DB 310

Six Sigma: Definition and underlying theory §

Roger G. Schroeder a,*, Kevin Linderman

a,1 , Charles Liedtke

b,2 , Adrian S. Choo

c,3

a Curtis L. Carlson School of Management, University of Minnesota, USA

b Strategic Improvement Systems, LLC Excelsior, MN, USA

c

www.elsevier.com/locate/jom

Journal of Operations Management 26 (2008) 536–554

ology, Rensselaer Polytechnic Institute, USA

Lally School of Management and Techn

Available online 22 June 2007

Abstract

Six Sigma has been gaining momentum in industry; however, academics have conducted little research on this emerging

phenomenon. Understanding Six Sigma first requires providing a conceptual definition and identifying an underlying theory. In this

paper we use the grounded theory approach and the scant literature available to propose an initial definition and theory of Six Sigma.

Our research argues that although the tools and techniques in Six Sigma are strikingly similar to prior approaches to quality

management, it provides an organizational structure not previously seen. This emergent structure for quality management helps

organizations more rigorously control process improvement activities, while at the same time creating a context that enables

problem exploration between disparate organizational members. Although Six Sigma provides benefits over prior approaches to

quality management, it also creates new challenges for researchers and practitioners.

# 2007 Published by Elsevier B.V.

Keywords: Quality management; Six Sigma; Organizational issues; Case/field study

All truth passes through three stages. First, it is

ridiculed. Second, it is violently opposed. Third, it is

accepted as being self-evident.

Arthur Schopenhauer

1. Introduction

Six Sigma has been characterized as the latest

management fad to repackage old quality management

§ This research was supported in part by National Science Founda-

tion grant, NSF/SES-0080318.

* Corresponding author at: Curtis L. Carlson School of Manage-

ment, University of Minnesota, 3-150 CarlSMgmt Building, 321-19th

Avenue South, Minneapolis, MN 55455, USA. Tel.: +1 612 624 9544.

E-mail addresses: [email protected] (R.G. Schroeder),

[email protected] (K. Linderman), [email protected]

(C. Liedtke), [email protected] (A.S. Choo). 1

Tel.: +1 612 626 8632. 2

Tel.: +1 952 380 0778. 3

Tel.: +1 518 276 3338.

0272-6963/$ – see front matter # 2007 Published by Elsevier B.V.

doi:10.1016/j.jom.2007.06.007

principles, practices, and tools/techniques (Clifford,

2001). At first glance Six Sigma looks strikingly similar

to prior quality management approaches. However,

leading organizations with a track record in quality have

adopted Six Sigma and claimed that it has transformed

their organization. For example, 3M’s Dental Division

won the Baldrige Award (Aldred, 1998) and then later

adopted Six Sigma to improve performance even further

(McClenahen, 2004). The financial performance of 3M

since Six Sigma adoption has been very impressive

(Fiedler, 2004). Other organizations with a quality track

record, such as Ford, Honeywell, and American

Express, have adopted Six Sigma as a way to further

enhance business performance (Hahn et al., 2000). This

creates a dilemma: on the one hand, skeptics argue that

Six Sigma lacks discriminate validity over prior

approaches to quality management; on the other hand,

quality-mature organizations adopt Six Sigma to

enhance performance.

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 537

Scholarly inquiry into this management approach

has been limited. While many books and papers on Six

Sigma have emerged in the practitioner literature

(Breyfogle, 1999; Harry and Schroeder, 2000; Pande

et al., 2000), academic research on Six Sigma is just

beginning to come forward. Scholarly research is

needed to develop an in-depth, scientific understanding

of Six Sigma and separate fact from fiction.

This paper finds that indeed the philosophy and tools/

techniques of Six Sigma are strikingly similar to prior

quality management approaches. However, the way Six

Sigma is practiced represents a new organization

structural approach to improvement. Six Sigma helps

an organization become more ambidextrous by provid-

ing a switching structure (Daft, 2001) that allows the

organization to act more organically in coming up with

new improvement ideas and operate more mechan-

istically when implementing them. Furthermore, the

structure of Six Sigma employs numerous mechanisms

that simultaneously promote the conflicting demands of

exploration and control in the improvement effort. As a

result, what is new in Six Sigma when compared to prior

quality management approaches is more its organiza-

tional implementation rather than the underlying

philosophy or the quality tools/techniques employed.

At this early stage in the development of scientific

knowledge about Six Sigma, academic research needs

to address three questions:

1. W

hat is the base definition of Six Sigma and possible

variants?

2. W

hat is the theoretical basis underlying Six Sigma?

3. W

hat is new about Six Sigma relative to the existing

literature?

Our research addresses these questions using a

grounded theory approach. This approach helps develop

an in-depth, relevant understanding of poorly under-

stood phenomena (Eisenhardt, 1989; Meredith, 1998;

Yin, 1994). Since no clear definition or theory has

emerged to explain Six Sigma, conceptual development

can take place by using field observation, the literature,

and/or pure thought. This paper employs all three

approaches to provide a solid basis for the emergent

theory development and subsequent testing.

After discussing the literature in the next section, we

define Six Sigma from our grounded theory research

and propose an underlying theory for Six Sigma. We

then address what is new and propose some future

research directions. The result in a grounded theory that

has potential value for advancing the scientific under-

standing of Six Sigma.

2. The literature

Motorola originally developed Six Sigma in 1987 and

targeted an aggressive goal of 3.4 ppm defects (Barney,

2002b; Folaron, 2003). In 1994 Larry Bossidy, CEO of

AlliedSignal, introduced Six Sigma as a business

initiative to ‘‘produce high-level results, improve work

processes, expand all employees’ skills and change the

culture’’ (ASQ, 2002, p. 14). This was followed by the

well-publicized implementation of Six Sigma at General

Electric beginning in 1995 (Slater, 1999).

Currently, there are many books and articles on Six

Sigma written by practitioners and consultants and only

a few academic articles published in scholarly journals

(Linderman et al., 2003, 2004). Reviewing the

practitioner literature and these academic articles

provides a starting point for defining Six Sigma.

Six Sigma has been defined in the practitioner

literature in a variety of ways. This disparity leads to

some uncertainty and confusion. Consider some of the

following definitions from the practitioner articles.

Quality Progress called Six Sigma a ‘‘high-performance,

data-driven approach to analyzing the root causes of

business problems and solving them’’ (Blakeslee, 1999,

p. 78). Harry and Schroeder (2000), in their popular book

on Six Sigma, described it as a ‘‘business process that

allows companies to drastically improve their bottom line

by designing and monitoring everyday business activities

in ways that minimize waste and resources while

increasing customer satisfaction’’ (p. vii). Hahn et al.

(2000) described Six Sigma as a disciplined and

statistically based approach for improving product and

process quality. On the other hand, Sanders and Hild

(2000) called it a management strategy that requires a

culture change in the organization. Recognizing the

divergence in definitions, Hahn et al. (1999) noted that

Six Sigma has not been carefully defined in either the

practitioner or academic literature.

Many of the definitions of Six Sigma found in the

literature are very general and do not provide

elements—or factors (variables, constructs, concepts),

as Whetten (1989) described them—to define the

‘‘what’’ of the theory, nor do they describe relationships

among the elements to define the ‘‘how.’’ Therefore, our

data collection focused on obtaining a scientific

definition of Six Sigma and then extracting both the

elements of Six Sigma and their relationships.

3. Field data and analysis

In order to develop a rich understanding of Six Sigma

we selected two corporations that had implemented it,

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554538

one in manufacturing and the other in service (hereafter

referred to as MFG and SERV, respectively). These two

companies were selected using the idea of theoretical

sampling (Eisenhardt, 1989) to inform the theory we are

developing. They were in two different industries, and

one had just started implementing Six Sigma, while the

other had extensive experience with it. We seek

theoretical sampling in theory building rather than

the generalizability sought in statistical studies, so the

cases were chosen for theoretical rather than statistical

reasons. In some cases, polar opposites are selected to

inform and expand the emergent theory (Eisenhardt,

1989). While the cases we selected were not polar

opposites, they provide enough differences to support

the development of an emergent theory that can

potentially apply across industries and to different

stages of implementation maturity.

Four projects were selected from each company: two

that were representative of the best results obtained and

two that had less successful results. These projects were

not selected randomly; they were selected to help

improve our understanding of Six Sigma. Furthermore,

studying two very different companies and several

projects should improve the richness of our findings.

MFG is a large manufacturing company (with multi-

billions of dollars in revenue) that produces electronic

components for the computer industry. They have been

using Six Sigma for 3 years and are very advanced in its

application. MFG has almost 3.5% of its professional

workforce (about 350 out of 10,000 full-time employ-

ees) working as full-time Black Belt specialists, and

they have completed over 1000 Six Sigma projects.

MFG has documented savings of over $400 million

from its Six Sigma efforts.

SERV is a large (billion-dollar-plus) service com-

pany providing computer software services to its

customers. It is a well-established business but has

been implementing Six Sigma at a slow pace. Only a

small number of Black Belts have been trained, and

only a few projects had been completed at the time of

this study.

In each company our research team interviewed

corporate officers in addition to individuals associated

with each of the projects. The corporate officers were

generally in charge of Six Sigma efforts and were at the

vice president or director level. We also interviewed

Black Belt specialists, Green Belts, and Master Black

Belts who had worked on each of the projects and often

reported to Project Champions (operating vice pre-

sidents) who were in charge of the particular processes

being studied. We conducted 22 interviews lasting from

1 to 2 hours each.

In each company we asked interviewees a series of

questions. At the corporate level we asked questions

about the history of Six Sigma deployment in the

company, the company’s definition of Six Sigma, the

approach used, what they thought was new about Six

Sigma compared to previous quality approaches, top

management support, and the training and benefits of

Six Sigma. We also asked extensive questions about

knowledge creation, diffusion, and retention as a result

of Six Sigma projects; however, this part of the

interview is outside the scope of the present paper.

The interviews at the project level followed a similar

format, starting with a description of the origin of the

specific project, followed by a description of the project

team and method used, an explanation of benefits and

costs, an update on what is new, and an overview of the

learning that occurred from the project. We also asked

about knowledge created, diffused, and retained from

the project.

All of the interviews were tape recorded with the

permission of the respondent on a confidential basis and

then transcribed after the meeting. The transcriptions

were entered into NUD*IST, a software program that

permits analysis and manipulation of qualitative data

(Gahan and Hannibal, 1998). Each transcript was coded

according to the key issues discussed by the informants.

The codes were subsequently used to extract data and

quotations for analysis.

In an effort to triangulate our research results, as

recommended by Jick (1979), we also collected the

following types of written materials from each

company:

� t

raining manuals;

� b

riefings on Six Sigma;

� a

rticles written about the company on Six Sigma;

� a

nnual reports pertaining to Six Sigma;

� r

eports on financial savings, number of people

trained, etc.;

� s

tory boards for individual projects;

� m

inutes of project meetings;

� p

resentations made to management;

� o

ther documents describing Six Sigma.

The researchers who conducted the interviews then

analyzed these materials to supplement the responses

obtained from the interviewees. This approach rein-

forced statements made during the interviews or helped

identify discrepancies that served as a basis for further

inquiry.

In line with qualitative research procedures, the

research team conducted a number of meetings to distill

R.G. Schroeder et al. / Journal of Operatio

the important findings and conclusions from the field

data (Eisenhardt, 1989; Miles and Huberman, 1994;

Yin, 1994). Prior to these meetings the researchers read

the transcripts and came prepared to discuss definitions

of Six Sigma, its constructs, relationships and important

research issues that could be developed further. We first

conducted within-case analyses to insure that all

researchers had the same understanding of the inter-

views and written information. Then we conducted

cross-case analyses to further understand differences

and similarities observed. After these meetings, team

members conducted additional analyses of the tran-

scripts and written documents to support or refute the

tentative conclusions.

4. Definition of Six Sigma

In order to develop a definition of Six Sigma, we

draw upon the field data we collected and then compare

it to the literature. We begin by presenting a number of

definitions offered to us during the interviews. Finally,

we will present an emergent theoretical definition based

on the interviews and the literature.

Note that in each interview the respondent was

specifically asked to provide a definition of Six Sigma,

which was then discussed and clarified with them. For

example, two top executives interviewed at MFG

defined Six Sigma as follows:

For us, you take from among your best people, give

them 4 weeks of problem-solving discipline skills,

you tie them to one of your most leveraged problems

that if you fix this it generates a lot of return, you give

them full time to lead a team to go get this thing

done, and you have active support of senior

management, and that’s what Six Sigma to us is

all about. But, if you boil it down to our view is we

want to improve the pace of improvement so that we

are significantly ahead of our competition, whom-

ever that might be. So if you can learn faster and fix

faster than your competition, then you will be on the

way to long-term health as a company. (Executive 1)

What’s different about six sigma from my perspec-

tive is number one you’re taking people out of their

full-time jobs . . . we’re teaching them how to solve a problem using statistics and methods. And then

they’re [Black Belts] assigned to work with a

Champion, a Champion typically is a vice president,

who ideally or hopefully understands what’s really

impacting the business and will pick a tough problem

for that Black Belt to work on. (Executive 2)

These executives viewed Six Sigma in very broad

terms as an approach to running a business that leads to

competitive advantage. These are not efficiency-

oriented definitions, although savings are important at

MFG. They also noted the importance of connecting the

Black Belt with a Champion to ensure Six Sigma teams

work on processes important to the business strategy.

This definition refers to how the business is run rather

than process improvement or statistical methods.

A Black Belt in SERV defined Six Sigma as follows:

As far as Six Sigma goes, there’s a couple of different

ways of looking at it from my perspective. One is

more of the technical aspect, where you’re looking at

the first time yield or the defects per million

opportunities. That’s one way of looking at it. The

way I tend to describe it to people that I work with in

business . . . is looking at a situation, identifying if there’s a problem, and then drilling down into the

root cause. What companies tend to do is they tend to

attack these symptoms and when they attack a

symptom they may fix that little problem but there

are still all these other problems. When you drill

down to the root cause, you not only resolve the

symptom you were originally looking at but

numerous other problems at the same time. . . So to me it’s a way of improving processes using a very

logical, sound method. It’s the right way to do

business.

This definition emphasizes the idea of getting to the

root cause of problems in order to improve a process.

This is very important because there is a tendency to

jump to conclusions and to attack symptoms rather than

the underlying problems in business.

Another Black Belt in SERV also noted the

importance of the Champion in Six Sigma:

And then besides that, it’s also re-checking now and

then with the project Champion, making sure we’re

on track. Sometimes you’ve got to look at it and say,

‘‘Okay, where are we going? Do we need to refocus

this project a little bit?’’ Just make sure you’re still

going off in the right direction.

Each of these definitions indicates somewhat

different views of Six Sigma. This diversity in emphasis

and points of view exists even within the same company.

From a practitioner’s perspective different defini-

tions may be considered valid, and which one is

preferred may depend on the individual interviewed, the

company, or the author’s prior experience. However,

scholars need to develop rigorous conceptual definitions

that can serve as the basis of theory building (Wacker,

ns Management 26 (2008) 536–554 539

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554540

Fig. 1. Six Sigma parallel-meso structure.

2004). Commonly used definitions are insufficient for

scientific investigation (Teas and Palan, 1997). Con-

ceptual definitions should show evidence of inclusivity,

exclusivity, differentiability, clarity, communicability,

consistency, and parsimony (Hempel, 1970, p. 654).

Wacker (2004) developed rules for constructing

conceptual definitions. With those rules in mind, we

propose the following rigorous base definition that

captures the theoretical aspects of Six Sigma from the

case study data and literature:

Six Sigma is an organized, parallel-meso structure to

reduce variation in organizational processes by using

improvement specialists, a structured method, and

performance metrics with the aim of achieving

strategic objectives.

We do not suggest one definition for everyone.

Companies may choose variations of this base definition

when implementing Six Sigma in order to customize it

to their situation. Later, we suggest some possible

variations. Contingency theory implies that the base

definition will not fit every company, but nonetheless it

is a starting point for research and implementation.

5. Elements of the Six Sigma definition

The elements in our base definition of Six Sigma

need further clarification. Our field research (see

Appendix) and literature suggest and inform the

following four relevant constructs or elements (paral-

lel-meso structure, improvement specialists, structured

method, and performance metrics).

5.1. Parallel-meso structure

Parallel structures ‘‘are extra creations that operate

outside of, and do not directly alter, an organization’s

normal way of operating’’ (Lawler, 1996, p. 132). From

this perspective Six Sigma operates as a parallel

structure dedicated to improving the organization (see

Fig. 1). Implementation of Six Sigma at both MFG and

SERV followed the logic of a parallel structure. Both

organizations employed Six Sigma teams led by Black

Belts and supported by Champions who focused on

improving the organization.

However, parallel structures are not new to quality

management. Scholars often cite Quality Circles as an

example of a parallel structure (e.g., Adler et al., 1999;

Lawler, 1996). From this perspective one might argue

that Six Sigma and Quality Circles are isomorphic and

lack discriminate validity. However, Quality Circles have

faced unique challenges in implementation (Lawler and

Mohrman, 1987). Lawler (1996) noted that because

‘‘quality circles have relatively little authority and power

to implement their ideas, many of their suggestions are

not implemented. There are other reasons as well,

including resistance from managers who are threatened

by the ideas, lack of funds, and, of course, the fact that

some ideas that sound good are based on incomplete or

inaccurate information’’ (p. 134). Although Quality

Circles allowed employees to explore problems, many

organizations experienced a fundamental failure with

control and authority in implementation. Six Sigma

provides an emergent structural evolution in quality that

can overcome some of these challenges, which can be

described as a parallel-meso structure.

‘‘Meso theory concerns the integration of both the

micro- and macro-levels of analysis. Individuals and

groups affect the organization and the organization in

return affects individuals and groups. To thrive in

organizations, managers and employees need to under-

stand multiple levels simultaneously’’ (Daft, 2001, p.

32). Scholars have recognized Six Sigma as an example

of a meso approach to work design (Sinha and Van de

Ven, 2005). Barney (2002a) described Six Sigma as a

‘‘combination of macro-organizational strategy and

meso and micro-tactics.’’ Six Sigma provides a

hierarchical structure where leaders (Champions)

initiate, support, and review key improvement projects;

Black Belts then serve as project leaders who mentor

Green Belts in problem-solving efforts (Barney, 2002b;

Sinha and Van de Ven, 2005). Both MFG and SERV

support the importance of connecting multiple levels of

the organization together in improvement projects.

Various mechanisms in Six Sigma – such as strategic

project selection and leadership engagement – help

achieve multilevel integration.

5.1.1. Strategic project selection

Six Sigma organizations develop formal mechan-

isms to select Six Sigma projects. These mechanisms,

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 541

1 MFG also used design for Six Sigma (DFSS) for new products, but

that was not part of the data collection reported here.

sometimes called project hoppers, involve senior

management to filter out Six Sigma projects that do

not have financial or strategic implications (Carnell,

2003; Kelly, 2002; Snee and Hoerl, 2003). From this

perspective the decision rights to initiate a project are

allocated to senior management. In contrast, other

approaches to quality have taken a bottom-up approach

where workers directly involved with the process

initiate improvement projects. Consistent with Six

Sigma, some academic research supports the view that

decision rights to initiate improvement projects

should be allocated to management (Wruck and Jensen,

1994, 1998). Wruck and Jensen (1994) gave an account

of implementing TQM at Sterling Chemicals that

resulted in ‘‘team mania’’ from an inappropriate

allocation of decision rights. Giving management the

decision rights to initiate a project helps ensure that

project selection is based on strategic importance and

not on convenience.

5.1.2. Leadership engagement

Leaders are also involved in the ongoing execution of

Six Sigma projects. Senior executive Champions,

typically vice presidents, perform many functions for

Six Sigma projects, including facilitating project

selection, defining project charters, selecting Black

Belts and other project resources, removing barriers to

project completion, and conducting progress reviews or

tollgate reviews with Black Belts (Gitlow and Levine,

2005; Snee and Hoerl, 2003). Tollgate reviews force

people to look at what they have been doing and serve as

a counterpoint to the freewheeling that can occur in

problem solving (Bastien and Hostager, 1988; Weick,

1993). Both MFG and SERV informants noted the

importance of ongoing senior executive engagement

and support for successful completion of Six Sigma

projects.

5.2. Improvement specialists

Both MFG and SERV used full-time improvement

specialists called Black Belts. Typically, these specia-

lists were trained in the Six Sigma structured method

through 4 weeks of training with hands-on experience in

improving one or more processes. Many organizations

also train most, if not all, employees assigned to

projects in Six Sigma basics. These individuals receive

2 weeks of training and are called Green Belts. There

are also Master Black Belts who receive extensive

training beyond the Black Belt level and whose main

responsibilities are to serve as instructors and to provide

technical assistance and mentoring (Slater, 1999).

In MFG and SERV, for each Six Sigma project, an

improvement team was formed, consisting of employ-

ees who had substantial knowledge of the process,

served on a part-time basis, and may have had Green

Belt training. The team leader was a full-time Black

Belt specialist. The Black Belt usually reported to the

team’s sponsor, the Champion, a member of senior

management trained in Six Sigma basics. The

Champion provided a holistic view of the organization,

helped establish project buy-in, and insured the

availability of critical resources to the team.

Both MFG and SERV selected Black Belts not only

on the basis of their technical skills but also for their

leadership skills. Black Belts play an essential role in

Six Sigma because they bridge the gap between senior

management and project improvement teams. One can

think of a Black Belt as a ‘‘heavyweight’’ project

manager who reports to higher levels of the organization

(e.g., the Champion). A heavyweight project manager

can help secure resources and break down barriers,

which is critical to a multifunctional team (Clark and

Fujimoto, 1991). Heavyweight project managers also

help maintain discipline and a vision of the big picture

solution as the team explores the problem (Brown and

Eisenhardt, 1995). A few organizations (e.g., small

companies) do not use full-time Black Belts and instead

use part-time project leaders. Also, other organizations

use full-time Black Belts but call them by another name,

such as ‘‘continuous improvement specialists’’ or

‘‘coaches.’’

5.3. Structured method

Six Sigma uses a structured method for process

improvement, which is patterned after the PDCA cycle

(Shewhart, 1931, 1939). The improvement method used

at both MFG and SERV was the familiar DMAIC

(define, measure, analyze, improve, and control)

method. 1

In both SERV and MFG we found a strong

emphasis on finding the root cause of the problem

through systematic use of the method. The Six Sigma

methodology employs standard quality tools such as

FMEA, cause-effect charts, and statistical process

control (Breyfogle, 1999; Hoerl, 1998; Ishikawa,

1985; Kume, 1985, 1995). These tools include many

of the seven classic tools of quality control and the

seven new tools for problem formulation and diagnosis

(Gitlow et al., 1995; Mizuno, 1988).

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554542

The structured method is related to the theory of

organizational routines. From this perspective the Six

Sigma method is a metaroutine, that is, a routine for

changing established routines or for inventing new

routines. The underlying assumption of metaroutines is

that problem solving can follow predicable steps (e.g.,

DMAIC). The DMAIC method is consistent with the

problem-solving steps of the PDCA model and places

more emphasis on integrating specific tools into each

step of the method.

DMAIC also involves different organizational mem-

bers at different steps in the method. Champions play an

active role in the Define step but a supporting role in the

remaining steps. On the other hand, Process Owners take

a much more active role in the control step but a

supporting role in the other steps. Green Belts tend to take

a more active role in the measure, analyze, and improve

steps. Finally, Black Belts serve as project leaders and are

active in all steps of the process. Prior approaches to

quality management have not given this much role clarity

to organizational members in each step of the method.

The benefits of the Six Sigma metaroutine go beyond

promoting rational decision-making. As one executive

at MFG noted:

Well, what we thought was important is that it [Six

Sigma] gives us a common methodology throughout

the company. I mean, it’s not just to accomplish good

results but it’s a common methodology for approach-

ing a substantial array of business activities, so on the

one hand it’s a problem-solving mentality, it’s a

common methodology, it’s common language, it’s

raising the performance level of a great number of

individuals. . . And the other part that we liked is that it could be pervasive, it could be used throughout the

company not just in manufacturing but engineering,

sales, marketing, and administrative functions. The

ability to analyze and solve problems is, of course, an

opportunity anywhere in an organization, not just the

factory.

This executive highlights the importance of establish-

ing a common language through the metaroutine. The

common language serves an integrative function that

facilitates diverse team member interaction in exploring

system-wide problems. However, getting the benefits of

the common language requires institutionalizing the

metaroutine across the organization (Scott, 2001).

5.4. Performance metrics

In MFG and SERV we found that Six Sigma used a

variety of special metrics, including process sigma

measurements, critical-to-quality metrics, financial

measures, and strategic measures. The Six Sigma

performance metrics were employed at multiple levels

of the organization and in service, administrative, and

manufacturing processes. Broadly, the metrics can be

categorized as customer-oriented metrics or financial

metrics.

5.4.1. Customer-oriented metrics

Deming (1986, 1994) and others have stressed the

importance of understanding customers’ present and

future needs when designing new products and services.

Understanding the true customer need is at the root of

Six Sigma. ‘‘A fundamental aspect of Six Sigma

methodology is identification of critical-to-quality

(CTQ) characteristics that are vital to customer

satisfaction’’ (Evans and Lindsay, 2005, p. 184). The

baseline and desired process sigma measure levels are

in fact defined relative to customer requirements. As a

result, customer requirements help establish project

improvement goals and direct improvement efforts of

Six Sigma teams (Linderman et al., 2003). Our

interviewees at MFG and SERV conclusively stated

that determining customer requirements must be part of

the Six Sigma process.

5.4.2. Financial metrics

Six Sigma improvement efforts have measurable

financial returns that are determined by accountants and

financial personnel in the organization. For example,

General Electric estimated that for 1999 the impact on

net income derived from their Six Sigma efforts minus

the implementation costs exceeded $2 billion (General

Electric Company, 1999). Most mature Six Sigma

companies track their financial results and report the

impact to all levels of management on a regular basis.

MFG included a financial analyst on Six Sigma

teams. The financial analyst provides an independent

auditing function to the team and validates the financial

and strategic benefits of the project. The financial

analyst’s role ‘‘is to help translate what the team does

into dollars and cents’’ (Smith et al., 2002, p. 188). The

financial analyst can play a role in each step of the Six

Sigma methodology (Smith et al., 2002). Upon

completion of the project, the financial analyst will

continue to track benefits for up to a year to make sure

the benefits are realized. SERV did not track financial

results as rigorously as MFG, but the company did

recognize the importance of connecting Six Sigma

projects to financial results.

Prior quality management approaches have made

efforts to establish connections between improvement

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 543

Fig. 2. Proposed mediation model for Six Sigma.

projects and financial performance. For example, Juran

(1989) advocated the use of cost-of-quality measures to

justify improvement efforts. However, embedding

financial analysts into the improvement process is

new, and Six Sigma provides a level of financial control

not seen in prior quality management approaches.

A measurement orientation at MFG and SERV

helped promote ‘‘fact-based’’ decision-making. This

not only promoted rational decision-making but also

helped encourage problem exploration. One respondent

shared the adage ‘‘In God we trust, all else bring data.’’

This measurement orientation promoted dialog in Six

Sigma teams based on expertise and facts rather than

positional authority and domination (Eisenhardt et al.,

1997). As a result, teams can more effectively explore

problems and identify the ‘‘root cause.’’

Six Sigma metrics also provide a basis for establish-

ing improvement goals (Linderman et al., 2003). Both

MFG and SERV employed improvement goals based on

target defects-per-million-opportunities (DPMO) or

process sigma metrics. Basing goals on Six Sigma

metrics results in specific, challenging goals that can

lead to higher levels of performance than do vague,

nonquantitative goals such as do-best goals (Locke and

Latham, 1990). Clear goals create team alignment, help

measure success, and provide a basis for feedback about

performance (Ivancevich and McMahon, 1982).

While it is important to have a definition of Six

Sigma for future research, there is a belief that

organizational performance will improve if the specific

practices and parallel-meso organization structure

associated with Six Sigma are implemented. Our

definition and its related elements need to be tested

in practice to determine whether Six Sigma has a direct

effect on performance improvement. Toward this end

we offer the following proposition.

Proposition 1. Organizational performance will tend

to improve with the use of a parallel-meso Six Sigma

structure to reduce variation in organization processes

by using improvement specialists, a structured method,

and performance metrics with the aim of achieving

strategic objectives.

These Six Sigma elements can be arranged in a

framework by the proposed mediation model in Fig. 2.

We have shown leadership as a driver of three other

elements, and it is an exogenous variable, as is

commonly proposed in the literature (Anderson et al.,

1994; Kaynak, 2003; National Institute of Standards

and Technology, 2006). Leadership should lead to

strategic project selection and the use of improvement

specialists. These two elements in turn enable the use of

the structured method for process improvement. Finally,

the structured method leads directly to improved

organization performance. From Fig. 2, specific

hypotheses can be empirically tested using structural

equation modeling or path models.

6. Underlying theory of Six Sigma

Organizations have been characterized as either

mechanistic in structure, with high levels of standardi-

zation, formalization, specialization, and hierarchical

authority; or organic in structure, with low levels of

standardization, formalization, specialization, and hier-

archical authority (Burns and Stalker, 1961; Courtright

et al., 1989; Scott, 2002). Contingency theory argues

that organizations will be more effective if their

structure fits their primary task (Donaldson, 2001).

From this perspective, the mechanistic structure fits

simple and stable tasks and promotes efficiency,

whereas the organic structure fits complex and uncertain

tasks and supports adaptability. The underlying

assumption is that tradeoffs need to be made when

selecting a structure. However, some argue for ‘‘dual

structures’’ from which organizations can realize the

benefits of both efficiency and adaptability (Duncan,

1976); this is often referred to as the ambidextrous

organization (Tushman and O’Reilly, 1996). Six Sigma

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554544

Table 1

Structural control and structural exploration in Six Sigma

Control mechanism Six Sigma

Structural control

Outcome Goals & metrics

Behavioral Metaroutine

Tollgate reviews

Decision rights allocation

Social Organizational socialization

Exploration mechanism Six Sigma

Structural exploration

Boundary spanning Multifunctional teams

Heavyweight project manager

Leadership involvement

Communication Common language

can be seen as one way to achieve organizational

ambidexterity.

Some organizational mechanisms to achieve ambi-

dexterity include job enrichment, contextual ambidex-

terity, partitioning, and switching (McDonough and

Leifer, 1983). Six Sigma can essentially operate as a

switching mechanism. Switching mechanisms ‘‘create

an organic structure when such a structure is needed for

the initiation of new ideas’’ (Daft, 2001, p. 361).

‘‘Switching can be supported by ‘parallel’ organiza-

tional structures’’ (Adler et al., 1999, p. 46).

Some scholars argue that in turbulent environments,

organizations need a structure that has both a

controlling and an exploring effect (Eisenhardt and

Tabrizi, 1995). Research in quality management

provides some support for this contention (Douglas

and Judge, 2001; Sitkin et al., 1994). In Table 1 we

propose that Six Sigma can be viewed from two

different structural dimensions: structural control and

structural exploration. Structural control is grounded in

control theory (Eisenhardt, 1985; Ouchi, 1979) and

helps ensure proper execution of Six Sigma. On the

other hand, structural exploration emphasizes bound-

ary-spanning roles (At-Twaijri and Montanari, 1987;

Jemison, 1984; Schwab et al., 1985) and communica-

tion (Hill and Levenhagen, 1995; Marschan-Piekkari

et al., 1999).

6.1. Structural control

Control strategies include outcome, behavioral, and

social controls (Eisenhardt, 1985; Ouchi, 1977; Ouchi

and Maguire, 1975). Outcome controls regulate activities

by specifying the outcomes of tasks (Nidumolu and

Subramani, 2003). This requires that the outcomes be

measurable (Eisenhardt, 1985). Extensive use of metrics

and measurements in Six Sigma help ensure that

outcomes are measurable. A number of measures and

metrics based on customer requirements, DPMOs, and

process sigma measures help establish explicit project

goals (Linderman et al., 2003). This creates a ‘‘cybernetic

process for monitoring and rewarding performance’’

(Eisenhardt, 1985, p. 135). The focus on financial and

non-financial results in Six Sigma also promotes outcome

control. For example, on each Six Sigma team MFG

embedded a financial analyst who provided an auditing

function and clarified the performance outcomes. Such

strong measurement and goals employed by Six Sigma

support outcome control.

‘‘Behavioral control processes regulate activities by

clarifying details of specific behaviors involved in task

execution’’ (Nidumolu and Subramani, 2003, p. 162).

These control mechanisms work well when behaviors

can be monitored. In Six Sigma the structured method,

DMAIC, provides a metaroutine that organizational

members follow to solve problems and improve

processes. Following a structured method helps avoid

jumping to conclusions and helps ensure an adequate

search for alternative solutions to a problem. Organiza-

tional leaders (Champions) can help monitor and ensure

proper execution of the metaroutine by conducting

tollgate reviews at each step in DMAIC. Other

monitoring mechanisms of the metaroutine can also

be used. MFG introduced a Program Evaluation System

to monitor the metaroutine. This system did a pre- and

postaudit of how the Six Sigma team used the DMAIC

process. Teams were rated on the appropriate use of

tools and steps within the method, which helped ensure

proper execution of the prescribed tools and method.

The metaroutine also helps establish role clarity in the

improvement process. Champions are more directly

involved in the define step, whereas Process Owners

take a more active role in the control step, and Black

Belts and Green Belts are more actively engaged in the

remaining steps. Establishing clear roles and respon-

sibilities helps ensure the execution of the improvement

process and avoids having things fall through the

cracks. Finally, strategic process selection in Six Sigma

allocates decision rights to different organizational

members in the improvement process that promotes

control. Senior managers decide which improvement

projects to select (via the project hopper), whereas

Black Belts and Green Belts decide how to make

improvements.

Finally, social controls, sometimes called ‘‘clan

mechanisms’’ or ‘‘culture control’’ (Ouchi, 1979), can

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 545

also provide control when neither outcomes nor

behaviors can be clearly observed. Ouchi (1979) gives

an example of social control in healthcare (a context

where outcome and behavior is difficult to monitor)

where, he observes, practitioners undergo ‘‘a highly

formalized and lengthy period of socialization during

which would-be-doctors are subjected to not only skill

training but also to value training and indoctrination’’

(p. 837). Extensive training of Six Sigma specialists not

only provides organizational members with important

skills but also promotes organizational socialization

(Ashforth, 1997; Bauer et al., 1998). Recall the adage

‘‘In God we trust, all else bring data.’’ Part of the

training in Six Sigma essentially socializes organiza-

tional members to the value of fact-based decision-

making (Detert et al., 2000). Black Belts at both MFG

and SERV demonstrated strong commitment to quality

values. The extensive level of training in Six Sigma

should allow for more socialization in quality values

that was not seen in prior quality management efforts.

6.2. Structural exploration

Structural exploration helps Six Sigma teams be

open to and flexible regarding new and different

perspectives. Traditionally, organizations have main-

tained buffers or boundaries to separate functional areas

to promote efficiency. GE popularized the boundaryless

organization through its Work-Out program (Ulrich

et al., 2002). Boundary-spanning roles can help break

down barriers that get in the way of problem under-

standing (Daft, 2001). Research indicates that indivi-

duals strongly linked to the external and internal

environment are more effective at boundary spanning

(Druskat and Wheeler, 2003; Tushman and Scanlan,

1981). In Six Sigma the Black Belt serves as a

heavyweight project manager who reports to senior

management. This structure promotes boundary-span-

ning activities that help employees understand and solve

problems that cut across functional domains. In

contrast, as noted by Lawler (1996), Quality Circles

did not provide this type of support structure.

Communication can also facilitate exploration and

boundary-spanning activities (Manev and Stevenson,

2001). Since Six Sigma employs multifunctional teams,

communication challenges can occur between diverse

organizational members, who may have different

interpretative schemes that can obstruct understanding

(Dougherty, 1992). However, as one executive at MFG

noted, institutionalizing Six Sigma creates a common

language and method for solving problems. This

common language helps overcome barriers created by

diverse interpretive schemes. For example, when a

financial analyst and an engineer use the term ‘‘process

sigma’’ they have a common understanding of what this

term means.

Proposition 2. Higher levels of simultaneous struc-

tural control and structural exploration in Six Sigma

tend to result in higher organizational performance.

Incorporating structural control with structural

exploration helps resolve some problems with prior

quality management approaches (e.g., Quality Circles

and TQM). Some elements of Six Sigma have features

that support both structural control and structural

exploration. For example, instituting the Six Sigma

metaroutine helps maintain behavioral control while

also establishing a common language. Thus, we believe

that implementing both structural control and structural

exploration will lead to higher performance levels.

7. Discriminating Six Sigma from TQM

Understanding Six Sigma requires identifying what

is new about it, if anything, compared to prior quality

management approaches. Various quality frameworks

and approaches could be used to determine what is new

in Six Sigma, including the Malcolm Baldrige National

Quality Award (NIST, 2006), ISO 9000 (Tsiakals et al.,

2002), TQM (Kaynak, 2003), Deming (1986, 1994),

Juran (1989, 1995), and Crosby (1979), etc. One can

view Six Sigma as an approach that can be used within

the Baldrige framework as one way to proceed (Byrne

and Norris, 2003). However, because the Baldrige

framework is not prescriptive in nature, a Baldrige

comparison would not by itself determine what is new

During the 1990s TQM was the dominant theoretical

and empirical paradigm for quality management

and included many of the elements advocated by

leading quality thinkers such as Deming, Juran, and

Crosby. Therefore, TQM seems to be an appropriate –

though not the only – basis for comparison with Six

Sigma.

Discriminating Six Sigma from TQM has been

widely debated. Some would argue that Six Sigma is the

latest banner of TQM (McManus, 1999). Others claim

that Six Sigma is something new (Pande et al., 2000). In

order to compare Six Sigma to TQM, we must first

establish a baseline definition for TQM.

Many studies have been done on TQM’s definitions

and its links to performance (Douglas and Judge, 2001;

Flynn et al., 1995; Kaynak, 2003). While we cannot

review all of these studies, we will draw on literature

reviews and current studies to define TQM.

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554546

Recently, Kaynak (2003) compared 18 studies of

TQM definitions and their relationship to performance.

While some of these studies use a single construct

definition of TQM, many of them present TQM as a

multi-dimensional construct. Table 2 shows five

different studies from the Kaynak paper that have

gained wide use in the literature for their definitions of

TQM. In the left column of the table are the dimensions

of TQM that are common to most, if not all, of the five

studies. As can be seen, with the exception of product/

service design that is common to three of the five

studies, the other dimensions are common to four or all

five of the studies. Table 2 also provides a description of

the TQM elements taken from the various studies that

can be used for direct comparison to Six Sigma.

The first element for comparison is product/service

design. While we did not emphasize this element in this

paper, it is an important part of design for Six Sigma

(DFSS). Both TQM and Six Sigma stress the

importance of cross-functional design, customer input,

design for manufacturability, robust design, and quality

function deployment (QFD). What is different is that

DFSS emphasizes following a structured method in

design projects. In MFG this process was being taught

to all design engineers and provided a common

language for both design and certain design tools.

The method MFG used for design was IDOV (identify,

design, optimize, verify), which functions as the method

for product design (similar to DMAIC for process

improvement). Thus, the Six Sigma design process is

more prescriptive in nature than TQM.

In TQM the area of process management stresses

clarity of process ownership, less reliance on inspection,

statistical process control (SPC), total productive

maintenance (TPM), and process definitions (Flynn

et al., 1994). Six Sigma takes a somewhat different

approach by stressing process improvement through the

use of DMAIC or a similar metaroutine for improve-

ment. While SPC and other tools are part of this process,

Six Sigma connects specific tools with specific steps in

the process. Similarities with TQM are Six Sigma’s

process ownership and clear process definitions.

Top management leadership is essential to both

TQM and Six Sigma (Harry and Schroeder, 2000;

Kaynak, 2003). One difference, however, is the well-

defined meso structure in Six Sigma that demands more

involvement of leaders on improvement projects. In

addition, Six Sigma engages leaders in the improvement

process on an ongoing basis. Champions, for example,

help direct and support improvement projects.

Training for quality is dramatically different

between TQM and Six Sigma. In TQM, training is

typically provided for all employees in a 1-week TQM

course (Saraph et al., 1989). In both MFG and SERV,

Six Sigma training was provided on an as-needed basis

and differentiated by task. Likewise, a different

approach is used for employee involvement and

participation. In TQM, teams are typically formed

within work groups or sometimes with cross-functional

membership (Flynn et al., 1994). One objective of the

TQM team is to involve all employees, frequently at the

shop-floor level or in the workplace. In Six Sigma,

projects are designated at a strategic level, and teams are

formed along process lines to improve a particular

process. There is no objective of wide team participa-

tion. Furthermore, salaried workers are more likely to

be on teams than hourly workers, since many processes

are transactional, administrative, or service in nature, or

they require engineering skills for improvement. Six

Sigma teams are disbanded after the process improve-

ment is implemented, unlike TQM teams, which often

have an ongoing charter for improvement in their work

areas.

Quality data and reporting under TQM is oriented

toward use of cost of quality data, feedback of quality

data to the employees, visual display of quality

information and benchmarking (Ahire et al., 1996).

Six Sigma quality data focuses on customer and

financial performance metrics for each specific project.

In addition, tracking cost savings on a project-by-

project basis has replaced the organization-wide ‘‘cost

of quality’’ calculations from TQM approaches.

Supplier management is an important element of

TQM. It is argued that long-term relationships, a

relatively small number of dependable suppliers, and

supplier involvement in design contribute to quality

improvement (Dow et al., 1999). In contrast, the Six

Sigma efforts we studied in MFG and SERV involved

suppliers only if the supplier was a critical part of the

process being studied.

Finally, customer focus from Table 2 can be seen as

an important element of TQM. It is also important in Six

Sigma and is given similar emphasis. In both TQM and

Six Sigma customer input is important at two levels: the

organization and the project level. At the organization

level, customer input is critical in establishing which

processes and products are in need of strategic

improvement. At the project level, customer input is

critical in defining those quality attributes that are

critical-to-quality and therefore constitute a defect.

Several distinctive features of Six Sigma are

illustrated in the above discussion. First, Six Sigma is

not distinctive by insisting on top management leader-

ship or in being customer driven. These elements are

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Table 2

Definitions of TQM

TQM quality elements Descriptions of quality elements Saraph et al. (1989) Flynn et al. (1994) Ahire et al. (1996) Dow et al.

(1999)

Douglas and

Judge (2001)

Product/service design Cross-functional design, customer

input, design for manufacturability,

robust design, use of QFD

Product/service

design

Product design: new

product quality;

interfunctional

design process

Design quality

management

Process management Clarity of process ownership, less

reliance on inspection, SPC,

TPM, process definition

Process

management

Process management:

cleanliness and

organization

SPC usage Total quality

methods

Top management

leadership

Clarity of quality goals, strategic

importance of quality, quality priority

in performance evaluation, resource

allocation for quality, acceptance of

quality responsibility

Management

leadership

Top management

support: quality

leadership; quality

improvement rewards

Top management

commitment

Shared vision Top management

team involvement:

quality philosophy

Training for quality Provision of statistical training, quality

training for all employees

Training Employee training Personnel

training

TQM training

Employee involvement

and teamwork

Participation by all on quality teams,

employee recognition for quality,

employee responsibility for quality,

suggestion systems, employee

involvement

Employee

relations

Workforce management:

selection for teamwork

potential; teamwork

Employee empowerment;

employee involvement

Workforce

commitment;

use of teams

Continuous

improvement

Quality data and

reporting

Use of cost of quality data, feedback of

quality data to employees, visual display

of quality information, benchmarking

Quality data and

reporting

Quality information:

process control;

feedback

Internal quality information

usage: benchmarking

Use of

benchmarking

Management

by fact

Supplier quality

management

Long-term relationships, fewer

dependable suppliers, reliance on

supplier process control, supplier

involvement in design

Supplier quality

management

Supplier involvement Supplier quality

management

Cooperative

supplier relations

Quality department Role of quality

department

Customer focus Customer requirements input,

feedback of customer sat

Customer involvement Customer focus Customer focus Customer driven

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554548

important in every type of quality management

initiative (Juran, 1989, 1995). However, Six Sigma

provides a well-defined organizational structure that

facilitates leadership engagement.

Differences between Six Sigma and TQM can be

succinctly summarized as follows:

1. T

he focus on financial and business results is to some

extent unique. Deming (1986) warned against

focusing on results and instead preferred a process

focus. On the other hand, the Baldrige Award and

related quality awards around the world have focused

extensively on results (NIST, 2006). The difference is

that Six Sigma usually requires financial returns from

most projects and from each full-time Six Sigma

specialist. Thus the financial focus is at the project

level, in contrast to being on the organizational level

in TQM and the Baldrige award. In addition, results

are tracked on a pre-project and post-project audit

basis by the financial organization. This aggressive

insistence on a financial return from improvement

projects is new to most organizations. However, Six

Sigma recognizes that not all projects produce short-

term financial returns; therefore, projects with purely

strategic value may also be undertaken (Pande et al.,

2000).

Many of our interviewees emphasized that having

strong financial measurement was new compared to

past quality efforts. For example, one executive in

MFG said:

My expectation was that it [Six Sigma] would go

the same path that all the other quality initiatives

have gone down. You really have to have some

ongoing demonstration that it’s making a

difference. . . We are very, very strict in our interpretation of this tie and this connection. . . And we are continuing to demonstrate that we can

produce results, which, more than anything else,

the evidence that this program produces results, it

will keep it going.

2. U

se of a structured method for process improvement

or new product and service introduction is also not

entirely distinctive. However, the degree of insistence

on following the structured method, the intense

training of the full-time specialists (see Snee and

Hoerl, 2003 for discussion of Six Sigma training),

and the full integration of statistical and nonstatistical

tools are unique. In the past, quality improvement

teams have been formed with minimal training

(perhaps 1 week or less) and set out to improve a

process with less emphasis on the use of data or a

well-structured method (Pande et al., 2000). Often

these teams were formed more for employee

involvement than for improvement. So the intensity

of using the specialized method is worthy of note.

One executive at SERV said:

Six Sigma brings together a very cohesive and

comprehensive approach to problem solving. It

kind of brings together a number of the better

methods and tools that I know and then combines

them in a novel way to look at things.

3. U

se of specific metrics is also new with Six Sigma.

Processes have not been measured in terms of their

DPMO, critical-to-quality (CTQ), or process sigma.

The effect of these measures highlights the impor-

tance of improvement and encourages difficult but

attainable goals for improvement. Stretch goals

motivate team members to think ‘‘out of the box’’

(Breyfogle, 1999; Hamel, 2000). Six Sigma requires

a disciplined approach toward measurement and

improvement that has not been evident in previous

quality improvement efforts. Six Sigma metrics also

help ensure a customer focus when engaging in

process improvement efforts. As one executive at

SERV noted, ‘‘to actually be able to calculate a sigma

you have to have a very specific focus on the

customer.’’

4. F

inally, the use of a significant number of full-time

improvement specialists in Six Sigma is new to many

organizations. In the past, organizations were

reluctant to make the investment in full-time

specialists and often assigned improvement tasks

to already overworked staff on a part-time basis.

Some organizations used full-time specialists but

provided little or no training in structured improve-

ment methods. By contrast, in 1997 GE invested

$250 million in training nearly 4000 Black Belts and

60,000 Green Belts out of a workforce of 220,000

employees (Harry and Schroeder, 2000). This large

investment paid off in 1997 alone by adding $300

million to net income. Since investments are

converted immediately to bottom-line results, man-

agement is able to justify the commitment of

extensive training and full-time employees.

Overall, much of what is being done in Six Sigma is

not entirely new with respect to prior quality tools or

principles, but the deployment approach and emergent

structure of Six Sigma are new. Six Sigma has been

attractive to many CEOs and executives precisely

because it is a very disciplined approach with a parallel-

meso organization structure that delivers a verified

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 549

financial return (e.g., see Slater, 1999). As a result,

organizations may find that Six Sigma fits their

improvement needs better.

This discussion of differences between Six Sigma

and TQM suggests that Six Sigma can be discriminated

from TQM in the critical elements described above.

Furthermore, we expect that these differences will

further improve performance in organizations that have

already implemented TQM.

Proposition 3. Six Sigma will differ from TQM prac-

tices as described herein and will tend to provide

incremental benefits in customer service and financial

results for organizations that have already implemented

TQM.

8. Research directions

There are several directions that future research can

take. One of them is testing the above propositions. Also

an important issue is investigating what types of

organizations are likely to successfully adopt Six

Sigma. It seems that there are at least three

contingencies regarding Six Sigma that could be tested

via contingency theory (Benson et al., 1991; Sousa and

Voss, 2001).

1. M

ost, but not all, companies track financial results

from each project. At SERV, for example, they were

tracking improvement in customer satisfaction rather

than dollars saved. Perhaps certain industries might

not be as interested in tracking financial savings as

others.

2. M

ost, but not all, companies use full-time Black

Belts to lead projects. At MFG we found that Black

Belts were not used in design for Six Sigma, since

engineers were already assigned to projects full-time.

3. E

mployees involved in the projects we studied varied

in their use of statistical tools and in their rigor at

following all the steps of DMAIC. This tended to be

true when the root cause for improving the process

was known in advance or when there was a lack of

data.

There are no doubt other contingencies that can be

specified and tested. This would stand in contrast to

those who argue ‘‘one size fits all.’’

Another interesting research project would be to

study the benefits that actually accrue from Six Sigma.

While project savings can be totaled, they might not

translate into organizational savings or improvements in

the bottom line. There is also the question of how to

measure savings from design projects when the major

benefit is cost avoidance. Also, there is no established

methodology for measuring revenue enhancements that

occur from improved customer satisfaction or increased

market share.

Internal fit could be another area of interesting

research. The culture of the organization, along with its

structure, might be averse to implementation of Six

Sigma and thus require changes in the shared values of

the employees and in the structure of the company

(Eckes, 2001). An aversive culture could inhibit the

implementation of Six Sigma and may ultimately defeat

it, particularly if there is CEO turnover. The study of Six

Sigma sustainability is closely related to the question of

internal fit.

Six Sigma is an organizational learning process and

one that results in greater knowledge. Viewing Six

Sigma through the lens of knowledge management and

organizational learning can lead to insights about how

to create, retain, and diffuse knowledge using a

structured approach (Choo et al., 2007; Lapré et al.,

2000).

Finally, we suggest that Six Sigma be viewed as an

organization change process. This might provide

improved ways for implementation of the Six Sigma

process and a more enlightened analysis of what needs

to be changed. It might also improve management of the

change management process itself. There is certainly

ample literature about organizational change that could

be used as a starting point (Van de Ven and Poole, 1995).

9. Conclusions

We have proposed an emergent base definition of Six

Sigma and an initial theory based on a grounded theory

approach. Although Six Sigma builds off prior quality

management practices and principles, it offers a new

structure for improvement. The structural differences

simultaneously promote both more control and explora-

tion in improvement efforts. Some organizations may

find benefit from the Six Sigma approach because it fits

their organizational needs better.

Academics need to better understand Six Sigma so

that they do not overhype it or too quickly dismiss it as

nothing new. By better defining and adequately

understanding Six Sigma, scholars can develop a

deeper and richer knowledge of this phenomenon.

Our research makes four contributions:

1. I

t proposes a rigorous base definition of Six Sigma

from the literature and field study that can be used for

further research. A phenomenon cannot be scienti-

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554550

Ap

Six

Par

Pe

fically studied until it is defined; therefore, we

provide a starting point for future research on Six

Sigma.

2. W

e provide an underlying theory for Six Sigma

research derived from observation and the literature.

The theory includes the concepts of ambidextrous

organizations, parallel-meso organization, structural

control and structural exploration.

3. W

e suggest well-grounded propositions and a

framework for future empirical testing.

4. W

e differentiate Six Sigma from TQM and other

quality management approaches in order to indicate

what is new about this approach.

There are some limitations to our research, including

the fact that grounded theory has inherent weaknesses.

The theory we have developed might require further

refinement, but this is a normal part of the theory

development and testing process. Nevertheless our

grounded theory has a reasonable chance for empirical

verification and a better chance than theory developed

without the triangulation methods and grounded theory

approach used here.

The choice of the two companies studied in depth has

perhaps limited the results in some ways. For example,

neither company stressed cultural change to a large

extent. Eckes (2001), for example, stresses the

pendix

Sigma elements obtained from interviews

allel-meso structure

Strategic project selection

Master Black Belt then would be supporting the Champion, would be

project selection, matching projects to Black Belts, making sure tha

resources for those Champions and for their specific critical busine

. . .projects . . . [should be] . . . selected by the system that we like to h

. . .the . . . project, that was selected based on what’s the greatest oppo

opportunity available within this functional area

. . .project selection . . . The ideal model is that you have a flow down key objectives for MFG. And within those objectives, each of the b

these corporate goals. His goal should roll down within his departm

those individual goals, there is a definite tie back to or setting indiv

Leadership engagement

There are two significant things. The most significant from my point

going to go do this, this is rational. The second thing is . . . we real

continuing to demonstrate that we can produce results . . . the evide . . .they are almost all tools that we used in TQM and these are not n

than the others. There is a top-down engagement to this process

. . .business unit Champion who owns segments of the total Six Sigm

dollars in hard savings, and how many Black Belts should that emp

rformance metrics

Customer metrics

Does your customer perspective help you to learn more about a solut

I were them and I saw this process change coming. . . I want to ma

importance of cultural change along with technical

change in an organization, and he proposes a

comprehensive approach to cultural change.

Finally, only MFG stressed the use of Six Sigma as a

leadership development program in the company. MFG

selected from among its best people, trained them as

Black Belts, and assigned them to challenging processes

in need of improvement. They also trained everyone in

the company who was assigned to projects at the Green

Belt level and clearly viewed Six Sigma as a way to

train, reward, and promote future leaders.

As we go forward in Six Sigma research, it is an

opportune time to begin testing the theory that has been

developed. This will require random sampling to

empirically test and validate the propositions and

theory provided. Such theory testing should add to our

scientific knowledge regarding Six Sigma and can either

verify or refute certain key elements of the definition

and theory proposed here.

We have also specified a number of additional

research projects using contingency theory, organiza-

tion learning, and organization change theories. It is

only through academic research that a better under-

standing of Six Sigma can be developed. We hope that

this initial effort will provide a beginning for future

scientific research and a better understanding of this

important phenomenon.

involved in project selection-project identification,

t we’re making the best utilization of the Black Belt

ss objective

ave projects selected by

rtunity for hard savings based on what’s the

from a top level corporate objective. Here’s the seven

usiness unit leaders have a set of those that support

ent and when they come to a level when they complete

idual goals, there is tie back to the corporate goals

of view is the buy-in of senior executives. They said we’re

ly are measuring hard savings very, very tough. And we are

nce that this program produces results . . . will keep it going ew. There is a rigor to this deployment that is probably better

a commitment in terms of how many projects, how many

loy and how green belts training going.

ion? Sure. I like to put myself in their shoes and [think] if

ke sure that that’s not going to impact me negatively

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 551

Appendix (Continued )

. . .let me just step back to the voice of the customer process . . . if that’s integrated and robust . . . there’s a huge amount

of knowledge and information that the customer is bringing in. So it’s not only . . . complaints, which are valuable

information, but it’s also like do you have this product, or do you have this feature or that? Or when the sales force is

out there and they see a product in the field. [The customer] may modify a car door handle [or] an aircraft engine, and

we see that and [bring] back that information on the customer—that ties back into new products. So once again, that

strategic element is tied in to define the opportunity and then [we] use the methodology, whether it’s like a DMAIC or

our CPI methodology or a DFSS/DMADV methodology to drive the new product design

Financial metrics

. . .what really distinguishes it or makes it different [from other quality movements] . . . is the heavy tie to the customer

and the financial focus

I don’t recall in the TQM initiative that there was any reporting of [the metrics] in the monthly operating results . . . it

was not part of every functional organization’s monthly results [to answer] how are you doing? And that is a

significant part of the commitment of the executives

[The] problem I’m having with my transactional or administrative deployment is . . . because most of them aren’t measured, the senior executives didn’t buy in to it can have a significant impact

Improvement specialist

What’s unique about it? We take people out of their full-time jobs, we take some of the best people. We don’t take good old

lazy Joe or Sally who are the retreads and ought to be retired. We take some of the more energetic, more dynamic, more

hungry people. We take them out of their full-time jobs and give them 4 weeks of training and we send them back

working with VPs on solving the biggest problems the company has. And that’s really unique . . . we train these lead

superstars and plant the seed that those guys in the end will be the leaders of the company

So you give these guys full-time to go drive the methodology and it works. You see clear improvement from it . . . the

teaching is nothing different. The methods of solving problems is nothing unique, but it’s . . . the dedicated resource

and the connection with the Champion that makes this thing really successful

People think Six Sigma is all about Black Belts, but it’s not. It’s all about Green Belts. And we’re using the Black Belts as

kind of the front end people to get trained and get visible successes

I think it’s extremely helpful to have full-time Black Belts working on projects and the training involved. I think many

other quality initiatives do not use people with that much training or that have a full-time dedication. And that I do think is a

critical issue and that could be a big difference in success rates too

Well, I think that first of all, having a dedicated Six Sigma Black Belt person facilitating the team, driving the team, that

that was a success factor. Oftentimes, you form teams and there are people who have other jobs and so therefore the project

becomes the last thing that gets addressed. This being my job [as a Black Belt], I have to address it

Structured method

What’s unique about it is the methodology. How to apply the tools. For example, if I taught you how to cut a board . . . when I tell

you now go and take out [the] windows in my lake house and install a sliding glass door, you wouldn’t [be able to] do that

because you need more than just the skill in how to use the saw. You need the methods as to how to apply it and that’s [the

difference] with six sigma. Having the skill is one thing but knowing how to apply it is the really important part

So it’s the methodology plus the tools that we teach you. [The] roadmap is kind of important in the grand scheme, and every week

of training you cover the roadmap [and] that’s . . . the checklist

I think the unique thing about Six Sigma is that it gives you a platform and a methodology to follow to be consistent and make sure

that you’ve touched all the bases

I think the processes help hold the team together to get consensus. Any project team, any project leader can do that if they’re a

good project leader. But the tools that we use made it very quick, very easy to get consensus because we’ve go our

facts and data to look at

I think the methodology is probably 50% of the improvement, the individual is probably 25%, and the Champion and the project

combine for the other 25%. That’s just a guess. But I think the methodology is the strong contributor here, the primary

contributor. And that’s why it’s important to train everyone in the company

My perspective, I guess, on Six Sigma is that it’s a good set of methods to reduce defects, improve sigmas, reduce variability in a

very methodical way. And I think the reason – a lot of the reason – why it’s successful is that it forces a company to dedicate

resources to a project

References

Adler, P.S., Goldoftas, B., Levine, D.I., 1999. Flexibility versus

efficiency? A case study of model changeovers in the

Toyota production system. Organization Science 10 (1), 43–

68.

Ahire, S.L., Golhar, D.Y., Waller, M.A., 1996. Development and

validation of TQM implementation constructs. Decision Sciences

27 (1), 23–56.

Aldred, K., 1998. Baldrige Award recognizes four U.S. companies. IIE

Solutions 30 (3), 8.

Anderson, J.C., Rungtusanatham, M., Schroeder, R.G., 1994. A

theory of quality management underlying the Deming manage-

ment method. Academy of Management Review 19 (3), 472–

509.

Ashforth, B.E., 1997. Petty tyranny in organizations: a preliminary

examination of antecedents and consequences. Canadian Journal

of Administrative Sciences 14 (2), 126–140.

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554552

ASQ, 2002. The Honeywell edge. Six Sigma Forum Magazine 1 (2),

14–17.

At-Twaijri, M.I.A., Montanari, J.R., 1987. The impact of context and

choice on the boundary-spanning process: an empirical extension.

Human Relations 40 (12), 783–797.

Barney, M., 2002a. Macro, meso, micro: Six Sigma. The Industrial

Organizational Psychologist 39 (4), 104–107.

Barney, M., 2002b. Motorola’s second generation. Six Sigma Forum

Magazine 1 (3), 13–16.

Bastien, D.T., Hostager, T.J., 1988. Jazz as a process of organizational

innovation. Communication Research 15, 582–602.

Bauer, T.N., Morrison, E.W., Callister, R.R., 1998. Organizational

socialization: a review and directions for future research. Research

in Personnel and Human Resource Management 16, 149–214.

Benson, P.G., Saraph, J.V., Schroeder, R.G., 1991. The effects of

organizational context on quality management: an empirical

investigation. Management Science 37 (9), 1107–1124.

Blakeslee Jr., J.A., 1999. Implementing the Six Sigma solution.

Quality Progress 32 (7), 77–85.

Breyfogle III, F.W., 1999. Implementing Six Sigma: Smarter Solu-

tions Using Statistical Methods. Wiley, New York.

Brown, S.L., Eisenhardt, K.M., 1995. Product development: past

research, present findings, and future directions. Academy of

Management Review 20 (2), 343–378.

Burns, T., Stalker, G.M., 1961. The Management of Innovation.

Tavistock, London.

Byrne, G., Norris, B., 2003. Drive Baldrige level performance. Six

Sigma Forum Magazine 2 (3), 13–21.

Carnell, M., 2003. Gathering customer feedback. Quality Progress 36

(1), 60–61.

Choo, A.S., Linderman, K.W., Schroeder, R.G., 2007. Method and

psychological effects on learning behaviors and knowledge crea-

tion in quality improvement projects. Management Science 53 (3),

437–450.

Clark, K.B., Fujimoto, T., 1991. Product Development Performance.

Harvard Business School Press, Boston, MA.

Clifford, L., 2001. Why you can safely ignore Six Sigma. Fortune 143

(2), 140.

Courtright, J.A., Fairhurst, G.T., Rogers, L.E., 1989. Interaction

patterns in organic and mechanistic systems. Academy of Man-

agement Journal 32 (4), 773–802.

Crosby, P.B., 1979. Quality is Free. McGraw-Hill, New York.

Daft, R.L., 2001. Organization Theory and Design, 7th ed. South-

Western, Mason, OH.

Deming, W.E., 1986. Out of the Crisis. MIT Press, Cambridge, MA.

Deming, W.E., 1994. The New Economics for Industry, Education,

Government, 2nd ed. MIT Press, Cambridge, MA.

Detert, J.R., Schroeder, R.G., Mauriel, J.J., 2000. A framework for

linking culture and improvement initiatives in organizations.

Academy of Management Review 25 (4), 850–863.

Donaldson, L., 2001. The Contingency Theory of Organizations.

Sage, Thousand Oaks, CA.

Dougherty, D., 1992. Interpretative barriers to successful product

innovation in large firms. Organization Science 3 (2), 179–202.

Douglas, T.J., Judge Jr., W.Q., 2001. Total quality management

implementation and competitive advantage: the role of structural

control and exploration. Academy of Management Journal 44 (1),

158–169.

Dow, D., Samson, D., Ford, S., 1999. Exploding the myth: do all

quality management practices contribute to superior quality

performance? Production and Operations Management 8 (1),

1–27.

Druskat, V.U., Wheeler, J.V., 2003. Managing from the boundary: the

effective leadership of self-managing work teams. Academy of

Management Journal 46 (4), 435–457.

Duncan, R.B., 1976. The ambidextrous organization: designing dual

structures for innovation. In: Kilmann, R.H., Pondy, L.R., Slevin,

D.P. (Eds.), The Management of Organization Design, vol. 1.

North Holland, New York, pp. 167–188.

Eckes, G., 2001. Making Six Sigma Last: Managing the Balance

between Cultural and Technical Change. Wiley, New York.

Eisenhardt, K.M., 1985. Control: organizational and economic

approaches. Management Science 31 (2), 134–149.

Eisenhardt, K.M., 1989. Building theories from case study research.

Academy of Management Review 14 (4), 532–550.

Eisenhardt, K.M., Kahwajy, J.L., Bourgeois III, L.J., 1997. How

management teams can have a good fight. Harvard Business

Review 75 (4), 77–85.

Eisenhardt, K.M., Tabrizi, B.N., 1995. Accelerating adaptive pro-

cesses: product innovation in the global computer industry.

Administrative Science Quarterly 40 (1), 84–110.

Evans, J.R., Lindsay, W.M., 2005. The Management and Control of

Quality, 6th ed. South-Western, Mason, OH.

Fiedler, T., 2004. Mopping up profits: With 3M sitting on solid

earnings, CEO James McNerney handled his fourth annual meet-

ing like a contented company veteran. Star Tribune, Metro ed.,

May 12, Minneapolis, MN.

Flynn, B.B., Sakakibara, S., Schroeder, R.G., 1995. Relationship

between JIT and TQM: practices and performance. Academy of

Management Journal 38 (5), 1325–1360.

Flynn, B.B., Schroeder, R.G., Sakakibara, S., 1994. A framework for

quality management research and an associated measurement

instrument. Journal of Operations Management 11 (4), 339–366.

Folaron, J., 2003. The evolution of Six Sigma. Six Sigma Forum

Magazine 2 (4), 38–44.

Gahan, C., Hannibal, M., 1998. Doing Qualitative Research Using

QSR NUD*IST. Sage, London.

General Electric Company, 1999. General Electric Company 1999

Annual Report. General Electric Company, Fairfield, CT.

Gitlow, H.S., Levine, D.M., 2005. Six Sigma for Green Belts and

Champions: Foundations, DMAIC, Tools, Cases, and Certifica-

tion. Prentice-Hall, Upper Saddle River, NJ.

Gitlow, H.S., Oppenheim, A., Oppenheim, R., 1995. Quality Manage-

ment: Tools and Methods for Improvement, 2nd ed. Irwin, Burr

Ridge, IL.

Hahn, G.J., Doganaksoy, N., Hoerl, R., 2000. The evolution of Six

Sigma. Quality Engineering 12 (3), 317–326.

Hahn, G.J., Hill, W.J., Hoerl, R.W., Zinkgraf, S.A., 1999. The impact

of Six Sigma improvement: a glimpse into the future of statistics.

The American Statistician 53 (3), 208–215.

Hamel, G., 2000. Reinvent your company. Fortune 141 (12), 98–118.

Harry, M.J., Schroeder, R., 2000. Six Sigma: The Breakthrough

Management Strategy Revolutionizing the World’s Top Corpora-

tions. Doubleday, New York.

Hempel, C.G., 1970. Methods of concept formation in science. In:

Neurath, O., Carnap, R., Morris, C. (Eds.), Formations of the

Unity of Science. University of Chicago Press, Chicago, IL.

Hill, R.C., Levenhagen, M., 1995. Metaphors and mental models:

sensemaking and sensegiving in innovative and entrepreneurial

activities. Journal of Management 21 (6), 1057–1074.

Hoerl, R.W., 1998. Six Sigma and the future of the quality profession.

Quality Progress 31 (6), 35–42.

Ishikawa, K., 1985. What Is Total Quality Control? The Japanese Way.

Lu, D.J. (Trans.). Prentice-Hall, Englewood Cliffs, NJ.

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554 553

Ivancevich, J.M., McMahon, J.T., 1982. The effects of goal setting,

external feedback, and self-generated feedback on outcome vari-

ables: a field experiment. Academy of Management Journal 25 (2),

359–372.

Jemison, D.B., 1984. The importance of boundary spanning roles in

strategic decision-making. Journal of Management Studies 21 (2),

131–152.

Jick, T.D., 1979. Mixing qualitative and quantitative methods: trian-

gulation in action. Administrative Science Quarterly 24 (4), 602–

611.

Juran, J.M., 1989. Juran on Leadership for Quality: An Executive

Handbook. Free Press, New York.

Juran, J.M., 1995. Managerial Breakthrough: The Classic Book on

Improving Management Performance, 2nd ed. McGraw-Hill,

New York.

Kaynak, H., 2003. The relationship between total quality management

practices and their effects on firm performance. Journal of Opera-

tions Management 21 (4), 405–435.

Kelly, W.M., 2002. Three steps to project selection. Six Sigma Forum

Magazine 2 (1), 29–32.

Kume, H., 1985. Statistical Methods for Quality Improvement. Loftus,

J.H. (Trans.). AOTS, The Association for Overseas Technical

Scholarship, Tokyo, Japan.

Kume, H., 1995. Management by Quality. Loftus, J.H. (Trans.). 3A

Corporation, Tokyo, Japan.

Lapré, M.A., Mukherjee, A.S., Van Wassenhove, L.N., 2000. Behind

the learning curve: linking learning activities to waste reduction.

Management Science 46 (5), 597–611.

Lawler III, E.E., 1996. From the Ground Up: Six Principles for

Building the New Logic Corporation. Jossey-Bass, San Francisco,

CA.

Lawler III, E.E., Mohrman, S.A., 1987. Quality circles: after the

honeymoon. Organizational Dynamics 15 (4), 42–54.

Linderman, K., Schroeder, R.G., Zaheer, S., Choo, A.S., 2003. Six

Sigma: a goal-theoretic perspective. Journal of Operations Man-

agement 21 (2), 193–203.

Linderman, K., Schroeder, R.G., Zaheer, S., Liedtke, C., Choo, A.S.,

2004. Integrating quality management practices with knowledge

creation processes. Journal of Operations Management 22 (6),

589–607.

Locke, E.A., Latham, G.P., 1990. A Theory of Goal Setting & Task

Performance. Prentice-Hall, Englewood Cliffs, NJ.

Manev, I.M., Stevenson, W.B., 2001. Balancing ties: boundary span-

ning and influence in the organization’s extended network of

communication. Journal of Business Communication 38 (2),

183–205.

Marschan-Piekkari, R., Welch, D., Welch, L., 1999. Adopting a

common corporate language: IHRM implications. International

Journal of Human Resource Management 10 (3), 377–390.

McClenahen, J.S., 2004. New world leader. Industry Week 253 (1),

36–39.

McDonough III, E.F., Leifer, R., 1983. Using simultaneous structures

to cope with uncertainty. Academy of Management Journal 26 (4),

727–735.

McManus, K., 1999. Is quality dead? IIE Solutions 31 (7), 32–35.

Meredith, J., 1998. Building operations management theory through

case and field research. Journal of Operations Management 16 (4),

441–454.

Miles, M.B., Huberman, A.M., 1994. Qualitative Data Analysis, 2nd

ed. Sage, Thousand Oaks, CA.

Mizuno, S. (Ed.), 1988. Management for Quality Improvement: The

Seven New QC Tools. Productivity Press, Cambridge, MA.

National Institute of Standards and Technology, 2006. Malcolm

Baldrige National Quality Award: 2006 Criteria for Performance

Excellence. National Institute of Standards and Technology of the

United States Department of Commerce, Gaithersburg, MD.

Nidumolu, S.R., Subramani, M.R., 2003. The matrix of control:

combining process and structure approaches to managing software

development. Journal of Management Information Systems 20 (3),

159–196.

Ouchi, W.G., 1977. The relationship between organizational structure

and organizational control. Administrative Science Quarterly 22

(1), 95–113.

Ouchi, W.G., 1979. A conceptual framework for the design of

organizational control mechanisms. Management Science 25

(9), 833–848.

Ouchi, W.G., Maguire, M.A., 1975. Organizational control: two

functions. Administrative Science Quarterly 20 (4), 559–569.

Pande, P.S., Neuman, R.P., Cavanagh, R.R., 2000. The Six Sigma

Way: How GE, Motorola, and Other Top Companies are Honing

their Performance. McGraw-Hill, New York.

Sanders, D., Hild, C.R., 2000. Six Sigma on business processes: com-

mon organizational issues. Quality Engineering 12 (4), 603–610.

Saraph, J.V., Benson, P.G., Schroeder, R.G., 1989. An instrument for

measuring the critical factors of quality. Decision Sciences 20 (4),

810–829.

Schwab, R.C., Ungson, G.R., Brown, W.B., 1985. Redefining the

boundary spanning-environment relationship. Journal of Manage-

ment 11 (1), 75–86.

Scott, W.R., 2001. Institutions and Organizations, 2nd ed. Sage,

Thousand Oaks, CA.

Scott, W.R., 2002. Organizations: Rational, Natural, and Open

Systems, 5th ed. Prentice-Hall, Upper Saddle River, NJ.

Shewhart, W.A., 1931. Economic Control of Quality of Manufactured

Product. D. Van Nostrand, New York.

Shewhart, W.A., 1939. Statistical Method from the Viewpoint of

Quality Control. The Graduate School the Department of Agri-

culture, Washington, DC.

Sinha, K.K., Van de Ven, A.H., 2005. Designing work within and

between organizations. Organization Science 16 (4), 389–408.

Sitkin, S.B., Sutcliffe, K.M., Schroeder, R.G., 1994. Distinguishing

control from learning in total quality management: a contingency

perspective. Academy of Management Review 19 (3), 537–564.

Slater, R., 1999. Jack Welch and the GE Way: Management Insights

and Leadership Secrets of the Legendary CEO. McGraw-Hill,

New York.

Smith, D., Blakeslee, J., Koonce, R., 2002. Strategic Six Sigma. Wiley,

Hoboken, NJ.

Snee, R.D., Hoerl, R.W., 2003. Leading Six Sigma. Prentice-Hall,

Upper Saddle River, NJ.

Sousa, R., Voss, C.A., 2001. Quality management: universal or context

dependent? Production and Operations Management 10 (4), 383–

404.

Teas, R.K., Palan, K.M., 1997. The realms of scientific meaning

framework for constructing theoretically meaningful nominal defi-

nitions of marketing concepts. Journal of Marketing 61 (2), 52–67.

Tsiakals, J.J., Cianfrani, C.A., West, J.E., 2002. The ASQ ISO 9000

Handbook. ASQ Quality Press, Milwaukee, WI.

Tushman, M.L., O’Reilly III, C.A., 1996. Ambidextrous organiza-

tions: managing evolutionary and revolutionary change. California

Management Review 38 (4), 8–30.

Tushman, M.L., Scanlan, T.J., 1981. Boundary spanning individuals:

their role in information transfer and their antecedents. Academy

of Management Journal 24 (2), 289–305.

R.G. Schroeder et al. / Journal of Operations Management 26 (2008) 536–554554

Ulrich, D., Kerr, S., Ashkenas, R., 2002. The GE Work-Out. McGraw-

Hill, New York.

Van de Ven, A.H., Poole, M.S., 1995. Explaining development and

change in organizations. Academy of Management Review 20 (3),

510–540.

Wacker, J.G., 2004. A theory of formal conceptual definitions: devel-

oping theory-building measurement instruments. Journal of

Operations Management 22 (6), 629–650.

Weick, K.E., 1993. The collapse of sensemaking in organizations: the

Mann Gulch disaster. Administrative Science Quarterly 38 (4),

628–652.

Whetten, D.A., 1989. What constitutes a theoretical contribution?

Academy of Management Review 14 (4), 490–495.

Wruck, K.H., Jensen, M.C., 1994. Science, specific knowledge, and

total quality management. Journal of Accounting & Economics 18

(3), 247–287.

Wruck, K.H., Jensen, M.C., 1998. The two key principles behind

effective TQM programs. European Financial Management 4 (3),

401–423.

Yin, R.K., 1994. Case Study Research: Design and Methods, 2nd ed.

Sage, Thousand Oaks, CA.