghaboni-Dutta and Moreland, 2004
Schlegel and Smith, 2005;
Bandyopadhyay and Jenicke, 2007
Lanyon, 2003
Institute of Management and
Administration, 2007
Juras et al., 2007
Fleming et al., 2005; Rylander and
Provost, 2006
Byrne et al., 2007
American Society of Safety Engineers,
2005; Cain, 2005
LaMarsh, 2005
Edgeman et al., 2005
Furterer and Elshennawy, 2005
Matchette, 2006; Reece, 2006; Hensley
and Dobie, 2005
Ho and Chuang, 2006
Keim, 2006
Ryan, 2005
Simmons-Trau et al., 2004
Lazarus and Novicoff, 2004
Johnstone et al., 2003
Porter, 2005
Benedetto, 2003; Martin, 2007; James,
2005; D’Eredita, 2003
Kumi and Morrow, 2006
Kim, 2006
Jenicke et al., 2008
Pheng and Hui, 2004
Cottrill, 2002
Table I.
Applications of six sigma
in services
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The healthcare industry in particular is an area where there has been considerable
research into six sigma applications. Benedetto (2003) examines the potential benefits
and drawbacks of implementing six sigma in a radiology film library and how that
environment compares to other areas in hospitals. D’Eredita (2003) describes ways to use
six sigma in the healthcare industry in order to lower costs in non-core departments,
while Johnstone et al. (2003) study the situation surrounding the implementation of six
sigma into various areas of healthcare in order to save lives and reduce costs.
There are numerous manufacturing companies applying six sigma to their various
non-manufacturing processes such as human resources, payroll, accounting, customer
relations, supply chain management, safety and hazard engineering, and organization
change and innovation. Lanyon (2003) describes how Raytheon Corporation is using
six sigma to improve human resource management processes. Juras et al. (2007)
describe how chief financial officers can apply six sigma in order to guarantee
compliance with the Sarbanes-Oxley Act. Fleming et al. (2005) report how companies
are applying six sigma to improve their customer relations processes.
Financial services are another area of the service sector where six sigma has been
very popular in recent years. Taghaboni-Dutta and Moreland (2004) report how six
sigma is applied to improve the process surrounding student loan refinancing, while
Roberts (2004) reports how credit unions are benefiting from six sigma. Carlivati (2007)
focuses on six sigma in the banking industry and how six sigma can be applied to
various non-core divisions like marketing.
Evaluation of six sigma applications
Although the adoption of six sigma by such companies as GE led to an enormous
expansion of this approach to the service operations of many large corporations, the
service sector has been considerably slower in embracing six sigma than the
manufacturing sector (Furterer and Elshennawy, 2005). Since its early days, however, the
application of six sigma has not been without difficulties and challenges, especially with
services (Biolos, 2002; Rylander and Provost, 2006; Antony, 2006; Matchette, 2006; James,
2005; Chakrabarty and Tan, 2007; Antony et al., 2007). In fact, an important part of the
literature on six sigma applications regards the specific difficulties with, and provides
useful advice for, its implementation in the service sector. Chakrabarty and Tan (2007,
pp. 200-201) suggest several critical success factors to consider when applying six sigma:
.
it is crucial that top management is committed to six sigma;
.
employees must have adequate training in order to implement six sigma effectively;
.
the company’s culture and values must adjust properly;
.
the six sigma initiative must be focused on the customer;
.
in order to do this, the company must have the proper metric;
.
the company must be able to clearly show how six sigma financially benefits the
company; and
.
management must properly understand the company’s processes.
While these are all important considerations when implementing six sigma in any
environment, there are specific difficulties in applying six sigma programs in the
service sector. Hensley and Dobie (2005, p. 87) identify some of the problems that come
about when implementing six sigma in the service sector:
.
.
.
.
it is harder to collect data in service industries;
it is harder to measure due to various things that happen when customers and
service providers interact;
it may be more difficult to control and measure six sigma in the service industry
due to the difficulties that arise from the various sub-processes;
the data are not as reliable since the data are collected through more direct (“face
to face”) means.
Biolos (2002, pp. 3-5) and Antony (2006, pp. 239-241) provide useful advice for
consideration when applying six sigma to a service business:
.
consider which processes can yield the most benefit from six sigma;
.
the customer comes first so you must consider the impact on your customer;
.
search relentlessly for the root causes;
.
get to the root cause of the main problems plaguing your process;
.
determine what is considered a service defect and how it will be measured;
.
compare your company and your company’s capabilities before and after six
sigma was implemented;
.
do not forget this is no short time commitment;
.
determine the risks that need to be considered with the project;
.
identify the costs as well as benefits associated with each part of the project;
.
clearly determine what everybody’s responsibilities are as well as any
milestones.
With training costs up to US$50,000 per worker, the costs of implementing six sigma in
an organization can be considerably high (Antony, 2006; Fahmy, 2006) and this has
kept many small- and medium-sized companies from adopting six sigma (Wessel and
Burcher, 2004; Antony, 2006; Fahmy, 2006). Wessel and Burcher (2004, p. 268-271)
describe ten imperatives for small and medium companies implementing six sigma:
(1) all projects must benefit the company’s bottom line;
(2) track results for 12 months;
(3) small and medium companies must focus their six sigma program on the first
two imperatives;
(4) incorporate a shorter training program that involves training the quality
leaders but not incorporating the large green belt base;
(5) implement a one day training program to create awareness in the company;
(6) allow the quality leaders to handle the six sigma projects;
(7) design a corporate structure that supports a six sigma culture;
(8) small and medium companies must make sure they have the “fundamental
elements of process management”;
(9) use consultants and trainers offering modular services;
(10) combine the efforts of six sigma and ISO 9000.
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The literature on six sigma applications to services is vast and varied. However,
something seems to be missing. While the importance of linking six sigma to customer
satisfaction is often mentioned in this literature, there is little analysis of what
customer satisfaction is and the role customer expectations may play in the evaluation
of quality. There seems to be little room to incorporate, or even provide linkages to, the
relevant research in the service quality literature. In none of the articles on six sigma
applications to services that we investigated did we find the recognition of a service
quality model or the development of a theoretical service framework; in only a few (e.g.
Hensley and Dobie, 2005; Kim, 2006) there was a brief reference to the service quality
model. It appears that the application of six sigma to services will be severely limited if
there is no deep understanding of the nature of services and of how people judge
quality in services.
Contributions of six sigma to quality
An excellent overview of six sigma’s assumptions, motivations, steps and tools can be
found in de Koning and de Mast (2006). Two basic references which provide a
comprehensive coverage of view of this approach are Pande et al. (2000) and Pyzdek
(2001). In this section we identify and discuss four fundamental contributions of six
sigma to the quality movement.
Six sigma as a philosophy: reducing process variability produces greater benefits than
just controlling for the process average
A critical contribution of the six sigma philosophy is the realization that the variation
of an operation impacts the rest of the process very significantly. This is due to the
interrelated nature of most production processes and to the impact that a single
defective may have across the entire process. Analytical studies show that the
reliability of a process is multiplicative, and thus the probability of producing a
defective item depends highly on the reliability of each operation. High variation of an
operation leads to a higher proportion of defectives and thus impacts the entire process.
An important assumption of the six sigma philosophy is that reducing the variation of
a process leads to greater insights about how it functions than simply focusing on how
to control its average. Associated with this assumption is the realization that in gaining
an understanding of how to reduce variation, one also learns how to control the process
average. These assumptions have totally replaced the focus on controlling the process
average with little regard to variation, as it was common in traditional statistical
process control (SPC) practices.
Six sigma as a quality standard
Six sigma can also be interpreted as a quality standard, in fact a rather stringent one.
This critical contribution came from the realization that in real life there are commonly
millions of incidences of an event, millions units of a product being used in the
marketplace, and millions of services being delivered every day. Its origin goes back to
early 1930s when Walter Shewhart (1931) introduced three sigma as a measure of
variability in a process output. A standard of quality based on three standard
deviations assumes an acceptance rate of 99.7 percent (based on the normal
distribution) or 0.3 percent defective rate, or 2700 errors per million opportunities
(EPMO). According to often-cited information reported by the Six Sigma Forum
(Thawani, 2004, p. 657), a three-sigma quality level would result in:
.
.
.
.
.
.
at least 200,000 wrong drug prescriptions each year;
two short or long landings at major airports each day;
5,000 incorrect surgical procedures per week;
unsafe drinking water for almost 15 minutes each day;
no electricity for almost seven hours each month;
50 dropped newborn babies each day.
In contrast, a six sigma standard would result in 68 wrong drug prescriptions each
year, one short or long landing at major airports every five years, unsafe drinking
water for one minute every seven months, and one hour without electricity every 34
years. The 3.4 EPMO associated with the six sigma standard reflects the sensibility
that a three-sigma quality standard is not good enough. The much tougher six sigma
standard reminds the organization that a seemingly low probability of error can be
seen in a quite different way if one imagines millions of occurrences rather than the
small number of units that the worker experiences directly. To illustrate this point, let
us assume that an airline company loses 19 bags on a particular day. Considering that
the airline transported 8,750 passengers that day, the ratio of lost bags per passenger of
0.2 percent seems rather small. If one factors in that passengers carry 1.6 bags per
person (1.6 bpp) on average, the ratio of lost bags to total bags handled is “just” 0.136
percent. How bad can this be? The six sigma standard of 3.4 EPMO brings in a much
tougher look at the same situation:
EPMO ¼ (No. of errors/No. of opportunities) (1,000,000).
¼ (No. of bags lost/No. of passengers 1.6 bpp) (1,000,000).
¼ (19/14,000)˙ (1,000,000).
¼ 1,357 errors per million opportunities.
It quickly becomes apparent that losing 19 bags in one day is far from a six sigma level
of performance. If the airline handles an average of 14,000 bags per day, the 3.4 EPMO
standard means that the there should be only (3.4/1,000,000)˙ 14,000 ¼ 0.05 bags lost
per day, which translates into the airline company running about 20 consecutive days
without losing any bag.
The meaning of 3.4 EPMO and its relation with six standard deviations is worth
clarifying. Suppose that a process adds a critical substance to a pharmaceutical
compound. The specifications for this critical substance are 1,000 mg ^ 6 mg. Let us
further assume that the process is so finely tuned having an average of 1,000 mg. and a
standard deviation of 1 mg. The process is said to be six sigma capable, that is, the
upper limit and the lower limit of specifications (ULS and LLS) are six standard
deviations away from the process average. The probability of the process adding the
critical substance below 994 mg or above 1,006 is only 0.0000001 percent, or 0.0001
times per million, that is, way below the 3.4 EPMO. Let us assume, however, that on a
particular day that the process average is 1,001.5, that is, higher than what it should be
by one and half standard deviations while the standard deviation is unchanged. What
is the probability of the process adding more that 1,006 mg of the substance to the
compound given that the process average is now 1.5 standard deviations higher? The
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answer is P (x . 1,006) ¼ P (z . (1,006 – 1,001.5)/1) ¼ P (z . 4.5) ¼ 0.0000034, or 3.4
times in a million. Figure 2 illustrates six sigma’s 3.4 EPMO standard.
3. Six sigma as a continuous improvement methodology
When compared with TQM, six sigma has many differentiated characteristics: While
TQM promotes employee empowerment and self-managed teams, six sigma is driven
by organization’s champions; six sigma projects are more often cross-functional and
strategic in nature than TQM department-based projects; TQM training is generally
restricted to simple tools and statistical techniques (e.g. the Magnificent Seven), while
six sigma focuses on more advanced statistical methods (such as experimental design,
fault analysis, simulation); and six sigma projects are much more accountable in terms
of return on investment than TQM projects ever were (Snee, 2000; Senapati, 2004;
Antony, 2006; Green, 2006). A summary comparison between TQM and six sigma is
presented in Table II.
The backbone of the six sigma methodology is the well-known five steps of the
DMAIC process: Define (determine which processes to improve), Measure (collect all
the necessary data), Analyze (identify the root of the problem), Improve (take actions to
reduce the amount of defects), and Control (reduce defects via a change in the process).
These five steps are very important to six sigma since they lay out the framework in
which six sigma is applied (de Koning and de Mast, 2006). However, the critics of six
sigma often claim that the DMAIC methodology of six sigma is not fundamentally
different from those of other quality movements (Senapati, 2004).
Six sigma as an organizational change agent and motivational tool
Six sigma is a means to reduce process variation, but it is much more than that also. It
is a philosophy that benefits everyone from the customers to the shareholders and even
the suppliers and employees (Chakrabarty and Tan, 2007). Unlike lean management,
which focuses on cost savings, six sigma is a means of saving both the company and
the customer not only money but also all the problems that come along with poor
quality. Chakrabarty and Tan (2007, p. 196) emphasize that six sigma is a “customer
Figure 2.
The six sigma’s 3.4 EPMO
quality standard
Feature
TQM
Six sigma
Emphasis
Customer satisfaction
Process reliability, reduction of
process variation
Goal
Continuous improvement
“improve everything forever”
Improve specific processes that
are critical-to-quality
Competitive analysis
Benchmarking
Improvement driven internally by
process data
Breadth
All phases of SIPOC value chain
(suppliers, inputs, processes,
outputs, and customers):
Supplier partnerships,
involvement
Product/service design
Process control, preventative
management
Employee relations,
empowerment, teamwork
Customer involvement,
satisfaction
Management’s quality
awareness
Focus on manufacturing and
service processes (only P of the
SIPOC chain):
Determine critical-to-quality
variables
Define appropriate metrics
Measure process variation
Design experiments to
determine causal relationships
Implement process
improvements
Continuous improvement
methodology
PDSA: plan-do-study-act
DMAIC: define-measure-analyzeimprove-control
Training
Across the organization; more
breadth than depth
Differentiated belt system: master
black belts, black belts, and green
belts; in depth statistics and data
analysis
Statistical tools
“Magnificent 7”:
Pareto charts
Flow charts Check sheets
Histograms
Scattered diagrams
Statistical process control
charts
Cause-effect diagrams
Failure mode and effects analysis
Process mapping
Process capability analysis
Regression analysis
Reliability
Design of experiments
Factorial designs
Fractional factorials
Block designs
Response surface designs
Leadership
Top leadership, CEO
Project champions and master
black belts
Rewards
Change in overall compensation
systems Elimination of
productivity-based ratings
Project champions incentives
based on project’ success
Market share, overall financial
performance
Project-focused Hard-dollar
savings
Measure of success
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Table II.
Comparing TQM and
six sigma
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focused methodology that drives out waste, raises levels of quality, and improves the
financial performance of organizations to breakthrough levels.”
Six sigma is not just a way of measuring the level of quality, it is a way of
determining weaknesses; where the organization could do better; and how to serve the
customer better (Edgeman et al., 2005; Antony, 2006; Antony et al., 2007). Six sigma is a
way of instilling in the people in the organization a new perspective on what’s
acceptable (Goh, 2002; Edgeman et al., 2005; Wessel and Burcher, 2004). While the
major benefit of six sigma may be its impact on the bottom line, there are many other
benefits such as increased customer satisfaction, higher understanding of problem
solving, increased teamwork, and increased employee morale (Chakrabarty and Tan,
2007). However, as Hensley and Dobie (2005, p. 87) remind us, “six sigma works most
successfully when it is adopted as a managerial philosophy not as a quick fix for a
particular problem.”
Six sigma’s hierarchy of expertise is based on the belt system, which has been
credited for fostering a culture of quality in which the ownership of quality is viewed
as the responsibility of the entire organization and for providing a common purpose
and language (Antony and Banuelas, 2002). The belt system is divided into five levels
(Henderson and Evans, 2000):
(1) champions (fully trained business leaders responsible for promoting and
directing the six sigma strategy, selection of critical projects, and deployment);
(2) master black belts (fully trained quality leaders responsible for six sigma
implementation, training, mentoring, and results);
(3) black belts (fully trained experts who are experienced in leading improvement
teams);
(4) green belts (fully trained experts in six sigma tools and methodologies deployed
in six sigma project teams); and
(5) team members (individuals supporting specific projects working in teams in
their areas).
Hoerl (2001) presents a sample black belt curriculum for manufacturing applications.
Gitlow and Levine (2005) and Evans and Lindsay (2005) show full-blown six sigma
curricula for black belts and master black belts.
The service quality model
In the quality literature, five different perspectives in defining quality are commonly
identified:
(1) transcendental (only through experience, not definable);
(2) product-based (performance, features, reliability, durability, serviceability,
perceived quality);
(3) user-based (fitness for use, defined by the customer);
(4) manufacturing-base (conformance, defined by the producer); and
(5) value-based (balancing conformance and performance with price) (Garvin, 1988;
Haksever et al., 2000; Metters et al., 2006).
A complementary framework that brings a deeper understanding on how customers
evaluate quality was proposed by Darby and Karni (1973) and Nelson (1974). These
authors identify three types of attributes of goods and services:
(1) search attributes are those characteristics that are known prior to purchase or
delivery of products or services;
(2) experience attributes are those characteristics that are knowable after purchase
as the product is being used or the service is being delivered; and
(3) credence attributes are those characteristics that can only be known or
evaluated long after the product is consumed or the service is delivered.
A number of researchers have attempted to define and model service quality. In their
classic study, Parasuraman et al. (1985) identified ten service quality determinants, i.e.
ten key criteria that customers use to evaluate quality regardless of the type of service:
reliability, responsiveness, competence, access, courtesy, communication, credibility,
security, understanding and knowing the customer, and tangibles. For Parasuraman et al.
(1985) credibility and tangibles are search attributes; access, communication, courtesy,
reliability, responsiveness, and understanding are experience attributes; and competence
and security are credence attributes. Using factor analysis, these researchers later
developed a service quality scale in which the ten original determinants of quality were
collapsed into five dimensions (Parasuraman et al., 1988, 1991):
(1) reliability – consistency of performance and dependability; performs service
right at the first time; honors its promises; keeps accurate records, correct
billing, and performs services at the designated times;
(2) responsiveness – readiness to provide the service; timeliness; setting up
appointments promptly;
(3) assurance – knowledge, competence and courtesy of employees; convey trust
and confidence; has the required skills and knowledge; polite, respectful,
considerate, friendly; trustworthiness, believability, honesty;
(4) empathy – caring; individualized attention, approachability, ease of contact;
effort in understanding the customers’ needs; and
(5) tangibles – physical evidence of the service; physical facilities, tools and
equipment; appearance of providers; appearance of other customers in the
service facility.
For each dimension, the service quality scale provides a score for customer
expectations (E) and a score for customer perceptions (P) of service quality. The
differences between the two scores on each dimension are called gap scores. Service
quality (SQ) is a function of the differences between perceived service (Pi) and expected
service (Ei) for n service quality factors, i.e.
SQ ¼
n
X
ðP i 2 E i Þ ¼ Gap 5
i¼1
and the gap equation, SQ ¼ P 2 E, has become the e ¼ mc 2 analog for service quality.
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Parasuraman and his colleagues have proposed one of the most important models of
service quality, known as ServQual or the Gap Model (Parasuraman et al., 1985, 1988,
1991, 1994; Zeithaml et al., 1988, 1996; Berry and Parasuraman, 1997). For these
authors, satisfaction is based on the disconfirmation of consumer expectations:
Satisfaction occurs when perceived performance meets or exceeds the customer
expectations and dissatisfaction results when there is a negative gap between
performance and expectations. The difference between perceived service and expected
service (Gap 5) produces satisfaction or dissatisfaction and is primarily due to four
organizational gaps, Gap 5 ¼ f (Gap 1, Gap 2, Gap 3, Gap 4). The four organizational
gaps, which fall under the responsibility of management, are:
(1) difference between consumer expectations or quality determinants, and
management’s perception of such consumer expectations;
(2) difference between management’s perceived quality determinants and service
specifications (i.e. the critical-to-quality specifications);
(3) difference between quality specifications and actual service delivery; and
(4) difference between actual service delivery and the company’s external
communications about its services (e.g. word of mouth, past experience,
promises, reputation, standard of care).
As shown in Figure 3, perceived service quality is the result of the consumer’s
comparison of expected service with perceived service. The relative importance of the
different criteria of evaluation and the impact of the different organizational factors in
shaping customer expectations will differ from situation to situation. However, an
important implication of the service quality model is that the gap between service
performance and customers’ expectations may lead to customer dissatisfaction even
when the service delivered meets the exact design specifications of the service
provider. Other researchers have developed competing models of service quality.
Ghobadian et al. (1994) provide an excellent overview of seven service quality models
presented in the literature. Woodall (2001) reexamines the service quality dimensions
proposed by Grönroos and discusses the implications of customer satisfaction and
dissatisfaction to six sigma in services. Seth et al. (2005) review 19 service quality
models that have emerged since the pioneering work of Grönroos in the early 1980s.
Figure 3.
The service quality model
Six sigma and service quality
Differences between goods and services lead to service firms and goods-producing firms
having different success factors (Ghobadian et al., 1994; Frei, 2008). To what extent does
six sigma fulfill the service quality gaps, lead to the improvement of the service quality
dimensions, and contribute to service quality management? The answers to these
questions are not trivial since there are apparent challenges posed by the very nature and
core premises of services: Is the reduction of variation always compatible with individual
customer attention and service customization? Is measuring product attributes
fundamentally different from measuring customer perceptions and expectations,
especially given that the latter are not controllable by the provider? Do the inherent
service characteristics of heterogeneity, intangibility, perishability, and inseparability
pose unique challenges in the definition and measurement of quality?
In one way or another, these questions are relevant in all types of services but their
answers depend on the type of industry and on the nature of the service being
provided. For example, in process-based dominated service industries such as banking,
auto registration, or telecommunications, services may be highly standardized.
Whereas in knowledge-based services (e.g. legal services, interior and architectural
design, health industry and software development) and in highly psychological
industries (e.g. travel, lodging and entertainment) each customer’s expectations and
needs play a much more critical role. We will examine these issues in terms of the six
sigma contributions to service quality and in relation to the main service quality
concepts presented above.
Six sigma’s contributions to service quality
.
Does six sigma make a significant contribution as a service quality philosophy? The
answer is yes. We suggest that the more the service provider understands the
variation in customers, the better off it will be. Realizing the range of preferences,
personalities, styles, cultures, and needs of customers contributes to the firm’s
ability to understand what is common in different market segments, how to
develop modular solutions, and how to build flexibility in its service delivery
processes. However, inasmuch as six sigma is interpreted as a methodology to
reduce all variation, the six sigma approach can be highly detrimental.
.
Does six sigma make a significant contribution as a service quality standard? We
believe the answer is no, at least in most situations. The 3.4 EPMO is too
stringent and not realistic (or even desirable) in many situations. For example, let
us compare the 19 lost bags mentioned in our earlier example with 19 complaints
in one day at a 14,000-student university. In the latter case, it may not be
possible, let alone desirable, to develop a management system at an institution of
higher education in which complaints are rarely made. The voicing of customer
complaints is often a necessary part in listening to and understanding the
customer, learning how customer expectations are evolving, and it could be a
part of the educational goals of such an institution.
.
Does six sigma make a significant contribution as a continuous improvement
methodology for services? The answer is that it may be possible, but the tools and
the training that are available to champions, black belts, green belts and others
need to be expanded. We strongly suggest that the six sigma toolkit be adapted
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and that new concepts and methods be developed for use in services. It is urgent
that six sigma training and educational programs adapt their curricula to service
operations.
Does six sigma make a significant contribution as a change agent for service
organizations? The answer is yes, but only if champions and black belts are
trained specifically to introduce change in service industries. Developing six
sigma curricula that focuses on the nature of services, how customers form
expectations, and how they evaluate service quality is an area of great
opportunity.
Six sigma and service quality gaps
What are the contributions of six sigma in terms of filling the five gaps of the service
quality model?
.
Does six sigma adequately address the differences between customers’ expected
services and perceived services (Gap 5)? No. Six sigma is primarily focused on the
delivery process; it measures the performance of service processes in physical
terms (e.g., response time, processing time, and cost of delivery).
.
Does six sigma adequately address the differences between consumer expectations of
quality and management’s perceptions of such consumer expectations (Gap 1)? Not
really. We believe that six sigma should put greater emphasis on quality function
deployment (QFD), techniques for listening to customers, such as customer circles,
focus groups, mystery shoppers (external or internal customers), as well as surveys
of customers and non-customers as suggested by Peter Drucker (1964).
.
Does six sigma adequately address the differences between management’s
perceived quality determinants and service specifications (Gap 2)? Not really. Six
sigma gives great importance to identifying critical-to-quality variables and to
experimental designs that test different combinations of levels of these variables.
However, all examples in the literature and training materials refer to
manufacturing applications and physical measures. There should be greater
emphasis on psychological variables and on studies of the factors that shape and
affect perceptions.
.
Does six sigma adequately address the difference between service quality
specifications and actual service delivery, the service performance gap (Gap 3)?
Yes, except when there are many different types of customers, since six sigma
attempts to deliver a constant level of service. However, six sigma makes a
superb contribution in identifying those service components and service delivery
processes in which variation should be reduced, and provides effective tools to
monitor and reduce variability.
.
Does six sigma adequately address the differences between actual service delivery
and the company’s external communications about the service delivery (Gap 4)?
Six sigma does not typically address the communication messages that the
organization releases about its services. This is an important area, which should
receive greater attention since it has an enormous impact in shaping customer
expectations. Service managers should monitor the consistency of their
messages to the customer more closely, and six sigma can make important
contributions in this area.
Six sigma and the service quality dimensions
According to the service quality model, service quality is defined in terms of five
dimensions. What are the contributions of six sigma in improving each of these
dimensions?
.
Does six sigma make significant contributions in terms of the reliability of service
delivery (Dimension 1)? This is the biggest strength and a critical contribution of
six sigma to services. By concentrating on reducing the variability of the services
delivered, a company can shape customers’ expectations especially if it monitors
the consistency of the messages it conveys to current and potential customers.
However, ensuring consistency of service delivery and consistency between
service and messages is only half of the battle; management must also pay
attention to changing customer expectations and the evolving standards of
service in the industry.
.
Does six sigma make significant contributions in terms of the responsiveness of
service delivery (Dimension 2)? Yes. Consistent performance in responsiveness
contributes to fulfilled customer expectations in all services, since improving
timeliness, accessibility, time of service, and ability to deliver the service seem to
be universally appreciated by customers.
.
Does six sigma make significant contributions in terms of the assurance of service
delivery (Dimension 3)? Yes. The key to less variation in service performance
seems to be the knowledge and competence of service providers, facilitated by
increasingly effective and cost-efficient information support systems. However,
most applications of six sigma to services seem to emphasize the routine and
technological aspects of service delivery. Six sigma should put greater emphasis
on the training and behaviour of the service providers. This is especially
important given that the perception of service quality is consistently associated
with the perception of the attributes of the service provider.
.
Does six sigma make significant contributions in terms of the empathy of service
delivery (Dimension 4)? No, at least not yet. No applications of the six sigma
methodology have focused on this aspect of the service delivery. This is a critical
aspect of service delivery that has a significant impact on the difference between
expected and perceived service quality.
.
Does six sigma make significant contributions in terms of the tangibles of service
delivery (Dimension 5)? Yes. This is another strong feature of the six sigma
methodology. By ensuring consistency of delivery of the physical aspects of the
service, e.g. availability, access, appearance, ease of use of facilities, customer
expectations are formed and fulfilled.
Implications and conclusion
In an era characterized by Pine II and Gilmore (1999) as the “experience economy”, the
need for a deeper understanding of what constitutes customer expectations and
experiences is greater than ever before. The gaps and quality dimensions identified in
the service quality framework provide an avenue to address the difficulties that service
organizations encounter when using six sigma to improve quality and reduce costs.
Many of the methods used in six sigma are applicable to services as well as to
manufacturing. In services, the DMAIC method and tools such as VOC (voice of the
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customer), QFD, value added flow charts, root cause analysis, and process measurement
are valuable, and the number of successful applications reported in the literature attest to
the usefulness of six sigma in services. However, the nature of services and the ways
customers tend to evaluate service quality pose important challenges for six sigma. As
evidence of this, all studies of six sigma applications to services reported in the literature
focus on manufacturing-like situations, i.e. highly repetitive processes with no or very
low human behavior component. This record indicates that the six sigma methodology
has limited application or that six sigma provides insufficient help in improving service
quality and meeting customer expectations.
The service quality framework provides an important intellectual contribution with
significant practical value to six sigma. When it comes to services, minimizing process
variation is not as important as minimizing the variation of the expectation-perception
gap. This model also highlights how the perception-expectation gap (Gap 5) can be linked
to four other gaps: quality determinants, quality specifications, quality delivery, and
quality communication gaps. While six sigma is the preferred approach for the
environments with a low behavior content and low variability in customer expectations,
its effectiveness is reduced as the behavior content and the role of customer expectation
increase. We understand that six sigma was not designed to be the “cure of all ills”.
However, as discussed in this paper, six sigma can be extended to many service operations
if new concepts and tools are developed and if the training of black belts is modified to
address areas that are critical-to-service-quality (CTSQs). Alas, the curricula used in six
sigma training focus on manufacturing industries, and all examples and applications that
we analyzed pertained to manufacturing or highly repetitive service processes.
Many of the concepts and methodologies critical to understanding and measuring
service quality are already available: customer surveys and panels, transaction
analysis, perception surveys, mystery shoppers, analysis of complaints, employee
research, competitive benchmarking analysis, and intermediary analysis. The full
potential of six sigma in services is yet to be realized. This will not happen unless black
belts are trained not only in six sigma tools and concepts but also are knowledgeable in
service quality ideas and methods. Service quality training is vital for the successful
development of six sigma in services.
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About the authors
Behnam Nakhai received his PhD in Management from the Claremont Graduate University in
1982, and is currently Professor of Management at the Millersville University of Pennsylvania,
USA. His current research includes topics in service quality, quality costs, negotiations and
teams. Behnam Nakhai is the corresponding author and can be contacted at:
Behnam.Nakhai@millersville.edu.
Joao S. Neves received his PhD in Social Systems Sciences from the Wharton School of The
University of Pennsylvania in 1984, and is currently Professor of Management at The College of
New Jersey, USA. His research interests include topics in service quality management,
negotiations and teams.
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