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This is to certify that the
dissertation entitled
AN ANALYSIS OF THE RELATIONSHIPS BETWEEN
SELECTED MANUFACTURING STRATEGIES, PRODUCTION
COMPETENCE, AND COMPETITIVE PRIORITY COMPETENCE

presented by

GREGORY MICHAEL MAGNAN

has been accepted towards fulfillment
of the requirements for

Ph.D. degree in Management—

 

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AN ANALYSIS OF THE RELATIONSHIPS BETWEEN SELECTED
MANUFACTURING STRATEGIES, PRODUCTION COMPETENCE, AND
COMPETITIVE PRIORITY COMPETENCE
B y

Gregory Michael Magnan

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Management

1994

ABSTRACT

AN ANALYSIS OF THE RELATIONSHIPS BETWEEN SELECTED
MANUFACTURING STRATEGIES, PRODUCTION COMPETENCE, AND
COMPETITIVE PRIORITY COMPETENCE

BY

Gregory Michael Magnan

The theory of manufacturing strategy states that firms with
manufacturing resources aligned with business strategy objectives
will outperform firms without properly aligned resources. The
production competence construct was created to obtain a measure of
the support provided to the business strategy by manufacturingl.
Upon improving the construct, a positive relationship between
production competence and firm performance was identifiedz.

As the global economy grows and becomes more competitive,
many firms are redirecting their attention to the manufacturing
function to provide a competitive advantage. Simultaneously, many
new and old manufacturing strategies are available to firms. With
limited resources, firms must decide which strategies to implement.

This research is directed at the identification of the
manufacturing strategies, programs, and techniques (SPTS) firms use
to support the business strategy (i.e., become “competent”). To
identify the SPTs, a survey was mailed to the manufacturing
managers of the firms in Vickery, et al.3, all of which compete in the
furniture industry. The survey collected data on the extent of use of

several different manufacturing SPTs and was combined with firm-

level data from Vickery, et al. Regression analysis was used to
measure the relationship between production competence and the
use of SPTS.

The 16 SPTS related to production competence include both
structural and infrastructural factors. Most notable was the large
number of employee—related and sourcing-related SPTS.

When regarding the list of SPTS related to production
competence, one becomes aware of the fact that these SPTS provide
little guidance to firms competing along specific competitive
dimensions. The competitive priorities of cost, delivery, flexibility,
and quality were used to create new competence constructs (e.g., cost
competence) directed at measuring the support provided to
particular strategic initiatives. Again, the list of SPTS related to the
each of the constructs contained several structural and
infrastructural elements.

Finally, the SPTS were grouped together to form bundles of
SPTS that the literature suggests can be used to support the
individual competitive priorities. Several of the SPT groupings were
related to production competence and competence within the

competitive priorities.

 

1Cleveland, Gary, Roger G. Schroeder and John C. Anderson (1989), “A Theory
of Production Competence,” W 20 (4), 655-668.

2Vickery, Shawnee K., Droge, Cornelia and Robert E. Markland (1993),
“Production Competence and Business Strategy: Do They Affect Business

Performance?", W 24 (2), 435-455.

3ibid.

ACKNOWLEDGMENTS

I would like to thank my wife, Janie, and my mother and father for
their constant support throughout this process. I would also like to
thank the members of my committee, Dr. Cornelia Droge, Dr. Robert
Markland, and Dr. Shawnee Vickery (Chair), for their dedication and

guidance.

iv

TABLE OF CONTENTS

 

 

 

 

 

 

 

I. INTRODUCTION.--. - -- -- - ................................... 1
Decline of American Competitiveness ..... ................... 5
Increasing Standards -- - ..................... -8
Manufacturing Strategy ................................................................................ 1 0
Production Competence: What Is It? ...................................................... 1 5
Research Purpose--- - - -- - -- - - - - -- - -2 0
Research Questions - - - __--2 5
Scope Of Research ............................................................................................ 2 9
Contributions Of Research ............................................................................ 3 0
Research Limitations ...................................................................................... 3 2
Organization Of Dissertation ........................................................................ 3 2

II. LITERATURE REVIEW AND THEORY DEVELOPMENT ........................ 3 4
Empiricism In Operations Management _- . - -- _ ---3 4
Manufacturing Strategy .............................................................................. .3 8
Production Competence - - ...... - --.4 5
Programs and Techniques ........................................................................... 5 4
What Is Good Theory? ................................................................................... 6 1
Production Competence as Theory ........................................................... 6 5

V

III.RESEARCHMETHODOLOGY. - -- ........ - - ................ 72

 

 

 

 

Overview ________ . ______ 72
Model Development ........................................................................................ 7 3
Strategies, Techniques and Programs ..................................................... 8 1
Data Collection ................................................................................................... 8 3
Hypotheses Development ............................................................................. 8 7
IV. RESULTS AND ANALYSIS ...... - -- -- - ..... - - --127
Production Competence and Individual Manufacturing
Strategies- 127
Competitive Priority Competence and Related Manufacturing
Strategies, Programs, and Techniques .................................................... 13 2
Cost Competence and Individual Manufacturing Strategies ......... 133
Delivery Competence and Individual Manufacturing SPTS ........... 137

Flexibility Competence and Individual Manufacturing SPTS ....... 139

Quality Competence and Individual Manufacturing SPTS ............. 143
Competitive Priority Performance And Related Individual

Manufacturing Strategies, Programs, And Techniques ................... 145
Cost Performance and Individual Manufacturing SPTS .................. 147
Delivery Performance and Individual Manufacturing SPTS ......... 149
Flexibility Performance and Individual Manufacturing SPTS ...... 150
Quality Performance and Individual Manufacturing SPTS ............ 155

Return On Assets (ROA) And Related Individual
Manufacturing Strategies, Programs, And Techniques ................... 157

vi

Manufacturing Strategies, Programs, And Techniques

 

 

Grouped By Competitive Priority/JIT ..................................................... 15 9
Quality-Related Manufacturing SPTS ...................................................... 15 9
Delivery-Related Manufacturing SPTS ................................................... 16 9
Flexibility-Related Manufacturing SPTS ................................................ 17 4
Cost-Related Manufacturing SPTS ............................................................ 17 5
JIT-Related Manufacturing SPTS .............................................................. 17 9
. IMPLICATIONS - ..... . .......................... 1 8 3
Review Of Hypotheses ................................................................................... 185
Production Competence ................................................................................ 1 8 5
Competitive Priority Competence and Individual SPTS .................. 1 8 8
Cost Competence- - - ...... - ............ 18 9
Delivery Competence ..................................................................................... 1 9 1
Flexibility Competence .................................................................................. 1 9 2
Quality Competence ........................................................................................ 1 9 5
Competitive Priority Performance and Individual SPTS ................ 1 9 6
Cost Performance ............................................................................................. 1 9 7
Delivery Performance .................................................................................... 1 9 8
Quality Performance ...................................................................................... 2 0 2
Return on Assets .............................................................................................. 2 O 4
Summary of Individual Manufacturing SPTS ...................................... 2 O 5
Manufacturing SPTS Grouped By Competitive Priority ................... 2 O9

vii

Managerial Implications ............................................................................... 2 1 6

Contributions Of Research2 l 7
Limitations Of Research ................................................................................ 219
Future Research/Extensions ....................................................................... 219
APPENDIX A: Copy of Survey Instrument and Glossary ....................... 223
LIST OFREFERENCES ............................................................................................. 242

viii

LIST OF TABLES

Table 2.1: 31 Competitive Priorities (from Vickery, et al.,

 

1993) - ................... 51
Table 2.1 (cont’d) ................................................................................................... 5 2
Table 2.2: Competitive Priorities and Action Plans ................................ 5 7
Table 2.3: Relationships Between Action Plans and Priorities ........... 5 8
Table 2.4: List of Authors and Competitive Priority Focus ................. 5 9
Table 3.1: Manufacturing SPTs Appearing in Questionnaire .............. 8 5
Table 3.1 (cont’d) ................................................................................................... 8 6
Table 3.2: Previous Studies Involving Competitive Priorities ........... 91

Table 3.3: 31 Competitive Priorities Categorized into Priority

 

 

 

Groups - - .----92
Table 3.4: Malcolm Baldrige Quality Categories and Items ................. 9 8
Table 3.5: Baldrige Criteria (BOLD)/Items and Related SPTs ............. 99
Table 3.6: Manufacturing SPTS Related to Delivery ............................... 109
Table 3.7: Manufacturing SPTs Related to Flexibility---- - -- -----114
Table 3.8: Manufacturing SPTS Related to Cost -- ---- - - ........... 118
Table 3.9: Manufacturing SPTS Related to Just-in-Time (JIT) ........... 123

Table 4.1: Individual SPTs Related to Production Competence ......... 130

Table 4.2: Individual SPTs Related to Cost Competence ....................... 135

 

 

Table 4.3: Individual SPTS Related to Delivery Competence .............. 138
Table 4.4: Individual SPTs Related to Flexibility Competence ........... 142
Table 4.5: Individual SPTs Related to Quality Competence ................. 144
Table 4.6: Individual SPTS Related to Cost Performance ..................... 149
Table 4.7: Individual SPTS Related to Delivery Performance ............ 151
Table 4.8: Individual SPTS Related to Flexibility Performance ......... 154
Table 4.9: Individual SPTs Related to Quality Performance ............... 156
Table 4.10: Individual SPTS Related to RCA (Internal

Assessment) ............................................................................................................. 159
Table 4.11: Baldrige Criteria/Items & Manufacturing SPTS ............... 162
Table 4.12: Competence/Performance Variables & Baldrige

Criteria - - - - ---163
Table 4.13: Competence/Performance Variables & Baldrige

Items ........................................................................................................................... 167
Table 4.14: Delivery Variables and Related Manufacturing

SPTS - ------ - ------ 171
Table 4.15: Competence/Performance & Delivery Variables ............. 171
Table 4.16: Flexibility Variables and Manufacturing SPTS ................. 173
Table 4.17: Competence/Performance and Flexibility Variables ..... 173
Table 4.18: Cost Variables and Related Manufacturing SPTS ............. 177
Table 4.19: Competence/Performance and Cost Variables .................. 177
Table 4.20: JIT Variables and Related Manufacturing SPT S ............... 181
Table 5.1: Structural/Infrastructural SPTs & Production
Competence - ................. 1 8 6

 

Table 5.2: Structural/Infrastructural SPTS & Cost Competence ........ 190

Table 5.3: Structural/Infrastructural SPTS & Delivery
Competence - - --------- - ............. 192

 

Table 5.4: Structural/Infrastructural SPTs & Flexibility

 

 

 

 

 

Competence -- 193
Table 5.5: Structural/Infrastructural SPTs & Quality

Competence - - - ........................... 196
Table 5.6: Structural/Infrastructural SPTS & Cost Performance ...... 198
Table 5.7: Structural/Infrastructural SPTS & Delivery

Performance -- - - ................ 199
Table 5.8: Structural/Infrastructural SPTS & Flexibility

Performance - -- -- ..... 2 01
Table 5.9: Structural/Infrastructural SPTS & Quality

Performance -----_..- _____ - 203
Table 5.10: Structural/Infrastructural SPTs & ROA ............................... 205
Table 5.11: Summary of SPTs and Competence/Performance ........... 206
Table 5.11 (Don’t) ................................................................................................... 207
Table 5.11 (con’t) ................................................................................................... 2 0 8
Table 5.12: Competence Constructs and Related Variables ................. 210
Table 5.13: Performance Constructs and Related Variables ............... 211
Table 5.14: Financial Indicators and Related Variables ....................... 212

xi

LIST OF FIGURES

Figure 1.1: Productivity Growth of Industrial Nations .......................... 4
Figure 1.2: A Process Model of Production Competence ....................... 19

Figure 1.3: A Closer View of the Production Competence

 

 

Construct - - - - - -- 23
Figure 3.1: A Process Model of Production Competence ....................... 7 5
Figure 3.2: Production Competence and Skinner’s Missing Link ...... 77
Figure 3.3: A Process Model of Competitive Priority

Competence -- .................... 78
Figure 5.1: A Process Model of Production Competence ....................... 184

Figure 5.2: A Process Model of Competitive Priority
Competence - -- 187

 

xii

I . INTRODUCTION

Competitiveness is “the degree to which a nation can, under free and
fair market conditions, produce goods and services that meet the test
of international markets while simultaneously expanding the real
incomes of its citizens” (Cohen and Zysman, 1987, p. 279). In the late
1940s, United States firms were extremely competitive, dominating
the manufacturing world and supplying nearly half of world Gross
National Product (Giffi, Roth and Seal, 1990). Gradually, that position
eroded until 1971 when, for the first time in this century, the
balance of trade for the United States became negative. After a brief
recovery and a positive balance in the mid-1970s, the trade balance
has been negative since 1982 and increases in magnitude every year
(Hill, 1994). Meanwhile, the United States’ share of the global

market is down to 19.2% (Giffi, Roth and Seal, 1990).

A major factor in the United States’ increasing trade deficit and
reduction in world share is the increased number of global
competitors. The number of competitors in an industry is an
important factor in determining the competitiveness of the industry
(Porter, 1980). The emergence of Japan, other Pacific Rim countries,
and Europe has greatly increased in the number of global
competitors. As the number of global competitors has grown, so has
the level of competitiveness.

Since the 19508, American firms have not responded to
increased global competition very well, resulting in a negative trade
balance and decreased world share. Using measures such as the

trade deficit, growth in profit margins and real wages, price

2
elasticities of imports, and productivity growth, Cohen and Zysman

(1987) demonstrate the delicate position of the United States
economy. For each measure, the performance of the United States—
relative to international competitors—is decreasing over time.
Currently, the trade balance is negative and increasing in magnitude,
profit margins and real wages are declining, and productivity growth
is lagging. The authors note that while the possibility of explaining
away the economic impact of any one measure exists, taken as a
group, they send a powerful message regarding the competitiveness
of the United States.

According to the United States government, the growth rate of
productivity is an important indicator of economic vitality and is
responsible for the long term prosperity and wealth of nations
(Freedman, 1989; Porter, 1990). Due to the long period in which the
growth rate of productivity in the United States has languished,
Bernstein (1991) purports the present generation might be the first ,
in this country that will be economically worse off than their parents.

In their recent study of productivity in the United States, the
MIT Commission on Productivity (Dertouzos, Lester, Solow and the
MIT Commission on Industrial Productivity, 1989) report that for the
period 1979-1986, the United States had the second highest growth
rate among industrialized nations. They note, however, that four
items generated much of the increase in productivity for this period—
closing inefficient plants, permanently laying off workers,
miscalculations in the growth rate by the Department of Commerce,
and that this time-frame included a post-recessionary period, which

historically have been periods of growth. These items, while

3
explaining the rise in productivity growth for the period, perhaps

obscure the dismal. level of productivity growth in the US due to
improvements in products, processes, and people.

Since 1986, the growth rate of productivity in the United States
is again one of the lowest among industrialized nations, never rising
above 3% (United States Department of Labor, Bureau of Labor
Statistics, 1991). Over the last 30 years, the growth rate of
productivity in the United States is the lowest among industrialized
nations at 2.9% (See Figure 1.1).

The MIT Commission analyzed the competitiveness of United
States firms in eight industries: automobile, chemical, commercial
aircraft, consumer electronics, machine tool, semiconductor, steel, and
textile. They observed that overseas competitors had surpassed
American firms, controlling the production of large percentages
of—if not entire—product groups (e.g., VCRs and televisions) and
industries (e.g., consumer electronics and machine tools). The MIT
Commission also indicated that American industry “indeed shows
worrisome signs of weakness. In many important sectors of the
economy, United States firms are losing ground to their competitors
abroad” (Dertouzos, et al., 1989, p. 8).

Along with declining productivity, the United States suffers
from inadequate quality, insufficient capital spending, and, sluggish
technological innovation (Hayes, Wheelwright, and Clark, 1988).

66

Hayes, et a1. attribute many of the problems to human behavior—
especially American managers' attitudes, capabilities, strategies——
particularly in the areas of manufacturing and technological

development” (1988, p. 11).

 

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figure 1.1: Productivity Growth of Industrial Nations

The MIT commission observes that manufacturing is
responsible for many of the competitiveness problems of the United

States:

“Much of the evidence we have gathered
points to the manufacturing sector as the area
where the American advantage in cost and
quality have been most severely eroded”
(Dertouzos, et al., 1989, p. 31).

Clearly, there is significant evidence of a competitiveness
problem in America and several analysts are indicating that the

manufacturing sector is a prime source of the problem.

5
Decline of American Competitiveness

Skinner (1985) offers an explanation for the decline of
American competitiveness: due to various distractions, US firms lost
sight of the importance of manufacturing. During the 1950s and
1960s, the emphasis of American companies and their top
management shifted away from manufacturing. He writes that their
new emphasis “was on growth in sales and market share,” and that
“top management seemed to be dominated and influenced more by
executives who were especially competent in marketing and
finance...” (Skinner, 1985, p. 4). Because of the shift in emphasis in
American firms, manufacturing executives felt separated and
possibly excluded from the core of the business. Conflicting business
requirements and outdated management methods also contributed to
manufacturing problems. Finally, Skinner notes that external
competitive pressures and rapidly increasing technology have
exacerbated the existing problems of US manufacturers.

The MIT Commission (Dertouzos, et al., 1989) indicates that the
competitiveness decline is the result of a set of factors. First, the
scope and extent of use of outdated strategies such as large-lot
production has limited the responsiveness of American firms.
Second, the Short planning horizons of financial institutions and
managers has reduced the ability of firms to achieve long-term
competitive changes. Finally, the Commission mentions a
fundamental lack of knowledge and training in human resources and
issues concerning cooperation, such as inter-functional
communication and labor-management relations.

Hill (1990) observes that, in the early part of this century,

6
world demand outstripped capacity. This imbalance, coupled with

post-WWII growth, provided importance and prestige to the
manufacturing function. In the mid-19605, however, the
relationship between world capacity and world demand shifted
(capacity becoming greater than demand), making it more difficult to
sell product in existing markets. This begat the rise of the marketing
function as a base of power in corporations. Following this was the
energy crisis and the recession in the early 1970s, heralding the
importance of the legal, finance and accounting functions.

Meanwhile, corporate policies of the 19605 and 1970s diverted
profits away from capital investment and caused management to
become focused on the short-term. This, coupled with the popularity
of portfolio management theory, which suggests firms diversify their
businesses, caused top management interest in the actual
manufacture of goods to wane. Also, as Crawford-Mason and Dobyns
(1991) observe, the Vietnam War and other social problems of the
19608 diverted the attention of society away from issues such as
quality and productivity.

Besides the declining corporate importance of the
manufacturing function, Hill (1990) suggests that the
competitiveness problem is related to other factors such as society’s
and management’s failure to recognize the size of the competitive
challenge, stockholder and management obsession with short-term
performance, and top management’s manufacturing inexperience.
These observations corroborate the arguments of Skinner and the
MIT Commission, and highlight top management’s shift in emphasis

away from production to marketing and finance.

7
In the late 1970s, the effects of previous manufacturing

“isolationism” became apparent as domestic firms started to feel
pressure from international competitors, especially the Japanese
(Giffi, Roth and Seal, 1990). Domestic firms responded to the new
economic threat, not by becoming more competitive, but instead by
managing international exchange rates. This action allowed domestic
firms to keep prices of American goods competitive, thus maintaining
international market share. Domestic firms did not, however, move
to make the goods themselves more competitive. Later, taking
advantage of lower wage rates in foreign countries, many companies
built factories overseas. Outsourcing production further depleted the
base of manufacturing skills and knowledge of American firms
(Prahalad and Hamel, 1990). Porter (1990) notes that both of these
actions—managing exchange rates and outsourcing production—will
have negative effects on firms and countries that respond to
international competition in this manner.

One result of sending production overseas was the inadvertent
creation of new competitors (Giffi, Roth and Seal, 1990). By
providing training and access to United States technology and
equipment, foreign countries were able to learn U.S. methods of
production and enter the global marketplace. This policy has had the
long term effect of increasing the competitive pressures experienced
by American companies, both in the Unites States and abroad, by

increasing the number of competitors (Meredith, 1992).

Increasing Standards

In countless industries, global competition has made long-term
viability much more difficult. In the past, tradeoffs between
competitive dimensions such as quality and cost, or features and
delivery Speed were thought to exist (Skinner, 1969). Firms
attempting to be competitive along multiple dimensions were either
introducing too much complexity or were “stuck-in-the-middle”, not
doing anything well (Porter, 1980). Today, in response to
competitive pressures, firms are simultaneously focusing on multiple
competitive dimensions in product and service offerings (Blackburn,
1990; Ferdows and DeMeyer, 1990; Chrisman, Hofer, and Boulton,
1988). Introducing products or services that compete along multiple
dimensions makes the traditional offerings of existing firms less
appealing and makes it more difficult for new competitors to enter
industries.

For example, American auto producers are making tremendous
strides in quality and productivity with quality records of some US
auto producers nearly equal to recent Japanese figures (Zellner,
1990). At the same time, however, leading Japanese manufacturers
are pushing out the limits of quality, redefining quality by stretching
the definition beyond defects per unit to include subtle human
perceptions (e.g., all control buttons require identical amounts of
force to activate) (Woodruff, Miller, Armstrong, and Peterson, 1990;
Walton, 1986). Domestic auto producers must move beyond the
already difficult task of reducing defects; they must simultaneously
build cars that consumers desire. Rates of improvement in quality

must be faster for domestic producers than they are for Japanese car

9
makers, otherwise, they will never catch up. Standards of excellence

are not static—they increase and move higher as competition
increases.

Global competitors in many industries have achieved
improvements in cost and quality through the concept of continuous
improvement or Kaizen (Imai, 1986; Brocka and Brocka, 1992;
Treece, 1993). Continuous improvement is constant and embraces
incremental product and process improvements made by all
members of an organization. Japanese firms have been practicing
Kaizen for several decades, making Kaizen an integral part of
Japanese management style. Since Kaizen is ingrained into Japanese
business practice, one should not expect its emphasis to diminish.
Therefore, US firms can expect the cost and quality levels of their
Japanese “competitors to continually improve. Increases in the
number of competitors in an industry and the concept of continuous
improvement or Kaizen are combining to constantly elevate global
standards of excellence.

Influenced by American computer producers and Japanese
automobile and consumer electronics manufacturers, global
customers are becoming accustomed to receiving high quality
merchandise at a fair price in a reasonable time period. As
customers come to expect more from product and service offerings,
the competitive standards in those industries will experience upward
pressure. It is irrefutable that characteristics and skills such as high
quality production, the speed with which a firm can change '
production from one product or model to another, quickly responding

to customer needs, and rapidly developing new products are also

10
becoming more critical (Stalk and Hout, 1990; Blackburn, 1990;

Wheelwright and Clark, 1992).

To close the gaps between themselves and their rivals, US.
firms must work extremely hard at choosing the appropriate means
and implementation methods (i.e., strategies) to achieve their
competitive goals. Meeting such demands presents new and
challenging problems for US firms, especially for the manufacturing
functions within these firms. Rapidly changing customer and market
expectations and increased competitiveness of global manufacturers
exacerbate the need for change in manufacturing. To guide and
direct the change process, many companies are focusing on

W to develop and implement competitive

manufacturing and business responses.

Manufacturing Strategy

Alfred Chandler defines strategy as “the determination of the
basic long-term goals and objectives of an enterprise, and the
adoption of courses of action and the allocation of resources
necessary for carrying out these goals” (1962, p. 13). Strategies can
occur at three levels in an organization: Corporate, Business, and
Functional (Hofer and Schendel, 1978; Ansoff, 1965; Andrews, 1971).
Corporate strategy defines which industries the firm should operate
in. Business strategy dictates the manner in which a firm will
compete within a given industry. Finally, functional-level strategies
are often determined by the business strategy and are designed to
support the business strategy.

Hill and Jones (1989) note that a major objective of functional

1 1
Strategy is to develop and exploit a distinctive competence within the

firm. Often, when companies possess a distinctive skill, ability or
technology, the business Strategy is formulated around this
distinctive competence (Porter, 1980; Hitt and Ireland, 1985; Snow
and Hrebiniak, 1980, Prahalad and Hamel, 1990). Business strategy
researchers have identified a strong relationship between the
presence of a distinctive competence and improved business
performance (Snow and Hrebiniak, 1980; Hitt and Ireland, 1985).
Such research highlights the critical relationship between business
strategy and functional strategy.

Porter (1980) presents the idea that companies compete using
three generic strategies (Cost Leadership, Differentiation, and Niche),
and that firms should only operate under one of these strategies at a
time (Dess and Davis, 1984). Firms that Simultaneously try to do
more than one are “stuck-in-the-middle” and, therefore, are
unsuccessful at any of the Strategies. While Porter suggests that
firms either differentiate (e.g., by product performance, or features,
or service, or quality, etc.) or become the low cost producer, it
became apparent in the 19708 and 19808 that international
competitors were succeeding in markets by simultaneously
competing on factors such as cost, quality and time (Stalk and Hout,
1990). Additional research into business strategy has revealed that
firms can compete on several dimensions simultaneously—results
that contradict Porter’s model (Chrisman, Hofer, and Boulton, 1988;
Ferdows and De Meyer, 1990; Roth and Miller, 1990).

Ferdows and De Meyer (1990) suggest that, to achieve

simultaneous capabilities, a sequence of skill and capability

12
acquisition exists. This sequence starts with improvements in

quality, which allow a firm to add the capability of dependability.
After mastering quality and dependability, a firm can develop speed
capability. Finally, once these skills have been developed, a firm can
work at increasing its cost efficiency. One key result of the authors’
early findings is that the manufacturing function can expect to play a
critical role in providing the ability for companies to concurrently
compete on several dimensions. For years, foreign competitors—-
namely the Japanese—based their business strategies on
manufacturing capabilities and, as a result, have driven customers to
expect more value from their purchases (Giffi, Roth, and Seal, 1990).
According to the results of Ferdows and DeMeyer, as global and
domestic markets demand products of higher quality, at lower prices,
and with shorter delivery cycles, U.S. firms will likely turn to the
manufacturing function for a source of competitive advantage.
Broadly stated, manufacturing strategy is the pattern of
manufacturing decisions that will provide the support necessary for
products to win orders in the marketplace (Hayes and Wheelwright,
1979a; Hill, 1994; Giffi, Roth and Seal, 1990). Skinner (1969, 1974,
1992a), one of the earliest writers on manufacturing strategy, notes
that manufacturing should be utilized as a source of competitive
advantage for a firm, not merely as a cost center. He argues that
corporate leaders misunderstand the function, and therefore,
delegate much of strategic manufacturing decision-making. Skinner
proposes that manufacturing have a voice in formulating corporate
and business strategy. In doing 80, manufacturing managers would

have the visibility to make manufacturing decisions that are in

1 3
alignment with the strategic direction of the firm. To make those

decisions, Skinner states that manufacturing managers must have
knowledge of what they must do well to support the business
strategy. Further developing the premise of manufacturing as a
source competitive advantage, Hayes and Wheelwright (1979b,
1984) discuss the notion of aligning manufacturing resources to
assist a firm in gaining competitive advantage. To focus resources on
the manufacturing task, they suggest that the concept of “competitive
priorities”—the dimensions along which firms choose to compete in
the marketplace—be used. Competitive priorities link manufacturing
objectives to the business strategy and other functional areas by
clearly establishing how a firm will compete in the market. Four
priorities have emerged as major categories: cost, quality, flexibility,
and delivery/time (Krajewski and Ritzman, 1990; Roth, De Meyer,
and Amano, 1989).

Another phase of development in manufacturing strategy has
occurred in which researchers have attempted to identify the specific
manufacturing practices and programs that allow firms to achieve
competitive objectives such as cost, quality, time and flexibility (De
Meyer and Ferdows, 1990; Roth, DeMeyer and Amano, 1989; De
Meyer and Ferdows, 1987). This research suggests that several
programs and strategies separately contribute to improvements in
cost, quality, flexibility and delivery.

Manufacturing strategy continues to be a rapidly growing area
for researchers, and an area of increasing concern for practitioners
(Voss, 1992a; Maruchek, Pannesi and Anderson, 1990; Anderson,
Schroeder, and Cleveland, 1991). Recently, research in the field has

14
matured to the degree that separate streams for the content and

process of manufacturing strategy have developed (Adam and
Swamidass, 1989; Ward, Leong and Snyder, 1990).

As strategists look to the manufacturing function as a source of
competitive advantage, the process of formulating manufacturing
strategy and the content of the strategy decisions must be
determined (Ward, Leong, and Snyder, 1990). The process decision
refers to methods of gathering and incorporating manufacturing and
firm information into strategy formulation. The content of
manufacturing strategy refers to the outcomes of the decision areas
that are of long term importance to the function and to the
competitive dimensions upon which a firm chooses to compete.
Outcomes can also be the programs and practices (i.e., manufacturing
strategies) implemented to achieve the objectives of the business
strategy or decision areas, including such items as just-in-time,
statistical process control, and inventory reduction techniques.

Choosing appropriate manufacturing strategies is a critical step
towards regaining competitiveness and meeting ever-increasing
customer requirements. As stated earlier, several authors have
linked the decline of American competitiveness to the manufacturing
function. To ensure that improvements will result, the
manufacturing strategies implemented by companies should be
aligned with the goals and objectives of the business strategy. The
wide range of manufacturing strategies and programs available
increases the complexity of these critical decisions.

One of the basic tenets of manufacturing strategy is that

manufacturing decisions and resource allocations should be in

15
alignment with business strategy. Firms with manufacturing

resources properly supporting business objectives should outperform
those firms whose manufacturing function is not in alignment with
the business strategy. Until recently, the necessary models to
adequately test and validate this tenet had not been constructed. To
this end, the notion of “production competence”—manufacturing
resources properly aligned with the business strategy—was

developed.

Production Competence: What Is It?

Production competence concerns the ability Of the
manufacturing function to support product-market initiatives. Hayes
and Wheelwright (1979a, 1979b) first discuss the concept of
competence in manufacturing in the context of their familiar
product-process matrix. They first observe that, just like products,
processes have life cycles. As product volumes change as the
product moves through its cycle, processes must also change. The
product-process matrix suggests that for a given product life cycle
stage, an appropriate production process (or stage) exists.

Hayes and Wheelwright designate an appropriate match of
products and processes as “being on the diagonal” and suggest that
this match is a requirement for firms desiring to be competitive.
They call the area or “patch” around the intersection of the product
and process structures “competence”—the ability of the production
process to support the characteristics of the products or product line.
In the product-process matrix, competence is something a firm either

has (being on the diagonal) or does not have (being off the diagonal).

16
Building on the product-process matrix, Cleveland, Schroeder

and Anderson (CSA) (1989) propose a theory of production
competence (PC) that attempts to explain what Skinner called the
“elusive set of cause-and-effect factors which determine the linkage
between strategy and production operations” (1969, p. 139). The
link between the business strategy and the manufacturing function is
what Cleveland, Schroeder and Anderson call production competence.
They define competence as “the preparedness, skill, or capability that
enables manufacturers to prosecute a product-market specific
business strategy” (Cleveland, et al., 1989, p. 655). One important
way in which the CSA definition of competence differs from that of
Hayes and Wheelwright is that the CSA model characterizes
competence as a continuous variable, rather than a fixed attribute.
In this context, a degree of competence exists, rather than the
dichotomous characterization of the Hayes and Wheelwright model.

In the CSA model, production competence is a “measure of the
combined effects of a manufacturer’s strengths and weaknesses in
certain key performance areas” (Cleveland, et al., 1989, p. 657). The
CSA method incorporates both the objectives of a firm’s business
Strategy—which determine the key performance areas—and the
Strengths and weaknesses of the firm’s present production process.
Together, these two items determine the competence score.

To verify that the theory of production competence was
tenable, the CSA model was tested on a small sample of
manufacturers (Cleveland, et al., 1989). Results suggest the existence
of strong linkages between competence and firm performance.

While the CSA model is a new and interesting method for

17
analyzing the contribution of production activities, there are some

problems with the methodology of the CSA study. For example, the
authors test the model on a very small sample (n=6) and use
regression analysis to investigate the nature of the relationship
between production competence and performance. When using such
small sample sizes, results must be viewed cautiously. Also, Vickery
(1991) observes that the variables used to operationalize the
business performance and production competence constructs are
closely related. On occasion, both constructs include the same
variables. This overlap of variables creates an artificially large
correlation between firm performance and production competence,
perhaps overstating the true relationship.

Vickery (1991) addresses these problems and presents an
improved theoretical framework for understanding the production
competence (PC) construct (see Figure 1.2). The Vickery model views
the PC construct in the context of a process model of manufacturing
strategy, one that translates the objectives of the business strategy
into manufacturing competitive priorities. Vickery states that
production competence is best understood within this framework
and that production competence can be determined for a firm
regardless of the strategic process utilized.

The Vickery model draws on the work of Schroeder and Lahr
(1990), who combine strategy formulation methodology from the
organizational literature with accepted ideas of manufacturing
strategy to form a proceSs model of manufacturing strategy. In
Vickery’s model, competitive priorities provide the linkage between

business strategy and manufacturing decision-making. Vickery

1 8
argues that production competence is a function of the importance of

various competitive priorities to the firm and the Strength or
weakness of the support provided to these priorities by
manufacturing. The strength of support provided (i.e.,
manufacturing performance) is a function of the selection and
implementation of various manufacturing strategies. Production
competence, therefore, is a function of manufacturing Strategy
selection and implementation.

In the model proposed by Vickery (1991), manufacturing
performance is determined by two elements—the strategic
manufacturing decisions made (i.e., facilities, technology, quality
management, etc.) and the projects and programs implemented.
Schroeder and Lahr (1990) indicate that manufacturing programs
link together strategies and tactics, and that the programs
themselves are also tactical in nature. It is clear from Vickery’s
model that the selection of manufacturing strategies, combined with
the implementation of the strategies through tactical programs and
techniques, determine whether performance targets are met, and,
therefore, the level of competence that a firm achieves. Vickery
concludes that the production competence construct can be a used to
investigate the link between manufacturing strategy and business
performance. I

Vickery, Droge, and Markland (1993) extend the earlier
Vickery model and develop an improved measure of production
competence. The model is extended to include a business strategy
construct for the purpose of investigating whether being competent

in manufacturing is enough to produce superior business

l9

 

 

(e.g., Differentiation, Cost)
1

Business Strategy |

 

 

 

1

Identification & Weighting
of Mfg. Competitive Priorities
(e.g., quality, cost, flexibility)

i

Strategic Manufacturing
Decisionmaking
(e.g., Facilities, Technology)

 

 

 

 

 

 

 

Implementation
(e.g., Manufacturing
Projects, Programs)

t

Manufacturing
Performance Measurement
(Mfg. Strengths, Weaknesses)

 

P
E
g
i
a

 

 

 

 

 

 

I

[ Business Performance J

 

Source: Adapted from Vickery (1991)

 

Figure 1.2: A Process Model of Production Competence

III

III

2 0
performance. The measure of production competence was improved

to include an enlarged number of competitive priorities and an
allowance was made for the proportion of each competitive priority
for which manufacturing is responsible. Results from this research
suggest a positive and significant relationship between production
competence and firm performance. This work validates the earlier
research of Cleveland, et al. (1989) and Vickery (1991) and

encourages additional research on production competence.

Research Purpose

Several authors and government statistics have identified
striking weaknesses in American competitiveness and manufacturing
(Giffi, Roth and Seal, 1990; Hayes, Wheelwright, and Clark, 1988;
Dertouzos, Lester, Solow and the MIT Commission on Industrial
Productivity, 1989; Cohen and Zysman, 1987). The authors and
reports suggest that poor quality, high production costs and lagging
productivity growth have reduced the competitiveness of American
firms in global markets. Today, increased global competition has
refocused the attention of top management, and manufacturing is
again being looked upon as a potential source of competitive
advantage for companies.

The task of generating advantage from within manufacturing is
extremely complex. To assist firms in becoming more competitive,
myriad strategies, programs and tools have been introduced (e.g., JIT,
TQM, group technology, MRPII). Given the multiplicity of programs
and methods available, companies face the challenging task of

determining which programs and methods to implement in view of

2 1
the firm’s strategic objectives. For example, if a company has chosen

to compete on product quality and delivery speed, which
manufacturing strategies and/or programs will enable it to excel in
these areas?

Recently, researchers have introduced the production
competence construct to determine whether the programs and
methods selected and implemented by the manufacturing function
are, in fact, supporting business strategy objectives. Vickery (1991)
improved an earlier model presented by Cleveland, et al. (1989) and
discussed the construct of production competence in the context of a
process model of manufacturing strategy. Vickery, Droge, and
Markland (1993), after further developing the measurement of the
construct, tested their model and discovered a significant positive
relationship between production competence and firm performance.

The theoretical framework introduced by Vickery indicates
that production competence is a function of the competitive priorities
important to a firm and the ability of the manufacturing function to
properly select and implement manufacturing strategies and
programs that support the competitive priorities (See Figure 1.2).

The purpose of this research is to identify the manufacturing
strategies, programs and techniques that best support manufacturing
strategic objectives or competitive priorities. Relating this research
objective to Figure 1.3, the purpose is to identify the strategies and
programs implemented in Stage 3 to support manufacturing
competitive priorities identified in Stage 1. The manufacturing
competitive priorities—determined by the business strategy

objectives—guide the strategic manufacturing decision-making

22
process portrayed in Stage 2. The manufacturing strategies and

programs implemented are the outcomes of this decision-making.
Stage 4 represents the measurement of manufacturing performance.
Finally, production competence is a measure of the support provided
to the manufacturing strategic objectives. In this context, production
competence provides a measure to evaluate the effectiveness of the
support provided by various manufacturing strategies and programs
implemented in Stage 3.

In the manufacturing strategy literature, four main competitive
dimensions have been identified: quality, delivery response, cost, and
flexibility (Skinner, 1985; Roth, De Meyer, and Amano, 1989). Within
a given competitive dimension, researchers have identified a set of
manufacturing techniques and action programs related to improved
performance (Hayes and Wheelwright, 1984; Sharma, 1987; Roth,
1987; Roth, De Meyer and Amano, 1989; Ferdows and DeMeyer,
1990). AS managers ready their firms for changes in strategic
posture and competition along multiple competitive dimensions, they
need to know which manufacturing techniques and strategies are
most, effective in supporting specific manufacturing competitive
priorities, and hence, the business strategy itself.

The Global Manufacturing Futures Project has perhaps
produced the largest body of research into the use of manufacturing
techniques. This research team has generated a list of 39
techniques—called “action programs”—which are presented to
respondent firms for evaluation and projection of use (Ferdows and
DeMeyer, 1990). In various papers, the team has linked the use of

particular action programs to competitive priorities. Other

Stage 1

Stage 2

Stage 3

Stage 4

23

 

 

Identification & Weighting
of Mfg. Competitive Priorities
(e.g., quality, cost, flexibility)

 

 

i

 

 

Strategic Manufacturing
Decisionmaking
(e.g., Facilities, Technology)

 

 

i

 

 

Implementation
(e.g., Manufacturing
Strategies and Programs)

 

 

i

 

 

Manufacturing
Performance Measurement

(Mfg. Strengths, Weaknesses)

 

 

Source: Adapted from Vickery (1991)

Figure 1.3: A Closer View of the Production Competence Construct

 
    

HDNHEHWOO NOIIDIICIOHd

24
researchers are also studying the choices of manufacturing

techniques that firms are making (Oakland and Sohal, 1987; Roth,
1987; Schmenner, 1988b; Tunalv, 1992). A major benefit of this
stream of work is that it begins to focus attention on the particular
activities necessary to both achieve manufacturing objectives and
make improvements within specific areas of manufacturing.

A key concept missing from this research stream, however, is
the appropriateness of the strategies and techniques that firms
implement. Skinner (1992a) notes the deficiencies in the
manufacturing strategy field, observing that adoption of “off the
shelf” technologies and strategies is not making firms more
competitive. He writes that manufacturing strategy will continue to
miss its potential until the field “can provide more links between
tasks, objectives and specific manufacturing policies” (Skinner,
1992a, p. 22). He has also identified “research and conceptual
development of concrete, explicit bridges between task and
structural decisions” as the primary need in the field (1992a, p. 25).

Knowing that the role of any functional strategy is to support
the overall business strategy, the most appropriate choices of
manufacturing techniques and programs are those that are most
effective in supporting the goals of the business. Firms
implementing the most effective strategies and techniques will have
the most “competent” manufacturing functions. Given the findings of
Vickery, et al. (1993), these firms should also realize improved
performance. Previous studies have investigated the use of
manufacturing strategies and programs without measuring their

effect on overall performance or performance in critical areas.

25
Results of this research will indicate the manufacturing

strategies and programs that are most effective in supporting
manufacturing and business objectives. Using data gathered from an
earlier study (Vickery, Droge, and Markland, 1993) and this project,
the overall competence and performance of a firm’s manufacturing
function can be determined. Thereby, those manufacturing
strategies and programs enabling firms to be competent in
production—and thus, good performers—will be identified.

In the same manner that performance and competence scores
can be determined and calculated for the entire manufacturing
function, competence scores can be computed for each major
competitive priority (i.e., cost, quality, delivery response, and
flexibility). Thus, constructs can be created that attempt to measure
manufacturing’s ability to support specific business objectives in the
areas of cost, quality, delivery, and flexibility.

The new constructs will be called cost competence, quality
competence, delivery response competence, and flexibility
competence. This research will identify the manufacturing strategies
and programs that, in addition to overall production competence, are
associated with competence and performance for the major
competitive priorities. These results will directly respond to the

research need identified by Skinner (1992a).

Research Questions
Vickery, Droge, and Markland (1993) observe a link between
firm performance and production competence. This project will

extend their results and investigate the relationship between the use

26
of manufacturing strategies and programs, and production

competence. AS such, the following research question will be

examined:

1. What is the relationship between the use of
manufacturing strategies and programs, and
production competence?

Vickery, Droge and Markland (1993) determine production
competence for a firm in part by identifying the importance,
performance, and manufacturing responsibility (expressed as a
percentage) of 31 competitive priorities. The competitive priorities
in that study are a combination of manufacturing, design, and
marketing dimensions.

Using previous research and the four established
manufacturing competitive priorities (cost, quality, delivery, and
flexibility) as a guide, the competitive priorities appearing in the
Vickery et a1. (1993) study that relate to manufacturing can be
placed into one of the four major categories. Each of the four priority
groups will then be comprised of a collection of “sub-priorities”.
Since each established priority would encompass several sub-
priorities, the same method used to determine the overall production
competence score (summing the product of strategic importance 0
firm performance 0 percent manufacturing responsibility across 31
priorities) can be applied to the four competitive priority groups.
This results in the calculation of a competence score for each of the
four priorities.

Using the method described above, a cost competence score, a

2 7
quality competence score, a delivery competence score, and a

flexibility competence score will be calculated for each firm. This
will expand the production competence construct, allowing for
analysis of the relationship of manufacturing strategies and
programs with specific business objectives and competitive priorities.
This analysis responds to the need identified by Skinner (1992a) to
develop specific linkages between tasks and strategic decisions. The

research questions this extension raises are:

2a. What is the relationship between the use of
manufacturing strategies and programs, and cost
competence?

2b. What is the relationship between the use of
manufacturing strategies and programs, and
delivery competence?

2c. What is the relationship between the use of
manufacturing strategies and programs, and
flexibility competence?

2d. What is the relationship between the use of
manufacturing strategies and programs, and quality
competence?

While some research has been conducted regarding the
relationship between action plans and competitive priorities, this
research does not, for the most part, account for firm performance in
the relationships (Roth, De Meyer, and Amano, 1989). In addition to
the major competence constructs described above, the notion of
categorizing the 31 priorities relating to manufacturing into four
groups can be applied to performance.

Each firm in the study has subjectively rated their own

2 8
performance on each of the 31 priorities. Using the same groups as

identified above, performance scores for cost, quality, delivery-
response and flexibility can be determined for each firm. A benefit
of analyzing the relationship between the use of manufacturing
strategies and performance is that a more direct assessment of the
effect of individual strategies and programs might be observed. This

raises the following research questions:

3a. What is the relationship between the use of
manufacturing strategies and programs, and
subjective cost performance?

3b. What is the relationship between the use of
manufacturing strategies and programs, and
subjective delivery performance?

3c. What is the relationship between the use of
manufacturing strategies and programs, and
subjective flexibility performance?

3d. What is the relationship between the use of
manufacturing strategies and programs, and
subjective quality performance?

Much of the research in the strategy/policy area relates the use
of strategies to overall firm performance. In this study, the use of
manufacturing strategies, programs, and techniques and their
relationship to overall firm performance would be of interest. This

raises the following research question:

4. What is the relationship between the use of
manufacturing strategies and programs, and overall
firm performance?

2 9
Finally, much of the practitioner and academic literature

contains suggestions for the manufacturing strategies and techniques
that may support a particular competitive priority. By combining
several of the strategies that relate to specific priorities, new
constructs can be created and the bundle of strategies can be tested
as one group. These bundles can be related to all of the competence
and performance constructs discussed above. As such, the following

research questions can be raised:

5. What is the relationship between the use of
groups of manufacturing strategies, programs, and
techniques and competence?

6. What is the relationship between the use of
groups of manufacturing strategies, programs, and
techniques and performance?

Scope Of Research

The furniture industry is one that is experiencing many
changes. Once an industry characterized by small shops producing
furniture by hand, it is now an industry striving to implement
competitive business and manufacturing techniques. This is a period
of transition for many furniture makers who seek to implement the
newest technology and practices into businesses that, in the past,
have relied on very traditional methods. The furniture environment
offers an opportunity to examine manufacturing practices and
changes among a diverse group of firms. There are participants at
both ends of the technology Spectrum, from programmable
technology to hand saws.

The objective of this research is not to chronicle the differences

30
between technology adopters and more traditional enterprises in the

furniture industry, but to see if, in fact, the new manufacturing
strategies, programs and technologies are doing what they are
purported to do—that is, to improve the competitiveness of the firm.
The study will be limited to participants in the furniture
industry, with annual sales of the target firms ranging from ten
million to hundreds of millions of dollars. The study will include
only the CEOS and managers in the manufacturing function of the
firms. Questionnaires will ask about the use of manufacturing
strategies and programs currently in use in their company. In
addition, measures relating to cost, quality, flexibility, and delivery
performance of participating firms will be included. Finally, the
participants will be asked about the level of interaction between the
managers in the manufacturing function and those working in both

marketing and product design.

Contributions Of Research

The ability of American firms to be competitive in a global
market has diminished over the past 45 years. Economic data and
government statistics indicate that the U.S. economy has several
weaknesses and many researchers have identified the manufacturing
sector as a primary source of the nation’s troubles. More positively,
these researchers are turning to the manufacturing sector to increase
the competitiveness of the nation and its firms.

In response to the complexities and difficulties in
manufacturing, a multitude of manufacturing programs has become

available during the past 20 years. Operating with finite resources

3 1
and limited time horizons, American firms are faced with important

decisions regarding which manufacturing strategies and programs
are best for their companies. Adding to the difficulties is the fact
that investments in manufacturing are often very expensive and,
therefore, difficult to reverse (Hill, 1994). This research will help to
identify the manufacturing strategies and programs firms should
adopt to achieve their goals and objectives.

Production competence is a measure of the support provided to
business objectives by manufacturing. Business goals and objectives
are communicated to manufacturing through competitive priorities.
It is manufacturing’s role to provide support to these priority areas.
Vickery, Droge, and Markland (1993) identified a significant positive
relationship between production competence and firm performance.
In their model of production competence, manufacturing
performance is a function of the appropriateness and effectiveness of
the manufacturing strategies and programs selected and
implemented by a firm. If positive firm performance and increased
competitiveness are related, and competence is related to
performance, it then follows that the selection of appropriate
manufacturing strategies and programs is directly related to
competitiveness. In other words, to increase their competitiveness in
a world of finite resources, U.S. firms must select and implement
manufacturing strategies and programs that are in alignment with
the firm’s strategic business objectives.

This study will identify the manufacturing strategies and
programs firms are using to achieve production competence and,

therefore, become more competitive. Given the multitude of

32
manufacturing programs and techniques introduced and the

competitiveness of the domestic and global markets, companies need
information regarding the effectiveness of these programs in
providing support for their business goals. Data about particular
programs will provide information to alleviate some of the
uncertainties involved in making critical manufacturing decisions.

The results of this study will provide that crucial information.

Research Limitations

Several factors limit the results of this study. First, it is
restricted to firms in the furniture industry, which reduces the
external validity, or generalizability, of the results (Kerlinger, 1986).
That the furniture industry is one experiencing rapid change may
mitigate the impact of this limitation. The rapid pace of change
provides an opportunity to gauge the success of the programs among
the early adopters.

Another factor that limits the study is that it does not account
for the resources or ‘methods/processes firms use to formulate and
implement the strategies and programs. Manufacturing strategy is a
relatively young field and is in need of additional research into the

formulation process.

Organization Of Dissertation

The organization of the remainder of the dissertation follows.
Chapter 2 contains the literature review which includes a discussion
of empirical-based research and theory development in operations

management, an examination of research pertaining to the

3 3
development of manufacturing strategy and the use of

manufacturing techniques, and an in-depth review of the production
competence construct. Chapter 3 is the methodology chapter and
includes discussion of model development, manufacturing strategies
and programs, hypotheses, method of testing, and data collection
issues. Chapter 4 contains the results and preliminary analyses of
the tests. Chapter 5 discusses further implications of the results,
contributions of the research, limitations, and suggestions for further

research on the topic.

II. LITERATURE REVIEW AND THEORY DEVELOPMENT

This section will discuss the need for more empirical-based research
and theory development in Operations management (OM), and
describe more fully the development of theories. In addition, this
section will address theory development in terms of the production
competence construct. Finally, research regarding the use of
particular manufacturing techniques and programs and their

relationship to competitive priorities is discussed.

Empiricism In Operations Management

Until the late 19508, manufacturing played a significant role in
developing the United States’ stature as a world economic power.
During the 19608 and 19708, however, as global capacity outstripped
demand, top management began to regard the finance and marketing
functions as strategic and critical, reducing manufacturing’s role to a
secondary, reactive one (Skinner, 1978; Hill, 1990).

Similarly, academics in operations management (OM) felt as
though researchers in organizational behavior, finance, and
marketing received more respect than they did (Miller and Graham,
1981).

Another problem facing academics in operations management
was that the practitioner community considered much of the
research in manufacturing and operations management to be of
dubious value (Miller and Graham, 1981; Fryer, 1981; Meredith,
Raturi, Amoako-Gyampah, and Kaplan, 1989). Practitioners lamented

that the problems studied by academics were unrealistic and that,

34

3 5
even if the problems were realistic, the solutions were

incomprehensible. In 1980, the bulk of the research in OM was
grounded in optimization and other operations research and
management science (OR/MS) techniques, solidifying the perception
that academic solutions were not applicable to practitioner problems
(Miller and Graham, 1981; Chase and Prentis, 1987; Wood, 1989).

To address the gap between what practitioners felt were the
real problems and those being researched by academicians, several
turn-of-the decade articles appeared (Miller and Graham, 1981;
Chase, 1980; Buffa 1980; Hax, 1981). The articles called for a move
away from traditional OR/MS research to research that was more
useful to practitioners. The authors hoped this move would raise the
consciousness of the entire research community to the field of OM,
thus increasing its stature within the academic community.
Recognizing that operations management is an applied field, the
authors suggested a more applied or empirical approach to OM
research.

In commentaries to Miller and Graham, Buffa (1980) and Groff
and Clark (1981) recognized that conducting empirical research
requires a completely new set of research tools, very different from
those developed for OR/MS research. Buffa hypothesized that a
movement to empirical research would be slow as the current OM
teachers, researchers, tenure committee members, and journal
editors had all been trained in the traditional ways. Furthermore,
training research methods for the doctoral students of the period
continued to be in techniques of the OR/MS school.

To investigate if research in OM had indeed acted on the

3 6
agenda presented by Miller and Graham (1981), Amoako-Gyampah

and Meredith (1989) conducted a review of articles published in OM-
related journals during the mid-808. Classifying articles according to
research area and methodology, their results indicated that, for the
most part, research in OM had continued along the same course, just
as Buffa had surmised it might. Empirical research comprised just
15% of the research appearing in their study, with the majority of
research falling under the headings of “model formulation”
(mathematical, algorithmic, heuristic, statistical and graphical) and
“laboratory simulation”.

Also addressing the issue of a lack of progress in closing the
industry-academia gap, Meredith, Raturi, Amoako-Gyampah, and
Kaplan (1989) proposed that the current research paradigm used by
OM researchers was inadequate. They said the paradigm “is typically
prescriptive, deterministic, non-contextual, and exhibits a
preponderance of ‘rational’ constructs” (Meredith, et al., 1989, p.
301). They noted that a lack of knowledge of alternative research
paradigms may contribute to this narrow view. Building on the work
of Emory (1985), they developed a research cycle and a 2-axes
generic framework for characterizing research methods. The first
axis of the framework concerned whether the research process was
rational or existential (i.e., deductive or inductive). The second axis
described the proximity of the model or problem to reality (artificial
or natural).

Applying this framework to operations management, Meredith,
et a1. classified research in three OM journals (Management Science,

Decision Sciences and the Journal of Operations Management) from

37
1977 and 1987 according to methodology used. They wrote “the

inescapable conclusion is that our research in operations is still
overwhelmingly artificial in nature, though breaking the
methodological tie with the field of management science has allowed
us to begin moving toward more existential (primarily interpretive)
paradigms and to move away from the more rationalistic, ‘scientific’
paradigms” (Meredith, et al., 1989, p. 317).

The call for more empirical research in operations management
still exists today, just as it did in the early 19808 (Swamidass, 1991;
Meredith, et al., 1989; Anderson, Cleveland, and Schroeder, 1989).
This time, however, it appears that the call will receive due attention
as articles that detail empirical research techniques (Flynn,
Sakakibara, Schroeder, Bates and Flynn, 1990; Wood, 1989), present
new paradigms for OM research (Meredith, et al., 1989), and discuss
theory development (Swamidass, 1991) are beginning to appear in
OM-related research journals. The Journal of Operations
Management continues to announce its receptiveness to empirical
and field-based research. These developments appear to be positive
steps toward overcoming many of the barriers to empirical research
in Operations management identified by Buffa (1980).

Researchers can reduce the gap that exists between academics
and practitioners by concentrating on problems that practitioners
perceive to be important. Using the notion of material requirements
planning (MRP) and production activity control (PAC) as examples,
Chase and Prentis observe: “The practitioner literature has
frequently led the way in identifying significant topics for OM

research and in providing new terminology to label particular

3 8
aspects of the field” (1987, p. 361). They further state “that OM,

perhaps more than any other field of business draws its research
thrusts from the real world” (Chase and Prentis, 1987, pp. 361-362).

Currently, the “real world” consists of increasing global
competition and diminishing competitiveness of U.S. firms, forcing
many companies to reevaluate their businesses. Facing difficult and
complex problems, businesses and manufacturing managers are
seeking solutions that they can understand and implement. This
presents a unique opportunity for researchers in the field of OM to
simultaneously close the gap between themselves and practitioners
and, to make significant contributions to business research.

This research project will attempt to accomplish both tasks. It
will identify manufacturing strategies and techniques being used by
firms in the furniture industry to improve financial performance and
become more competitive. Results of the research should be of value

to practitioners and researchers alike.

Manufacturing Strategy

Skinner (1969) was among the first to recognize that
manufacturing can be a competitive weapon for a firm. Skinner
observed that, in most American companies, the interrelationships
between manufacturing policy decisions and business strategy
alternatives were being ignored. Skinner’s notion of the
interrelationships was “that a company’s competitive strategy at a
given time places particular demands on its manufacturing function,
and, conversely, that the company’s manufacturing posture and

operations should be specifically designed to fulfill the task

39
demanded by strategic plans” (1969, pp. 138-139). Skinner called

the set of activities required of manufacturing to support the
Strategic plans the “manufacturing task”.

Skinner noted that, without knowledge of the overall strategic
direction of a firm, manufacturing will be unaware of the business
implications of policy decisions made within the function. Therefore,
manufacturing will be unable to proactively and effectively
contribute to the pursuit of strategic competitive Objectives (i.e., the
manufacturing task). Skinner also noted that, long dominated by
Specialists and experts, the manufacturing function was considered
too technical and was, therefore, avoided by top management. AS a
result, manufacturing policy decisions were delegated to
manufacturing executives. Usually, these executives did not
participate in formulating strategic policy for the business.
Consequently, manufacturing policy decisions were made in isolation
from the rest of the organization and, therefore, did not contribute to
strategic business objectives as strongly as they might have. This is
part of what Skinner meant by using manufacturing as a competitive
weapon—allowing manufacturing executives entree to the strategic
debate so they can make strategic decisions that align with business
strategy objectives.

Manufacturing strategy is rapidly gaining in popularity as
witnessed by the dramatic increase in books and papers published
on the subject (Wheelwright and Hayes, 1985; Swamidass, 1986;
Gunn, 1987; Suzaki, 1987; Ettlie, Burstein and Feigenbaum, 1990; Hill,
1994; Swamidass and Newell, 1987; Voss, 1992a; Gunn, 1992).

Several models have been presented describing the purpose and

40
process of manufacturing Strategy (Skinner, 1969; Wild, 1980; Hayes

and Wheelwright, 1984; Fine and Hax, 1985; Cleveland, Anderson,
and Schroeder, 1989; Gunn, 1987; Schroeder and Lahr, 1990; Roth
and Miller, 1990; Vickery, 1991; Anderson, Schroeder, and Cleveland,
1991; Voss, 1992b). Since it is still a young discipline, many of the
models contain philosophical differences. Still other differences can
be attributed to misunderstandings arising from mixed uses of
terminology. This terminology problem also existed in the
strategy/policy field.

To facilitate the development of business strategy/policy
research, researchers classified previous work into two categories—
content and process. Fahey and Christiansen wrote that content
research refers to “research which examines the content of decisions
regarding the goals, scope, and/or competitive strategies of
corporations” (1986, p. 168). Process research refers to the actions
involved in the formulation and implementation of strategy (Huff
and Reger, 1987). Recently, OM researchers employed this
dichotomy and classified manufacturing strategy literature into
content and process categories (Schroeder, Anderson, and Cleveland,
1986; Adam and Swamidass, 1989; Ward, Leong, and Snyder, 1990).

In the context of manufacturing strategy, mm usually refers
to two categories: 1) the strategic decision areas of manufacturing
and the programs implemented in those areas, and 2) competitive
priorities. Building on the work of Skinner, Hayes and Wheelwright
(1984) identify eight strategic decision categories and place them
into two groups: structural and infrastructural. Structural categories

include capacity, facilities, technology, and vertical integration.

41
Infrastructural categories include workforce, quality, production

planning/materials control, and organization (Hayes and
Wheelwright, 1984; Anderson, Cleveland, and Schroeder, 1989). The
second content category—competitive priorities—are the ways in
which firms choose to compete in markets and include low cost,
conformance quality, design quality, delivery speed, delivery
dependability, product development speed, volume flexibility, and
product flexibility (Krajewski and Ritzman, 1993; Wood, Ritzman and
Sharma, 1990).

Work in the process area has progressed at a Slower pace.
Skinner’s (1969) breakthrough work presented one of the earliest
manufacturing strategy process models. Skinner’s model was later
refined by Hayes and Wheelwright (1978, 1984). Fine and Hax
(1985) adapted a corporate strategy model to manufacturing
strategy development. Sharma (1987) developed a comprehensive
model linking manufacturing to corporate strategy, business strategy,
other functional areas and external forces. Schroeder and Lahr
(1990) merged traditional policy models from strategy research with
concepts from manufacturing strategy to create a process model for
use by practitioners. Gunn (1987) presented a four-pillar approach
to developing a manufacturing strategy.

Throughout the development of various manufacturing
strategy process models, a fairly common set of Stages has emerged.
Additionally, the elements or stages of process models often overlap
with content areas of manufacturing strategy. Generally,
manufacturing strategy process models start with the formulation of

corporate or business strategy. Competitive priorities, or the

42
competitive dimensions along which firms choose to compete,

communicate the strategic business objectives to manufacturing.
After the identification and communication of competitive priorities,
manufacturing organizations must decide how to allocate resources to
successfully support competitive business objectives.

In several models of manufacturing strategy, the
manufacturing decisions regarding manufacturing resources or
strategic variables are called “strategic manufacturing decisions”. It
is at this point in process models that the overlap to content
variables occurs. The strategic decisions made in process models
concern content issues and variables. For example, to ensure
adequate capacity exists to produce a new product, additional
capacity may be required. Capacity is one of the major content
variables. Process models and research are concerned with how the
decision was made, while content research is concerned with the
outcome of the decision process.

Following the strategic decisions, the next general stage in
manufacturing strategy process models is the identification and
implementation of Specific strategies and programs to execute the
strategic decisions and achieve business objectives. Again, there is
some overlap with content issues as the strategies and programs to
be implemented can be classified as content variables (Fahey and
Christensen, 1987). In the final stage of process models, the
performance of the strategies and programs is evaluated and the
performance results are fed back to earlier Stages or decision making
points in the model.

Similar to the Hayes and Wheelwright designation, the strategic

43
variables in Sharma’s (1987) manufacturing strategy process model

were broadly defined as those dealing with (l) structural decisions,
concerning the design of operations systems (i.e., location, facilities,
layout, etc.), and (2) infrastructural decisions, or those concerned
with the Shorter-term management of operations (i.e., aggregate
planning, scheduling, inventory control, etc.). In research by Sharma
and others, content and process variables are discussed
simultaneously (see Fine and Hax, 1985; Schroeder, Anderson, and
Cleveland, 1986; Roth and Miller, 1989). Adam and Swamidass
(1989) noted that manufacturing strategy researchers often combine
process and content ideas and suggested that development in the
field would be aided by establishing two distinct streams.

Recently, Adam and Swamidass (1989) and Anderson,
Cleveland and Schroeder (1989) separately review manufacturing
strategy and synthesize progress in the field, together highlighting
three common areas in need of research. The first area of
opportunity concerns the link between manufacturing strategy and
firm performance. Anderson et al. write: “The underlying, and often
presumed argument that exists within the literature that links
Operations strategy and Operations decisions with corporate strategy
is that proper strategic positioning or aligning of operations
capabilities can significantly impact competitive strength and
business performance of an organization” (1989, p. 134). Several
others share this position, including Stobaugh and Telesio (1983),
Wheelwright (1984), and Fine and Hax (1985). Anderson et a1.
observe that this premise, while powerful, has only recently been

empirically tested. Adam and Swamidass (1989) also identify the

relati

353

work
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opera

idem

in II
cont:
expo
p. 1.
(.‘OlllI

relat

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44
relationship between operations strategy and business performance

as a “missing theme”.

The second area of manufacturing strategy requiring additional
work is in the area of content issues. Anderson et al. report that
“The literature pays very little attention to the actual content of
operations strategy” (1989, p. 151). Again, Adam and Swamidass
identify content issues as a “missing theme”.

The third issue common to both reviews is a call for an increase
in the amount of empirical research performed in both process and
content areas. Anderson et a1. write: “The literature is largely
expository in nature—it contains very few empirical studies” (1989,
p. 152). Adam and Swamidass corroborate: “The shortcoming of
content research is that it lacks empirical investigations of
relationship among its variables” (1989, p. 185).

The three missing themes of research in manufacturing
strategy—its effect on business performance, increased coverage of
content issues, and more empirical research—are each addressed in
the study proposed here, as is the separation of process and content
issues. This study is the second stage of a research project
investigating production competence. The first stage (Vickery, Droge,
and Markland, 1993) identified a link between production
competence and performance that will be augmented by this project.

The results of the study by Vickery et a1. indicated that firms
with higher production competence scores outperformed firms with
lower scores. The authors also accounted for two other variables in
the study: (1) the main effect of the business strategy on

performance, and (2) the interaction of business strategy and

45
production competence on performance. Results of this analysis

revealed that, for this study, the main effect of business strategy
type was not related to performance. However, the interaction
between business strategy and production competence did have an
effect, particularly when the strategy adopted was one of
Differentiation. This result broadens the spectrum of manufacturing
involvement and support of business strategy from a traditional low
cost focus to one that must support a variety of strategic objectives
and corroborates what Skinner has been saying all along.

This project, an extension of Vickery et al. (1993), is an
empirical study directed at the identification of the specific strategies
and programs implement by firms and their relationship to
production competence. As such, the content issues related to the
firm’s manufacturing strategies will be captured. Data regarding
overall firm performance gathered by Vickery et a1. and new
performance data obtained in this study will be used to relate the
use of manufacturing strategies to overall performance and
performance within competitive priorities. Thus, this study is a
direct response to the manufacturing strategy research needs
identified by Anderson et al. (1989) and Adam and Swamidass
(1989) and an extension of current research in manufacturing

strategy.

Production Competence
While the notion that a properly aligned operations strategy
can improve business performance is consistent and prevalent in the

literature, Anderson, Cleveland and Schroeder (1989) observed that

46
it has never been empirically tested. To investigate the relationship

between operations strategy and performance, Cleveland, Schroeder,
and Anderson (CSA) (1989) propose a model of manufacturing
strategy that includes the construct of “production competence”.

According to Cleveland et al., the production competence
construct explains the “long-suggested link between production
processes and business strategy” (1989, p. 667). This addresses what
Skinner (1969) called the “missing link”. The CSA model defines
production competence as “the preparedness, skill, or capability that
enables manufacturers to prosecute a product-market specific
business strategy” (Cleveland, Schroeder, and Anderson, 1989, p.
655). The production competence construct describes the degree of
support supplied to the business strategy by manufacturing.

Earlier, Hayes and Wheelwright (1979) had proposed a
narrower definition of production competence saying that
competence was the result of proper alignment between the life
cycle stages of the product and the production process. In their
model, competence was a characteristic a firm either possessed or
did not possess. In contrast, the CSA model suggests that production
competence can be expressed as a continuous variable, rather than
the dichotomous characterization of Hayes and Wheelwright.

Production competence, in the CSA model, is a “measure of the
combined effects of a manufacturer’s strengths and weaknesses in
certain key performance areas” (Cleveland, Schroeder, and Anderson,
1989, p. 657). The calculation of the production competence score
involves several steps. First, the authors identify nine performance

areas from the literature considered to be critical to the success or

47
failure of the business plan: adaptive manufacturing, cost-

effectiveness of labor, delivery performance, logistics, production
economies of scale, process technology, quality performance,
throughput and lead time, and vertical integration. Second, the
business strategy of the firm is captured by ranking the nine critical
manufacturing performance areas in descending order of importance
to the business strategy of a particular firm (1 = most important, 9 =
least important). The importance rankings of each performance area
are then inverted so that a larger value is associated with increased
importance (9‘ = most important, 1 = least important). Next, using the
type of production process (job shop, batch, connected line flow, or
continuous flow) adopted by the firm as a guide, the nine
performance areas are evaluated as being a strength, neutral, or a
weakness. Based on the evaluation, a rating is assigned (strength =
+1, neutral = 0, weakness = -1) to each performance area. To
improve the fit of the CSA model and compensate for the narrow
performance scale, the authors incorporated a logarithmic
transformation of the inverted rankings.

The final step is to calculate the production competence score,
which is accomplished by multiplying the assigned
strength/neutral/weakness rating (+1, 0, -l) by the log-transformed
inverted ranking for each of the nine performance areas. This
product is summed across all nine performance areas to determine
the total production competence score.

The theory represented by the CSA model is that firms with
competent manufacturing functions—one that provides strong,

aligned support to a business strategy—will outperform firms with

4 8
less competent manufacturing functions. To test this theory, both a

competence score and a measure of firm performance are needed.
The calculation of the production competence score is described
above.

In the CSA model, firm performance was measured by rating,
relative to competitors, performance on the dimensions of cost,
quality, dependability, flexibility, market share, Share growth rate,
and return on assets. Each dimension was rated on a 5-point Likert
scale (5 = best in industry, 1 = worst in industry) and the firm
performance score was simply the sum of the Likert scores.

Cleveland et a1. (1989) tested this model on a sample of six
firms to investigate if a relationship between manufacturing strategy
and business performance existed. For each of the six firms, a
production competence score and the index of firm performance
were determined. A simple regression was run and the coefficient of
determination registered very strongly (r2=.97), indicating an
extremely strong relationship between production competence and
firm performance. This result suggests validity for the theory of
manufacturing strategy, which claims that firms with properly
aligned manufacturing functions will achieve superior performance
than firms whose functions are not properly aligned.

Vickery (1991) addressed this study and the circumstances
that contributed to create such an extraordinary coefficient of
determination. Vickery recognized that several of the components of
the firm performance index overlapped considerably with
components of the production competence score. It was also

observed that the performance measure itself contained a degree of

49
redundancy. For example, in the CSA calculations, performance areas

such as cost and flexibility are closely related to the balance sheet
data and market share. Each of these issues—overlap and
redundancy—contributed to the inflated coefficient of determination.

Vickery (1991) also pointed out potential problems in the
theoretical treatment of production competence given by Cleveland
et al. (1989). First, it was observed that manufacturing strategic
decision outputs (e.g., facilities, technology, policies, etc.) could not
adequately be captured and operationalized by the four-category
production process definition. Second, Vickery observed that the
CSA model failed to relate production competence to the formulation
and implementation of manufacturing strategy.

To overcome perceived deficiencies in the CSA model, Vickery
presented a conceptual framework “based on the premise that
manufacturing strategy is developed in the context of and
concomitantly with a firm’s business strategy...” (1991, p. 639) (see
Figure 1.2). This model accounts for strategic manufacturing
decision-making and portrays production competence as a “snapshot”
of manufacturing’s performance with respect to identified
competitive priorities. The Vickery model draws on the work of
Schroeder and Lahr (1990) and is similar to basic strategic planning
models one observes in organization strategy literature.

In the model proposed by Vickery, business strategic
objectives are communicated to manufacturing through the
identification and weighting of competitive priorities (e.g., quality,
cost, delivery, and flexibility). To achieve success in the competitive

dimensions, decisions concerning strategic manufacturing areas (i.e.,

5 0
facilities, technology, quality management, etc.) are made. Next,

manufacturing strategies and programs are implemented to support
the Strategic decisions. Finally, manufacturing performance on the
competitive dimensions is measured. Production competence is a
function of the level of manufacturing support provided to
competitive priorities.

Vickery, Droge, and Markland (1993) empirically investigated
the relationship between production competence and business
performance. Adapting the earlier Vickery model, they defined
production competence as: “The degree to which manufacturing
performance supports the firm’s business strategy” (Vickery, Droge,
and Markland, 1993, p. 436). The authors developed an improved
method for calculating production competence scores that included
three factors: (1) a comprehensive assessment of what is important
to a firm’s strategic profile, (2) manufacturing’s responsibility for the
areas identified in the strategic profile, expressed as a percentage,
and (3) firm performance measures.

After an exhaustive review of the operations, marketing,
innovation, organization theory, and strategy/policy literature, 31
competitive priorities were identified as “competitive abilities a firm
was seeking to acquire, sustain, or improve on, with a goal of
differentiating itself relative to competitors and/or lowering costs”
(Vickery, et al., 1993, p. 437). The competitive priorities are listed in
Table 2.1.

Respondents were asked to rate, for each of the 31 priorities,
the strategic importance of each priority on a seven-point Likert

scale (1 = least important, 7 = most important), the percentage of

51

Table 2.1: 31 Competitive Priorities (from Vickery, et al., 1993)

 

Product Flexibility
(Customization)

The ability to handle difficult, nonstandard orders,
to meet special customer specifications and to
produce products characterized by numerous
features, options, Sizes and/or colors.

 

Volume Flexibility

The ability to rapidly adjust capacity so as to
accelerate or decelerate production in response to
changes in customer demand.

 

Process Flexibility

The ability to produce low quantities of product
cost efficiently so that product mix changes are
easily accommodated.

 

Low Production Cost

The ability to minimize the total cost of production
(inclusive of labor, materials, and Operating costs)
through efficient operations, process technology
and/or scale economies.

 

New Product

The ability to rapidly introduce large numbers of

 

 

 

 

 

 

 

 

 

 

 

 

DeveloLment

 

 

Introduction product improvements/variations or completely
new products.

Delivery Speed The ability to reduce the time between order
taking and customer delivery to as close to zero as
possible.

Delivery The ability to exactly meet quoted or anticipated

Dependability delivery dates and quantities.

Production Lead The ability to reduce the time it takes to

Time manufacture products.

Product Reliability The ability to maximize the time to product failure
or malfunction.

Product Durability The ability to maximize the time to product
replacement.

Quality The ability to manufacture a product whose

(Conformance to operating characteristics meet established

Specifications) performance standards.

Design Quality The ability to provide a product with capabilities,

(Design Innovation) features, styling, and/or operating characteristics
that are either superior to those of competing
products or unavailable with competinngoducts.

Product Development The ability to minimize the time it takes to develop

C cle Time new products.

Product The ability to engage in new product development

Technological involving major advances in product technology.

Innovation

Product The ability to further develop and refine existing

Improvement] products.

Refinement

New Product The ability to develop new products for existing

gevelopmggt markets. ‘

Original Product The ability to develop original (i.e., "new-to-the-

world") products that create entirely new markets.

 

 

Table 2.1 (cont’d).

52

 

 

Brand Image The ability to create a positive or favorable image
in the customer's mind when he/she hears the
product's brand name.

Competitive Pricing The ability to Offer a lower product price than

direct competitors.

 

Low Price

The ability to offer one of the lowest or the lowest
available product price.

 

 

 

 

 

Advertising and The ability to create effective advertising and/or

Promotion promotional campaigns.

Target Market(s) The ability to identify promising target markets

Identification and and select the best ones for consideration.

Selection

Responsiveness to The ability to respond to the needs and wants of the

Target Marketflfl firm's target market(s).

Pre-Sale Customer The ability to service the customer during the

Service purchase decision process (i.e. before the customer
buys the product).

Post-Sale Customer The ability to service the customer after the sale of

Service the product to ensure continuing customer

satisfaction.

 

Broad Product Line

The ability to provide a comprehensive set of
related items within a given product line offering._

 

 

 

 

 

Widespread The ability to effectively provide widespread

Distribution and/or intensive distribution coverage.

Coverage

Low Cost DistributiolThe ability to minimize the total cost of
distribution.

Selective The ability to effectively target selective or

Distribution exclusive distribution outlets.

(Coverage

Personal Selling The ability to successfully move products through

Proficiency personal selling activities.

 

 

Company Reputation]

The ability to create a positive or favorable image
in the customer's mind when he/she hears the
compapy's name.

 

 

5 3
responsibility accorded to manufacturing, and their firm’s

performance relative to their competitors, again on a seven-point
scale (1 = poor, 7 = excellent). Eventually, this scale was transformed
(-3 = poor, +3 = excellent) to give credit for superior performance and
subtract credit for inferior performance. The production competence
score for each firm was calculated by summing the product of
[importance 0 performance 0 % manufacturing responsibility] across
the 31 priorities.

The study consisted of 65 firms in the furniture industry. The
CEO of each firm received and answered the questionnaire. As
discussed previously, the results indicated a significant positive
relationship between production competence and firm performance.
This work validated the earlier research of Cleveland, et. al. (1989)
and Vickery (1991), and encourages additional research into the
competence construct.

The authors also investigated the impact of the business
strategy on performance, as well as its interaction with competence.
For a Differentiation strategy, the interaction of between strategy
and production competence was also significantly related to
performance, indicating a need for manufacturing support beyond
cost reduction.

Interestingly, this result corroborates and magnifies the
research need previously identified by Skinner, in which he states
that “research and conceptual development of concrete, explicit
bridges between task and structural decisions” is the primary need
in the field (1992, p. 25). Specifically, there are several ways that a

firm can differentiate itself from competitors, including design,

54
quality, brand image, technology, features, service, distribution,

delivery speed, and others (Porter, 1980; Stalk and Hout, 1990). If
the interaction of production competence and a Differentiation
strategy can affect firm performance, then the importance of
successfully executing the manufacturing task is dramatically
increased.

The manufacturing task describes the competitive areas of the
business strategy that manufacturing must support. Since there is a
wide variety of business strategies (e.g., differentiation), there will
be many variants of the manufacturing task. What is needed is
guidance on the relationship between the manufacturing task,
structural decision making, and manufacturing strategies, programs,
and techniques. The study being proposed is an attempt to build a

theory to describe these relationships.

Programs and Techniques

Schroeder and Lahr (1990) observe that manufacturing
programs are developed to link strategies and tactics, and that
programs themselves are developed to implement strategies. They
point out the differences between the objectives of a firm, which
refer to performance areas such as quality, service, etc.
(manufacturing priorities) and the strategies developed by a firm,
which refer to how to achieve the objectives. Strategy development
can occur in topic areas such as make or buy, process technology,
quality assurance, suppliers, just-in-time, service response, etc.

Implementation, as discussed by Schroeder and Lahr (1990),

involves the application of manufacturing programs and techniques

5 5
to assist in the achievement of business and manufacturing goals. It

is at this juncture that content and process models of manufacturing
strategy come together. The programs and techniques used to
implement strategies (i.e., strategy content), embody the outcome of
the process of formulating manufacturing strategies. For example,
the choices made regarding the strategic variables of process models
developed by Sharma (1987) and Vickery (1991) are evident in the
strategies and programs implemented. It is clear from the Vickery
(1991) model of production competence that the selection and
implementation of manufacturing strategies and programs determine
whether performance targets are met and, therefore, the level of
competence that a firm can achieve.

As mentioned earlier, Skinner (1992a) has reported this—the
identification of the strategies and techniques firms should
implement to achieve specific business objectives—to be a critical
need in OM research. In this area, the Manufacturing Futures Project
(MFP) research and the Manufacturing Roundtable at Boston
University have been instrumental. For each year since 1982, the
team surveys companies in North America, Europe, and Japan and
gathers data regarding the level of emphasis—both current and two
years hence—placed by the firms on particular manufacturing tech-
niques and programs (Roth and Miller, 1990). Over time, the Futures
team has generated a list of 39 techniques, called “action programs”,
which they present to respondent firms for evaluation (Ferdows and
DeMeyer, 1990).

Results of this research stream suggest that many of the 39

action programs contribute separately to improvements in cost,

5 6
quality, flexibility and delivery (DeMeyer and Ferdows, 1990; Roth,

DeMeyer and Amano, 1989; Ferdows and DeMeyer, 1987). Results of
Roth (1987) and Ferdows and DeMeyer (1990) appear in Tables 2.2
and 2.3 respectively. Analysis of these two tables indicates that
there is not much agreement regarding the competitive priority best
served by each action plan. For example, Value Analysis is
negatively related to quality and delivery response in Roth (1987)
and positively related to quality, speed, and cost in Ferdows and De
Meyer (1990).

Several other books and articles relating to the use of
manufacturing programs and techniques have been written, both
with and without reference to competitive priorities. Beyond the
competitive priority framework, discussion and analyses of tech-
niques have used linking mechanisms such as productivity
(Schmenner, 1982; Harmon and Peterson, 1990), Just-in-Time
(Gilbert, 1990; Chan, Samson and Sohal, 1990) and management
barriers (Oakland and Sohal, 1987) to further study in the area. A
list of authors and the competitive priority(ies) included in their
articles is in Table 2.4.

The most recent efforts of the MFP team have centered around
the relationship between action plans and competitive priorities.
Applying principal components analysis (PCA) to a larger set of
competitive priorities resulted in the emergence of four main
priorities—flexibility, quality, delivery and cost efficiency (Roth,
1987; Roth, De Meyer and Amano, 1989). To determine usable sets
. of competitive techniques and programs, Roth (1987) applied PCA to

the 39 action programs resulting in 11 categories. To maintain

5 7
Table 2.2: Competitive Priorities and Action Plans

Key action programs Low Flexibility: Quality: Delivery:
Price Product, Conformance, Reliability,
V Ium Performance S ed
B S *It 1|!!!
Worker Plannin **
Labor/Mgt.
Rel tionshi s
M v
eor nizati It
Safe

Automati n

Maintenance
Def
Production &
nvento C ntrol
Time
rch in M

uce -
Value Anal sis
T hnol
uce Workf
x ansion
# of mf .
R 10 a io
New processes/Old ,
r d
New processes/New
ducts
tand r izin
tra ic P] n
Info.
ral nfo.
con ti nin

 

NOTE: (**) indicates positive relationship; (--) indicates negative
relationship (adapted from Roth, 1987)

5 8
Table 2.3: Relationships Between Action Plans and Priorities

ACTION PLAN Qual. Cost lnv. Prod. 0n Deliv. Over- Batch
Turn- Dev. Time Speed head Sizes
over S Deliv. Cost

Changing labor/mgt.
a i n
Worker
f zation
Worker saf
i circl

defects

inf
tionin

lead time

 

I""': Indicates Action Plan being emphasized by best performers
00: Indicates Action Plan being emphasized by worst performers

Source: (Ferdows and De Meyer, 1990)

 

Table 2.4: List of Authors and Competitive Priority Focus

DATE
h n r 19 2
& Peterson
& S 1
Shin 1987
Oakland &
White &
Toni
il 1
et a]. 1990
Voss Robi 1
Im & Lee 1989
1988
& 1990
& 1
hmenn r 9 8
Hopp, Spearman & Woodruff,
1990
Bower &
Ruch 1990
Blackburn 1 1
ins 1 89
n 1987
T l
DeMeyer, Nakane, Miller &
l

1987

1987
1987

& Vinelli 1988

1988

l 1990

& Miller
Horte Li T v 1
Miller, Amano, De Meyer,

N 1989

De & 1989
De 1987 1990
W l Vollman 1988

1988 l
Saraph, Benson & Schroeder,
1989
Modarress & Ansari
l 3 1

1989
1984b
1

59

Flex.

XX X XX XXX

Deliv.

X

Cost

X

I

Other

Productivit

ervice

Productivit

IT
I IT
J IT
I IT

Futures

Futures

Futures

F ure
Future
Futures
Futures

 

60
consistency with previous work in manufacturing strategy, Hayes

and Wheelwright’s (1978) traditional ideas of structural and
infrastructural variables served as a guide to describe and make
sense of the 11 new “components of manufacturing strategy”.

Continuing to apply techniques from other disciplines, Roth and
Miller (1990) used cluster analysis to segregate high and low
performing firms in the 1988 Futures database. High manufacturing
performers were termed “superstars” and low performers
“weaklings”, with the group in between called “middlemen”. In this
study, the authors were working the constructs of managerial ability
and success, as well as overall firm performance, into the model.
High overall performing firms were called “winners” and low
performers “losers”. They discovered that, for the most part,
superstars were more likely to be winners and weaklings more likely
to be losers. However, there were several cases of
weaklings/winners and superstars/losers, indicating that it might be
better for firms to be good managers, rather than strong
manufacturers.

Principal components analysis of the action programs was also
conducted in the Roth and Miller (1990) study with 28 of the 39
programs combining to form seven dimensions of strategy—materials
flow/JIT, advanced process technology, capacity upgrade,
restructuring, resources improvements, quality programs and
information systems. These dimensions were similar to the 11
identified earlier by Roth (1987).

The relationship between action programs and competitive

priorities was also studied by Roth, De Meyer and Amano (1989).

61
After using principal components analysis to identify the four major

competitive priorities (flexibility, quality, delivery and cost
efficiency), these priorities were regressed onto the 39 action
programs to evaluate the relationships between priorities and action
plans.

An emerging discovery of the work by the MFP team indicates
that firms may be attacking several competitive priorities simulta-
neously. Ferdows and De Meyer (1990) investigated the possibility
of simultaneous improvements in competitive priority areas, showing
some support. They also presented a theory stating that there is a
sequence of capability acquisition that begins with quality and ends
with cost reduction. This result of simultaneously competing on
different priorities is contrary to the trade-off model first proposed
by Skinner (1969), in which he stated that manufacturing must focus
on a limited set of tasks.

Summarizing the MFP research, the 39 action programs
identified form a good starting base for developing a list of important
manufacturing techniques. Data analysis techniques new to OM, such
as principal components analysis and cluster analysis, were applied
with good success. Further evidence of the existence of a limited set
of competitive priorities was discovered. Finally, some statistical
evidence regarding the presence of simultaneous improvements in

priorities was identified.

What Is Good Theory?
Swamidass (1991) asserts that OM researchers are quite adroit

at using deductive research methods and have made many

62
worthwhile contributions in doing so. Realizing, however, that OM

research must become more empirically oriented, Swamidass states
the need to base new research ideas in “empirical theory”. Pointing
out that the field of OM has some empirical theory of its own (even
though we may not know it), he uses the example of waiting line
theory (which we do know about) to highlight the steps in evaluating
what a good theory is and how one is developed. As an example,
Swamidass uses the frameworks developed by Whetten (1989) and
Bacharach (1989) to develop the waiting line theory.

Whetten (1989) describes the elements of what a “complete
theory” should have. He uses a familiar framework—questions of
what, how, and why—to describe a complete theory. The what
question asks: “Which factors (variables, constructs, concepts)
logically should be considered as part of the explanation of the social
or individual phenomena of interest” (Whetten, 1989, p. 490). A
complete theory should explain a given phenomenon with a great
level of comprehensiveness, while simultaneously being as
parsimonious as possible. The 1193; question seeks to understand
how the factors included in the theory are related. Whetten reminds
us that these relationships are the “arrows that connect the boxes,”
which introduce cauSality into the theory. Taken together, the what
and how questions describe or define the domain or subject matter
of the theory and are combined to “produce the typical model, from
which testable propositions can be derived” (Whetten, 1989, p. 491).

The why question seeks to identify “the underlying
psychological, economic, or social dynamics that justify the selection

of factors and the proposed causal relationships” (Whetten, 1989, p.

6 3
491). This justification constitutes the assumptions of the theory.

These three factors combine to form the essential elements of good
theory—description and explanation.

Bacharach describes theory as “a statement of relations among
concepts within a set of boundary assumptions and constraints”

(1989, p. 496). He gives the following definitions of terms:

THEORY: A statement of relationships between
units observed or approximated in the
empirical world.

W units mean variables, which are
operationalized empirically by measurement.

W units mean constructs, which

by their nature cannot be directly observed.

Kerlinger (1986) defines a variable as a symbol to which
numerals or values can be assigned. He describes a concept as an
expression of abstraction formed by generalization from particulars
(e.g., weight, heavy, light, mass). A construct is defined as a concept,
with the added meaning of having been deliberately and consciously
invented or adopted for scientific purposes. OM constructs can be
items such as quality, flexibility, or competence.

Constructs can have a constitutive definition, meaning that the
construct is defined in terms of other constructs, or they can have an
Operational definition, which assigns meaning by specifying the
activities or operations necessary to measure it. An operational
definition can be one of two types: measured or experimental. A
measured operational definition describes how a variable will be

measured. An experimental definition spells out the details of the

64
investigator's manipulations (Kerlinger, 1986).

Bacharach (1989) presents a framework and two primary
criteria (falsifiability and utility) for evaluating theories. The falsifi-
ability criterion “determines whether a theory is constructed such
that empirical refutation is possible” (Bacharach, 1989, p. 501). If it
is not refutable, it is not a good theory. The utility criterion “refers
to the usefulness of theoretical systems” (Bacharach, 1989, p. 501).

Falsifiability applies at three levels: variables, construct, and
relationships. For a theory to be falsifiable, the operationalized
variables must be valid, noncontinuous, and reliable. Constructs
must have convergent validity (objects from alternative
measurements must share variance) and discriminant validity
(objects of analysis must be distinguishable from one another).
Finally, the relationships among component constructs and variables
must have logical adequacy and empirical adequacy.

Logical adequacy is “the implicit or explicit logic embedded in
the hypotheses and propositions which ensures that the hypotheses
and propositions are capable of being disconfirmed” (Bacharach,
1989, p. 505). Accordingly, the hypotheses and propositions must be
non-tautological and the nature of the relationship between the
antecedent and consequent must be Specified (i.e., necessary and
sufficient). Bacharach states that: “An empirically adequate theory is
one in which the hypotheses and prOpositions may be
operationalized in such a manner as to render the theory subject to
disconfirmation” (Bacharach, 1989, p. 506).

Utility also applies to variables, constructs and relationships.

For variables and constructs to have utility, they must be of

65
adequate scope, or “must sufficiently, although parsimoniously, tap

the domain of the constructs in question, while the constructs must,
in turn, sufficiently, although parsimoniously, tap the domain of the
phenomenon in question” (Bacharach, 1989, pp. 506-507). Utility of
relationships refers to the ability of the theory to fully explain the
phenomenon.

To summarize Bacharach (1989) and Whetton (1989), good
theory should—sufficiently and parsimoniously—describe and explain
phenomena, while at the same time be constructed so that empirical
research can test the relationships. This construction should allow
for disconfirmation—that is, the theory should be able to be
disproved. Finally, Van de Ven states that: “Good theory is practical
precisely because it advances knowledge in a scientific discipline,
guides research toward crucial questions, and enlightens the

profession of management” (1989, p. 486).

Production Competence as Theory

Swamidass (1991), borrowing from the social and
organizational sciences, relates three levels of theories that may
exist: general theories, middle-range theories, and empirical
generalizations. General theories are at the top of the hierarchy and
explain some of the conflicts that may arise in the formation of
midrange theories and empirical generalizations. Unprecedented in
the field of operations management (OM), he places several OM
theories into the three levels and relates the amount of testing of the
theories in OM research. General theories include JIT principles and

the economic theory of the firm. Midrange theories include waiting

66
lines, the product-process ideas of Hayes and Wheelwright (1979),

and focus (Skinner, 1974). Swamidass notes that of the theories
presented, only waiting lines and JIT principles have had any
amount of study. Production competence, a mid-range theory, had
no testing prior to Cleveland, et al. (1989) and Vickery, et a1. (1993).
Broadly stated, the theory of production competence
(Cleveland, Schroeder and Anderson, 1989) explains that firms with
production processes and structures properly matched to business
strategy objectives will perform better than those with mismatched
processes and structures. Cleveland et al. describe production

competence as a continuous variable and as a:

“...measure of the combined effects of a
manufacturer's strengths and weaknesses in
certain key performance areas. The degree of
process SOphistication relative to tools and
equipment is the basis for determining
strength in any particular area. The business
strategy then determines how important it is
to be strong in that area” (Cleveland,
Schroeder and Anderson, 1989, p. 657).

Before testing Cleveland, Schroeder, and Anderson’s (1989)
theory of production competence, it should first be evaluated
according to the criteria developed by Bacharach (1989) and
Whetten (1989). In all fairness to the authors, it should be pointed
out that they indeed realized their research to be the very first step
in developing a theory of production competence, and in no way
state that what they had developed was the definitive answer. In
fact, they call for additional development before widespread testing.

For a theory to be classified as a “good” theory, it must have

6 7
two basic characteristics—it must be falsifiable and it must have

utility. The utility of the PC theory stems from the desire of
manufacturing practitioners and researchers to contribute to
business success. Production competence helps to explain what
manufacturing must do and the skills it must possess for a firm to be
successful. If American firms become more successful, then the
country as a whole will be more successful. As such, it has
tremendous utility.

In the CSA model, production competence is, in part,
determined by analyzing the strength or weakness of the support
provided by manufacturing with respect to the nine critical
manufacturing performance areas. The relative importance of the
performance areas is subjectively determined by ranking the areas
according to their importance to the business strategy of the firm.
The business strategy is determined by classifying the firm according
to Porter’s (1980) model. The strength of the support provided by
manufacturing is determined by first categorizing the production
process in place as either a job shop, batch, connected line flow or
continuous flow process. Once categorized, the relative strength
provided by the process to each of the nine performance areas is
subjectively evaluated and then assigning a numerical value (+1 if
Strong support, 0 if neutral, -1 if weak support).

Determining the level of support provided by manufacturing
using the production process in place, especially with broad
categories (four), limits the usefulness and explanatory power of the
theory by not “establishing the substantive meaning of the constructs

and variables” (Bacharach, 1989, p. 501). Categorizing the type of

6 8
production processes is extremely difficult for two reasons. First,

most firms use hybrid systems, which are by definition a
combination of more than one process type. Second, there are
tremendous differences between processes, even those that are
classified into the same categories. Thus, the substantive meaning of
the strength provided by manufacturing to a particular performance
area is difficult to ascertain.

Falsifiability refers to the ability of a theory to be empirically
refuted. In the CSA model, performance scores were determined
using some of the same measures used to in the construction of the
competence measure. This oversight makes it unlikely that
competence can ever be refuted. Due to the nature of the measures,
competence and performance will almost always be positively
related. This severely limits the usefulness of production
competence—as characterized by Cleveland, et al.—as a theory.

As mentioned earlier, these errors were identified and
corrected by Vickery (1991). In this new method of measuring
competence, the performance within specific competitive dimensions
is directly ascertained, thereby removing inconsistencies. Second,
performance of a firm is described only through measures not
included in the competence construct, namely financial indicators.
Finally, the scale regarding performance on particular competitive
priorities was increased to better capture differences.

This new way of characterizing production competence should
also be evaluated using the method described by Whetten (1989),
which seeks to determine whether or not a theory is “complete”.

First, Whetten asks what factors are involved in the theory, seeking

69
to be as comprehensive and parsimonious as possible. Included as

variables in the Vickery, Droge, and Markland (1993) model are the
importance of competitive priorities to the business strategy of a
firm, the performance of the firm in regards to the priorities, and
manufacturing’s responsibility for each priority, expressed as a
percentage. Using 31 competitive priorities in the model helps to
ensure comprehensiveness. The authors state that completeness and
parsimony were the objectives in selecting the 31 priorities.

One of the major tenets of manufacturing Strategy is that firms
providing the best manufacturing support to the business strategy
should outperform those firms receiving less support. Production
competence is a construct designed to evaluate the degree of support
provided. This addresses Whetten’s second question, which seeks to
determine the relationships in the model or how the factors are
related. In the model of production competence, more support is
theorized to be better. For example, firms differentiating (or winning
orders) based on conformance quality must have processes in place
to control for quality. Firms that have process control systems in
place will provide more support to this priority and, therefore, the
firm should perform well in its market.

Whetten’s third question relates to the justification for
including the various factors in the model. Building on the work of
Sharma (1987) and Roth (1987), using competitive priorities to
describe the business in manufacturing terms has proven to be
extremely valid. The stream of research conducted on the use of
“action plans” and strategies by the Manufacturing Futures Team has

also provided grounded impetus to include this type of construct in

7 0
models.

The process model of manufacturing strategy proposed by
Vickery (1991) is used to present the production competence con-
struct. This model fails, however, to adequately capture the “how”
question asked by Whetten, which is concerned with how the various
factors are related, or, in the words of Whetten: “involves using
arrows to connect the boxes” (1989, p. 491). In the Vickery model,
production competence is determined by the relationship between
(1) the importance of a set of priorities to the business strategy, and
(2) the performance of the manufacturing function with respect to
the support provided the priorities. What is missing from the model
is how that performance is brought about.

Cleveland et a1. (1989) substituted the production process of a
firm as a proxy for strategic actions taken by a firm. Vickery uses a
straight measure of performance to capture this variable. In both
paradigms, the question remains—to add explanatory power to the
theory—as to just how performance in a particular competitive
priority is attained?

What is being proposed in this research is to determine the
specific manufacturing strategies, programs, and techniques applied
by firms to be competitive or to achieve high performance levels
within particular competitive dimensions. For example, the
production competence theory will be expanded with the ability to
explain how firms become successful in specific competitive
priorities. This necessitates understanding which manufacturing
strategies and programs are used by firms successfully competing

along the dimensions of cost, quality, flexibility, or delivery/time.

7 1
This is precisely what this research will attempt to discover, thereby

adding explanatory power to the theory of production competence.
Ward, Miller and Vollmann (1990) have criticized OM
researchers for failing to build on the work of previous studies. They
observe that to facilitate faster theory development and testing,
building and improving upon the work of others has been used
repeatedly in disciplines such as marketing and organizational
behavior. The study being proposed here builds on the Cleveland et
a1. (1989) and Vickery (1991) models, the work of Vickery, Droge,
and Markland (1993), as well as that of the Manufacturing Futures
Project. It is hoped that this Study will facilitate the acceptance and

“completion” of the production competence theory.

I I I . RESEARCH METHODOLOGY

This chapter will describe an extended model of production
competence, discuss data collection issues, present specific testable
hypotheses based on the models, and discuss the methodologies and

techniques that will be used to test the hypotheses.

Overview

The central tenet of manufacturing strategy is that proper
strategic alignment of the manufacturing function and operations
capabilities with the objectives of the business strategy can
significantly affect firm performance and competitive position (Fine
and Hax, 1985; Anderson, Cleveland and Schroeder, 1989).

Anderson, et a1. (1989) noted that this tenet, while prevalent in
the literature, had only recently been tested. Swamidass and
Newell’s (1987) study was one of the first to analyze the relationship
between manufacturing strategy variables (flexibility and
manufacturing managers’ role in decision making) and firm
performance, finding that increased flexibility was related to
improved performance. Roth and Miller (1990) presented results
showing that business performance was greatest in firms that were
strong in both manufactUring and in managerial capability. Tunalv
(1992) observed that firms with a formulated manufacturing
strategy significantly outperformed firms that did not have such a
strategy.

To further study the relationship between firm performance

and manufacturing strategy, the construct of production competence

72

73
was introduced (Cleveland, Schroeder, and Anderson, 1989).

Production competence relates to the level and appropriateness of
the support being provided by manufacturing to the business
strategy of a firm. Cleveland, et a1. (1989) presented results showing
a strong relationship between production competence and
performance. Vickery, Droge, and Markland (1993) improved the
original production competence construct and tested their model on
65 firms. Their results also indicated a strong positive relationship
between production competence and firm performance.

This study will extend the work of others, specifically Vickery,
et al. (1993), in the area of production competence by identifying the
manufacturing strategies, programs, and techniques firms are using

to support the business strategy (i.e., being competent).

Model Development

The research being proposed is an extension of previous work
in the production competence area. Still a very young area of
research, most of the work thus far can be called “theory building” as
researchers are merely trying to understand the relationships and
complexities involved in manufacturing strategy and firm
performance (Dubin, 1969). As such, one of the objectives of this
research is to further investigate linkages appearing in previous
models. This has the added benefit of strengthening previous models
by adding to their comprehensiveness (Whetten, 1989) and utility
(Bacharach, 1989).

The model of production competence that will be tested in this

study was first presented by Vickery (1991) in a response to the

74
research of Cleveland, et a1. (1989). Vickery presented a process

model of manufacturing strategy (see Figure 3.1) in which the
business strategy objectives of a firm are translated into
manufacturing objectives through a procedure that assigns weights
(based on strategic importance) to manufacturing competitive
priorities.

After the weights have been assigned to the competitive
priorities, a firm can begin to formulate how the manufacturing
function can best support the priorities. Strategic decisions regarding
the structural and infrastructural elements of manufacturing must be
made such that the deployment of resources is in alignment with the
business strategy (Hayes and Wheelwright, 1984; Skinner, 1985).
The decision categories included in this framework can include
capacity, facilities, technology, vertical integration, workforce,
quality, prodUction planning and control, and organizational issues.
The next step in the process is to implement the appropriate
strategies, programs, and techniques as required by the previous
step. Finally, the performance of the manufacturing function—in
terms of its ability to support competitive priorities—is measured.
Using the performance data and the weighted importance of the
competitive priorities, a production competence score can be
calculated.

Several researchers have previously studied the
appropriateness of using competitive priorities in the manner
described above, showing priorities to be a viable method of
operationalizing organizational objectives as they relate to manufac-

turing (Roth, 1987; Sharma, 1987; Wood, Ritzman, and Sharma, 1990;

75

 

 

Business Strategy
(e.g., Differentiation, Cost)

1

 

 

 

Y

Identification & Weighting
of Mfg. Competitive Priorities
(e.g., quality, cost, flexibility)

i

Strategic Manufacturing
Decisionmaking
(e.g., Facilities, Technology)

 

 

 

 

 

 

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(e.g., Manufacturing
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VL

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Performance Measurement
(Mfg. Strengths, Weaknesses)

 

£8
E
i
i
a

 

 

 

 

 

 

 

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Source: Adapted from Vickery (1991)

Figure 3.1: A Process Model of Production Competence

76
Roth and Miller, 1990; Ferdows and De Meyer, 1990). Many of the

studies involving competitive priorities, especially those involved
with the Manufacturing Futures Project (MFP), have incorporated the
manufacturing techniques and programs firms use to support a
particular competitive dimension. Swamidass (1991) noted,
however, that the overwhelming majority of this previous research is
descriptive in nature and not linked to performance in any way.

Skinner (1992a) has observed that, while validating the
relationship between manufacturing strategy and performance, the
academic community has not responded very well in terms of
providing practitioners with specific mechanisms for improvement.
For example, academics have provided decision categories (structural
and infrastructural) but have not provided insight as to what

decisions to make and how to implement them. Skinner writes:

“There is no textbook or article that helps managers make
these decisions to design the structure to meet the
manufacturing task. We say that manufacturing policy
decisions must be made such that the system designed meets
the manufacturing task. But the manager is left to figure out
how to get from task to structure without much specific
guidance” (1992, p. 22).

Skinner has reported this to be another “missing link” in OM
research—the identification of the strategies and techniques firms
should implement to achieve specific business objectives (see Figure
3.2).

The general model of production competence (Figure 3.1) can
be adapted to directly address the issue identified by Skinner
(1992a). The adapted model (see Figure 3.3) allows for the analysis

77

 

I Business Strategy I

 

i

Identification, Weighting &
Manufacturing % Responsibility

 

 

of Competitive Priorities

 

 

Strategic Manufacturing
Decisionmaking

Structural Infrastructural

 

0 Capacity 0 Workforce

0 Facilities ° Quality

- Technology 0 Planning/control

- Vertical ' Organization
Integration / \

Skinner's (1992a)
Missing Link

 

 

 

 

 

 

Selection and mplementation of
Manufacturing Strategies, Programs,
and Techniques to Support
Strategic Decisions

I

Manufacturing

HDNEILEIJWOO NOLLDIICIOHcI

 

 

 

 

Performance Measurement ‘

 

 

 

 

 

 

I

L Business Performance I

 

Source: AdaptedfrornVickery(l991)

Figure 3.2: Production Competence and Skinner’s Missing Link

78

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79
of the relationship between the use of manufacturing strategies,

programs, and techniques and performance within specific
competitive priorities.

Previous research has identified the four major competitive
priorities as cost, delivery response, flexibility, and quality. Figure
3.1 is the general process model presented by Vickery (1991) that
translates business objectives into manufacturing objectives through
competitive priorities. Figure 3.3 extends this model to better
capture the relationship between strategic manufacturing objectives
(i.e., the manufacturing task) and the structures and techniques used
to support those objectives. It does this by creating a process model
for each priority area.

For example, quality-related business objectives are translated
into quality oriented manufacturing competitive priorities such as
conformance quality and performance/features. Using Figure 3.3,
this research will capture the outcomes of the formulation process
(i.e., content) by identifying the quality related strategies and
programs implemented. Note that performance along the quality
related priorities can be measured. The information regarding
importance, weights, and performance—within the quality
dimension—can be used to construct a “quality competence” score.
The quality competence score can be used to evaluate the
relationship between quality objectives, the use of quality-related
strategies and techniques, and quality performance. This approach
can also be applied to the other competitive priorities. This analysis
simultaneously adds to the comprehensiveness and utility of the

theory of production competence, while also addressing an urgent

80
research need in the field.

In the study by Vickery et a1. (1993), the production
competence construct strengthened by improving the measurement
of business objectives and performance. Strategic objectives were
identified using a comprehensive list of 31 competitive priorities.
Recognition was also given to the functional coordination necessary
to implement business strategy through a weighting of the priorities
by function. Production competence was measured by (l) obtaining
a strategic profile of the firm (gathering data on the strategic
importance of 31 competitive priorities), (2)“ determining the
proportion of each priority for which manufacturing is responsible,
and (3) measuring firm performance across each competitive
priority. The production competence score is the product of (1), (2),
and (3) summed across 31 priorities. This can be expressed in the

following equation:

PC = 321:1CPtmp x CPperf x % mfg resp. (Eq. 3.1)

where, PC = Firm production competence score
CPimp = Competitive priority importance (1 to 7)
CPperf = Competitive priority performance (Adjusted to
reflect excellent and poor performance: -3 to +3)
% mfg resp. = percent of priority for which
manufacturing is responsible.

As previously discussed, the ability of manufacturing to
support the objectives of the business strategy is, in part, determined

by the strategies, programs and techniques a firm elects to

81
implement. Therefore, manufacturing support—and production

competence—is influenced by the selection and implementation of

manufacturing techniques.

Strategies, Techniques and Programs

The manufacturing strategies, techniques and programs that
firms implement vary widely depending on the business strategy of
the firm, resources available and competitive position. The business
strategy of a firm dictates the particular manufacturing techniques
and programs implemented. A company following a strategy of low
cost will implement a much different bundle of techniques and
programs than would a firm using a strategy based on time or
service.

The multitude of strategies and programs available to firms has
increased the complexity of the decision. Many of these strategies
can be expensive and time-consuming to implement, adding pressure
to make the correct decision. As Hill (1994) observes, these
strategies may be irreversible, or at minimum, take several years to
change. Some require tremendous outlays in training, information
technology, or manufacturing equipment and often involve multiple
functions in the company.

The manufacturing strategies, techniques and programs
included in this study were selected after a thorough search of both
the practitioner and academic literature. Due to the wide differences
in business strategies and available resources, the strategies and
techniques included in this study are quite diverse, ranging from

very specific techniques such as value analysis to broad programs

82
such as employee involvement.

Most of the research in this area has been conducted by the
Manufacturing Futures Project (Ferdows, Miller, Nakane, and
Vollmann, 1986; Roth, De Meyer, and Amano, 1989; Ferdows and De
Meyer, 1990). All of the strategies identified by that team were
included (36 action plans). The Boston University Manufacturing
Roundtable performance measurement project (Dixon, Nanni, and
Vollmann, 1990) was also a source of strategies and objective
performance measures.

Several practitioner-oriented books contributed to the list of
manufacturing improvement programs. Books related to cost
reduction (Harmon and Peterson, 1987), Japanese manufacturing
techniques (Abegglen and Stalk, 1985; Schonberger, 1982; Imai,
1986; Suzaki, 1987), manufacturing strategy (Hayes and
Wheelwright, 1984; Skinner, 1985; Hayes, Wheelwright, and Clark,
1988; Hall, 1987; Gunn, 1987), quality (Rogerson, 1986; Juran and
Gryna, 1980; Juran, 1988; Walton, 1986), and time (Blackburn, 1990;
Stalk and Hout, 1990) were consulted.

Numerous research articles were also used as sources of
strategies and techniques (Hopp, Spearman and Woodruff, 1990;
Chan, Samson and Sohal, 1990; De Toni, Caputo and Vinelli, 1988;
Gerwin and Tarandeau, 1989; Gilbert, 1990; 1m and Lee, 1989;
Modarress and Ansari, 1989; Oakland and Sohal, 1987; Ross and
Georgoff, 1991; Saraph, Benson and Schroeder, 1989; Schlie and
Goldhar, 1989; Schmenner, 1982, 1988b; Suzaki, 1985; White and
Flores, 1987). Although most of these articles did not relate the use

of the strategies to overall performance, they were techniques that

8 3
the authors considered relevant to competitiveness. Several

practitioner-oriented journals were also consulted, including Quality,
Quality Progress, Industry Week, Manufacturing Review, Purchasing,
and Management Accountant.

Once the comprehensive set of techniques and programs were
identified from the literature, they were shown to academics in
operations management and to several furniture manufacturing
executives. The majority of the executives indicated that several of
the strategies and programs presented to them were not currently
used in the furniture industry. Most of these involved computerized
manufacturing and planning techniques. Many of these techniques
remained in the survey, however, because some of the firms
interviewed were using these technologies. The interviews ensured
that the strategies and techniques included in the study maintained a
high degree of relevance to the field and the furniture industry. The
techniques appearing in the questionnaire are presented in Table 3.1.
Each technique was defined in a glossary that accompanied the

survey

Data Collection

The research being proposed is an extension of research started
by Vickery, Droge, and Markland (1993). The firms that participated
in their study were drawn from a pool of firms that met two criteria.
First, they had to be in one of four Standard Industry Codes (SIC)
relevant to the furniture industry: wood office furniture (2521),
office furniture other (2522), wood house furniture (2511), and

upholstered wood house furniture (2512). Second, each firm had to

84
have at least $10 million in annual sales. Firms that met these

criteria were mailed a letter and questionnaire, and received a phone
call (or calls) to secure participation. Their sample consisted of 65
firms in the furniture industry, which represented about 20% of the
total number of questionnaires mailed. The respondents to their
survey were mainly chief executive officers, with an occasional
respondent from the Vice-president or Director level.

Using information regarding competitive priority importance,
competitive priority performance, percentage manufacturing
responsibility, and firm performance, a production competence score
was calculated for each firm using Equation 3.1. The production
competence scores for each firm become inputs to the analysis in this
study.

This research extends the work of Vickery et al. by addressing
the decisions and actions of the manufacturing function within the
firms studied. Each of the 65 firms that participated in the earlier
study provided the name, address and title of the individual
responsible for the manufacturing function. This individual received
a questionnaire designed to obtain information regarding the use of
the manufacturing
strategies, programs, and techniques appearing in Table 3.1—a critical
component of the models presented in Figures 3.1 and 3.3 and
directly related to the research need identified by Skinner (1992a),
portrayed in Figure 3.2.

The questionnaire mailed to the manufacturing personnel was
validated through a process that included conversations with

academics in the Operations management field and personal

85

Table 3.1: Manufacturing SPTs Appearing in Questionnaire

 

Mat]. Requirements PlanninLLMRP)

Mfg. Resource Planning (MRPII)

 

 

 

Capacity Requirements Planning Just-In-Time (JIT)
(CRP)

Automation Total Quality Control (TQC)
Training For Executives and Training For Workers

‘ Managers

 

Zero Defects

Design For Manufacturability

 

 

 

 

 

 

 

 

Group Technology Cellular Manufacturing

Backward Integration Forward Integration

Capital Investment Computer Integrated Manufacturing_
Functional lntemtion Goalsetting

Activity-Based Costing ABC Analysis

Worker Motivation Gainsharing

Quality Of Work Life Initiatives Product-Focused Factory
Process-Focused Factory Variety Reduction

 

Reduce Engineering Change Orders

Simplified Material Flow

 

Product Simplification

Computer-Aided Design (CAD)

 

Synchronous Manufacturing

General Purpose Equipment

 

_I_)edicated Equipment

Large Batch Production

 

Cross-Training Workers

Employee Suggestions

 

Reduction In Throughput Times

Quality Circles

 

 

Product Standardization Vertical Job Enlggement
Reduction In Raw Materials Reduction In WIP Inventory
In v e n to r y

 

Reduction In Finished Goods
In v e n to r y

Purchase In Large Quantities

 

Supplier Selection Based On Quality

Supplier Selection Based On Price

 

Advanced Forecastirm

Work Measurement

 

Value Analysis

Reducing Setup Times

 

 

 

Preventive Maintenance Failsafing Or Foolproofing
Lot Splittirm Electronic Data Interchange (EDI)
Worker Specialization Quality Function Deployment (QFD)

 

Total Productive Maintenance (TPM)

Mean and Range Control Charts

 

Advanced Statistical Techniques

Use of Seven Basic Qual. Improvement
Tools

 

Inspection Of Incomifl Materials

Inspection Of In-Process Work

 

Inspection Of Finished Goods

100% InsLection

 

Acceptance Sampligg

Workplace Orderliness

 

anlity Audit

Product Reliability Testing

 

Measuring Product Reliability

Avail. Of Qual. Related Data To
Managers

 

Avail. Of Cost Of Qual. Data To
‘ Managers

Avail. Of Qual. Related Data To Workers

 

Benchmarking

Employee Involvement

 

Employees Responsible For Quality

Timely Feedback Of Quality Data

 

 

Employee Recognition

 

Visible Performance Charts

 

 

86

Table 3.1 (cont’d).

 

Adoption 0f Quality Standards

Emphasis On "Doing It Right The First
Time"

 

Coordination Among Depts. In Prod.

Design

Supplier Certification

 

Training Provided To Suppliers

Reliance On Fewer Suppliers

 

Involve Suppliers In Product Design

Separate Mfg. Lead Time Into
Components

 

Common Manufacturing Database

Concurrent Engineering

 

Advanced Manufacturipg Technolo

Mixed-Model Production Scheduling

 

Line Balancm

Automated Monitoring Devices

 

Maintain Excess Equipment Capacity

Reducing Size of Work Force

 

Self-Directed Work Teams

Subcontracting

 

Programmable Technolgy

Flexible Manufacturing System (FMS)

 

Cross-Functional Teams

Worker Safety

 

Product Teams

Proprietary Technology

 

Produce Same Part on Same Machine

Color Coding of Parts and Machines

 

 

 

 

 

interviews with furniture industry manufacturing managers.

The

academics provided feedback regarding the survey design and the

strategies and programs that were included (see Table 3.1).

Three

personal interviews with manufacturing managers from respondent

firms were completed, which resulted in the removal of a limited

number of techniques from the list.

regarding wording and survey layout.

Other minor changes were made

A glossary of terms was also

included with each questionnaire, so that respondents would be clear

on the meaning of each strategy, program and technique.

The survey

instrument and glossary are included in Appendix 1.

Each respondent was asked to rate the “extent of use” of each

of the manufacturing strategies, programs, and techniques appearing

in Table 3.1.

scale with (1) indicating low use and (7) indicating high use.

Extent of use was measured on a seven-point Likert

As in

the Vickery, et a1. study, all data pertain to 1990. Questions

87
regarding the level of integration between functional managers, also

using a seven-point Likert scale, were included. Finally, respondents
were also asked to provide data pertaining to objective performance
measures in the areas of quality, delivery response, flexibility and

COSt.

Hypotheses Development
1. Wasting;

To investigate the relationship between manufacturing support
and firm performance, the theory of production competence was
proposed (Cleveland, et al., 1989). Vickery (1991) presented aimodel
of production competence in the context of a process model of
manufacturing strategy. This model indicated that manufacturing
performance was influenced by the selection and implementation of
manufacturing programs and techniques. Vickery, et al. (1993)
revised the original theory and measurement of the construct and
identified a positive relationship between firm performance and
production competence.

This research extends the previous work of Vickery (1991) and
Vickery, et al. (1993) by investigating the relationship between
manufacturing strategies, programs, and techniques and production
competence. Ultimately, it seeks to identify if there exists a set of
techniques and programs that is common to those firms experiencing
the greatest success in supporting their business strategy (i.e., most
competent). This research objective is aligned with the objectives of
theory building, in that the research seeks to describe the behavior

of the variables and constructs in the model and not to predict

8 8
behavior. This objective can be expressed in the following

hypothesis:

Hypothesis 1: There is a positive relationship
between the extent of use of individual
manufacturing strategies, programs and
techniques (SPTs), and production competence .

For each of the strategies, programs and techniques
appearing in Table 3.1, regress the production
competence score onto the extent of use (EOU) score of

the SPT.

Y = 80 + 31X]

where: Y = production competence score,
and X1 = extent of use of SPT.

Perform a t-test to see if 81 is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If 81 is positive and different from zero, we can
claim that there might exist a positive relationship
between production competence and the use of the
particular strategy, program, or technique.

This analysis will result in a bundle of manufacturing
strategies, programs, and techniques that are associated with
production competence. Since, in this case, competence is a general
term and not related to any particular competitive priority, the
strategies and programs identified could serve as a base for

companies upon which to develop differentiated strategies.

2. C .. ..

The production competence score for a firm is comprised of
three elements—the importance of the competitive priorities to the

business strategy, manufacturing’s responsibility for a particular

89
priority (expressed as a percentage), and the performance of

manufacturing in that area. The mathematical formula is listed in
Equation 3.1. In Vickery, et a1. (1993), production competence was
determined by applying this formula across 31 different competitive
priorities. The result is an overall production competence score for a
firm’s manufacturing function. Analysis at this level does not,
however, reveal any relationships between the firm’s manufacturing
task and the strategies and programs implemented to achieve
strategic objectives.

Just as a competence score can be calculated for the entire
manufacturing function, a competence score can also be constructed
for each broad competitive priority (i.e., quality, cost, delivery, and
flexibility). This analysis would directly address the research need
expressed by Skinner (1992a), in which he calls for academics to
provide guidance for the structural and infrastructural decisions
practitioners must make. Figure 3.3 indicates how this refinement
expands Vickery’s (1991) original model.

The next set of hypotheses addresses the relationship between
each strategy, program, and technique and the four major
competitive priorities. One method to group the 31 sub-priorities
into major priorities would be to factor analyze them. This analysis
would result in statistically different groups being created. One
requirement for the use of factor analysis is a fairly large sample
size, one that has about 10 responses per sub-factor (Nunnally,
1978). The sample sizes to be used in this study are too small to
support the use of factor analysis.

In the absence of a factor analysis, a combination of methods

90
was used. First, a literature-based analysis was conducted. Previous

studies involving competitive priorities have been synthesized in
Table 3.2. In this table, the stars indicate that the sub-priority has
been linked to the main priority by the author(s). Second, in
collecting the data for the production competence score, firms were
asked to assign responsibility, expressed as a percentage, to
manufacturing. When manufacturing’s share was at least 25%, the
priority was assigned to a manufacturing-related priority. For
example, the literature suggests that responsiveness to target
markets is the responsibility ' of the marketing function. Respondents
assigned an average of 27% to the manufacturing function. That
priority was moved from the marketing group to the flexibility
group. Likewise, several of the quality priorities moved to
marketing (image, customer service).

Using the data in Table 3.2 and early survey results, Table 3.3
displays the manner in which the 31 competitive priorities are to be
arranged to generate competence and performance scores for the
four major priority areas.

An example of how to determine a competence score for a
competitive priority follows. Using Table 3.3, the delivery-response
competence score would be calculated by summing the product of
(importance)'(% manufacturing responsibility)-(performance) across
the three delivery-related competitive sub-priorities: delivery speed,
delivery dependability, and production lead time. As in Vickery, et
a1. (1993), the peformance scores will be adjusted from a l to 7 scale

to a -3 to +3 scale.

91

TABLE 3.2: Previous Studies Involving Competitive Priorities

NOTE: 1" indicates link to
Market prtomy. 'F‘ indicates
link to mummy.

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Broad Product Line
Product Introduction

Production Cost

Price
Cost Distribution

Lead Time
Dev't. Time

Conformance)
Cust. Service

Cust. Service

a
Distribution

Product Dev't.
Tech'l. lnnov.

Product

 

92
Table 3.3: 31 Competitive Priorities Categorized into Priority Groups

ELEXIBILIIIX QUALIIX ‘
Product Flexibility (Customization) Product Reliability
Volume Flexibility Product Durability
Process Flexibility Quality (Conformance)
Broad Product Line Design Quality
Responsiveness to Target Product

Market(s) Improvement/Refinement
Product Development Cycle Time
W W
Brand Image Delivery Speed
Pre-Sale Customer Service Delivery Dependability
Post-Sale Customer Service Production Lead Time

Advertising and Promotion
Target Market(s) Identification Q31

and Selection Low Production Cost
Low Cost Distribution Competitive Pricing
Widespread Distribution Coverage Low Price
Selective Distribution Coverage

Personal Selling Proficiency DESIGN

Company Reputation Original Product Development
Product Technological
Innovation

New Product Development
New Product Introduction

 

93
Characterizing competence in this manner raises the following

research hypotheses:

Hypothesis 2a-2d: There is a positive
relationship between the use of individual
manufacturing strategies, programs and
techniques, and (a) cost competence, (b) delivery
competence, (c) flexibility competence, and ((1)
quality competence.

For each of the strategies, programs and techniques
appearing in Table 3.1, regress the competitive priority
competence score onto the extent of use (EOU) score of
the technique.

Model: Y = Bo + B]X1

where: Y = competitive priority competence (e.g., cost),
and X1 = extent of use of technique.

Perform a t-test to see if 81 is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If 81 is positive and different from zero, we can
claim that there might exist a positive relationship
between competitive priority competence and the use of
the particular strategy, program, or technique.

3. C .. .. f

In addition to analyzing the relationship between the
competence of a firm and the use of manufacturing strategies,
programs, and techniques, investigating the relationship between the
use of manufacturing techniques and performance would also be
useful.

Using the arrangement of priorities in Table 3.2, the subjective

performance in each priority/competence area (e.g., quality

94

competence) is determined by taking an average of the performance

scores for the priorities listed in each category.

The following hypotheses test for relationships between

subjective firm performance within each main priority/competence

area and the use of manufacturing strategies, programs, and

techniques:

Hypothesis 3a-3d: There is a positive
relationship between the use of manufacturing
strategies, programs, and techniques (SPTs) and
the performance component of (a) cost
competence, (b) delivery competence, (c)
flexibility competence, and ((1) quality
competence.

For each of the strategies, programs, and techniques
appearing in Table 3.1, regress the subjective
performance component of competitive priority
competence (see above and Table 3.2 for calculation) onto
the extent of use score of the techniques.

Model: Y = 80 + 81X]

where: Y = performance component of competitive
priority competence,
and X1 = extent of use of SPT.

Perform a t-test to see if 81 is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If 81 is positive and different from zero, we can
claim that there might exist a positive relationship
between competitive priority performance and the use of
the particular strategy, program, or technique.

4. W

Researchers in business strategy often study the relationship

between the use of strategies and firm overall performance (Hitt and

95
Ireland, 1985; Snow and Hrebiniak, 1980). The performance

measures used in these studies are usually global measures such as
stock price return (if available), return on assets, return on sales, etc.

Vickery, et a1. (1993) measured business performance using
the financial measures of return on assets before tax (ROA before
tax), return on assets after tax (ROA after tax), return on investment
after tax (ROI), and return on sales (ROS). They obtained data for
each of these measures in three forms—a firm’s performance relative
to competitors, a firm’s performance relative to its historic
performance, and actual data. Not all firms provided actual data to
the study, therefore, subjective measures were used for final
analysis. Of the subjective performance measures, ROA after tax
relative to historic performance (internal assessment) and ROA
before tax relative to historic performance (internal assessment) had
the highest correlations with actual ROA data.

Investigating the relationship between the use of
manufacturing strategies, programs, and techniques and overall firm
performance, while not leading to causality, will provide information
regarding the strategies that the highest overall performing firms
feel are important. This will add to the body of knowledge being
created regarding manufacturing strategies.

Overall firm performance will be measured using ROA pretax
relative to historic performance (internal assessment). The following
hypothesis will serve to identify the strategies implemented by high

performers:

Hypothesis 4: There is a positive relationship
between the extent of use of manufacturing

96

strategies, programs, and techniques, and
subjective overall firm performance.

For each of the strategies, programs, and techniques
appearing in Table 3.1, regress the subjective “ROA
pretax” firm performance measures from Vickery, Droge,
and Markland (1993) onto the extent of use (EOU) score
of the techniques.

Model: Y = 30 + 81X}

where: Y = subjective ROA pretax
and X1 = extent of use of technique.

Perform a t-test to see if 81 is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If B] is positive and different from zero, we can
claim that there might exist a positive relationship
between overall firm performance and the use of the
particular strategy, program, or technique.

5. Wm

One drawback of the large number of individual manufacturing
SPTs tested in the first four sets of hypotheses and the large alpha
(.10) is that confidence is lost when interpreting results. For
example, if 80 SPTs are tested at an alpha of .10, chance alone would
produce eight significant SPTs. One method to overcome this
problem is to reduce the alpha level to .05, which would reduce the
effects of chance by half. That, however, would detract from the
exploratory nature of the study.

An alternative method would be to assemble the SPTs into
logical groups so that fewer tests are needed. Given the structure of
the model being tested in this study, using the four competitive

priorities of quality, cost, delivery, and flexibility as group headings

9 7
is logical.

To guide the assignment of SPTs to a quality group, an
underlying theory or framework is appropriate. The Malcolm
Baldrige National Quality Award program, administered by the
National Institute of Standards and Technology (NIST), “was
established to stimulate American organizations to improve quality
through a well-conceived and well-defined quality system” (George,
1992, p. 1). The Baldrige criteria serve as a guide for companies to
design and implement quality improvement programs and to change
quality systems (George, 1992). Table 3.4 lists the categories and
items of the Baldrige criteria, which are divided into seven
categories: leadership, information and analysis, strategic quality
planning, human resource development and management,
management of process quality, customer focus and satisfaction, and
quality and operational results. Except for the measurement of
results, the categories concern changes to a firm’s quality system,
which can lower costs, help to retain a firm’s customers and
employees, and improve profitability. Of those categories,
Information and Analysis, Human Resource Development and
Management, and Management of Process Quality directly concern
the implementation of quality changes.

A search of quality improvement literature relating to the
Baldrige award (Ross, 1993; George, 1992; Brocka and Brocka, 1992)
reveals that there are several strategies and techniques firms can
use to improve performance within a category. Table 3.5 lists the
manufacturing SPTs from Table 3.1 that these authors have

suggested are appropriate for the Baldrige categories and items.

98

Table 3.4: Malcolm Baldrige Quality Categories and Items

 

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Leadership

Senior Executive Leadership
Management for Quality
Public Responsibility

Information and Analysis

Scope and Management of Quality Information and Performance Data
and Information

Competitive Comparisons and Benchmarks

Analysis and Uses of Company-Level Data

Strategic Quality Planning
Strategic Quality Planning and Company Performance Planning Process
Quality and Performance Plans

Human Resources Development and Management
Human Resource Management

Employee Involvement

Employee Education and Training

Employee Performance and Recognition

Employee Well-Being and Morale

Management of Process Quality

Design and Introduction of Quality Products and Services

Process Management—Product and Service Production and Delivery
Processes

Process Management—Business processes and Support Services
Supplier Quality

Quality Assessment

Quality and Operational Results
Product and Service Quality Results
Company Operational Results

Business Process and Support Service results
Supplier Quality results

Customer Focus and Satisfaction

Customer Relationship Management

Commitment to Customers

Customer Satisfaction Determination

Customer Satisfaction Results

Customer Satisfaction Comparisons

Future Requirements and Expectations of Customers

SOURCE: George (1992)

 

Table 3.5: Baldrige Criteria (BOLD)/Items and Related SPTs

 

BALDRIGE CRITERIA & ITEMS

RELATED MANUFACTURING SPTs

 

Information and Analysis

HR Development and Management
Employee Involvement

Employee Education and Training

Human Resource Management

Employee Performance and Recognition

Employee Well-Being and Morale

Process Quality
Product Production and Deliv. Processes

Quality Assessment

Process Management—Business Processes

Design and Intro. of Quality Products

Supplier Quality

 

 

Avail. Of Cost Of Qual. Data To Managers
Avail. Of Qual. Related Data To Workers
Timely Feedback Of Quality Data

Avail. Of Qual. Related Data To Managers
Benchmarking

Employee Suggestions
Self-Directed Work Teams
Employees Responsible For Quality
Employee Involvement

Training For Executives and Managers
Training For Workers

Product Teams

Vertical Job Enlargement
Worker Motivation
Cross-Training Workers
Quality Circles

Visible Performance Charts
Cross-Functional Teams

Employee Recognition
Goalsetting
Gainsharin g

Quality Of Work Life Initiatives
Worker Safety

Failsafing Or Foolproofing

Total Productive Maintenance (TPM)
Preventive Maintenance

Emphasis On "Right The First Time"
Mean and Range Control Charts

Use of 7 Basic Qual. Improvement Tools

Product Reliability Testing
Measuring Product Reliability
Quality Audit

Functional Integration

Coord. Among Depts. In Product Design
Quality Function Deployment (QFD)
Concurrent Engineering

Involve Suppliers In Product Design
Design For Manufacturability

Supplier Certification
Supplier Selection Based On Quality
Training Provided To Suppliers

 

 

100
For each category and item in Table 3.5, the extent of use score

for the related manufacturing SPTs are summed to create new
variables. For example, the score for the category “information and
analysis” would be the sum of the extent of use scores for the
manufacturing SPTs in Table 3.5 associated with that category:
availability of cost of quality data to managers through
benchmarking. For the second category—HR development and
management—the manufacturing SPTs have been grouped by item,
not category. The score for the item “employee involvement” is the
summation of the extent of use scores for the SPTs from employee
suggestions to employee involvement. Finally, the item-level
variables can be summed to construct category-level variables. For
example, the HR development and management score is the sum of
the score of the items related to the HR criteria, including employee
involvement, education and training, human resource management,
performance and recognition, and employee well-being and morale.
The collection and assignment of manufacturing SPTs into
groups organized by Baldrige categories can assist firms in selecting
and implementing the SPTs that can aid in the quality improvement
process. George (1992, p. xi) quotes Curt Reimann, director of the
Baldrige program, as stating that the Baldrige criteria are something
of a “do-it yourself kit” for quality improvement. Identification of
critical manufacturing SPTs can aid firms by suggesting the SPTs that
are most effective in achieving Baldrige criteria. In addition,
improvements in the quality area have been suggested as
requirements for operating in many environments and markets

(Ferdows and De Meyer, 1990; The Economist, 1994). Regardless of

101
the direction of strategic objectives, quality improvement is

necessary.

Ferdows and De Meyer (1990) presented their sand-cone
model which stated that capability in quality is achieved before
capabilities in delivery, flexibility, and cost can be attained. Hill
(1994) intimates that quality is now a qualifying criterion to enter
many global markets, especially automobiles. The quality movement
has educated many companies and consumers on the benefits of
higher quality. Competitors have raised the level of quality that is
acceptable to consumers. Because of this, quality is now a basic
element of the strategies of many companies.

Competence, as stated already, measures support provided to
strategic objectives. If quality is now becoming a qualifying
criterion, quality improvement programs should be an element of
strategy regardless of the particular strategic direction. Given this,
the use of quality-related SPTs should be positively related to
production competence. Furthermore, when firms compete on other
dimensions (delivery, flexibility), the use of quality SPTs will be
critical (Ferdows and De Meyer, 1990). Therefore, the use of quality-
related SPTs should be positively related to competence within the
four priorities of cost, delivery, flexibility, and quality. Given the
requirement for quality in many markets, the association between
the Baldrige categories and the manufacturing SPTs presented in the
literature, and the sequence of capability acquisition suggested by
Ferdows and De Meyer (1990), the following hypotheses can be

presented:

102
Hypotheses 5a-5e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with Baldrige mm and (a)
production competence, (b) cost competence, (c)
delivery competence, (d) flexibility competence,
and (e) quality competence.

Regress the competence score onto the summated extent
of use scores of the three criteria.

Model: Y = 80 + 81X] + 32x2 + B3X3

where: Y = production, cost, delivery, flexibility, or
quality competence, and the independent variables are
the summation of extent of use scores of the SPTs related
to the criteria and items (see Table 3.5).

X1 = information and analysis
X2 = HR development and management
X3 = process quality

An F-test will be used to investigate the
inappropriateness of the model (i.e., 81 = 82 = 33 = 0). As
in earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Earlier it was noted that the competence scores may obscure a
performance relationship present between the use SPTs and a
competitive priority. To address this issue, a performance score for
the competitive priorities was constructed by summing the
performance scores for the individual priorities associated with a
particular priority (see Table 3.3). Investigating the relationship
between the use of manufacturing SPTs and performance may reveal

SPTs that are hidden by the competence analyses. Just as a

103
performance score was determined for the priorities of cost, delivery,

flexibility, and quality, an mu performance score can be
determined. Production competence is calculated by taking the
product of the importance and performance of individual competitive
priorities. Production perforrnance—the summation of the
performance scores for all 31 priorities—can serve as an overall
performance measure that can be used to detect relationships
between SPTs and performance. Production performance will be
included as an overall performance measure in several of the
subsequent hypotheses.

The following hypotheses seek to investigate the existence of a
relationship between SPTs associated with the Baldrige criteria and

performance.

Hypotheses Sf-Sj: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with Baldrige criteria and (f)
production performance, (g) cost performance, (h)
delivery performance, (i) flexibility performance,
and (j) quality performance.

Regress the performance score onto the summated extent
of use scores of the three criteria.

Model: Y = Bo + 81X] + 82X2 + B3X3

where: Y = production, cost, delivery, flexibility, or
quality performance, and the independent variables are
the summation of extent of use scores of the SPTs related
to the criteria and items (see Table 3.5).

X] = information and analysis
X2 = HR development and management

X3 = process quality

104

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = 82 = B3 = 0). As
in earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Firm performance can also be measured using financial
measures. Vickery, Droge, and Markland (1993) measured several
different financial indicators and discovered that subjective
measures of ROA correlated highly with actual ROA. The subjective
measures included internally assessed and externally assessed
pretax and aftertax measures of ROA. Deming (1982) indicated that
quality improvement can lead to lower costs and increased share.
This combination will lead to increased profits. George (1992)
indicates that the journey to quality improvement and
implementation of plans to pursue the Baldrige Award has produced

financial gains. The following hypotheses test this notion:

Hypotheses Sk-Sn: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with Baldrige
mum and (k) pretax ROA-external assessment,
(1) pretax ROA-internal assessment, (n) aftertax
ROA-external assessment, (0) aftertax ROA-
internal assessment.

Regress the performance score onto the summated extent
of use scores of the three criteria.

Model: Y = Bo + 81X1 + 82X2 + B3X3

where: Y = pretax ROA-external assessment, pretax

105

ROA-internal assessment, aftertax ROA-external
assessment, or aftertax ROA-internal assessment, and the
independent variables are the summation of extent of use
scores of the SPTs related to the criteria and items (see

Table 3.5).
X] = information and analysis
X2 = HR development and management-
X3 = process quality

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = 82 = B3 = 0). As
in earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Alternatively, the individual items included in each Baldrige
criteria may be more important to competence (see Table 3.5). The
macro analysis of the criteria-related hypotheses may obscure any
relation between competence and the lower-level Baldrige items.
The relationships between quality-related SPTs and the various
competitive thrusts are still of interest. Therefore, the following

competence- and performance-related hypotheses are suggested:

Hypotheses 5p-St: There is a positive relationship
between the extent of use manufacturing SPTs
associated with Baldrige m, and (p)

production competence, (q) cost competence, (r)
delivery competence, (s) flexibility competence,
or (t) quality competence.

Regress the competence score onto the summated extent
of use scores of the Baldrige items.

Model: Y = 80 + 81X1

106

where: Y = production, cost, delivery, flexibility, or
quality competence,
and X1 = Baldrige item (e.g., employee

involvement). The item scores are the summation of
extent of use scores of the SPTs related to the Baldrige
items (see Table 3.5).

Perform a t-test to see if B], is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If B], is positive and different from zero, we can
claim that there might exist a positive relationship
between that particular Baldrige item and the associated
competence measure.

Hypotheses Su-Sy: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with Baldrige
items, and (u) production performance, (v) cost
performance, (w) delivery performance, (x)
flexibility performance, or (y) quality
performance.

Regress the performance score onto the summated extent
of use scores of the Baldrige items.

Model: Y = 80 + 81X1

where: Y = production, cost, delivery, flexibility, or
quality performance,
and X1 = Baldrige item (e.g., employee

involvement). The item scores are the summation of
extent of use scores of the SPTs related to the Baldrige
items (see Table 3.5).

Perform a t-test to see if 81, is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If B], is positive and different from zero, we can
claim that there might exist a positive relationship
between that particular Baldrige item and the associated
performance measure.

107

Hypotheses Sz-Sac: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with Baldrige
m; and (z) pretax ROA-external assessment,
(aa) pretax ROA-internal assessment, (ab)
aftertax ROA-external assessment, (ac) aftertax
ROA-internal assessment.

Regress the ROA score onto the summated extent of use
scores of the Baldrige items.

Model: Y = 80 + 81X]

where: Y = pretax ROA-external assessment, pretax
ROA-internal assessment, aftertax ROA-external
assessment, or aftertax ROA-internal assessment, and

‘ X1 = Baldrige item (e.g., employee
involvement). The item scores are the summation of
extent of use scores of the SPTs related to the Baldrige
items (see Table 3.5).

Perform a t-test to see if 81, is different from zero. Since
this is exploratory research, a generous alpha of .10 will
be used. If 81, is positive and different from zero, we can
claim that there might exist a positive relationship
between that particular Baldrige item and the associated
performance measure.

6. Wang:

To overcome problems in identifying manufacturing SPTs
related to competitive priorities mentioned in section five above (i.e.,
large number of tests and alpha=.10), it was suggested that the SPTs
can be grouped together. In general, the delivery component of a
firm’s strategy can be sub-divided into delivery speed and delivery
reliability. In this study, however, the delivery competence and

delivery performance constructs do not differentiate between speed

108
and reliability (see Table 3.3). Therefore, manufacturing SPTs

related to both speed and reliability are grouped together.

The literature is somewhat lacking in empirical research
relating to delivery performance. Several articles suggest methods of
improving delivery performance, but there are few which have
empirically tested or identified the suggested techniques. Three
articles that have addressed the issue (Roth, De Meyer, and Amano,
1989; De Meyer and Ferdows, 1990; and Handfield and Pannesi,
1992) have identified several manufacturing strategies and
techniques that were found to be associated with superior delivery
performance.

The most common techniques related to delivery appear in
Table 3.6. The division of the techniques in Table 3.6 into the
categories of “process” and “infrastructure” was not made by the
cited authors and was not done in a statistical manner. They do,
however, represent a logical breakdown of the SPTs into categories
similar to Hayes and Wheelwright’s (1984) structural and
infrastructural categories. The new variables created (DELPROCS and
DELINFRA) are equal to the sum of the extent of use scores of the
SPTs in each category.

Production competence measures the support provided to the
business strategy by manufacturing. One of the major objectives of
this study is to identify the relationship between production
competence and manufacturing strategies, programs and techniques.
Grouping delivery-related SPTs together improves the ability of the
model to identify potential relationships between the SPTs and

competence, and to determine if delivery-related SPTs are important

109
Table 3.6: Manufacturing SPTs Related to Delivery

InfrastructuralJPls WEB
Coordination Among Dedicated Equipment
Departments Group Technology

in Product Design Just-in-Time
Cross-Functional Teams Preventive Maintenance
Cross-Training Workers Reducing Setup times
Design For Manufacturability Reduction in Throughput Times
Reliance on Fewer Suppliers Simplified Material Flow

Supplier Certification
Supplier Selection Based on

Quality
Workplace Orderliness

Sources: Roth, De Meyer, and Amano, 1989; De Meyer and Ferdows, 1990; and
Handfield and Pannesi, 1992.

to all firms, regardless of strategic direction.

According to the sand cone model presented by Ferdows and
De Meyer (1990), capability in delivery follows quality and precedes
flexibility and cost. Increasingly, writers are observing that
companies can and must compete on several dimensions (Wallace,
1992). For these reasons, it seems that delivery skills are becoming
important for firms in many industries. Since delivery capability is
becoming necessary for more companies, use of delivery-related
SPTs should be related to production competence.

Additionally, as previous research indicates, use of delivery-
related SPTs should be related to the delivery constructs of delivery
competence and delivery performance.

The priority of delivery speed is related to the idea of

responsiveness—the ability to respond to changing customer needs.

1 10
Flexibility definitions also indicate some propensity to quickly

respond to customer needs (Gerwin, 1989, 1993). Therefore,
improvements in delivery capability might add to flexibility
capability.

Also, the suggested delivery-related SPTs indicate
improvements in quality and efficiency. These benefits suggest that
the use of delivery-related SPTs may be related to the cost
constructs of competence and performance.

Finally, the affect of the use of delivery-related SPTs on overall
firm performance is of interest, due to the increasing importance of
this priority (Hill, 1994; Giffi, Roth, and Seal, 199; Stalk and Hout,
1990).

The following hypotheses capture the above arguments and
investigate the relationship between delivery SPTs, production
competence, competence and performance within the other

competitive priorities, and overall firm performance.

Hypotheses 6a-6e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with Mm and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, or (e)
quality competence.

Regress the competence score onto the summated extent
of use scores of the new _ variables.

Model: Y = Bo + 13le + 82X2

where: Y = production, cost, delivery, flexibility, or
quality competence, and the independent variables are
the summation of extent of use scores of the SPTs related
to delivery (see Table 3.6).

lll

X1 = delivery infrastructure (DELINFRA)
X2 = delivery process (DELPROCS)

An F-test will be used to investigate the
inappropriateness of the model (i.e., 81 = B2 = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 6f-6j: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with 191133;: and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, or (j)
quality performance.

Regress the performance score onto the summated extent
of use scores of the new variables.

Model: Y = 30 + 81X] + B2X2

where: Y = production, cost, delivery, flexibility, or
quality performance, and the independent variables are
the summation of extent of use scores of the SPTs related
to delivery (see Table 3.6).

X1 = delivery infrastructure (DELINFRA)
X2 = delivery process (DELPROCS)

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = 82 = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

112

Hypotheses 6k-6n: There is a positive

relationship between the extent of use of
manufacturing SPTs associated with 0.6111111! and
(k) pretax ROA-external assessment, (1) pretax
ROA-internal assessment, (m) aftertax ROA-
external assessment, (n) aftertax ROA-internal
assessment.

Regress the ROA score onto the summated extent of use
scores of the new variables.

Model: Y = Bo + 81X1 + B2X2

where: Y = pretax ROA-external assessment, pretax
ROA-internal assessment, aftertax ROA-external
assessment, aftertax ROA-internal assessment, and the
independent variables are the summation of extent of use
scores of the SPTs related to delivery (see Table 3.6).

X] = delivery infrastructure (DELINFRA)
X2 = delivery process (DELPROCS)

An F-test will be used to investigate the
inappropriateness of the model (i.e., B1 = 82 = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

7. El 'l'l' -Bl lSEI 12 [EE

As in the above discussions of quality and delivery, the SPTs
related to flexibility can be grouped together. Research in flexibility
is less developed than even delivery research. Roth, De Meyer, and
Amano (1989) have published one of the few studies relating the use

of techniques and strategies to flexibility. Other writers in the area

1 13
include Gerwin (1993), who discussed several ways to define

flexibility, ,Stalk and Hout (1990) and Wallace (1992), who discussed
the strategic advantages of time and flexibility, and Parthasarthy and
Sethi (1993), who studied the fit with flexible automation of strategy
and organizational structure choices.

Table 3.7 lists the manufacturing SPTs that the above authors
suggest are related to achieving improved performance in the
flexibility arena. As in the case of delivery, the SPTs were divided
into the categories of “process” and “infrastructure”. This breakdown
was not made by the cited authors and was not done in a statistical
manner. They again represent Hayes and Wheelwright’s (1984)
structural and infrastructural categories. The new variables created
(FLEXPROC and FLEXINFR) are equal to the sum of the extent of use
scores of the SPTs in each category.

The SPTs in Table 3.7 are purported by the cited authors to
improve flexibility performance. If they do, the use of the SPTs
should be positively related to flexibility competence and flexibility
performance.

As previously stated, one objective of this study is to identify
relationships between SPTs and production competence. The
contribution that flexibility-related SPTs can make, especially in very
competitive markets, can be critical. Investigating their use and.
relationship to production competence can contribute to the bundle
of important SPTs.

Flexibility capability, according to Ferdows and De Meyer
(1990), is acquired after quality and delivery. Therefore, the use of
flexibility-related SPTs should be positively related to competence

114
Table 3.7: Manufacturing SPTs Related to Flexibility

W 12mm

Coordination In Product Design Advanced Manufacturing

Cross Functional Teams Technology

Cross Training Workers CIM

Employee Involvement FMS

Supplier Certification General Purpose Equipment

Tm Group Technology

Use Of 7 Basic Quality Tools I IT

Workplace Orderliness Maintain Excess Equipment
Capacity

Product Focused Factory
Reduce Setup Times

Reduction In Throughput Times
Simplified Material Flow

Sources: Roth, De Meyer, and Amano (1989); Gerwin (1993); Wallace (1992);
Stalk and Hout (1990): and Parthasarthy and Sethi (1993).

and performance within those two competitive dimensions.

Additionally, the suggested flexibility-related SPTs indicate
improvements in quality and efficiency, and also indicate the use of
technology to increase efficiency. As in the delivery case, these
benefits suggest that the use of flexibility-related SPTs may be
related to the cost constructs of competence and performance.

Finally, as with delivery, flexibility is increasingly becoming an
important competitive advantage that firms can leverage into
increased profits (Pine, Victor, and Boynton, 1993). Investigating the
benefits of the use of flexibility-related SPTs can give insight into
this important source of competitive advantage.

The following hypotheses capture the above arguments and

investigate the relationship between flexibility SPTs, production

115
competence, and competence and performance within the other

competitive priorities.

Hypotheses 7a-7e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with flexibility and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, or (e)
quality competence.

Regress the competence score onto the summated extent
of use scores of the new variables.

Model: Y = Bo + 81X1 + 82X2

where: Y = production, cost, delivery, flexibility, or
quality competence, and the independent variables are
the summation of extent of use scores of the SPTs related
to flexibility (see Table 3.7).

X1 = flexibility infrastructure (FLEXINFR)
X2 = flexibility process (FLEXPROC)

An F-test will be used to investigate the
inappropriateness of the model (i.e., Bl = 82 = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 7f-7j: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with W and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, or (j)
quality performance.

Regress the performance score onto the summated extent
of use scores of the new variables.

116

Model: Y = Bo + 81X] + B2X2

where: Y = production, cost, delivery, flexibility, or
quality performance, and the independent variables are
the summation of extent of use scores of the SPTs related
to flexibility (see Table 3.7).

X1 = flexibility infrastructure (FLEXINFR)
X2 = flexibility process (FLEXPROC)

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = Bz = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 7k-7n: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with W
and (k) pretax ROA-external assessment, (1)
pretax ROA-internal assessment, (m) aftertax
ROA-external assessment, (11) aftertax ROA-
internal assessment.

Regress the ROA score onto the summated extent of use
scores of the new variables.

Model: Y = Bo + 81X1 + 82X2

where: Y = pretax ROA-external assessment, pretax
ROA-internal assessment, aftertax ROA-external
assessment, aftertax ROA-internal assessment, and the
independent variables are the summation of extent of use
scores of the SPTs related to flexibility (see Table 3.7).

X1 = flexibility infrastructure (FLEXINFR)
X2 = flexibility process (FLEXPROC)

117

An F-test will be used to investigate the
inappropriateness of the model (i.e., B1 = Bz = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual B5 are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

8. W

In the practitioner literature, achieving cost reductions is of
paramount importance. Over time both the academic and
practitioner thinking on cost reduction has changed—from a
hierarchical, mechanistic organization emphasizing high volumes and
economies of scale, to a more organic structure that emphasizes
improved quality, in addition to obtaining economies where possible,
as a source of cost reduction.

In the manufacturing and policy/strategy literature, several
authors have written about methods of cost reduction. Porter (1980)
observed that low cost was a viable strategy and indicated several
economies of scale-type strategies and techniques that could support
the low cost business objective. Dess and Davis (1984) tested
Porter’s model and also identified cost reducing techniques. Kim and
Lee (1993) observed several characteristics of production systems
that support lower costs. Harmon (1987) mentioned some new ways
of thinking about cost reductions in factory settings that included
quality improvements. Several operations management texts also
highlight the economies/quality approach to lowering costs
(Krajewski and Ritzman, 1993; Meredith, 1992). Ward, Miller, and
Vollmann (1988) and Roth, De Meyer, and Amano (1989) conducted

1 18
Table 3.8: Manufacturing SPTs Related to Cost

W
Failsafing Or Foolproofing Automation
Total Quality Control (TQC) Backward Integration
Use of Seven Basic Quality Dedicated Equipment
Improvement Tools Forward Integration
Zero Defects Large Batch Production

Proprietary Technology
Purchase In Large Quantities

Design For Manufacturability Reducing Size of Work Force
Product Simplification Work Measurement
Product Standardization Worker Safety

Value Analysis Worker Specialization

Variety Reduction

Sources: Krajewski and Ritzman (1993); Meredith (1992); Kim and Lee (1993);
Ward, Miller, and Vollmann (1988); Roth, De Meyer, and Amano (1989); Harmon
and Peterson (1987); Dess and Davis (1984); and Porter (1980).

empirical analyses that observed the use of manufacturing strategies
and techniques that were related to lower costs.

Table 3.8 lists the manufacturing SPTs from Table 3.1 that the
literature suggests are related to lower costs. The literature suggests
that costs can be lowered by improving quality, improving product
designs, or operating more efficiently. These categories form new
variables (COSTQUAL, COSTDES, and COSTEFF) that are equal to the
sum of the extent of use scores of the SPTs in each category.

The SPTs in Table 3.8 are cost-reduction approaches culled
from the policy/strategy and operations literature. Therefore, the
use of these SPTs should be positively related to the constructs of
cost competence and cost performance. Additionally, as cost becomes
more important to consumers, cost reductions become an important

component to business strategies. In a mature industry such as

119
furniture, cost issues are important and companies must develop

new methods of lowering costs. Production competence and the use
of cost-related SPTs might be related, given this late stage in the life
cycle.

The final step in the sand cone model (Ferdows and De Meyer,
1990) says that cost capability is acquired after quality, delivery,
and flexibility capabilities. Therefore, the use of cost-related SPTs
should be associated with competence and performance in those
three areas.

Cost reduction strategies are considered one of the basic
strategies firms can use to compete (Hill and Jones, 1989; Porter,
1980). Firms in a mature industry such as the furniture will face
cost pressure and the firms that successfully implement cost
reducing strategies should fare better than firms that are less
successful (Hill, 1994).

The following hypotheses capture the above arguments and
investigate the relationship between cost-related SPTs, production
competence, and competence and performance within the

competitive priorities.

Hypotheses 8a-8e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with £031 and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, and (e)
quality competence.

Regress the competence score onto the summated extent
of use scores of the new variables.

Model: Y = Bo + 81X1 + mm + B3X3

120

where: Y = production, cost, delivery, flexibility, or
quality competence, and the independent variables are
the summation of extent of use scores of the SPTs related
to cost (see Table 3.8).

X1 = quality oriented SPTs (COSTQUAL)
X2 = design oriented SPTs (COSTDES)
X3 = efficiency oriented SPTs (COSTEFF)

An F-test will be used to investigate the
inappropriateness of the model (i.e., 81 = Bz = B3 = 0). As
in earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 8f-8j: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with 9151 and (f) production
performance, (g) cost performance, (h) delivery
performance, (1) flexibility performance, and (j)
quality performance.

Regress the performance score onto the summated extent
of use scores of the new variables.

Model: Y = Bo + B1X1 + 82X2 + B3X3

where: Y = production, cost, delivery, flexibility, or
quality performance, and the independent variables are
the summation of extent of use scores of the SPTs related
to cost (see Table 3.8).

X] = quality oriented SPTs (COSTQUAL)

X2 = design oriented SPTs (COSTDES)
X3 = efficiency oriented SPTs (COSTEFF)

An F-test will be used to investigate the

121
inappropriateness of the model (i.e., B1 = Bz = B3 = 0). As
in earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual 83 are related to
competence. If multiple coefficients appear, partial

correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 8k-8n: There is a positive

relationship between the extent of use of
manufacturing SPTs associated with 1251 and (k)
pretax ROA-external assessment, (1) pretax ROA-
internal assessment, (m) aftertax ROA-external
assessment, (n) aftertax ROA-internal assessment.

Regress the ROA score onto the summated extent of use
scores of the new variables.

Model: Y = 80 + 81X1 + 82X2 + B3X3

where: Y = pretax ROA-external assessment, pretax
ROA-internal assessment, aftertax ROA-external
assessment, aftertax ROA-internal assessment, and the
independent variables are the summation of extent of use
scores of the SPTs related to cost (see Table 3.8).

X] = quality oriented SPTs (COSTQUAL)
X2 = design oriented SPTs (COSTDES)
X3 = efficiency oriented SPTs (COSTEFF)

An F-test will be used to investigate the
inappropriateness of the model (i.e., Bl = 82 = B3 = 0). As
in earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial

correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

122
9. WW

One response to increased competitive pressures is for firms to
implement the latest “hot” technique. Skinner (1992a) notes that
this is not an effective approach. However, just-in-time (JIT) is one
of these new approaches that has received an extraordinary amount
of attention. Both the academic (Journal of Operations Management,
Decision Sciences, International Journal of Operations & Production
Management, Production and Inventory Management Journal) and
practitioner literature (Production, NAPM Insights, and APICS’ The
Performance Advantage) have published many articles on the
subject. Reported benefits include improvements in cost, quality,
delivery and flexibility. Gunn (1992) suggests that, along with total
quality management (TQM) and CIM, JIT is one of the cornerstones of
manufacturing strategy.

Given the growing popularity of JIT, it would be interesting to
investigate the relationship between JIT and competence. Heiko
(1991) discussed several aspects of JIT and Gilbert (1990)
investigated the manner in which US firms implemented their JIT
programs. Recently, two empirical studies were published that
presented results of studies that were directed at identifying the
basic elements of JIT (Davy, White, Meritt, and Gritzmacher, 1992;
Mehra and Inman, 1992).

Table 3.9 lists the manufacturing SPTs from Table 3.1 that the
above authors identified as elements of JIT. As in the cases above,
the SPTs are grouped into process and infrastructure categories. The
variables created are called JITINFRA and JITPROCS.

The benefits of JIT can impact all of the competitive priorities.

123
Table 3.9: Manufacturifl SPTs Related to Just-in-Time (JIT)

W PM

Product Simplification Group Technology

Reduction in WIP Inventory Just-in-Time

Supplier Certification Preventive Maintenance
Cross-Training Workers Total Productive Maintenance
Employee Involvement Workplace Orderliness
Training for Workers Simplified Material Flow

Reducing Setup Times

Sources: Heiko (1991); Gilbert (1990); Davy, White, Meritt, and Gritzmacher
Q992); and Mehra and Inman (1992).

JIT is being suggested and written about by several authors (see
above). Examining the SPTs in Table 3.9, it can be seen that they
include many of the most common suggestions for improving
competitiveness (Gunn, 1992; Stalk and Hout, 1990; Wallace, 1992).
Given this, the JIT-related SPTs should be positively related to
production competence and performance, as well as competence and
performance within the priorities of cost, quality, delivery, and
flexibility. The reported benefits of JIT are widespread and can
affect several elements of a balance sheet (e.g., cash flow). Given this
widespread impact, it is logical that the use of JIT-related SPTs
should have a positive affect of a firm’s financial indicators.

The following hypotheses capture the above arguments and
investigate the relationship between JIT SPTs, production
competence, and competence and performance within the
competitive priorities.

Hypotheses 9a-9e: There is a positive relationship

between the extent of use of manufacturing SPTs
associated with III and (a) production

124

competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, and (e)
quality competence.

Regress the competence score onto the summated extent
of use scores of the new variables.

Model: Y = 8]) + B]X] + 82X2

where: Y = production, cost, delivery, flexibility, or
quality competence, and the independent variables are
the summation of extent of use scores of the SPTs related
to JIT (see Table 3.9).

X] = JIT infrastructure (JITINFRA)
X2 = JIT process (JITPROCS)

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = B2 = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 9f-9j: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with 111 and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, and (j)
quality performance.

Regress the performance score onto the summated extent
of use scores of the new variables.

Model: Y = 80 + 81X] + B2X2

where: Y = production, cost, delivery, flexibility, or
quality performance, and the independent variables are
the summation of extent of use scores of the SPTs related
to JIT (see Table 3.9).

125

X] = JIT infrastructure (JITINFRA)
X2 = JIT process (JITPROCS)

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = 82 = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

Hypotheses 9k-9n: There is a positive

relationship between the extent of use of
manufacturing SPTs associated with .111 and (k)
pretax ROA-external assessment, (l) pretax ROA-
internal assessment, (m) aftertax ROA-external
assessment, (n) aftertax ROA-internal assessment.

Regress the ROA score onto the summated extent of use
scores of the new variables.

Model: Y = 30 + 31X] + B2X2

where: Y = pretax ROA-external assessment, pretax
ROA-internal assessment, aftertax ROA-external
assessment, aftertax ROA-internal assessment, and the
independent variables are the summation of extent of use
scores of the SPTs related to JIT (see Table 3.9).

X] = JIT infrastructure (JITINFRA)
X2 = JIT process (JITPROCS)

An F-test will be used to investigate the
inappropriateness of the model (i.e., B] = Bz = 0). As in
earlier tests, an alpha level of .10 will be enforced.
Stepwise regression will be used to test the above model
and to determine if the individual Bs are related to
competence. If multiple coefficients appear, partial
correlation coefficients will be tested using the t-statistic
(Cohen and Cohen, 1983, pp. 172-173).

126
The hypotheses listed above will be tested on the collected data

using SPSS (4.0) for the Macintosh. The hypotheses requiring
multiple regression analysis will be tested using the stepwise method

(Neter and Wasserman, 1974).

IV. RESULTS AND ANALYSIS

This chapter will present results and analysis of the study described
in Chapter 3. The first section discusses the relationship between the
production competence construct and individual manufacturing
strategies, programs, and techniques (SPTs). That will be followed by
results of the investigation of the relationship between competence
within the four main competitive priority areas (cost, delivery,
flexibility, and quality) and the individual manufacturing SPTs. The
third area of analysis involves the relationship between the use of
manufacturing SPTs and performance within the four main
competitive priority areas. The fourth section presents results
investigating the relationship between overall firm performance and
manufacturing SPTs.

Following the results of the analysis of individual
manufacturing SPTs will be several sections that analyze the results
of hypotheses five through nine—those that analyze collections of
SPTs that have been grouped according to competitive priority (cost,
delivery, flexibility, and quality). The final section presents results
from the analysis of just-in-time (JIT) related SPTs, which were
included because of the tremendous interest in JIT and its published

benefits.

Production Competence and Individual Manufacturing
Strategies
The theory of manufacturing strategy states that firms with

manufacturing resources aligned with business strategy objectives

127

128
will outperform those whose manufacturing resources are not in

alignment (Anderson, Cleveland, and Schroeder, 1989). The
production competence construct was developed to measure the
alignment or degree of fit between manufacturing resources and
business strategy objectives (Cleveland, Schroeder, and Anderson,
1989). Recently, Vickery, Droge, and Markland (1993) improved the
measurement of the production competence construct and discovered
a positive relationship between firm performance and production
competence.

This study is an attempt to expand previous research in the
production competence area by investigating relationships between
production competence and the use of particular manufacturing
strategies, programs, and techniques. A potential result of this
section of the study is the development of a bundle or core set of
strategies that are associated with production competence.

Hypothesis 1 was developed to test the relationship between
production competence and the use of individual manufacturing

strategies, programs, and techniques. It appears below:

Hypothesis 1: There is a positive relationship between
the extent of use of individual manufacturing
strategies, programs and techniques and production
competence.

The manufacturing strategies, programs and techniques tested by
this hypothesis are listed in Table 3.1. To test this hypothesis, a
series of simple regression analyses were conducted with production
competence as the dependent variable and the extent of use of the

manufacturing SPTs as the independent variable. A t-test was

129
performed to test if the regression coefficient was significantly

different from zero in the positive direction (one-way test). Given
that this is theory-building research, an alpha-level of .10 was used,
resulting in a critical t-value of 1.319 (n=24) (Emory, 1985).

Table 4.1 presents the manufacturing SPTs with regression
coefficients that are significantly and positively related to production
competence. To add an underlying structure to the analysis, the
significant SPTs can be further classified according to Hayes and
Wheelwright’s structural and infrastructural factors of
manufacturing strategy (Hayes and Wheelwright, 1984). This
classification is not statistically driven (due to small sample size), and
therefore is merely an estimate of how the SPTs might be classified.
The estimate, however, should be adequate for the purposes of
discussion.

The structural factors appearing in Table 4.1 include
proprietary technology, product-focused factory, synchronous
manufacturing, process-focused factory, and flexible manufacturing
systems. These SPTs are similar in that, except for proprietary
technology, they are concerned with the integration and flow of
product through an entire facility. This might indicate that firms
taking a total systems approach to the manufacturing process possess
greater understanding of the linked nature of the function. As a
result, the manufacturing function is better aligned with business
objectives.

The presence of both product- and process-focused factories in
Table 4.1 is interesting in that it might not matter which process

position a firm takes, as long as they clearly understand their

130

Table 4.1: Individual SPTs Related to Production Competence

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t-stat

Programs, and Techniques value
1 Proprietary Technology .571 0.002 3.189
2 Worker Specialization .533 0.004 2.889
3 Workplace Orderliness .532 0.004 2.881
4 Supplier Selection Based On Price .441 0.018 2.249
5 Product-Focused Factory .435 0.019 2.213
6 Synchronous Manufacturing .413 0.025 2.078
7 Worker Motivation .405 0.028 2.031
8 Process-Focused Factory .367 0.043 1.808
9 Worker Safety .345 0.053 1.685
10 Product Standardization .340 0.056 1.659
1 1 Reduce Num. Of Eng. Change Orders .337 0.058 1.643
12 Employee Involvement .325 0.065 1.576
13 Total Productive Maintenance .325 0.065 1.573
14 Vertical Job Enlargement .299 0.083 1.434
15 Training For Workers .293 0.087 1.406
16 Flexible Manufacturing System .285 0.094 1.364

 

business and appropriately position the manufacturing process.

Krajewski and Ritzman (1993) observe that this decision is critical—

one that determines many of the subsequent downstream decisions.

The furniture industry is one experiencing rapid change

brought on by increased competition and a slowing global economy.

A response many firms are choosing is to develop and implement a

new technology, allowing the firm a competitive advantage that is

difficult to imitate.

machine that improves productivity, increases quality, or

accomplishes both objectives.

For furniture manufacturers, this may be a

These results show that, in this study,

firms that have developed their own technology are providing

tremendous support to their business strategies.

This might be a

 

131
situation where the manufacturing function, instead of supporting

the business strategy, is actually the source of distinctive competence
for the firm (Hayes and Wheelwright, 1984).

Upon analyzing the manufacturing SPTs appearing in Table 4.1,
one is struck by the predominance of SPTs that are related to the
employees. Five of the sixteen significant SPTs directly concern
worker-related/empowerment issues, including motivation, safety,
involvement, job enlargement, and training. Total productive
maintenance (TPM), a program that bestows responsibility for
maintenance on the operator, can be thought of as employee-related
as it broadens job requirements and is often accompanied by pushing
decision-making and authority lower in firm hierarchies (Giffi, Roth,
and Seal, 1990; Maggard and Rhyne, 1992).

The presence of employee-related issues is an important
result—regardless of strategic direction, employee involvement and
support play an important role in strategy implementation. For the
firms included in the survey, there is strong evidence of a
relationship between production competence and giving attention to
workers, either through taking to steps to ensure their safety or
involving workers in decision processes. If so, this result lends
credence to statements many firms make concerning the importance
of people to their firm and their value as an asset.

The remaining infrastructural SPTs include workplace
orderliness and design issues (reduce engineering change notices and
product standardization). Hayes and Wheelwright (1984) note that
the cumulative affect of infrastructural factors can be just as

important to manufacturing strategy as the structural factors. The

132
results of this analysis indicate that the infrastructural factors of

people-management and management of the manufacturing system
are critical to production competence.

In summary, the manufacturing SPTs that are associated with
production competence indicate two general areas are critical to
supporting the business strategy. First, the importance of employees
to the system and the experience, knowledge, and creativity that
they contribute is evident. Second, the particular positioning of the
manufacturing process—either product or process—is not as important
as having the vision to see the process as a linked system. The
ability to understand the linked nature of the system might be
related to having the strategic vision to tie manufacturing resources

to business strategy objectives.

Competitive Priority Competence and Related
Manufacturing Strategies, Programs, and Techniques

Skinner (1992a) observes that one of the problems with research in
manufacturing strategy is that it is not prescriptive. He indicates
that practitioners are not receiving adequate guidance from the
research community regarding the strategic decisions they make.
Specifically, Skinner mentions that linkages between competitive
thrusts and the manufacturing strategic decision categories are
missing (see Figure 3.2). While the results in the previous section
suggest manufacturing SPTs that relate to production competence,
they do not give guidance regarding decision making within a
particular competitive thrust or priority. This section presents
results that link the manufacturing SPTs to a particular competitive

priority.

133
This section begins the analyses of the second group of

hypotheses—those relating to competitive priority competence.
Hypotheses 2a—2d were constructed to address the issue of linking

results to specific competitive thrusts. Hypotheses 2a is listed below:

Hypothesis 2a: There is a positive relationship
between the extent of use of individual manufacturing
strategies, programs and techniques, and cost
competence.

Chapter 3 introduced the competitive priority constructs and
described their construction. As a brief review, that process will
again be discussed. In the study by Vickery, Droge, and Markland
(1993), the production competence score was determined by
summing the product of [competitive priority importance *
competitive priority performance (adjusted) * percent manufacturing
responsibility] across 31 competitive priorities (see Table 2.1 for the
full list of priorities). Table 3.3 lists (exclusive, not exhaustive) the
categorization of those 31 priorities into the familiar cost, delivery,
flexibility, and quality priority areas. Applying the same logic as in
the production competence construct, a competence score can be

determined for each of the four main priority areas.

Cost Competence and Individual Manufacturing Strategies
Table 4.2 displays the manufacturing SPTs that are positively related
to cost competence (as in the production competence analysis, a
critical t-statistic of 1.319 was used). The individual competitive
priorities of low production cost, competitive pricing, and low price

were used to create the cost competence construct (see Table 3.3). A

134
series of simple regression analyses was conducted with cost

competence as the dependent variable, while the individual
manufacturing SPTs were included as independent variables.

Using Hayes and Wheelwright’s (1984) categories, four of the
SPTs in Table 4.2 can be roughly (without statistical analysis)
classified as structural factors—backward integration, computer
integrated manufacturing (CIM), advanced manufacturing technology
(AMT), and forward integration. The integration SPTs are classic
cost-reduction strategies, so it is no surprise that they appear
(Porter, 1980). Forward integration might be more crucial to the
furniture industry as distribution channels can be critical to the '
business. Backward integration can include wood-related
technologies such' as rough mills to reduce raw lumber and other
input material costs. The presence of the technology SPTs—CIM and
AMT—indicates that advanced technologies are very important to
cost-reduction efforts.

The infrastructural SPTs in Table 4.2 can be roughly (without
statistical analysis) divided into the categories of quality, purchasing,
and production planning and control. The quality-related SPTs are
benchmarking, 100% inspection, failsafing, a “do-it-right-the-first-
time” emphasis, and timely feedback of quality data. At one time, it
was thought that quality and cost objectives were in conflict. Firms
are now understanding the true relationship—quality improvement
leads to cost reduction. Ferdows and De Meyer (1990) observed that

quality improvement was a prerequisite to cost reduction. Given the

135

Table 4.2: Individual SPTs Related to Cost Competence

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- ‘ t-stat

Progams, and Techniques value
1 Backward Integration 0.520 0.006 2.791
2 Computer Integrated Manufacturing 0.508 0.007 2.703
3 Benchmarking 0.482 0.010 2.520
4 Advanced Mfg. Technology (AMT) 0.468 0.012 2.433
5 100 % Inspection 0.450 0.016 2.313
6 Purchase In Large Quantities 0.428 0.021 2.176
7 Failsafing Or Foolproofing 0.409 0.026 2.058
8 Reliance On Fewer Suppliers 0.370 0.041 1.829
9 Emphasis On “Right-The-First-Time” 0.365 0.043 1.800
10 Advanced Forecasting 0.365 0.043 1.798
11 Supplier Selection Based On Quality 0.358 0.047 1.759
12 Preventive Maintenance 0.349 0.051 1.710
13 Large Batch Production 0.329 0.062 1.602
14 Forward Integration 0.317 0.070 1.534
15 Training Provided To Suppliers 0.316 0.071 1.527
16 Supplier Certification 0.312 0.073 1.509
17 Departmental Coord. In Prod. Design 0.298 0.083 1.433
18 Timely Feedback Of Quality Data 0.296 0.085 1.421

 

 

136
new understanding, one would expect to see more of the quality SPTs

associated with cost competence than appear in Table 4.2.

The purchasing-related SPTs in Table 4.2 include buying in
large quantities, reliance on fewer suppliers, supplier selection based
on quality, supplier training, and supplier certification. The large
number of purchasing strategies highlights the importance of sound
purchasing to low cost strategies, and to cost reduction in general.
These results reflect a general trend where many firms are reducing
their supplier base and rewarding those that remain with increased
volumes. Quantity discounts are important to cost savings and can
be easier to achieve if fewer vendors are used. Supplier training can
reduce variation of inputs, which improves quality which leads to
cost reduction. Once suppliers have achieved adequate quality
levels, they can be certified, removing the need for costly inspec-
tions. In the long term, certification can reduce incoming variation,
as well as establish relationships that move beyond variation to in-
corporate other cost-reducing methods and strategic alternatives
(Ellram, 1991).

The production- planning and control SPTs appearing in Table
4.2 include advanced forecasting, maintenance programs, and large
batch production. In high volume product industries—as some
furniture products are—line flow production systems are often
employed. Capacity changes can be difficult and expensive, which
increases the importance of reliable forecasts (Hill, 1994).
Additionally, furniture can be expensive to hold in inventory, again
indicating the importance of good forecasting. In line-flow systems,

machine breakdowns can close down entire lines. Therefore,

137
preventive maintenance programs work to keep equipment

operating, lines moving and utilization rates high—all critical to
managing line-flow production. Finally, departmental design
coordination ensures that products can be produced efficiently,
further reducing unnecessary manufacturing costs.

In summary, cost competence is accomplished through a
combination of standard vertical integration strategies, advanced
machine technologies, purchasing and production planning strategies
directed at economies of scale, and an emphasis on quality

improvement.

Delivery Competence and Individual Manufacturing SPTs

Table 4.3 displays the manufacturing SPTs related to delivery
competence. The delivery competence construct is comprised of the
individual competitive priorities of delivery speed, delivery
dependability, and production lead time (see Table 3.3). A series of
simple regression analyses was conducted with delivery competence
as the dependent variable, while the individual manufacturing SPTs
were included as independent variables.

The manufacturing SPTs that are related to delivery
competence can be further divided into structural and infrastructural
factors. The structural SPTs include product-focused factory, flexible
manufacturing system, proprietary technology, process-focused
factory, and simplified material flow. These SPTs are almost
identical to the structural factors related to production competence.
Again, the presence of these structural SPTs indicates an

understanding of the entire manufacturing system, which is very

138

important to reducing system variability. The reduction in

variability can be accomplished through establishing product-focused
factories, installing dedicated proprietary technology, and simplifying
material flow. Finally, reducing system variability makes it easier to

meet due dates, which improves delivery performance.

Table 4.3: Individual SPTs Related to Delivery Competence

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t—stat

Programs, and Techniques value
1 Worker Safety 0.468 0.012 2.430
2 Product-Focused Factory 0.448 0.016 2.297
3 Workplace Orderliness 0.439 0.018 2.242
4 Flexible Manufacturing System 0.402 0.028 2.016
5 Proprietary Technology 0.398 0.030 1.991
6 Employee Involvement 0.346 0.053 1.691
7 Total Productive Maintenance 0.326 0.065 1.578
8 Employees Resp. For Output Quality 0.324 0.066 1.570
9 Self-Directed Work Teams 0.323 0.066 1.563
10 Process-Focused Factory 0.293 0.087 1.405
11 Reduction In Work-In-Process Inv. 0.281 0.097 1.342
12 Supplier Selection Based On Price 0.278 0.100 1.326
13 Simplified Material Flow 0.277 0.100 1.323

 

 

The infrastructural SPTs related to delivery competence

include worker safety, workplace orderliness, employee involvement,

total productive maintenance (TPM), employee responsibility for

their output quality, self-directed work teams, reduction in WIP

inventory, and supplier selection based on price.

Worker safety,

workplace orderliness, employee involvement, and total productive

' maintenance also are related to production competence.

Maintenance programs keep machinery and equipment running and

 

139
dependable, which also reduces system variability. Orderliness and

reducing WIP levels are related the structural SPT of simplified
material flow in that they each address the smooth, swift movement
of materials through the facility.

Increasing employee responsibility for quality, coupled with
increasing their authority in the system—through the use of TPM and
self-directed work teams—and showing respect by caring for
employee safety might help to engender ownership of products and
orders by the workforce. This ownership can be critical to

maintaining excellent delivery records.

Flexibility Competence and Individual Manufacturing SPTs
Table 4.4 lists the manufacturing SPTs related to flexibility
competence. The flexibility competence construct is comprised of the
competitive priorities of product flexibility, volume flexibility,

process flexibility, product development cycle time, and
responsiveness to target markets (see Table 3.3).

The structural SPTs in Table 4.4 related to flexibility
competence include group technology, synchronous manufacturing,
just-in-time, product-focused factory, proprietary technology, and
general purpose equipment. This collection of SPTs indicates the
application of technologies directed at simultaneously achieving the
benefits of low- and high-volume manufacturing processes. The use
of general purpose equipment following a line-flow arrangement
allows the application of synchronous and just-in-time
manufacturing principles (Hill, 1994). While this group of

technologies does not contribute the highest degree of flexibility

140
possible, it does provide the opportunity to impart moderate

flexibility levels while simultaneously keeping costs in line. This a
method of achieving flexibility without incurring great expense.

The infrastructural SPTs in Table 4.4 that support flexibility
can be roughly divided into five categories, including quality,
training, design, workforce management, and material flow. Quality-
related SPTs include zero defects, use of the seven basic quality
improvement tools (flowcharting, pareto charts, fishbone diagrams,
etc.), acceptance sampling, control charts, reliability measurement
and testing, and advanced statistical tools. Whereas quality SPTs
were missing in the delivery and cost competence analyses, they are
strongly represented in these results. The quality SPTs include both
defect detection and prevention techniques, perhaps reflecting the
transitional period for the industry. Inspection has been used
extensively in the furniture industry, and, as of 1990, firms were
just beginning to see the benefits of prevention techniques appearing
in their inspection results.

Training of workers, suppliers and management is also critical
to flexibility competence. Due to the integrated nature of competing
on flexibility, members at several stages of the value-added chain
need to be trained in new methodologies. The quality initiatives also
require training support. Product design SPTs include reducing
change notices, computer-aided-design (CAD), and standardizing
designs and products. Improving the design process through the use
of CAD and ensuring designs are correct early on, can assist firms in
planning process technology and layout arrangements required to

make the products.

141
Workforce management SPTs include worker specialization,

safety, motivation, and vertical job enlargement. These are very
similar to the worker-related SPTs that are associated with
production competence and delivery competence. Expanding duties
and proactively improving the workplace through safety
improvements can instill the feeling of ownership required to
support flexibility initiatives

Material flow SPTs include shop orderliness and reducing setup
times. Setup time reduction is the among the most important
improvements that can be made to improve low-volume production
(Shingo, 1986; Hill, 1994). Faster changeovers allow for a wider
range of products to be produced in a facility by improving
utilization rates of the process equipment and reducing total costs.
Shop orderliness is also related to production competence and
delivery competence, and is a requirement for smooth material flows
and world-class competitiveness (Schonberger, 1986).

Two of the infrastructural SPTs—worker specialization and
product standardization—appear to be in conflict with flexibility
thrusts. Given the structural SPTs, however, one can argue that they
are in harmony. For example, worker specialiZation supports
product-focused factories, just-in-time and group technology
manufacturing. Each of these is directed at higher volume
production of product families with limited options. Specialization
and standardization support process choice decisions that attempt to
attain benefits of both low- and high-volume manufacturing (Hill,

1994).

142

Table 4.4: Individual SPTs Related to Flexibility Competence

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Programs, Beta p- t-stat

and Techniques value
1 Workplace Orderliness 0.537 0.004 2.920
2 Worker Specialization 0.507 0.007 2.693
3 Training For Workers - 0.492 0.009 2.593
4 Reduce Num. Of Eng. Change Orders 0.487 0.009 2.554
5 Group Technology 0.000 0.000 2.493
6 Synchronous Manufacturing 0.463 0.013 2.395
7 Just-In-Time 0.461 0.013 2.382
8 Zero Defects 0.458 0.014 2.360
9 Worker Safety 0.452 0.015 2.325
10 Product-Focused Factory 0.447 0.016 2.288
1 1 Use Of The Seven Basic Quality Tools 0.438 0.018 2.235
12 Computer-Aided Design 0.407 0.027 2.042
13 Acceptance Sampling 0.406 0.027 2.037
14 Use Of Control Charts 0.396 0.031 1.978
15 Worker Motivation 0.396 0.031 1.974
16 Proprietary Technology 0.395 0.031 1.973
17 Measuring Product Reliability 0.381 0.036 1.890
18 Vertical Job Enlargement 0.372 0.040 1.839
19 Setup Time Reduction 0.327 0.064 1.587
20 Product Standardization 0.325 0.065 1.576
21 General Purpose Equipment 0.323 0.067 1.562
22 Advanced Statistical Tech. (Quality) 0.316 0.071 1.524
23 Training for Execs. and Managers 0.311 0.075 1.497
24 Product Reliability Testing 0.302 0.081 1.452
25 Training Provided To Suppliers 0.293 0.087 1.404

 

 

143
Quality Competence and Individual Manufacturing SPTs

Table 4.5 contains results of a series of simple regression analyses
with quality competence as the dependent variable and individual
manufacturing SPTs as the independent variables. The quality
competitive priorities comprising the construct are product
reliability, product durability, conformance quality, design quality,
and product improvement/refinement (see Table 3.3).

The structural SPTs identified include synchronous
manufacturing, flexible manufacturing systems (FMS), process-
focused factory, and automation. Process-focused factories and
flexible systems are generally not associated with the highest levels
of quality. Because of the wider product ranges and lower volumes
produced on these technologies, they do not achieve levels of I
repeatability that are normally associated with quality. Synchronous
manufacturing and automation can be associated with quality, if
procedures and responsibility are clearly delineated (Umble and
Srikanth, 1990).

The infrastructural SPTs associated with quality competence
are striking due to the paucity of traditional quality-related SPTs.
The infrastructural SPTs could be roughly categorized into suppliers,
material flow, workforce management, and design. The individual
SPTs in these categories are indirectly related to quality, but there
are very few SPTs that are directly quality oriented. The supplier
oriented SPTs include electronic data interchange (EDI) and selection
of suppliers based on price. It is difficult to relate the use of these to
quality, except that EDI might be an indicator of partnering or

related to reducing paperwork errors. Selecting vendors on price,

144

however, is certainly not associated with the partnering model.
Material flow SPTs include total productive maintenance,
preventive maintenance, and failsafing. These SPTs are most related
to quality. Maintenance programs keep equipment running and
operating at specification. Ensuring that equipment is operable,
especially machinery that is used most often for high-volume
components, can contribute to quality improvement. Failsafing
involves the implementation of small, inexpensive additions to
processes that prevent mistakes from occurring and reduce the need

for corrective action (Shingo, 1986).—

Table 4.5: Individual SPTs Related to Quality Competence

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t-stat

Programs, and Techniques value
1 Supplier Selection Based On Price 0.492 0.009 2.591
2 Synchronous Manufacturing 0.434 0.019 2.209
3 Electronic Data Interchange 0.418 0.023 2.111
4 Flexible Manufacturing System 0.416 0.024 2.097
5 Total Productive Maintenance 0.397 0.031 1.980
6 Process-Focused Factory 0.387 0.034 1.926
7 Failsafing or Foolproofing 0.381 0.037 1.887
8 Preventive Maintenance 0.365 0.044 1.795
9 Employee Involvement 0.352 0.050 1.726
10 Automation 0.340 0.056 1.657
11 Product Standardization 0.325 0.065 1.575
12 Quality Function Deployment (QFD) 0.307 0.077 1.479
13 Worker Motivation 0.406 0.081 1.448

 

and motivation.

not included here, such as employee responsibility for output quality,

Workforce management SPTs include employee involvement

Unfortunately, other management-oriented SPTs are

 

145
use of quality improvement tools, etc. Involvement and motivation,

while important, cannot and do not place enough authority with the
workers to make true process improvements (Walton, 1986).

Product design SPTs include product standardization and
quality function deployment (QFD). Standardization reduces variety
and increases repeatability, which increases quality levels. QFD is a
methodology directed at capturing customer requirements and
assigning responsibility for fulfilling these needs (Hauser and
Clausing, 1987). It is a marketing/design tool that can ensure
customer requirements are being met by production personnel.

To summarize the quality competence analysis, poor
performance and support is being offered to quality competitive
initiatives, mostly due to an insufficient number of quality-related
SPTs—both structural and infrastructural—being implemented.
Perhaps Table 4.5 is most striking for what is missing from the table,

rather than what is contained.

COMPETITIVE PRIORITY PERFORMANCE AND RELATED
INDIVIDUAL MANUFACTURING STRATEGIES, PROGRAMS,
AND TECHNIQUES

This section begins the analyses of the third group of hypotheses—
those relating to competitive priority performance. As stated in the
previous section regarding competitive priority competence, Skinner
(1992a) indicates that linkages between competitive initiatives and
the manufacturing strategic decision categories are not being
established for practitioners. While results from the earlier sections
indicated relationships between individual manufacturing SPTs and

competence, results from this section will indicate the manufacturing

146
SPTs that are related to performance. These are the SPTs respondent

firms are implementing—without the pretense of strategic direction—
and achieving excellent performance within a competitive priority.

Analysis of the relationship between the use of manufacturing
SPTs and performance within the competitive priorities may reveal
an association beyond the competence constructs. If companies are
not emphasizing a particular competitive priority (quality, cost, etc.),
but are performing well in that area, they might have lower
competence scores while still achieving excellent performance
results. In fact, investigating the relationship between the SPTs and
performance may reveal a clearer picture—one that is not affected by
importance scores—of the SPTs that have a direct impact on
performance within a competitive priority.

Hypotheses 3a-3d were constructed to address the issue of
linking results to specific competitive thrusts. ' Hypotheses 3a is

listed below:

Hypothesis 3a: There is a positive relationship
between the extent of use of individual manufacturing
strategies, programs and techniques, and cost
performance.

This section will analyze the relationships between
performance within the competitive priority constructs and the use
of manufacturing SPTs. The performance values for each major
priority are the sum of the performance scores for the individual
competitive priorities combined to form the cost, delivery, flexibility,

and quality constructs (see Table 3.3).

147
Cost Performance and Individual Manufacturing SPTs

Table 4.6 displays the manufacturing SPTs that are related to
cost performance. The individual competitive priorities comprising
the cost performance construct are low production cost, competitive
pricing, and low price. Cost performance is the sum of the subjective
performance scores for the three priorities.

Comparing Table 4.6 to Table 4.2 reveals that, of the nine SPTs
related to cost performance, only the infrastructural SPT of reducing
finished goods inventory is not related to cost competence. Reducing
the level of finished goods can have a significant impact on costs, as
FGS inventory is held when the value added is highest. Savings here
releases cash for other purposes, which can be extremely important
for smaller and medium size companies. The other eight SPTs also
appear in Table 4.2.

The structural factors that are related to cost competence and
not related to cost performance are advanced manufacturing
technology and backward integration. Perhaps these SPTs were only
marginally contributing to cost reductions, due to the inherent risks
each carries. Computer-integrated-manufacturing (CIM) and forward
integration are related to 129111 cost competence and performance. At
its most basic level, CIM is a hybrid process that combines the
benefits of process and product layouts for mid-volume production.
Perhaps companies that have advanced to the stage where CIM is a
realistic option have an adequate understanding of the complexities
involved in managing a CIM operation. Forward integration is a
likely cost-related SPT and firms in the sample were successful in

implementing this strategy to achieve cost reductions. As stated

148
earlier, distribution of furniture products can be a costly activity and

firms that integrate into this industry can control distribution and do
not have to add the profits of the transportation firm into their price
structure, allowing for lower retail prices.

The infrastructural SPTs that are related directly to cost
performance can be classified as related to production planning,
purchasing and quality. Planning SPTs include forecasting, reducing
finished goods inventory, and producing in large batches. The first
two relate to efficiency and reducing wastes due to overproduction,
one of Ohno’s (1988) seven waste categories. The third is associated
with achieving economies of scale.

The purchasing SPTs include purchasing in large quantities and
selecting quality suppliers. Cost savings can be generated through
quantity discounts and a reduction in inspection and rework costs.
Finally, the quality SPTs of “doing things right the first time” and a
heavy amount of inspection are related to cost performance. Based
on several plant visits, the 100% inspection technique appears to be
standard in the furniture industry, especially for large products.
This detection approach is, however, expensive and conflicts with the
prevention approach to quality.

In summary, cost performance is a difficult area for firms to
achieve performance improvement (Ferdows and De Meyer, 1990).
The sample firms that are earning cost reductions have used
standard approaches—vertical integration and economies of scale in
production. They have not, however, successfully implemented

many quality-oriented SPTs to support cost reduction.

149

Table 4.6: Individual SPTs Related to Cost Performance

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t-stat

Programs, and Techniques value
1 Advanced Forecasting 0.507 0.007 2.693
2 Emphasis on “Right-The-First-Time” 0.424 0.022 2.143
3 Purchase in Large Quantities 0.423 0.022 2.138
4 Reduction in Finished Goods Invent. 0.395 0.031 1.973
5 100% Inspection 0.390 0.033 1.940
6 Computer-Integrated-Manufacturing 0.375 0.039 1.856
7 Large Batch Production 0.365 0.044 1.794
8 Forward Integration 0.346 0.053 1.687
9 Supplier Selection Based On Quality 0.304 0.079 1.461

 

 

Delivery Performance and Individual Manufacturing SPTs

Table 4.7 displays the competitive priority constructs that are
related to delivery performance. The individual competitive
priorities comprising the delivery performance construct are
delivery speed, delivery dependability, and production lead time
(see Table 3.3). The delivery performance score for a firm is the sum
of the subjective performance scores for the individual competitive
priorities above.

The manufacturing SPTs associated with delivery performance
are very similar to those associated with delivery competence.
Therefore, this analysis will be brief. A more detailed discussion
appears in the section regarding delivery competence.

All of the structural SPTs related to delivery competence (see
Table 4.3) also appear in Table 4.7. They include product-focused
factory, flexible manufacturing system, proprietary technology,
process-focused factory, and simplified material flow. As stated

earlier, these factors are very closely related to the structural factors

150
associated with production competence. These SPTs are directed at

reducing system variability to improve delivery performance, while
maintaining the capability to produce wider ranges of products and
varying quantities.

All of the infrastructural SPTs in Table 4.7 related to delivery
performance appear in the analysis of delivery competence—except
for reducing workforce size. Perhaps the firms that were downsizing
were forced to improve processes and reducing waste in the system.
Reduced variability and faster throughputs may have resulted from
the process improvements. The majority of the infrastructural SPTs
are related to workforce management issues, particularly in the area
of granting increased responsibility to workers and decision-making
authority to work teams.

The increased worker responsibility and authority can have
two benefits. First, workers feel more ownership of the product and
process and, therefore, will make the extra effort required to
overcome problems and meet due dates. Secondly, the workers
might finally have the authority and opportunity to make
suggestions directed at improving process flow, which can

dramatically improve cycle times and improve delivery performance.

Flexibility Performance and Individual Manufacturing SPTs
Table 4.8 displays results of a series of simple regression analyses
with flexibility performance as the dependent variable and the

individual manufacturing SPTs as the independent variables. The

151

Table 4.7: Individual SPTs Related to Delivery Performance

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t-stat

Programs, and Techniques value
1 Product-Focused Factory 0.392 0.032 1.955
2 Worker Safety 0.391 0.033 1.947
3 Employee Involvement 0.364 0.044 1.792
4 Employees Respons. for Output Qual. 0.348 0.052 1.699
5 Workplace Orderliness 0.334 0.060 1.624
6 Proprietary Technology 0.318 0.070 1.538
7 Reducing Size Of Workforce 0.313 0.073 1.508
8 Flexible Manufacturing System 0.304 0.079 1.465
9 Self-Directed Work Teams 0.290 0.090 1.388
10 Process-Focused Factory 0.288 0.092 1.377
11 Total Productive Maintenance 0.278 0.100 1.326

 

individual competitive priorities (from Table 3.3) that comprise the

flexibility performance construct are product flexibility, volume

flexibility, process flexibility, product development cycle time, and

responsiveness to target markets.

Flexibility performance is

calculated by summing the subjective performance scores for the

five priorities above.

The six structural SPTs related to flexibility performance are

identical to those related to flexibility competence.

They include

 

product-focused factory, just-in-time, group technology, synchronous
manufacturing, proprietary technology, and general purpose
equipment. This collection of SPTs is directed at obtaining the
flexibility benefits of a process approach to manufacturing while
maintaining the competitive cost structures of the product approach
(Hill, 1994). This is made possible by dedicating general purpose

equipment to the production of product families in a product-focused

152
factory approach. The group technology/synchronous approach,

combined with general purpose equipment, allows companies to
accomplish this difficult combination. It is interesting that JIT
appears in Table 4.8, as it can provide some, but limited flexibility.
JIT works best in situation with limited product flexibility and stable
volumes.

The infrastructural SPTs in Table 4.8 can be roughly (without
statistical analysis) classified into the categories of workforce
management, quality, product design, production planning, material
flow, and supplier management. The workforce and organizational
management oriented SPTs include specialization, training (for
workers, executives, and managers), motivation, safety, vertical job
enlargement, employment involvement, self-directed work teams,
and cross-functional teams. These SPTs emphasize including workers
in decision-making and implementing process improvements. The
cross-functional team approach helps to improve horizontal
processes such as completing delivery and providing flexibility
(Byme, 1993). Placing the workforce in teams and enlarging
responsibilities can improve motivation levels and engender a
culture that embraces the organizational change that accompanies
strategies that emphasize flexibility. Worker specialization may
appear counter-intuitive, but it is in alignment with the structural
SPTs in Table 4.8 that emphasize the product-focused approach.

The abilities of a trained and motivated workforce are
capitalized by the many quality-oriented SPTs related to flexibility
performance. These SPTs include employing the seven basic quality

tools (flow diagrams, check sheets, histograms, pareto charts,

153
fishbone diagrams, scatterplots, and control charts), using advanced

statistical techniques, measuring and testing product reliability, zero
defects programs, and acceptance sampling. Less obvious quality
SPTs include the use of color coding machines and parts to minimize
time wasted during changeovers. This is largest representation of
quality-related SPTs in any of the previous analyses, indicating the
crucial importance of quality improvement when competing on
flexibility. This substantiates the sand cone model presented by
Ferdows and De Meyer (1990), in which quality is the building block
for other strategic initiatives.

The material flow/planning SPTs related to flexibility
performance include setup reduction, which may be the most
important SPT in the entire table (Shingo, 1986). Reducing setup
times allows firms to economically produce smaller batches of
products. This contributes to the support of all of the individual
priorities comprising the delivery performance construct, indicating
the critical importance of setup reduction. The planning SPT in Table
4.8 is mixed model production scheduling. Capitalizing on the
synchronous and JIT capabilities, and the short setup times, this SPT
greatly contributes to flexibility by running small quantities of goods
through the flexible facility, rounding out the entire system.

In summary, flexibility performance is being achieved by
respondent firms through several critical channels. First, general
purpose equipment is combined with other product-oriented
technologies, allowing firms to simultaneously obtain the benefits of
product and process layouts. Reduced setup times and mixed model

scheduling, which (can improve the effective capacity of a factory,

154

Table 4.8: Individual SPTs Related to Flexibility Performance

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t—stat

Programs, and Techniques value
1 Worker Specialization 0.584 0.002 3.298
2 Product-Focused Factory 0.547 0.004 2.991
3 Workplace Orderliness 0.539 0.004 2.933
4 Training For Workers 0.537 0.004 2.918
5 Just-In-Time 0.524 0.005 2.822
6 Group Technology 0.490 0.009 2.576
7 Worker Motivation 0.479 0.010 2.498
8 Worker Safety 0.458 0.014 2.363
9 Synchronous Manufacturing 0.434 0.019 2.210
10 Proprietary Technology 0.421 0.023 2.125
1 1 Use Of The Seven Basic Quality Tools 0.414 0.025 2.085
12 Computer-Aided Design 0.404 0.028 2.026
13 Product Reliability Testing 0.397 0.030 1.982
14 Reduce Num. Of Eng. Change Orders 0.396 0.031 1.976
15 Training For Execs. And Managers 0.391 0.032 1.949
16 Acceptance Sampling 0.389 0.033 1.937
17 Vertical Job Enlargement 0.383 0.036 1.901
18 Product Standardization 0.373 0.040 1.842
19 Zero Defects 0.355 0.048 1.740
20 Self-Directed Work Teams 0.351 0.050 1.718
21 Measuring Product Reliability 0.342 0.055 1.668
22 Setup Time Reduction 0.326 0.065 1.578
23 Employee Involvement 0.310 0.075 1.497
24 Mixed-Model Production Scheduling 0.307 0.07 7 1.480
25 Adv. Statistical Techniques (Quality) 0.302 0.081 1.451
26 Cross-Functional Teams 0.298 0.083 1.433
27 General Purpose Equipment 0.289 0.090 1.385
28 Supplier Selection Based On Price 0.289 0.091 1.383
29 Color Coding Of Machines And Parts 0.286 0.093 1.370

 

 

155
also allow for increased responsiveness. Second, the management

style in firms with high flexibility performance appears to be
oriented toward pushing authority and responsibility down the
organization. Employees work in cross functional and self-directed
teams to solve process related-problems. Third, taking advantage of
the motivated workforce, quality SPTs are widely implemented to
support process improvements. Finally, scheduling and planning
SPTs emphasize the efficient flow of materials through‘a facility,
while also using the flexibility of the process and employees to

schedule a variety of products.

Quality Performance and Individual Manufacturing SPTs
This section discusses the results of a series of simple regressions
with quality performance as the dependent variable and the
individual manufacturing SPTs as independent variables. The
quality competitive priorities comprising the quality performance
construct are product reliability, product durability, conformance
quality, design quality, and product improvement/refinement (see
Table 3.3). Quality performance is determined by summing the
subjective performance scores for the five individual priorities
above.

The structural SPTs that are related to quality performance are
dominated by technologies used in high-volume, repetitive
manufacturing. Automation is used to replace more variable humans
in tasks that are repetitive. Proprietary technology can include that
which accomplishes several tasks in a short period, all with minimal

variability. Except for automation, the structural SPTs are different

156

for quality competence, an inconsistency not found in the delivery

and flexibility analyses.

The infrastructural SPTs related to quality performance can be

roughly classified into the categories of quality, design, workforce

management, and suppliers.

Table 4.9: Individual SPTs Related to Quality Performance

The quality SPTs are reliability testing,

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta p- t-stat

Programs, and Techniques value
1 Supplier Selection Based On Price 0.585 0.002 3.308
2 Product Reliability Testing 0.546 0.004 2.983
3 Acceptance Sampling 0.469 0.012 2.436
4 Product Standardization 0.437 0.019 2.225
5 Design For Manufacturability 0.412 0.025 2.071
6 Proprietary Technology 0.404 0.028 2.021
7 Product-Focused Factory 0.401 0.029 2.004
8 Automation 0.379 0.037 1.875
9 Worker Motivation 0.372 0.040 1.839
10 Inspection Of Incoming Materials 0.367 0.042 1.808
11 Worker Specialization 0.350 0.051 1.714
12 Variety Reduction 0.307 0.077 1.476
13 Quality Function Deployment (QFD) 0.300 0.082 1.441

acceptance sampling, and inspection of incoming materials. The

emphasis on quality SPTs was much stronger in the areas of delivery

and flexibility, and fairly weak in the areas of quality and cost.

As with quality competence, the SPTs in Table 4.9 should be

noted for their emphasis on detection rather than prevention.

This

indicates the lack of maturity and transitional state of the furniture

industry, with respect to production quality.

Design-oriented SPTs

include design for manufacturability, quality function deployment,

 

157
and product standardization. Variety reduction, essentially a

business issue, is also related to design. These SPTs indicate a
movement toward preventing quality problems and increasing
repeatability, while keeping customers satisfied. Finally, the
workforce SPTs—motivation and specialization—should have a far
greater representation. It is in this area that the majority of the
quality-oriented SPTs that are related to delivery and flexibility
appear.

In summary, respondent firms afforded relatively weak
support to quality strategic initiatives. When compared to the nature
of support provided delivery and flexibility, the SPTs supporting
quality performance are too few, too focused on detection, and not

oriented enough toward employee involvement.

RETURN ON ASSETS (ROA) AND RELATED INDIVIDUAL
MANUFACTURING STRATEGIES, PROGRAMS, AND
TECHNIQUES

This section begins the analyses of the fourth hypothesis, which
investigates the relationship between firm performance and the use
of manufacturing SPTs.

Investigating the relationship between the use of
manufacturing strategies, programs, and techniques and overall firm
performance provides information regarding the strategies that the
highest overall performing firms feel are important. This will add to
the body of knowledge being created regarding manufacturing
strategies.

Overall firm performance was measured using the ROA before

tax relative to historic performance (internal assessment). The

158
following hypothesis was tested in this analysis:

Hypothesis 4: There is a positive relationship
between subjective overall firm performance and
the use of manufacturing strategies, programs,
and techniques.

Table 4.10 presents results from a series of simple regression
analyses, in which pretax ROA (internal assessment) was the
dependent variable, and the manufacturing SPTs were the
independent variables.

The highest performing firms used dedicated and proprietary
equipment, combined with workers who performed narrow,
specialized tasks to obtain advantages. Quality tools such as control
charts were used by high performers to maintain quality levels and
take full advantage of economies of scale. High performers
motivated the employees in narrow jobs through gainsharing
programs.

The manufacturing SPTs related to overall performance are
fewer in number than in the previous analyses. This may be due, in
part, to the small sample and that the performance scores were on a
seven point Likert scale, which does not have the variability of the
combined measures (production competence, and competitive

priority competence and performance).

159
Table 4.10: Individual SPTs Related to ROA (Internal Assessment)

 

 

 

 

 

 

 

 

 

 

Manufacturing Strategies, Beta Ip-value t-stat

Programs, and Techniques
1 Use of Control Charts .470 .014 2.379
2 Proprietary Technology .408 .029 1.999
3 Use of the Seven Basic Quality Tools .382 .039 1.849
4 Worker Motivation .379 .049 1.833
5 Worker Specialization .338 .062 1.608
6 Gainsharing .303 .085 1.424
7 Dedicated Equipment .296 .091 1.383

 

 

 

 

 

MANUFACTURING STRATEGIES, PROGRAMS, AND
TECHNIQUES GROUPED BY COMPETITIVE PRIORITY/JIT

Previously, the relationship between individual manufacturing SPTs
and production competence, competitive priority competence,
competitive priority performance, and overall firm performance was
discussed. This section begins analyses between the competence and
performance constructs, and SPTs arranged into logical groups.
Specifically, the groups are arranged according to competitive
priority (cost, delivery, flexibility, and quality). Additionally, due to
rapidly growing importance, manufacturing SPTs related to just-in-
time have also been grouped together to test their association with

competence and performance.

Quality-Related Manufacturing SPTs

Table 4.11 lists the arrangement of individual manufacturing SPTs
into groups according to the criteria and items of the Malcolm
Baldrige National Quality Award. The left column indicates the
variable name for each criteria and item (in parentheses). The

variable names are used in all of the subsequent tables presenting

160
results. The criteria are listed in bold and the items are in regular

type. The right column lists the associated manufacturing SPTs
determined through a literature search. The scores for the items
(e.g., employee involvement) are equal to the sum of the extent of
use scores of the individual SPTs associated with the item. The
scores for the criteria are equal to the sum of the associated item-
level scores.

Hypotheses 5a through 5n are constructed to investigate the
existence of relationships between the use of SPTs associated with
Baldrige criteria, and competence and performance. The first
analysis is directed at the relationship between the Baldrige criteria

and competence. The hypotheses are listed below:

Hypotheses Sa-Se: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with Baldrige um and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, and (e)
quality competence.

Hypotheses Sf-Sj: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with Baldrige m and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, and (j)
quality performance.

Hypotheses Sk-Sn: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with Baldrige mm and (k) pretax

ROA-external assessment, (1) pretax ROA-internal
assessment, (11) aftertax ROA-external assessment,
(0) aftertax ROA-internal assessment.

Table 4.12 displays the results of the multiple regression

161
analyses used to test the hypotheses concerning the Baldrige criteria.

Table 4.12 only displays results of models with significant results
(significant F-test). The stepwise regression technique was used.
Each cell in the table (defined by bold borders) represents one test.
For example, the first cell represents the model with production
competence as the dependent variable and the three Baldrige Criteria
as the independent variables (see Hypothesis 5a).

Contrary to claims of Baldrige and quality management
proponents, the results do not indicate any relationship between
production competence and the Baldrige criteria (and associated
SPTs). This result indicates that firms that provide manufacturing
support to their strategic objectives are doing so without focusing on
quality initiatives relating to Baldrige criteria—either information-,
human resource-, or process—oriented.

Table 4.12 indicates some support for the for the sand cone
model presented by Ferdows and De Meyer (1990). The model
suggests that quality programs must be in place before capability in
other areas can be achieved. These results indicate that SPTs related
to quality processes and human resources contribute positively to
the support of cost and flexibility initiatives. The QPROCESS criterion
is comprised of several traditional quality improvement tools,
including maintenance, the seven basic improvement tools, failsafing,
vendor issues, and design issues (see Table 4.11). These SPTs
provide operable, reliable equipment upon which well-designed
products can be produced. Results linking quality tools with cost

reduction substantiates the claim that these items are

162

Table 4.11: Baldrige Criteria/Items & Manufacturing SPTs

 

Baldrige criteria (BOLD) & items

Related manufacturing SPTs

 

Information & analysis (QINFO)

HR devt. and mgt. (HRDM)
Employee involvement (HREI)

Employee education and training (HRET)

HR management HRM

Emp. perform. & recognition (HRPR)

Employee well being/morale (HRWB)

Process quality (QPROCESS)
Product production
and deliv. processes (PQP)

Quality assessment (PQA)

Process mgt.—business processes (PQB)

Design and intro. of quality prod. (PQD)

Supplier quality (PQS)

 

 

Avail. of cost of qual. data to managers

Avail. of quality related data to workers
Timely feedback of quality data

Avail. of qual. related data to managers
Benchmarking

Employee suggestions
Self-directed work teams
Employees responsible for quality
Employee involvement

Training for executives and managers
Training for workers

Product teams

Vertical job enlargement
Worker motivation
Cross-training workers
Quality circles

Visible performance charts
Cross-functional teams

Employee recognition
Goalsetting
Gainsharin g

Quality of work life initiatives
Worker safety

Failsafing or foolproofing

Total productive maintenance (tpm)
Preventive maintenance

Emphasis on “right the first time”
Mean and range control charts

Use of 7 basic qual. Improvement tools

Product reliability testing
Measuring product reliability
Quality audit

Functional integration

Coord. Among depts. In product design
Quality function deployment (qfd)
Concurrent engineering

Involve suppliers in product design
Design for manufacturability

Supplier certification
Supplier selection based on quality
Training provided to suppliers

 

 

163
Table 4.12: Competence/Performance Variables & Baldrige Criteria

Depend. Production Cost Delivery Flexibility Quality
Variable om . m . m . C . m .
Inde . Beta Beta Beta Beta Beta
Info
Hrdm -.37 .08 .285 .090
Process .474 .03
R .229 .081

Production Cost Delivery Flexibility Quality
Perform. Perform. Perform. Perform. Perform.

Beta Beta Beta Beta Beta

Inf
Hrdm .44 .02
Process .41 .03
R .168 .200
Pretax ROA Pretax ROA Aftertax Aftertax
External In er al ROA-Ext. ROA-Int.
Beta Beta Beta Beta

 

complementary, not contradictory. Although it was not
hypothesized, the human resource criteria was negatively related to
cost competence, perhaps indicating that sample firms felt that more
rigid, mechanistic structures were more conducive to low costs that
structures that promote teams.

The criterion concerning human issues (QHRDM) contains SPTs
related to increasing the level of authority given to workers, team-
centered approaches, training, and rewards. A happy, well-trained
workforce with the authority to make process changes is able to
provide excellent support to flexibility initiatives. The Baldrige
criteria were not related to delivery or, more surprisingly, quality

competence.

164
The competitive priority performance constructs are slightly

similar to the competence constructs, except that they do not account
for the importance of a competitive dimension to a firm’s strategy or
manufacturing’s contribution. They are simply the sum of the
performance scores of the individual included in the construct. The
performance scores can indicate relationships between SPTs and
particular competitive dimensions that may be obscured by strategic
direction.

Regarding the performance models, Table 4.12 indicates that
the QPROCESS criterion is positively related to production
performance, negatively related to flexibility performance, and that
the QHRDM criterion is positively related to flexibility. These results
differ slightly from the competence results. First, sample firms that
scored highest across the 31 competitive priorities employed the
SPTs associated with QPROCESS. This indicates that there may be a
relationship between the use of quality-related SPTs and general
strategies. The competence construct did not support this. The
second difference is that a relationship to cost performance is not
supported, perhaps indicating that quality programs may not be
related to lower costs.

The SPTs associated with the Baldrige criteria were not related
to overall firm performance (as measured by ROA). Again, this result
may be attributed to low variance within the performance measures,
rather than the absence of true relationships.

It was observed in Chapter 3 that, due to aggregation, the
variables representing the Baldrige criteria may obscure

relationships between the quality-related SPTs and

165
competence/performance. It was suggested that simple regression

analysis using the Baldrige items may reveal additional information.

The hypotheses investigating this approach are below.

Hypotheses 5p-5t: There is a positive relationship
between the extent of use manufacturing SPTs
associated with Baldrige i_t_e_ms_, and (p)

production competence, (q) cost competence, (r)
delivery competence, (s) flexibility competence,
or (t) quality competence.

Hypotheses Su-Sy: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with Baldrige
111m; and (u) production performance, (v) cost
performance, (w) delivery performance, (x)
flexibility performance, or (y) quality
performance.

Hypotheses Sz-Sac: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with Baldrige
111m and (z) pretax ROA-external assessment,
(aa) pretax ROA-internal assessment, (ab)
aftertax ROA-external assessment, (ac) aftertax
ROA-internal assessment.

Table 4.13 presents the results of the simple regression
conducted to test the above hypotheses (analyses of— the relationship
between the SPTs associated with Baldrige items, and
competence/performance). The Baldrige items range from employee
issues to design to process issues (see Table 4.11). The section of the
table concerning competence reveals that, similar to the Baldrige
criteria, there are no significant relationships between the Baldrige
items and production competence. This result contradicts much of

the current thinking regarding the necessity to improve the overall

166
quality of products and processes. This result may be due to the fact

that sample firms have not yet realized the importance of the quality
issue.

The discussion regarding Baldrige criteria indicate that the
QPROCESS criterion was related to cost competence. Of the five
Baldrige items associated with the criterion, only items relating to
process quality (PQP) issues and vendor issues (PQS) are related to
cost competence. The SPTs included in the process quality item are
traditional items such as maintenance and basic quality
improvement tools. This result also supports the writings of many
authors claiming that quality improvement and lower costs are not to
be traded off against each other, but, instead are complementary.
Vendor issues are also quality-related in that they strive to reduce
the variability of incoming parts from suppliers. This is
accomplished by eliminating marginal suppliers and granting the
selected suppliers increased volumes and training. This move to a
partnership model can reduce costs, as these results indicate (Ellram,
1991). The analysis does not indicate support for the claim that
improving the design process or quality assessment are positively
associated with cost competence.

Delivery competence is associated with the Baldrige items of
employee involvement (HREI) and employee well-being and morale
(HRWB). Involvement includes SPTs concerning placing decision-
making authority with the workforce through self-directed teams or
allowing worker direct accountability for their own output. These

changes may provide a feeling of product ownership to the

167

Table 4.13: Competence/Performance Variables & Baldrige Items

Production
Com .

Beta

Depend.
Variable
Inde .
HREI
HRET
HRM
HPR
HRWB

Production
Perfo
Beta
.358
.568
.299

.031
.002
.083
.360 .046

.001

Pretax ROA
Ex ernal
Bet

Beta

Cost
Com .

Delivery
Com .

Beta

.309 .075

.498 .008

Cost
erform.

Beta

Delivery
Perform.
Beta

.309 .076

.287 .093

Pretax ROA Aftertax
Int rna ROA-Ext.

e a Beta

Flexibility
Com .
Beta

Quality
Com .

Beta

.442 .018

.385 .035

.322 .067

.333 .060
Quality
Perform.

Beta

.096
.007
.063

Flexibility

Perform.
Beta
.282
.508
.328 .294
.31 .071

.52

Aftertax
ROA-In
Beta

 

NOTE: see Table 4.11 for Variable Definitions & Associated SPTs

168
employees, who may then work to ensure that delivery dates are

met. Alternatively, placing authority lower in an organization can
speed up decision making cycles by eliminating the need for
management approval. Perhaps the other items related to the
criterion HRDM obscured the association between delivery and the
employee involvement and morale issues.

Flexibility competence can be achieved by implementing
employee education and training programs (HRET), keeping a safe
workplace (HRWB), and periodically ensuring quality through testing
(PQA). These quality items can assist firms by training both
employees and management to improve processes. Improved levels
of safety can serve to motivate workers to learn new skills.

The only Baldrige item related to quality competence was
vendor related (PQS). This relationship indicates the critical nature
of the supply base and its impact on the quality system of a
company. The quality of incoming parts is a critical input to the
quality of a firm’s end product.

Production performance is a very broad measure of
performance, equal to the sum of the performance scores of the
priorities listed in Table 2.1. The Baldrige items that are associated
with production performance, except for the assessment item,
primarily concern employee-related issues. The use of SPTs related
to employee involvement (HREI), training (HRET), team approaches
(HRM), and safety concerns (HRWB) appear to be implemented by
firms who feel they perform well across the 31 dimensions. This is
an important result as human issues are often the most difficult for

firms to overcome when implementing quality improvement

169
programs, and can frequently derail improvement efforts (Walton,

1986). These results indicate that firms must work extremely hard
at successfully increasing employee responsibilities.

The same Baldrige items are also related to flexibility
performance. It is apparent that firms competing on this dimension
must place a substantial investment in its employees.

The Baldrige items related to quality performance are the
team-oriented approaches (HRM), improved designs (PQD), and
periodic testing (PQA). The SPTs associated with design concern
cross-functional efforts directed at reducing downstream problems
by including several functions, including suppliers, into the design
process.

Finally, the only association between the Baldrige items and
ROA occurred in the items related to team building (HRM),
motivation and an expanded role for employees. Also, the use of
traditional quality tools (PQP) is related to improved returns. Again,
these two items—people issues and the use of traditional
improvement tools—are not radical ideas, but, instead are the

building blocks of quality improvement (Brocka and Brocka, 1992).

Delivery-Related Manufacturing SPTs

In a recent article (The Economist, 1994), it was noted that as quality
becomes an order qualifier, or a requirement to do business in a
particular market, companies are winning orders or gaining
competitive advantage by reducing the time it takes to deliver
products. This section presents results of multiple regression

analyses conducted to test a series of hypotheses relating to the

170
contribution of delivery-related SPTs to competence and

performance. The hypotheses are listed below.

Hypotheses 6a-6e: There is a positive relationship
between the use of manufacturing SPTs

associated with M11111! and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, or (e)
quality competence.

Hypotheses 6f-6j: There is a positive relationship
between the use of manufacturing SPTs
associated with 111113.911! and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, or (j)
quality performance.

Hypotheses 6k-6n: There is a positive

relationship between the use of manufacturing
SPTs associated with 11.21.11.111 and (k) pretax
ROA-external assessment, (1) pretax ROA-internal
assessment, (m) aftertax ROA-external
assessment, (n) aftertax ROA-internal assessment.

Table 4.14 displays the manufacturing SPTs that comprise the
delivery variables (DelProcs and DelInfra). Table 4.15 displays the
results of the regressions. Stepwise regression was used and only
the results of significant models (determined through an F-test)
appear. As in previous analyses, an alpha level of .10 was used.

The results of the tests indicate that, of the first set of
hypotheses, only 6c and 6e are rejected. The data indicate a
relationship between the two delivery variables and production, cost,
and flexibility competence. The DelProcs variable was positively
related to both production and flexibility competence.

The process-oriented SPTs include items directed at improving

171

Table 4.14: Delivery Variables and Related Manufacturing SPTs

1291mm

Depart. coordination in design
Cross-functional teams
Cross-training workers
Design for manufacturability
Reliance on fewer suppliers
Supplier certification
Supplier selection - quality
Workplace orderliness

W

Dedicated equipment

Group technology
Just-in-time

Preventive maintenance
Reducing setup times
Reduction in throughput times
Simplified material flow

Table 4.15: Competence/Performance & Delivery Variables

Production Cost
Com .

Be

. 2

-.32

.213

Depend.
Variable

Inde .

elProcs
DelInfra

R

Be

.07 .2

.082
Production Cost
Perform. Perform.
e B ta

DelProcs . 5 .0

Dell fra

R .129

Pretax ROA Pretax ROA Aftertax

Extern 1 Int rn l

lProcs
D lInfr

R2

Note: Betas are standardized.

.09

Delivery
Com .

Be

Flexibility
Com .
B ta

.61 . 1
-.432 .02
.379 .01
Flexibility
Perform.
Beta

.650

-.459 .02
.423 .004

Aftertax
ROA-Int.
B .

Quality

Delivery
Perform.

Beta

Quality
Perform.

B t

ROA-Ext.
B a

 

172
material flow, either through layout design or operating policies (see

Table 4.15). The association of these SPTs with production
competence indicates that they may represent a core set of SPTs
firms should implement, regardless of strategic direction. It does
seem that simplifying flows and reducing set-up times can be
beneficial to all firms.

Flexibility competence is defined as the measure of support
provided to flexibility-directed competitive thrusts. These include
product, volume, and process flexibility, offering a broad product
line, quick product development of products, and being responsive to
target markets see Table 3.3). By reducing setup times and
improving throughput times, firms can be more responsive to
customers and handle a wider variety of products—critical benefits to
a firm competing on flexibility. Ensuring that equipment is operable
increases processing alternatives for firms.

The relationship between the infrastructural elements of
delivery and cost competence is interesting. It indicates that
eliminating waste in systems, improving the design process,
implementing a vendor management program, and keeping the
facility clean can contribute to cost reduction initiatives. Many of
these SPTs are related to elements of just-in-time which has been
linked to lowering costs (Schonberger, 1986).

Table 4.14 also indicates that the delivery variables are related
to production performance and flexibility performance. The
hypotheses regarding relationships between performance in the
priorities of cost, delivery, and quality, and the delivery variables

were not supported. Again, the variable DelProcs was positively

173

Table 4.16: Flexibility Variables and Manufacturing SPTs

W

Coordination in product design
Cross functional teams

Cross training workers
Employee involvement
Supplier certification

"IQC

Use of 7 basic quality tools
Workplace orderliness

W
Advanced mfg. technology

CIM

FMS

General purpose equipment
Group technology
Just-in-Time

Maintain excess capacity
Product focused factory
Reduce setup times

Reduction in throughput times
Simplified material flow

Table 4.17: Competence/Performance and Flexibility Variables

Depend. Production Cost
Variabl . m .

1nd
1 x

R

Production Cost
f

.138

Pretax ROA Pretax ROA

Bet B

Note: Betas are standardized)

Delivery
Com . Com . Co

Beta B Beta

Delivery

Aftertax

Flexibility Quality

.209

Flexibility
f Perf r

Bt Be

4

.173
Aftertax

Beta Beta

 

174
related to both production and flexibility—this time with
performance.
The hypotheses claiming a relationship to ROA measures were

not supported. As stated several times, this may be more due to the

ROA measure than the affects of the delivery variables.

Flexibility-Related Manufacturing SPTs

Flexibility is a complicated construct that has many meanings
(Gerwin, 1993). The new flexibility variables created by grouping
related SPTs are called FlexProc (process-related) and FlexInfr
(infrastructural) (see Table 4.16). The SPTs associated with FlexInfr
concern management, design, and quality issues, while FlexProc
concerns layout and technology issues. The hypotheses related to the

flexibility variables and SPTs are listed below.

Hypotheses 7a-7e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with flexibility and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, or (e)
quality competence.

Hypotheses 7f-7j: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with flexibility and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, or (j)
quality performance.

Hypotheses 7k-7n: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with flexibility
and (k) pretax ROA-external assessment, (1)
pretax ROA-internal assessment, (m) aftertax

175

ROA-external assessment, (11) aftertax ROA-
internal assessment.

Table 4.17 indicates that the only competence construct related
to a flexibility variable is flexibility competence. The remaining
hypotheses in the first set were not supported. The significant model
explains about 21% of the variance in the flexibility competence
construct, all of that from the process-oriented variable. The
combination of technology and efficient material flow provides a
powerful capability for firms. The SPTs, identified through a
literature search, are shown to be supportive of a flexibility strategy,
just as the authors of the studies suggested they would be.

The table also reveals that the flexibility variables are related
to production performance and flexibility performance, just as the
case with the delivery variables. The DelProcs and FlexProc
variables share a couple of SPTs and are highly correlated (r=.88), so
it is not surprising that they are related to the same constructs.
Again, just as with the delivery variables, there is no relationship

between the two flexibility variables and the ROA variables.

Cost-Related Manufacturing SPTs

In the sand cone model presented by Ferdows and De Meyer (1990),
cost capability is the last to be acquired by firms. This indicates that
cost reduction is a difficult endeavor, requiring abilities in several
areas. Table 4.18 lists the cost variables and'associated
manufacturing SPTs indicated by the literature to be effective tools
to reduce costs. These new variables (CostQual, CostDes, and CostEff)

contain elements related to quality, design, and economies of scale.

176
Given this broad scope of capabilities represented, the cost variables

may have implications for competence and performance along other
competitive dimensions. The hypotheses below express this

potential.

Hypotheses 8a-8e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with met and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, and (e)
quality competence.

Hypotheses 8f-8j: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with e_o_5_t_ and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, and (j)
quality performance.

Hypotheses 8k-8n: There is a positive

relationship between the extent of use of
manufacturing SPTs associated with em; and (k)
pretax ROA-external assessment, (1) pretax ROA-
internal assessment, (m) aftertax ROA-external
assessment, (n) aftertax ROA-internal assessment.

Table 4.19 displays results of the stepwise regression analyses
used to test the hypotheses related to the cost variables. Regarding
competence, the results support the hypotheses stating a relationship
between cost variables, and production, cost, and flexibility
competence. The other competence hypotheses were not supported.
CostEff, which is comprised of traditional economies of scale SPTs
(see Table 4.18), is the only variable related to production and cost
competence.

The SPTs associated with CostEff include automation, buying

Table 4.18: Cost Variables and Related Manufacturing SPTs

CostQuaLSEL‘s
Failsafing Or Foolproofing

Total Quality Control (TQC)

Seven Quality Improvement Tools

Zero Defects

W

Design For Manufacturability
Product Simplification
Product Standardization
Value Analysis

Variety Reduction

QQSIEELEEIS

Automation

Backward Integration
Dedicated Equipment
Forward Integration

Large Batch Production
Proprietary Technology
Purchase In Large Quantities
Reducing Size of Work Force
Work Measurement
Worker Safety

Worker Specialization
Simplified material flow

Table 4.19: Competence/Performance and Cost Variables

Depend.
Variable Com .

Inde . Beta Beta
osteff . 29 . . 8
os ual

R .109 .147

Production Cost
Perform. Perfor

Beta B ta
. 24 01

.275

Pretax ROA Pretax ROA Aftertax
Intern l

Extern l
t B

C ste f
os al
Cos

R2

Note: Betas are standardized.

Production Cost

Delivery Flexibility Quality

C m . m . m .
Beta Beta Beta

.4

.208

Flexibility Quality
Perform.

Delivery
Perform.

.06

392
.120 .154

Aftertax

R -Ext. R A-Int.

Beta Be

 

Perform.
B ta Beta Beta

178
and producing in large quantities to achieve economies, and a

specialized workforce utilizing dedicated equipment. These SPTs are
most effective in situation requiring a line process, which would
include standardized products in the latter stages of their life cycle
(Hill, 1994). Many furniture products could be classified as mature,
standard products, and furniture manufacturers have been able to
achieve economies of scale in their facilities. For firms in the sample,
traditional cost-related SPTs are implemented by firms providing the
best support to cost objectives.

The variable related to flexibility competence—CostDes—is
comprised of SPTs concerned with design issues. These SPTs seek to
simplify and standardize products, thereby increasing repeatability
and allowing for larger order quantities. They also contribute to the
design of products that are easier to manufacture, further reducing
costs. The relationship between a cost variable to a flexibility
construct may, at first, seem contradictory. However, firms that
compete on flexibility do not solely rely on wide variety. Other
dimensions are more concerned with responsiveness. Designing
products that can be made quickly and without error are very much
complementary to flexibility agendas.

The CostDes variable is also related to quality performance. It
is, in fact, the only variable that is significantly related to either
quality conformance or performance. The relationship of CostDes to
both flexibility and quality is an important result. This indicates the
critical nature of design issues and also supports the interrelatedness
intimated by the sand cone model (Ferdows and De Meyer, 1990).

Recent studies indicate that upwards of 80% of a product’s cost is

179
determined at the design stage (Giffi, Roth, and Seal, 1990). As long

as the design in linked to customer demands, applying the SPTs
contained within the CostDes variable can help in firms in several
areas.

CostEff is also positively related to production competence and
performance. This perhaps reflects the notion that, while many
furniture products are in the mature stage of the product life cycle,
the technology-oriented SPTs associated with CostEff may be
contributing to performance within other competitive dimensions

included in the production constructs.

JIT-Related Manufacturing SPTs

The just-in-time (JIT) variables were included because of the
growing base of literature that suggests JIT-type systems can greatly
improve performance (Schonberger, 1982; Finch, 1986; Gunn, 1992).
The SPTs found to be associated with the JIT variables (JitProcs and
JitInfra) are listed in Table 4.20. The potential benefits of JIT
implementation include lower costs, improved quality, timely
production, and better competitive performance (Heiko, 1991;
Walleigh, 1986; Schonberger, 1986). The tested hypotheses related

to these benefits are below:

Hypotheses 9a-9e: There is a positive relationship
between the extent of use of manufacturing SPTs
associated with .11]: and (a) production
competence, (b) cost competence, (c) delivery
competence, (d) flexibility competence, and (e)
quality competence.

Hypotheses 9f-9j: There is a positive relationship

180

between the extent of use of manufacturing SPTs
associated with LL]: and (f) production
performance, (g) cost performance, (h) delivery
performance, (i) flexibility performance, and (j)
quality performance.

Hypotheses 9k-9n: There is a positive
relationship between the extent of use of
manufacturing SPTs associated with m and (k)
pretax ROA-external assessment, (1) pretax ROA-
internal assessment, (m) aftertax ROA-external
assessment, (n) aftertax ROA-internal assessment.

Table 4.21 displays the significant results of the series of
(stepwise) multiple regressions conducted to test the above
hypotheses. The JIT models are significantly related to production,
delivery, and flexibility competence. In each model, only the JitProcs
variable is significant.

The SPTs associated with JitProcs are very similar to those
associated with DelProcs (r=.92). The SPTs include maintenance,
reducing setup times, and workflow issues (see Table 4.20). Relative
to DelProcs, this set of SPTs is also related to production and
flexibility competence. However, the JitProcs variable is also related
to delivery competence, while the DelProcs variable is related to
flexibility competence. These results further indicate the wide
variety of capabilities generated by these SPTs.

JIT is concerned with eliminating waste and improving
material flow (Ohno, 1984). The results indicate that the use of these
SPTs can support strategic objectives related to delivery and
flexibility.

The performance section reveals that the infrastructural

181

Table 4.20: JIT Variables and Related Manufacturing SPTs

111mm

Product Simplification
Reduction in WIP Inventory
Supplier Certification
Cross-Training Workers
Employee Involvement
Training for Workers

W

Group Technology
Just-in-Time

Preventive Maintenance
Total Productive Maintenance
Workplace Orderliness
Simplified Material Flow
Reducing Setup Times

Table 4.21: Competence / Performance and JIT Variables

Cost

Production

Depend.
Variable

Inde .
itProcs
I r
R .184
Production
P f
Beta

Beta Beta

429 .02

Cost

Beta

.451
.203

Pe form

Beta
. 57

.123

Delivery
P .

Beta

Pretax ROA Pretax ROA

Extern 1
Bet
.416 .04

R2 .347

Beta

.027

Note: Betas are standardized.

In ern 1

Delivery

Aftertax
ROA-Ext.
Beta

Flexibility Quality
m Co m
Beta Beta
.484 .01

.234

Flexibility
Perform.
Bet

Quality
Perform.

Beta

.272

Aftertax
ROA-Int.
Beta

.415 .04

.351 .03

 

182
variable—JitInfra—is related to production performance. The JitInfra

variable is associated with SPTs concerning product design,
workforce issues, and materials management issues. This result is
interesting in that it indicates that issues beyond material flow and
the process are important. Preparing the people and products to
work in a JIT system also contributes to performance.

JitProcs, already related to flexibility competence, likewise is
related to flexibility performance. This result increases the
confidence in statements linking the use of JIT-related SPTs to
supporting flexibility initiatives.

Finally, the JIT variables are related to the overall financial
performance measures—pretax return on assets (ROA). JitProcs is
positively related to financial performance. This, coupled with the
relationship between JitProcs and production
competence/performance, can be interpreted as providing further

support for claiming that these SPTs form a core set of strategies.

V . IMPLICATIONS

This chapter will review results of the previous chapter as they
relate to the hypotheses presented in Chapter 3, highlight the
contributions of the research, indicate the limitations of the research
project, and finally, mention several extensions of the project.

Before reviewing the hypotheses, it should be noted that this
study is an extension of the production competence work initiated by
Cleveland, et a1. (1989), which was extended by Vickery, et al.,
(1993). In the latter study, the production competence construct was
expanded and the measurement of the production competence score
was improved. In Vickery, et a1. (1993), a significant relationship
between production competence was identified.

This study extends that research by expanding the process
model of manufacturing strategy presented by Vickery (1991) (see
Figure 5.1). In this model, competence is a measure of the support
(i.e., manufacturing performance) provided business strategic
objectives. The extension of this study is the identification of the
strategies, programs and techniques implemented to support the
manufacturing competitive priorities. Previous research in the
competence area emphasized the existence of the construct and its
relationship to firm performance.

This study utilized a subset of the sample in Vickery, et al.
(1993). Results presented in Table 4.10 indicate that, within the
subset, a positive relationship between production competence and
firm performance was again identified. Given the existence of the

relationship, the discussion of the hypotheses follows. In all

183

184

Business Strategy
(e.g., Differentiation, Cost)

 

 

 

1

Identification & Weighting
of Mfg. Competitive Priorities
(e.g., quality, cost, flexibility)

l

Strategic Manufacturing
Decisionmaking
(e.g., Facilities, Technology)

 

 

 

 

 

 

 

Implementation
(e.g., Manufacturing
Projects, Programs)

i

Manufacturing
Performance Measurement
(Mfg. Strengths, Weaknesses)

 

 

E
§
5
i
a

 

 

 

 

 

 

 

l

L Business Performance

 

Source: Adapted from Vickery (1991)

 

Figure 5.1: A Process Model of Production Competence

185
hypotheses, significance was determined using a t-test with an

alpha-level of .10.

Review Of Hypotheses
This section will review the hypotheses presented in Chapter 3 and

the associated results appearing in Chapter 4.

Production Competence

The first hypothesis is directed at the identification of the
manufacturing strategies, programs, and techniques (SPTs) related to
production competence. These SPTs are the strategic content
(outcomes) of the decision making process as shown in Figure 5.1.

Hypothesis 1 is restated below:

Hypothesis 1: There is a positive relationship between
the extent of use of individual manufacturing
strategies, programs and techniques, and production
competence.

Table 5.1 presents the SPTs that are significantly related to
production competence. These SPTs can be further classified into
Hayes and Wheelwright’s (1984) categories of structural and
infrastructural factors. The structural SPTs that relate to production
competence are most concerned with the flow of product through a
facility. It does not seem to matter if a facility employs a product- '
focus or a process-focus. What does matter is that firms understand
the critical nature of the process positioning decision (Hill, 1994;

Krajewski and Ritzman, 1993).

186
Table 5.1: Structural/Infrastructural SPTs & Production Competence

 

 

 

 

 

 

Structural SPTs Infrastructural SPTs
Proprietary Technology Worker Specialization
Product-Focused Factory Workplace Orderliness
Synchronous Manufacturing Worker Motivation
Process-Focused Factory Employee Involvement
Flexible Manufacturing Vertical Job Enlargement
System

 

Worker Safety

Training For Workers

Product Standardization
Reduce Number Of Engineering
Change Orders

Supplier Selection Based On
Price

 

 

 

 

 

 

 

Total Productive Maintenance

 

The infrastructural SPTs related to production competence are
dominated by those that directly relate to the workforce. The theme
of the SPTs in Table 5.1 is one of pushing responsibility and
authority down in a firm’s hierarchy, while providing the training
and knowledge necessary to accomplish new tasks. A different set of
SPTs supports the structural SPTs by focusing on a clean, orderly
shop and keeping machinery in working order.

To summarize, production competence measures the support a
manufacturing function provides to business strategy objectives,
regardless of their strategic direction. Given this general guideline,
manufacturing support requires that firms have adequate
communication structures so functional managers and executives can

align resources with strategic objectives. In manufacturing, the

 

187

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188
important decision of process positioning is critical to providing that

support. Having a knowledgeable, motivated, and involved
workforce within this process is also critical. This can be
accomplished by pushing responsibility downward in an

organization.

Competitive Priority Competence and Individual SPTs
The competitive priority competence constructs are created similarly
to the production competence construct. They refine the production
competence construct by focusing on particular competitive
dimensions. Thus, their use can reveal information about
manufacturing strategies pertaining to specific competitive
initiatives. The constructs are comprised of several individual
competitive priorities (see Tables 2.1 and 3.3). The assignment of
individual priorities to either the cost, delivery, flexibility, or quality
construct is based on relevant literature in manufacturing strategy
and the proportion of responsibility assigned to manufacturing for
each individual priority by respondent firms.

The process model developed by Vickery (1991), which
contains the production competence construct, has been expanded to
include the competitive priority competence constructs. Figure 5.2 is
a process model incorporating the four priorities and serves as a
guide for discussion in this section. The relationship between
indiyigiuel manufacturing SPTs and each of the four competence
constructs will be discussed. The nest four sections contain analyses

related to the following set of hypotheses:

189

Hypothesis 2a-2d: There is a positive
relationship between (a) cost competence, (b)
delivery competence, (c) flexibility competence,
and ((1) quality competence, and the use of
individual manufacturing strategies, programs
and techniques.

Cost Competence

The cost-related constructs are comprised of the individual
competitive priorities of low production cost, competitive pricing, and
low price (see Table 3.3).

Table 5.2 presents the manufacturing SPTs positively related to
cost competence. They, too, are categorized according to Hayes and
Wheelwright’s (1984) structural and infrastructural factors. This
determination is merely subjective and was not performed using
statistical grouping procedures.

The structural SPTs in Table 5.2 include both forward and
backward integration, which are classic cost-reduction strategies.
Porter (1980) and Harrigan (1985) observe several strategic benefits
of vertical integration, including economies of integration (combined
operations, control and coordination, information, and stable
relationships), a tap into technology, assurance of supply and/or
demand, offset bargaining power of suppliers, an enhanced ability to
differentiate, and higher barriers to entry. Forward integration
allows better access to market information and distribution channels,
and an improved ability to differentiate products. The technology
SPTs may have come to the respondent firms from value chain
members either fully or partially owned. These technology SPTs are

also indicative of firms with advanced manufacturing knowledge.

190
Table 5.2: Structural/Infrastructural SPTs & Cost Competence

 

 

 

 

 

Structural SPTs Infrastructural SPTs

Backward Integration Failsafing Or Foolproofing
Computer Integrated Mfg. Preventive Maintenance
Advanced Manufacturing Emphasis On "Doing-It—Right-The-
Technology First~Time"

Forward Integration Benchmarking

 

Timely Feedback Of Quality Data

 

100 % Inspection

 

Purchase In Large Quantities

 

Training Provided To Suppliers

 

Reliance On Fewer Suppliers

 

Supplier Certification

 

Supplier Select. Based on Quality

 

Large Batch Production

 

Departmental Coordination In
Product Design

 

 

 

 

The infrastructural SPTs are roughly organized into areas of
quality, purchasing, planning and control, and design. The planning
and purchasing SPTs focus on economies of scale by buying and
producing in large quantities. Firms are also reducing their base of
suppliers and rewarding those that become certified with larger
volumes. The quality-oriented SPTs combine both detection and
prevention techniques, with a heavier emphasis on prevention.
Based on earlier visits to furniture companies, complete inspection
seems to be an old standard in the industry, potentially indicating a
lack of maturity. .

Furniture firms use a combination of vertical integration,
economies of scale, and new to the industry quality prevention

techniques to support cost reducing initiatives.

191
Delivery Competence

The individual competitive priorities that comprise the delivery
competence construct are delivery speed, delivery dependability,
and production lead time (see Table 3.3). Table 5.3 presents the
manufacturing SPTs positively related to delivery competence. They
are categorized according to Hayes and Wheelwright’s (1984)
structural and infrastructural factors. This determination is merely
subjective and was not performed using statistical grouping
procedures.

The structural SPTs are similar those related to production
competence. They are a combination of efficiency- and flexibility-
oriented strategies, which are critical skills in supporting the speed
and dependability requirements of the construct. Again, the process
positioning decision appears to be important, not for its outcome, but
because of its importance in shaping other strategic decisions (Hill,
1994). The flexibility and speed components provide an element of
responsiveness to the firms, further aiding in delivery support.

The infrastructural SPTs in Table 5.3 are roughly organized into
categories of workforce management and planning and control.
Involving and empowering workers provides them with the feeling
of ownership in the process that supports a delivery commitment.
Maintenance, cleanliness and reducing WIP inventories keep
factories running and efficient, which reduces waste and unnecessary
delays.

Delivery competence, the measure of a firm’s ability to support
delivery-related competitive initiatives, requires firms be efficient,

flexible, and instill authority in the workforce.

192
Table 5.3: Structural/Infrastructural SPTs & Delivery Competence

 

 

 

 

 

 

Structural SPTs Infrastructural SPTs
Product-Focused Factory Worker Safety

Flexible Manufacturing System Workplace Orderliness
Proprietary Technology Employee Involvement
Process-Focused Factory Self-Directed Work Teams
Simplified Material Flow Employees Responsible For

Output Quality

 

Total Productive Maintenance

 

Reduction In Work-In-Process
Inventory

 

 

 

Supplier Selection Based On Price

 

 

Flexibility Competence

The flexibility constructs are comprised of the following individual
competitive priorities: product flexibility, volume flexibility, process
flexibility, product development cycle time, and responsiveness to
target markets. Table 5.4 presents the manufacturing SPTs
positively related to flexibility competence. They are categorized
according to Hayes and Wheelwright’s (1984) structural and
infrastructural factors. This determination is merely subjective and
was not performed using statistical grouping procedures.

The structural SPTs related to flexibility competence range
from very flexible (general purpose equipment) to moderately
flexible (just-in-time). The individual flexibility-related competitive
priorities that form the flexibility constructs emphasize agility and
responsiveness. The structural SPTs appear to contain elements of
speed (synchronous manufacturing and JIT), efficiency (group

technology and product-focused factory), and the ability to produce a

193
Table 5.4: Structural/Infrastructural SPTs & Flexibility Competence

 

 

 

 

 

 

 

 

Structural SPTs Infrastructural SPTs
Group Technology Worker Safety
Synchronous Manufacturing Vertical Job Enlargement
Just-In-Time Workplace Orderliness
Product-Focused Factory Worker Specialization
Proprietary Technology Worker Motivation
General Purpose Equipment Training For Workers
Advanced Statistical Techniques
(Quality)

 

Acceptance Sampling

Use Of Control Charts

Zero Defects

Use Of The Seven Basic Quality
Tools

Measuring Product Reliability
Product Reliability Testing
Reduce Number Of Engineering
Change Orders
Computer-Aided Design
Product Standardization

Setup Time Reduction

Training For Executives And
Managers

Training Provided To Sypliers

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

194
wide range of products (general purpose equipment and proprietary

technology). Together, this collection of SPTs forms a powerful base
upon which flexibility strategies can be implemented.

The infrastructural SPTs firms are using to support the
structural SPTs are roughly organized in Table 5.4 into groups,
including workforce management, quality, training, and design.
Given the difficult manufacturing task associated with flexibility
competence, the large number of infrastructural SPTs is justified.
Firms following flexibility strategies must be committed to training
programs for internal and external entities. The use of quality tools
(seven tools, advanced techniques, zero defects) has a larger
representation in flexibility competence than in any other analysis.
To effectively utilize these techniques, new attitudes toward
employees and increased responsibility for workers are
characteristics of competent firms. Design SPTs are also well
represented and focus on reducing rework, design cycle times, and
changes to build schedules. This stability allows increased flexibility
through improved planning. Setup time reduction allows smaller
production lots and increased volume flexibility.

Flexibility competence is difficult to achieve and requires
heavy investment in training, process technology, and design.
Infrastructural support is broad-based and relies on worker
involvement. Companies not prepared to make the financial or
emotional investment to flexibility strategies would be best served

by competing along other dimensions.

195
Quality Competence

The quality constructs are comprised of the individual competitive
priorities of product reliability, product durability, conformance
quality, design quality, and product improvement/refinement..
Table 5.5 presents the manufacturing SPTs positively related to
flexibility competence. They are categorized according to Hayes and
Wheelwright’s (1984) structural and infrastructural factors. This
determination is merely subjective and was not performed using
statistical grouping procedures. ’

The structural SPTs related to quality competence are
somewhat surprising due to the emphasis on flexibility and low
volume technologies. Process-focused factories are low volume, job-
shop oriented facilities and flexible systems are best utilized for mid-
volume production (Hill, 1994). Synchronous manufacturing has
higher volume connotations, as does automation, but there is not the
emphasis on high volume manufacturing one would expect to
support quality initiatives.

The infrastructural SPTs associated with quality competence
are few in number. Compared to the constructs associated with
delivery and flexibility, the number of SPTs is surprisingly small.
There are far fewer worker-related SPTs in Table 5.5 than on other
analyses. Those that do appear provide support to the individual
priority of conformance quality. The supplier-oriented SPTs are also
surprising in that they appear to be associated with larger volume
production that the structural SPTs indicate. Selecting suppliers
based on their price is rarely advocated, especially when discussing

quality improvement (Walton, 1986). Standardizing designs helps to

196
Table 5.5: Structural/Infrastructural SPTs & Quality Competence

 

 

 

 

 

Structural SPTs Infrastructural SPTs
Synchronous Manufacturing Employee Involvement
Automation Worker Motivation
Flexible Manufacturing System Electronic Data Interchange
Process-Focused Factory Supplier Selection Based On

Price

 

Failsafing or Foolproofing
Preventive Maintenance
Total Productive Maintenance
Product Standardization
Quality Function Deployment

(QFD)

 

 

 

 

 

 

 

 

increase repeatability, which aids in quality improvement. Failsafing
and maintenance programs assure that machinery and process are
operable and also work toward preventing defects before they occur.
The SPTs associated with quality competence are surprising
due to their low numbers, their emphasis on low volume technology,
and the lack of employee-related SPTs. Not allowing workers
authority and responsibility for quality improvement is not the way

to quality improvement.

Competitive Priority Performance and Individual SPTs
This section will review the third set of hypotheses—those relating to
competitive priority performance and the use of individual
manufacturing SPTs. Performance is calculated by summing the
subjective performance scores for the individual competitive
priorities comprising a construct. For example, cost performance is

the sum of the performance scores of the individual competitive

197
priorities of low production cost, competitive pricing, and low price.

Tables 5.6 - 5.10 follow the same format as those in the competence
section—the related manufacturing SPTs are roughly placed into
structural and infrastructural categories.

Analysis of performance data may indicate relationships
hidden by the competence scores. The performance scores may, in
fact, reveal more direct relationships between strategic decisions and
strategic direction than previous analyses involving competence. The

hypotheses discussed in this section are:

Hypothesis 3a-3d: There is a positive
relationship between the subjective performance
component of (a) cost performance, b) delivery
performance, (c) flexibility performance, and (d)
quality performance, and the use of
manufacturing strategies, programs, and
techniques.

Cost Performance

The cost-related constructs are comprised of the individual
competitive priorities of low production cost, competitive pricing, and
low price (see Table 3.3). As stated, performance analyses may
reveal more direct results regarding the manufacturing SPTs firms
must implement to properly support strategic initiatives.

In Table 5.6, the structural SPTs are quite sparse. The benefits
of forward integration were described in the previous section. The
appearance of CIM in the table is somewhat surprising as CIM is not
often regarded as a cost reducing approach.

When compared to the other constructs, infrastructural SPTs

relating to cost performance are also sparse. Ferdows and De Meyer

198
Table 5.6: Structural/Infrastructural SPTs & Cost Performance

 

 

 

 

Structural SPTs Infrastructural SPTs
Forward Integration Advanced Forecasting
Computer-Integrated- Emphasis On “Doing-It-Right-
Manufacturing The-First-Time”

Supplier Selection Based On
Quality

 

Purchase In Large Quantities
Reduction In Finished Goods
Inventory

100% Inspection

Large Batch Production

 

 

 

 

 

 

 

(1990) observed that cost capabilities are the last to come to
companies, which must first acquire capability in quality, then
delivery, then flexibility before attaining true cost reductions. The
SPTs in Table 5.6 are generally either quality related or economies of
scale oriented. A firm’s production relies heavily on the quality of
incoming materials, and selecting quality suppliers is a critical step.
The emphasis on “doing things right” does not have the same impact
it might if employee-related SPTs were also related. The economies
of scale SPTs are classically related to lower costs and need no
further discussion. The presence of 100% inspection is curious in
that it is very expensive for firms to inspect each product. This

technique does not seem to fit cost reduction initiatives.

Delivery Performance
The individual competitive priorities that comprise the delivery

performance construct are delivery speed, delivery dependability,

199
Table 5.7: Structural/Infrastructural SPTs & Delivery Performance

 

 

 

 

 

 

 

 

Structural SPTs Infrastructural SPTs
Proprietary Technology Employees Responsible For
Output Quality
Process-Focused Factory Self-Directed Work Teams
Flexible Manufacturing System Workplace Orderliness
Product-Focused Factory Employee Involvement
Worker Safety
Reducing Size Of Workforce
Total Productive Maintenance

 

 

 

 

and production lead time (see Table 3.3).

Table 5.7 presents the structural and infrastructural SPTs
associated with delivery performance. The structural SPTs again
indicate the critical importance of understanding the nature of the
process positioning decision (Hill, 1994; Krajewski and Ritzman,
1993). Having the vision and understanding to see how the entire
facility works together aids in the movement of product throughout a
factory. The reduced time variability and quicker throughputs of the
product focus support speed and dependability. The process focus
also supports the speed dimension, while adding to the confusion
regarding “responsiveness”.

There .are fewer infrastructural SPTs related to delivery
performance than competence. There remains, however, a
commitment to employees (responsibility for quality and self-
directed teams) and a clean, well-maintained facility. Keeping the
workplace organized reduces chances of materials being misplaced or
buried.

Delivery performance requires firms to make the critical

200
decisions to properly position the facility and allow the employees to

be involved in improving the system.

Flexibility Performance

The flexibility constructs are comprised of the following individual
competitive priorities (from Table 3.3): product flexibility, volume
flexibility, process flexibility, product development cycle time, and
responsiveness to target markets.

Table 5.8 presents the manufacturing SPTs—structural and
infrastructural—that are related to flexibility performance. This
section contains the largest number of related SPTs. The structural
SPTs concern a mixture of flexible equipment and higher volume
technology. These technologies combine to form the base of
responsiveness. They maintain the flexibility to adapt to varying
product types and volumes, while also having the ability to quickly
respond orders—a speed component. This approach—dedicating
general purpose equipment to product families has been used by
Japanese firms to achieve flexibility objectives (Hill, 1994).

This arrangement appears to directed at mid-volume production,
although keeping some general purpose equipment separate could
fulfill this need.

The infrastructural SPTs are dominated by workforce
management and quality SPTs. Motivation, training, the use of teams
and involving workers is just what is needed to support the
structural SPTs. The quality-related SPTs make heavy use of process

improvement techniques, which adds to the responsiveness and

201
Table 5.8: Structural/Infrastructural SPTs & Flexibility Performance

 

 

 

 

 

 

 

Structural SPTs Infrastructural SPTs
Product-Focused Factory Worker Motivation
Synchronous Manufacturing Worker Safety
Proprietary Technology Worker Specialization
General Purpose Equipment Training For Executives And

hdanagers
Group Technology Vertical Job Enlargement
Just-In-Time Cross-Functional Teams

 

Self-Directed Work Teams
Vertical Job Enlargement
Training For Workers
Employee Involvement
Workplace Orderliness

Zero Defects

Measuring Product Reliability
Advanced Statistical Techniques
(Quality)

Use Of The Seven Basic Quality
Tools

Computer-Aided Design
Product Reliability Testing
Acceptance Sampling

Reduce Number Of Engineering
Change Orders

Product Standardization
Setup Time Reduction
Mixed-Model Production
Scheduling

Color Coding Of Machines And
Parts

Supplier Selection Based On
Price

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

202
flexibility of a system. Standardizing designs and limiting late

change orders allows the planning system the stability required to
maximize utilization and employ complex techniques such as mixed-
model scheduling. Reducing setup times through color coding
equipment adds flexibility and capacity to the system.

The ambitious collection of structural SPTs related to flexibility
performance requires an infrastructure that is trained, motivated,
and empowered to make changes. The infrastructural SPTs related
to flexibility performance allow the structural elements to be
effective. Only firms willing to push responsibility down the
organization should compete along this dimension. A commitment to
training and cross-functional communication is also necessary to

support a flexibility strategy.

Quality Performance

This is the last segment regarding competitive priority performance.
The quality competitive priorities comprising the quality
performance construct are product reliability, product durability,
conformance quality, design quality, and product
improvement/refinement (see Table 3.3).

Table 5.9 presents the structural and infrastructural
categorization of SPTs related to quality performance. The structural
SPTs in Table 5.9, when compared to those related to flexibility and
delivery, are few in number. A product-focus denoted higher
volumes and a degree of repeatability conducive to quality
improvement. The SPTs of automation and proprietary are too vague

to make declarative statements, although it can be presumed that

203 .
Table 5.9: Structural/Infrastructural SPTs & Quality Performance

 

 

 

 

Structural SPTs Infrastructural SPTs
Proprietary Technology Supplier Selection Based On
Price
Product-Focused Factory Product Reliability Testing
Automation Insp. Of Incoming Materials

 

Acceptance Sampling
Quality Function Deployment
Product Standardization
Design For Manufacturability
Variety Reduction

Worker Motivation

Worker Specialization

 

 

 

 

 

 

 

 

 

 

they replace human labor and operate with less variation.

The infrastructural SPTs, as is the case with quality
competence, are lacking in employee-oriented SPTs. Only worker
motivation directly relates to the workers, and that technique does
not provide the authority or responsibility required to improve
quality levels. There is a preponderance of detection SPTs, rather
than prevention. Again, this may indicate the novice state of quality
management in the furniture industry at the time of the survey
(1990). There are several design-related SPTs which are prevention-
oriented. Improving the quality of designs and narrowing product
ranges can improve quality dramatically by increasing repeatability.

Quality performance, perhaps due to the stage of development
within the furniture industry, is being supported by a small number
of SPTs. These are ignoring the employee and seem to be—except for

the design SPTs—focused on detection rather than prevention.

204
Return on Assets

This section discusses the relationship between manufacturing SPTs
and firm performance. Table 5.10 contains the related SPTs. This
table is the smallest analyzed, most likely due to the nature of the
measures. Firm performance was measured using a 7-point Likert
scale (7 = high performance, 1 = low performance). This scale does
not contain as much variance as the production competence,
competitive priority competence, or competitive priority
performance measures. Given the limited sample size, significant
relationships will be more difficult to reveal.

Table 5.10 displays the structural and infrastructural SPTs
related to firm performance. Three important items can be
ascertained from the table. First, the best performers in the sample
seem to be emphasizing high-volume technologies (dedicated
equipment and worker specialization). Second, there is a movement
toward becoming more quality-oriented in high performing firms,
indicated by the use of control charts, the seven basic quality
improvement tools, and motivating the workers through gainsharing
programs. These are indicators of a move to granting workers
increased authority and decision-making responsibility. Finally, high
performers have all adopted or invented some proprietary
technology to give the firm a competitive advantage.

High performing firms are continuing to use traditional
manufacturing approaches (economies of scale oriented), but appear
to be starting the move toward improving process quality through

increased employee involvement.

 

205
Table 5.10: Structural/Infrastructural SPTs & ROA

 

 

 

Structural SPTs Infrastructural SPTs
Proprietary Technology Use of Control Charts
Dedicated Equipment Use of the 7 Basic Quality Tools

 

Worker Motivation
Worker Specialization
Gainsharin g

 

 

 

 

 

Summary of Individual Manufacturing SPTs

Table 5.11 displays significant manufacturing SPTs and the
constructs to which they are related. Some of the SPTs that are
related to multiple constructs will be discussed. Proprietary
technology (7), product-focused factory (6), and worker motivation
(6) were the SPTs related to the most constructs. The SPTs related to
five (5) constructs include employee involvement, workplace
orderliness, product standardization, supplier selection based on
price, synchronous manufacturing, worker safety, and worker
specialization. These nine SPTs have provided the broadest support
for sample firms.

This collection of SPTs appears to emphasize higher volume,
structural elements (standardization, specialization, synchronous
flow, low price vendors, and product-focused factory). One
explanation might be that the skills required to produce furniture
are best suited to high volume production. The cyclical nature of the
industry also creates pressure for firms to contain costs. As the
economy worsens, often furniture purchases are the first to be cut

from consumer budgets. Proprietary technology, in the furniture

206

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industry, generally involves productivity enhancing improvements,

further reducing total costs.

The remaining SPTs are directed at involving workers and
housekeeping. Housekeeping is a first-glance indicator of world-class
companies and is important to response-centered strategies (Giffi,
Roth, and Seal, 1990). The furniture industry is moving toward
involving workers in decision-making. There is not much focus,
however, on including workers in process and quality improvement.

Perhaps this has changed in the last two years.

MANUFACTURING SPTs GROUPED BY COMPETITIVE PRIORITY
A literature search was done in the areas of cost, delivery, flexibility,
quality, and just-in-time (JIT), directed at identifying

implementation strategies and techniques in each area. Empirical
studies had highest priority, followed by general writings. Tables

4.11, 4.15, 4.17, 4.19, and 4.21 contain the resultant manufacturing
SPTs associated with the competitive priorities noted above.

This section will discuss the implications of the results of the
hypotheses (hypotheses five through nine) associated will collections
of SPTs. First, the relationship between the variables constructed of
several SPTs and production competence and performance will be
discussed. Second, the relationship between the grouped SPTs and
the various competitive priorities and the associated implications will
be discussed. Finally, this section will address any relationship
between the variables and overall firm performance. Tables 5.12 to
5.14 present the results for the competence, performance, and RCA,

respectfully.

210
Table 5.12: Competence Constructs and Related Variables

Variable Product. Cost Delivery Flexibility Quality
Co . Co . Com . Com. Co

Beta Beta Beta Beta Beta

Info

Hrdm

Process

R2

JitProcs .429 .02
JitInfra

R2 .184

CostEff
Cos
CostDes
R2
DelProcs
DelInfra
R2
FlexProc
FlexInfr
R2

 

211

Table 5.13: Performance Constructs and Related Variables

Variable

Info
Hrdm
Process .
R2
J itProcs
J itInfra

R2

CostEff
Cos
CostDes
R2
DelProcs
DelInfra
R2
FlexProc
FlexInfr

R2

Product.
Perform. Perform. Perform. Perform. Perform.

Cost Delivery Flexibility Quality

Beta Beta Beta Beta

.392 .03
.154

.650 .005
-.459 .02
.423 .004

.415 .03

.173

 

212

Table 5.14: Financial Indicators and Related Variables

Variable

Info

Hrdm

Process
R2
JitProcs
JitInfra

R2

CostEff
Cos
CostDes
R2
DelProcs
DelInfra
R2
FlexProc
F lexInfr
R2

Pretax ROA Aftertax Pretax ROA Aftertax
External ROA-Int. Internal ROA-Ext.
Beta Beta Beta Beta

.416 .04
-.59 .004
.347 .027

 

213
The variables related to production competence—a general

measure of manufacturing’s support to business objectives—are those
related to JIT (JitProcs), cost (CostEff), and delivery (DelProcs) (see
Table 5.12). Common themes among the SPTs associated with each
variable include simplified and efficient material flow, preventive
maintenance, automation, and group technology-oriented layouts.
Setup time reduction also appears to be a critical element. The
relationship between these variables and production competence
might indicate that these SPTs are sound practices that firms should
implement regardless of strategic direction.

The variables related to production performance come from
each of the four competitive priorities and JIT. Process-oriented
variables include QProcess, CostEff, and DelProcs. These are, except
for the quality variable, similar to the variables related to production
competence. Common themes present in these variables include
simplified material flow, maintenance, automation, traditional quality
improvement tools, and design issues. The quality and design SPTs
add a more rounded dimension to the production construct. This is
logical in that it should take skills from several areas to support
broadly defined strategies, which are captured by the performance
construct.

The only infrastructural variable associated with production
performance is FlexInfr. Themes in this variable center around team
approaches, employee involvement, and a broad quality plan
utilizing basic improvement tools. The combination of the process
and infrastructural variables produces a strong base of skills and

capabilities from which companies can support many strategies.

214
Capabilities concerning quality and simple material flows can be used

in many strategic settings.

The support of cost objectives is best offered through these
methods: implementation of SPTs related to economies of scale,
quality improvement, design, and vendor issues. Buying and
producing in large batches, assuming ownership in multiple phases of
the value chain, and dedicating equipment and workers to narrow
tasks all support cost objectives. In a mature industry such as
furniture production, economies of scale can be critical to overall
profitability. The presence of the traditional quality tools supports
the writings of several authors (Crosby, 1979). Simplifying designs
makes it easier to build products, reducing costs. Finally, the supply
base can be used to reduce costs. These results provide fairly strong
support to the sand cone model, which suggests that capability in
several areas must be acquired before cost reduction can really be
made. (Ferdows and De Meyer, 1990).

The JIT variable, JitProcs, is the only one significantly related
to delivery competence. Again, centered around simple material
flows, these SPTs ensure that equipment is operable and logically
oriented. This allows for greater tracking ability and faster
throughput, thereby contributing both reliability and speed issues.

Superior support and performance in flexibility requires
contributions along several fronts. The five variables related to
flexibility competence (QHrdm, JitProcs, CostQual, DelProcs, and
FlexProc) contain several themes. First, a theme of equipment
maintenance and orderliness is present. This suggests that

equipment and shopkeeping can contribute to flexibility by

215
providing consistent, organized resources that reduce the burden of

managing the system. This allows managers to concentrate on the
more complex tasks associated with flexibility.

Another theme associated with flexibility is simplicity. The
study results indicate that simplifying layouts, reducing setup times
and improving throughput times are repeatedly connected to
flexibility. This theme is one often observed by manufacturing
strategy writers (Gunn, 1992; Wallace, 1992; ).

Quality items are also a theme related to flexibility. Use of the
seven basic quality tools, failsafing, and an overall quality system
provide the ability to continually improve the already simplified
system. Process improvements made possible by the quality tools
add a synergistic effect to the simplification theme. As defects are
permanently removed from the system, the system becomes more
straightforward. As the system becomes more straightforward,
quality problems are more easily detected and removed. Another
quality theme present is the increased responsibility given to
workers so that the improvements can be achieved. Altering work
structures and utilizing team approaches seem to be effective tools
for supporting flexibility initiatives.

Flexibility objectives are best supported through a three-
pronged approach: process simplification, rigorous maintenance, and
continuous quality improvement. These three themes can combine
to provide powerful support to one of the most complex competitive
dimensions. Underlying this approach is a movement to push
authority and decision making lower in an organization.

The grouped data were especially unsupportive of the quality

216
constructs. Only the CostDes variable was related. This included

SPTs concerned with reducing product complexity so that
manufacturing of the product was easier to complete. While this is
important, it is by no means sufficient to support a priority that has
now become a qualifier to enter markets. As stated several times
earlier, perhaps the sample firms (in 1990) had not yet been
convinced of the necessity for process quality improvements.

Table 5.14 indicates that only the JitProcs variable is positively
related to ROA. Remember that this variable is also the only one
related to production competence. This relationship with ROA
solidifies the perception that the SPTs associated with JitProcs can
provide a substantial building block upon which to build a

manufacturing strategy.

Managerial Implications

The results of the study can also give insight to managers who
are interested in improving the competitiveness of their
manufacturing functions. As stated earlier, there are numerous
manufacturing strategies, programs, and techniques available to
firms. The issue for managers is to determine which of the SPTs are
most appropriate for their firms.

The first conclusion that can be drawn from the results is the
importance of employee-oriented strategies. Across all of the
competitive priorities, employee-oriented strategies were related to
the associated competence and performance constructs. Many times,
they accounted for the largest percentage of SPTs related to any one

construct. Clearly, the role of the human in making the

217
manufacturing operations system competitive is critical.

The employee-related strategies most frequently observed as
significantly related to competence and performance include worker
training/cross-training, involving workers in decision-making,
worker motivation, and teaming. These SPTs are among those on
Table 5.11 related to the largest number of constructs. They are also
included in the infrastructural SPTs associated with JIT (see Table
4.20), which is important as the JIT variables are significantly
related to several constructs across multiple competitive priorities.
These results hint at the importance of well-trained, motivated, and
empowered employees in helping a firm compete in a global
economy.

Another set of infrastructural SPTs that was frequently
observed as significantly related to multiple constructs concerned
sourcing practices. Strategies such as reducing the number of
suppliers, supplier certification programs, and selecting suppliers
based on quality were often among the SPTs significantly related to
the competence and performance constructs. Interestingly, these are
among the purchasing practices cited in the literature as important
for a move to a partnership approach (Ellram, 1991). For industries
where cost and quality are important order qualifiers or winners—
such as the furniture industry—the use of purchasing strategies such
as these can help to keep a firm competitive.

The final set of implications can be classified as structural and
are related to the general flow of materials through the production
system. The SPTs involving technology, material flow, and

maintenance practices were often observed to be significantly

218
related to multiple priorities (i.e., delivery and flexibility). The

technology SPTs include the use of proprietary technology, general-
purpose equipment, and a strong emphasis on reducing setup times.
Material flow SPTs include having a product-focus, simplifying
material flow, and keeping the workplace orderly. Built on a
foundation of regular maintenance, this collection of SPTs can
contribute to the simultaneous pursuit of multiple competitive

priorities (i.e., delivery, flexibility, and quality).

Contributions Of Research

This research makes several contributions to the manufacturing
strategy literature. First, it is an empirical study that focuses on the
relationship between manufacturing strategy and firm performance,
and manufacturing strategy content, three previously identified
research needs (Adam and Swamidass, 1989; Anderson, Cleveland
and Schroeder, 1989).

A second major contribution is the expansion of an earlier
manufacturing strategy process model (Vickery, 1991). The
expansion is directed at identifying the manufacturing strategies,
programs, and techniques (SPTs) firms implement to support
business objectives. This contribution includes identifying a bundle
of manufacturing SPTs that provide support to business objectives at
a general or macro level. It also contributes by further verifying the
relationship between production competence and firm performance.

While the production competence construct measures
manufacturing support provided to business strategic objectives, it

does not provide guidance to firms making decisions regarding

219
competitive initiatives in specific dimensions. Skinner (1992a)

observes that academics are not providing research results that
assist managers in making decisions that link manufacturing
resources to strategic objectives such as cost, quality, delivery and
flexibility. This study makes a third major contribution by
expanding the production competence construct through the creation
of additional competence constructs in the areas of cost, quality,
delivery and flexibility. These “competitive priority competence”
constructs form the foundation to expand the competence construct
in response to Skinner’s observation. The new competence
constructs have also been linked to particular manufacturing SPTs,
thereby completing the link between specific competitive initiatives
and manufacturing strategies.

A related contribution are the results that link particular
manufacturing SPTs to performance within specific manufacturing
competitive priorities. This also responds to the research need
identified by Skinner (1992a). Finally, this research adds to the
general body of knowledge concerning the use of individual
manufacturing strategies.

To investigate relationships between sets of individual
manufacturing SPTs, the SPTs were grouped according competitive
priorities using existing literature as a guide. Another significant
contribution is linking these groups of SPTs to the various
competence and performance constructs. In several cases, the SPTs
groupings suggested by the literature were in fact related to
competence or performance within a competitive priority. These

results validate previous work in the field.

220
Limitations Of Research

This research has several limitations. First, the sample size (n=24) is
fairly small. This limits the confidence of statements regarding
relationships between constructs and manufacturing SPTs. A larger
sample would have alleviated this problem and increased the array
of statistical tools available.

Another limitation is that the statistical tests were conducted
with a large alpha (.10), which also reduces confidence. The reason
for the large alpha was that the research was theory building in
nature and not confirmatory. Nonetheless, the large alpha restricts
generalizability.

Third, the sample was confined to one industry (furniture),
which also limits generalizability. Approaches that work in the
furniture indistry may not apply to other industries.

A problem with the sections using grouped SPTs is that the
groupings were not based on statistical procedures such as factor
analysis. The use of factor analysis or principal components analysis
would allow for increased confidence in interpreting the results of

these sections.

Future Research/Extensions

This project can be extended to include analysis of the use of
manufacturing SPTs in a wider variety of industries. The furniture
industry is one in transition. Therefore, many of the firms in the
industry are not as developed regarding recent manufacturing
initiatives such as quality improvement programs, JIT, etc.

Replicating the experiment in a more mature industry might yield

221
different results or perhaps validate findings of this study.

The research could also be extended by replicating the study
on the same sample of firms. A longitudinal study such as this would
provide the opportunity to identify the manufacturing SPTs that
continue to be important in specific priority areas, while also
indicating the new SPTs being implemented.

Another extension would be to further study the relationships
between the competitive priority competence constructs and their
relation to business strategies. This would include statistically
constructing the constructs based on factor analysis of the individual
competitive priorities (see Table 2.1). Borrowing well—developed
strategic typing models such as Miles and Snow’s strategic types and
relating them to the priority competence constructs would
strengthen the competence constructs.

The competitive priority competence constructs could also be
expanded by applying them to several functions of the firm, not just
the manufacturing function. Potential functions include marketing,
design, and finance. The functional strategies identified could be
linked together to form an integrated strategy model for the firm
based on competitive priorities. For example, for a firm following a
low cost strategy, each functional area would have a set of SPTs to
implement and guide resource allocation. Integration of functional
strategies is a difficult task for firms and linking mechanisms could
aid in simplifying the job.

Skinner (1992b) has identified six critical areas of
manufacturing strategy that need additional development—make or

buy, capacity, equipment and process technology, workforce

222
management, production scheduling and control, and quality

management. Further studies that include manufacturing SPTs
directed at these six areas would provide a more direct link between
critical manufacturing decision areas and the strategies and
programs firms are implementing to achieve success in supporting
the business strategy or various competitive priorities. This would
aid managers in making the link between strategic direction and
strategy implementation.

More rigorous techniques could also be applied (with a larger
sample) to study the relationship between the manufacturing SPTs
and support provided to competitive priorities simultaneously. As
the global environment continues to become more competitive, the
ability to compete along multiple priorities will be critical.

Once the critical strategies and programs are identified, the
research could change direction to investigate the implementation
process associated with the particular strategies.

Hayes and Pisano (1994) claim that having strategic flexibility,
or the ability to rapidly change strategic direction, will be critical in
the future. Refinement of the survey instrument and longitudinal
study could aid in identifying the manufacturing STPs that contribute
to strategic flexibility.

Finally, the approach to identifying bundles of accepted
strategies could be applied to service firms. The development of a
service competence construct and associated competitive priority
constructs may provide additional insight into the subtle differences
between strategic management in manufacturing and service

industries.

Appendix A

The Survey Instrument and Glossary

223

 

 

 

 

NAME: FIRM:
TITLE: PHONE:
RESEARCH QUESTIONNAIRE

MICHIGAN STATE UNIVERSITY
Part I. FUNCTIONAL COMPE'I'ENCIES

‘Ihissecticrnisddgnedtodeterminewhichfunctional competenciesymrfirmfeelsareimportanttosuceafirl
implementation ofyourbnsinus strategy. First, please irndieatethemqflmnmywattach toeach oftlne
following competencies with respect to their contribution to your overall business strategy for the year 1990. A seven
point scale is provided below for use in assmdng the degree of importance of each competency. Please specify the
appropriate response by indicating a single scale value. If the item of interest is not applicable to your situation, pleas
specify NA (Not Applicable) instead of a single scale value. Although we recognize that all of the competencies listed

belowmaybeimportanttoyourcompanywssuccmwerequeettlntymcarefirllyassesseaehonesdgmfimm
withraspecttothecontributionitmalmatotheaclnievementofyonncompany'soverallbus’nesstrategy.
Seven Point Scale for 1990 Importance Rating
LeastIrnportant 1 2 3 4 5 6 7Extr'ennelyInnpon-tant

Secornd,pleasespecifytheperfonmnceofyourfirminrelatiantoitsmajorcompctitorsforthepastyear(l990)foreach
competency. Asevenpointscaleispmvidedbelowforyoutouseinassessingtheperformanceofyourfirmwithreepect
toagiverncornpetency. Plemespecifyuneappropniatempansebyindicatingasinglescalevalue. Donotreeporndfor
any competency that you marked 'Not Applicable" inthe Importance Rating section of tlnequestionnaire.
SevenPolntSealeforlMPerfomanceRattng
Poor 1 2 3 4 5 6 ‘7 Excellent

1. Product Flexibility (Customization): The ability to handle difficult, nonstandard orders, to meet special cnstorrner
spxifwafimafibpmmchmnzdbynwfmopdmdmandmcdax

lrnportanceRating_ PerformanceRating_

2. Volume flexibility: The ability to rapidly adjust capacity so as to accelerate or decelerate production in response to
clunges in cnstorner demarnd.

Importance Rating Performance Rating

3. Prone-Flexibility: Theabilitytopmdwelowqumfifieeofpmductcostefi'wiendysodntpmduamixdmgesare
easilyaceornmodated.

Importance Rating Performance Rating

4. LowProdnctlonCoat: 11neabihtybmirfimizedntddcoddproducfim¢wlusiveofhbonmfledflsmd
operating costs) through efficient operations, process technology andlor scale ecanomiee.

Importance Rating Performance Rating

224

SevenPolntSeaIeforl99OImportaneeRatIng ,
LeastInnportantl 2 3 4 5 6 7Extrernelylrnportant

SevenPolntSealeforlMPerfor-rnanceRatlng
Poor 1 2 3 4 5 6 7Eacellent

S. New Product Introduction: The ability to rapidly introduce large numbers of product improvements/variations or
completely new products.

Importance Rating Performrnce Rating

6. DeliverySpeed: 'I'heabilitytoreducednedmebetweanmderuldngandcnstomerdeliverywascloaewzemas
possible.
lmportanceRating PerformanceRatirng

7. Delivery Dependability: The ability to exactly meet qnnoted or anticipated delivery rhtes and gratuities.

 

Importance Rating Performance Rating

 

8. ProductionIead'I'ime: Theabilitytoredueethetimeittalneatornanufactureprodncts.

Importance Rating _ Performance Rating _

9. Product Reliability: The ability to maximize the time to product failure or malfnrrnctiorn. .

Importance Rating _ Performance Rating _

10. Product Dun-ability: The ability to maximize the time to product replacement.

Importance Rating _ Performrnce Rating _

ll. Quality (ConformaneetoSpecificatlona): Tlneabilitytomamfacuneaproductwhooeoperaingchancteristicsmeet

Importance Rating Performance Rating

12. Design Quality (Design Innovation): The ability to provide a produetwith capabilities, featnru. styling, andlor
opaafingdmfiedsfisdflmddmwpenumdmedmpamgmumahuefimmdngm

ImportanceRating Perfor-unnum—
13. ProductDeveloprnentCyele'I'irne: Theabilitytominimiudnetimeittakestodevelopnewprodnm
ImportaneeRating ' PerformnceRating

14. ProductTechnobglealInnovation: Theabilitytoangageinnewproductdevebpmaumvolvingmajoradvances
inproductteclnnology.

Importance Rating Perfumance Rating

225

SevenPointSeaIefor199OImportanceRatlng
Leastlmportant 1 2 3 4 5 6 7ExtremerImportant

' Seven Point Scale for 1990 Performance Rating
Poor 1 2 3 4 5 6 7mm

15. Product ImprovementIReIinement: The ability to further develop and refine existing products.
Importance Rating _ Performance Ratin8 _

16. NewProduct Development: ‘I‘heabilitytodevelopnewproductsforexistingmarkets.
Importance Rating _ Perform-me Mn: __

17. Original Product Development: The ability to develop original (i.e. 'new-to-tlne-world') prodncts that create entirely
new mrkets. .

Importance Rating Performance Rating

18. BrandImage: Theabilitywereateaposidvemfavmbkimageinthecnstuner‘snnndwhanluldnheamdu
product'sbrandname

ImportanceRating_ WWW!—
19. Competitive Pricing: The ability to offera lower product price than direct competitors.
ImportaneeRating__ PerfornnrnceRating_
20. ImPrice: Theabilitytoofferaneofdnelowestordneloweaavailableproductpnce.

Importance Rating Perforrmnce Rating

 

21. Advertidngand Promotion: 'I'heabilitytocreateeffectiveadvertisingand/orpromotioml campaigns
Importance Rating

22. Target Market(s) Identification and Selection: The ability to identify promising target markets and select the best
ones for consideration.

PerformarnceRating

 

ImportanceRating PerfornnrnceRating
23. ReapendveneatoTargetMarheto): Theabilitytoreepandtotheneedsandwausoftheflrm'stargetmabus).
ImportaneeRatirng PerforrrmnceRating-

24. Pre-SaIeCuatomer-Servlee: Tinabilhybaavicednastomerdudngthepwdnsedecisimprocemfiebefme
tlnecnrstomerbuystheproduct).

Importance Rating Perfa'marnce Rating

226

SevenPointSealeforlMImportanceRating
Leastlmportant 1 2 3 4 5 6 7 Extremelylmportant

‘ SevenPointSealefor1990PerformanceRating
Poor 1 2 3 4 5 6 7Escellent

25. Post-Sale Customer Service: The ability to service the customer after the sale of the product to ensure corntirnuing
cnstomer satisfactiorn.
Importance Rating Performnce Rating

26. Broad Product Line: The ability to provide a comprehersive set of related items within a givern product line
offering.

Importarnce Rating _ Performance Rating

 

27. Widespread Distribution Coverage: The ability to effectively provide widespread and/or internsive distributiorn
coverage.
Irnportarnce Rating Performance Rating

28. LawCost Distribution: 11neabilitytomirnimiaethetotalcostofdistribution.

Importance Ratirng __ Performance Rating __

29. Selective Distribution Coverage: The ability to effwtively target selective or exclmive distributian outlets. I
Importance Rating __ Perforrmnce W8 __

30. PersonalSellingProficieney: Theabilitytosuccesfully moveproductsthroughpersonalselling activities.
Importance Rating _ Performance Rating

31. Company Reputation: The ability to create a positive or favorable image in the eustoma‘s mirnd when helshe hears
the company‘s name.

 

Importance Ratirng Performarnce Rating

227

PART II. - MANUFACTURING TECHNIQUES AND PROGRAMS

Partiiisdirectedatgeterminingwhichmanrfacmrhngteclnnquesandpmgmnsaebdnguscdmymnfinnmadnevedn
competenciesselectedinPatI. Indussecum,weaskthayw-aseadnofdnetednnqucsandpmgmmsindnemble
preaentedonthefollowing pages individually. Ifyouareurnfamiliar with the technique,orunclear of the meaningof the
name of a technique, a GLOSSARY has been provided IN YOUR PACKET. Piece use tine glosary if you have any
hesitationaboutthemeaningofatechnique. 'I'hegloaaaryisinalplmbetiealorder. Pleaseevalnnteeachtechniqueor
program with regard to the following items:

0W: Rdmwhmwmfiwmamwumifindin
yourfirmin1990.

MWRdflswfitWflflMmdmdwwm

GW=Rduswwmmdwwwmmbw
aelnievemerntof1990mralitygoalssuchasfewerdefects,lowercostofquality,fewercnstomercomplaints,higlner
incomingquality,etc.

d)W:Rdmbdncmfihfimddnbchfiqmamgmmflwaduwmt
of1990costgoalssuchaslowerperunitcosts,loweroverhead,reducedirnvantorycosts,lowerpurchmeprice,etc.

0W: kfmwwmhfimdwwwmmbflw
achievement of 1990 flexibility goals. Flexibility refers to ileum such as the alility to alter productian volumes,
theabilitytoproducennulriplepmdrmnuwabifinymadaprwdmgingcandimwabifirympmvideimmd
prodnrct cnstomization, the ability to increme workerflexibility, etc.

0W=hfmwwmmfihmwmww
adnwementddmebaedgodssnhsdmemmabtfmmmemednememdanbd
timereduction,setuptimemducdonmncwedhnvaaorynmfasamspanedmetoaraomercomplamsac.

Foralloftlneitenslistcdabove,except faNUMBEROFMONMSINUSEpleaseameaeaehtecianiqueorprogram
usingtheaevenpdntscalesprovidedbelow. Pleaaeevaltntetlnctecinn'quesfortheyearl990. ForNUMBEROF
MONT'I-ISINUSEpleaaewriteinthetotalmunbaofmandnsdnattlfistecinfiqueorprogmminsbeaninmeflyomfirm.

 

EX'I'EN'I‘OFUSEINIM:
J J 3 A j 6 7
ExtrernclyLOW Extremelyl-IIGIIuse
useoftlnetecimique ‘ oftlnetechnique

CONTRIBUTION TO GOALS IN 19”:

4234567

Extremely LOW Extremely I-IIGII
to goals to goals

m Ifyourfirmisnoteurrentlyusingatednfiqnnormpleaaerespmdbyplachngaomdnblankform
OFUSEandproceeddirectlytothenexttechniqueorprogram.

\

228

 

 

MATERIAL REQUIREMENTS PLANNING
(MRP)

 

 

Flexibi-
lity
Goals

 

(MRPII)

MANUFACIURING RESOURCE W6 :3:

 

CAPACITY REQUIREMENTS PLANNING

 

mam-mas (rm

 

AUTOMATION

 

TOTAL QUALITY mNTROL (TQC)

 

TRAINING FOR EXECUTTVES AND
MANAGERS

 

 

TRAINING FOR WORKERS

 

ZERO DEFECTS

 

DESIGN FOR MANUFACT‘URABILITY

 

GROUP TFL'HNOLOGY

 

 

CH..LULAR MANUFACTURING

 

BACKWARD INTEGRATION

 

FORWARD INTEGRATION

 

CAPITALINVESTMEN'I‘

 

COMPUTER INTEGRATED
MANUFACTURING

 

FUNCITONAL INTEGRATION

 

GOALSET'I'ING

 

ABC ANALYSIS

 

WORKER MOTIVATION

 

GAINSI'IARING

 

QUALITY OF WORK-LIFE INITIATIVES

 

 

PRODUCT -FOCUSH) FACTORY

 

 

PROCESS-FOCUSED FACTORY

 

VARIETY REDUCTION

 

 

 

 

REDUCE momma CHANGE ORDERS $5531"

 

 

 

 

 

 

 

 

229

 

 

 

SIMPLIFIED MATERIAL FLOW

 

 

    

W

 

PRODUCT SIMPLIFICATION

 

 

COMPUTER-AIDE) DESIGN (CAD)

 

SYNCI'IRONOUS MANUFACTURING

 

 

GENERAL PURPOSE EQUIPMENT

 

DEDICATED EQUIPMENT

 

LARGE BATCH PRODUCTION

 

CROSS-TRAINING WORKERS

 

EMPLOYEE SUGGESTIONS

 

REDUCITON IN THROUGI-IPUT TIMES

 

QUALITY CIRCLES

.........

 

PRODUCT ST ANDARDIZATTON

 

 

VERTICAL JOB ENLARGEMENT'

 

 

REDUCITON IN RAW MATERIALS
INVENTORY

 

 

 

 

REDUCTION IN WIP INVENTORY

 

REDUCTION IN FINISHED GOODS
INVENTORY

 

PURCHASE IN LARGE QUANTITIES

 

SUPPLIER SEIECTTON BASE) ON
QUALITY

 

 

 

SUPPLIER SELECTION BASH) ON PRICE

 

 

 

ADVANCED FORECASTING

 

WORK MEASUREMENT

 

 

VALUE ANALYSIS

 

 

REDUCING SETUP TIMES

 

 

PREVENTTVE MAINTENANCE

 

FAILSAFING OR FOOLPROOFING

 

 

LUTSPIJTI'ING

 

 

 

 

 

 

 

 

 

 

230

 

 

 

mono DATA momma (ram)
WORKER snacmuzxnou s‘iv‘iiéisg 1.2:???aia'"i§;;i

    

 

QUALIFY FUNCTION DEPLOYMENT (QFD) ,
TOTAL PRODUCTIVE ”WANG: ;;55:5,.,:.,555 5
USE OF THE M BASIC STATISTICAL
mom
mspacnon or: INCOMING MATERIALS
INSPECTION OF [hi-PROCESS WORK 5f
INSPECTION OF FINISHED GOODS

 

 

 

 

 

 

 

 

 

loos mmon 5
ACCEPTANCE SAMPLING :
women ORDERLINESS ; ' 55.5355
QUALITY AUDIT 5; 3
PRODUCT Rmaarmv TESTING " . $3553.35
MEASURING PRODUCT RELIABILITY

AVAILABILITY OF QUALITY RELATED
DATA TO MANAGERS

AVAILABILITY OF (1381‘ OF QUALITY
DATA TD MANAGERS

AVAILABILITY OF QUALITY RHATED
DATA TO WORKERS

BENCHMARKING 5 =5 55.5.55
mom nrvorvramau'r _ 3:35,;
mover-:3 Ham RESPONSIBLE FOR ’

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ourwr cum 3
my FEEDBACK or: 011me DATA ;

 

 

 

 

 

moves Racocnmon 52%:

VISIBLE PERFORMANCE CHARTS

 

 

 

 

 

231

 

 

ADOPTION OF QUALITY STANDARDS

 

Cost

 

EMPI-IASISON 'DOINGITRIGI-TTTHE
FIRST'ITME"

 

IN PRODUCT DESIGN

COORDINATION AMONG DEPARmEN'rs

 

SUPPLIEI CERTTFICATTON

 

TRAINING PROVIDED TO SUPPLIERS

 

RELIANCE ON FEWER SUPPLIES

 

INVOLVE SUPPLIERS IN PRODUCT
DESIGN

 

INTO COMPONENTS

SEPARATE MANUFACTURING tEAD TIME

 

COMMON MANUFACTURING DATABASE

 

CONCURRENT ENGINEERING

 

ADVANCED MANUFACTURING
TECHNOLOGY

 

MIXED-MODEL PRODUCTION
SCHEDULING

 

LINE BALANCING

 

AUTOMATED MONITORING DEVICES

 

MAINTAIN EXCESS EQUIPMENT
CAPACITY

 

 

REDUCING SIZE OF WORK FORCE

 

SHE-DIRECTED WORK TEAMS

 

SUDCDNTRACITNG

 

PROGRAMMABLE TECHNOLOGY

 

FLEXIBLE MANUFACTURING SYSTEM

 

CROSS-FUNCTIONAL TEAMS

 

WORKER SAFETY

 

PRODUCT TEAMS

 

PROPRIETARY TECHNOLOGY

 

 

 

 

 

 

     

 

 

 

 

232

 

Low. 1 2 3. s 6 7mm;

 

B; I: 'm'j Number CONTRIBUTION To 1990

Program _ lity

ALWAYS PRODUCE SAME PARTON ‘ .,

COLOR CODING or PARTS m 5 _
M p, 4;: ‘52:. , ‘ ::

OTHER -Please Write In ..

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Part III. MANUFACTURING PERFORMANCE MEASURES

Intinissectiornweasktlntyoupleaeprovideobjectiveperforrnancedatafortheareaslistedbelow. Pleaseusel990as
theyearofreferernce. Ifyonnfirmdoesnotcollectinformafimhndneaea,pleaserespondwiflnaN/A (notapplicable).

 

1. PERCENTAGE OF 2. DOLLAR COSTS OF

Pats Scrapped 1 Scrap S

Pats Reworked fi Rework §

Products Returned 5 Inspection and taming 3

Process in statistical corntrol fl Education and training i

Your time spernt on qmlity improvement 5 Supplier certificatiorn §
Supplier Development 1

3. NUMBER OF 4. OTHER (Average across all products and process)

Ctflomerofcomplaintspermonth Incomingqmlity level a
Warraruyclaimspermnnth MeantimetoproductfailureMTTF)___
Quality audits per year Mean time betweern failure (MTBF) _
Suppliers Mean time to first failure (MTFF)
Certified suppliers Process capability (Cp) 5
Visits to suppliers per year Process capability index (Cpk)
Doesyourfirmhavea'qmlity manual'containing
written procedures and policies?

 

 

233

EW

1. NEW PRODUCT DEVELOPMENT

Average time from product idea to market (rnontlns)

Rate of new product introduction (ttlyeer)
Percentofnew productsreleasedonschedule___1
Percentofproductsfirsttomarket fi

2. PROCESSING AND PRODUCTION

 

Valueaddedtimeasapercentoftotalelapsedmanufacmringleadtime __&
Manor: turns (per year) _
Cycle tinne (days)
Average age of equipment (years)
Production throughput time (weeks)
Average production batch size
Average number of setups per week
How would you classify your operatiorn (check one)?
Make-tO-order (MTO) _ Make-tO-stock (M'TS) _ Amble-to-order (ATO) _

 

3. CUSTOMER SERVICE

Order response time (weeks)
Average quoted lead time (weeks)

Pereerntage of deliveries on time fi

Average respome time to cnstomer feedback (days)

Number of stockouts per mornth
Pereentageofordersrequiringasecondcallbycustomers g
Percentage of orders shipped on time fl

Percerntage of orders past dnre fi

Percentage of orders shipped irncomplete fl

 

9.. 7W

I. PRODUCTS

Numberofproductsoffered
Numberot'partnumbers
Numberofnewproductsofferedperyear
Numberofproductsretired peryear

234

2. MACHINERY

Nurinber of manufacturing plants
Number of different nnanufacturing procemes
Numberofprogranmablemachineswleeseeheckone)

 

 

o___, I-5___, 6-Io__,11-25_, >25—

3. WORKFORCE

Averagemunberofmachineseaehworlaercanoperate
Percentage of employee suggestions implemernted _&

 

W

10.

11.

Please estimate the Cost of Goocb Sold for your average product 5

Piece estimate the cost breakdown for your average product (as a percentage).

Rawmaterials 2 W4

Whatistheaveragemechirnenailizatianmteforyourequipment? __$_n_

What is the average capacity utilization rate for your facilities? ___fi

What is the average number of days of RAW MATERIALS inventory held? __£
What is the average number of days of WORK-IN-PROCESS inventory held? __&
Wint is the average number of days of FINISHED GOODS inventory held? ___&
Howmanyinverntoryurrnsdidyoulmvein1990? _fi_

What is your Direct Labor productivity? _1
Whatisyouraverageproductianlotsine? __fi

Pleaseratethelevelofordedirnessandcleanhnesofymumanufacmfingshops,ascomparedtoymu
competitors. Circletheeppropriatevahrensingtlneacalebelow.

1 2 3 4 5 j 7
Significantly About the Significantly
less orderly same more orderly

235

12. Pleaseplaceachecknexttothecostacconmtingmethodutilizedbyyourfirm.

Activity-bued costing _ Direct costing _
Irndirect costing _ Life-cycle costing __
Other , please list nnethod

 

Part IV. STRATEGIC INTEGRATION

Indissccfiorapleaseindicatednedegreeofimegmtianbetweanfimcuanalmanagersinstrategyformulation. Usethescale
belowforyourrespomes.

L 2 3 4 5 6 1
N0 Integration MUCH Integratiorn
1. What is the level of integration between Manufacturing marnagers and Marketing managers in strategic planning?
Level of Integration

2. What is the level of integratiorn between Manufacturing managers and Product Design managers in strategic
planning?

Level of Integration
3. What is the level of irntegratiorn between Product Design mgers and Marketing managers in strategic planning?
Level of Integratiorn

4. WhatisthelevelofhuegmtionbaweeanDedgnpemnwlandMamdacmnngpemmelinwpmdua
designphase?

Leveloflntegration

5. WMisdnkveldeaumbawemMakedngpmlaflMandammngpmnlmmemoduadedgn
phase?

Levelofintegration

THANK YOU AGAIN FOR YOUR PARTICIPATION! PLEASE RETURN T'I'IE COMPLETED QUESTIONNAIRE IN
ENVELOPE PROVIDED. THERE IS NO NEED TO RETURN TI-IE GLOSSARY.

236

MAW

100% INSPECTTON:ErmfingqnfltyadpmcesscaflrddumghhspecfimofAILpaflsndneyamprorhmedbya
givenprocess. ‘

ABC ANALYSIS: A materials cless'fication system irn which all stocked item are classified by anntnl dollar volume.

ACCEPTANCESAMPIJNG:hapecfimmwluchdcdsianammademacceptornaacceptamoraervicebascd
oneradomsample,asopposcdtoanentirelot (AttribmeorVariables).

ACTTVTTY-BASED COSTING: A method ofcosting wherebyajob, product orservice isssigncd overhead costsornly
if overhead activity is actually expanded irn support of it.

ADOPTION OF QUALITY STANDARDS: Adoptingadusingmtional adinternetiornalstandadstoestablishqnnlity
gdsfidindnomauzfim,mmmmogmmmnhqimovammmabdngmemnn6anad
developing suppliers.

ADVANCED MANUFACTURING TECHNOLOGY: Irnvolving new technologies such as Artificial Intelligence, CNC-
unchincs, Dee’sion Support Systems (DSS), CAD/CAM, Flexible Manufacturing Systems (FMS) in production processes.

ADVANCEDSTA‘I‘IST'ICALTECHNIQUES:Thoaetecimiqnnsnnedtolnelpanlyaedneiruaacdonoffaetorsindesigrn

adpmducfiantoreducethevanalihtymhaaaindemrfacuningprocess. IncludcdareANOVA,

ccrrelatianlregression, multivariate analysis, DOE. ad Taguchi methods.

AUTOMATED MONITORING DEVICES: Using devices which can anrtornnatieally detect defects during
l' . ' l .0“.

AUTOMATTON: Ammapiecedqmpmandmhmlfacnnguadfomguhdng,mbaiudngmedmucd
orelectrudcdevieesforhnnanobaanfianeffortaddecia’onmaking.

AVAILABILITY OF COST OI" QUALITY DATA T0 MANAGERS: Collecting data regarding the 'Cost of Quality"
and made available to nrrnit managers.

AVAILABILITY OF QUALITY RELATED DATATOMANAGERSfl‘hedegreetowhiehmanagershaveeccmto
qualitydatatoaidirnleaning,dccisianmaking,ardmranitoring.

AVAILABILITY OFQUALITYRELAT‘EDDATAT‘OWORKERS:Thedegreetowla'chhourlywodrersinveaccess
toqnnfltyrhumasdainlunmngthtyimprovananadprovideasanedownednp

BACKWARDINTEGRATION:TI:degmewaddnymafimcmddsad/aopemmdwmpplychinfromraw
maerialtoyarrfinishcdproduct.

amcmamcsmmmdmmmmmmmwm
canpetitorsorthoeecompaniesrecognizedasirndustryleaders.

CHAmmumnmormnAWdemm-nmm-
cadabarhardrbtanfidngdnhbmadmachimmmedcdwnineveplanmdmnpms

cmumnmmmmmprummmwmwmm
eqripmantmrnew process technology toreduceoverall unrarfacturing costs.

CHLULARMANUFACWRWG:AhyanmwmcthaBaMWmWiMOWmedk

237

that provide families of parts with similar flow pads.

COLOR CODING FOR PARTS AND MACHINES: A foolproofrng system wlnich ersures that parts get tmchirned on
the proper machine.

COMMON MANUFACTURING DATABASE: Databee of marnrfacturing information accedble by several different
functional area.

COMPUTER INTEGRATED MANUFACTURING (CIM): The trial illegratian of product design, engineering, proces
planning, and marnufactming through computer systems.

COMPU'I'ER-AIDED DESIGN (CAD): Ddgning products using a computer arnd a data-base of part numbers allowing
for speed and simplification through increased standardization.

CONCURRENT/SIMULTANEOUS ENGINEERING: Redncing lead times in projects by doing design arnd production
oflaterstagsatdwamedmemcomdimdwimurfiawfififieshnltfimdmppfiusmmmmuing
engineers, and marketing personnel early irn product design.

COORDINATION AMONG DEPARTMENTS IN PRODUCT DESIGN: Irncluding representatives from various
finedmflumawhsmmufacuning,marbfing,andpmcbadnginprodmtdedgn

CROSS-FUNCTIONAL TEAMS: The formation of teams whoae members come from different ftunctianal ares.

CROSS-TRAINING WORKERS: Training worlwrs to have tlne ability to perform multiple traits or operate multiple
machines.

DESIGN FOR MANUFACTURABILITY (DEM): An approach which clnracterized by the simultaneous involvement
of variors departments withinthefirm (e.g. manufacturing, marketing, purelnsing, etc.) and/or suppliers along with product
designmddevelopMperaumelindnedcsignpmtoreducethecostandtimeinvolvedindceigning,developing
and prodnning a product.

ELECTRONIC DATA INTERCHANGE (EDI): Electronic connection with customers arnd suppliers using computers
to quickly place arnd receive orders.

EMPHASISON 'DOINGTHINGSRIGE'TTHEFIRS’TTIME':Redncingcostol'qmlity(scraparndrework.and
external failures such warranty expanse, failure detection/inspection, and failure prevention) by focusing efforts an
qrnlityproductsprodrcedonthefirdnan.

EMPEASIS ON QUALITY BY UPPER MANAGEMENT: Upper managemeu‘a involvement and support of qnnlity
mum

EMPLOYEE INVOLVEMENT: Allowing and encouraging employee deciaim making, implementation of ideas, free
uptimetocreateideas,eommnanicatewluntiseapectedofemployeee,etc.

EMPLOYEE RECOGNITION: Irndivichal employeeeorteamsareformally recognizedtlnroughawards.gifts.timeoff,
muit pay increaaea. bomnea. parking pdvilegaetc.

EMPLOYEE SUGGESTIONS: Aformlayatemforefidfingempbyeemggediomformdbofiofimprovingopaaflm
araiforrewardingworbrswhoaemggeationsareimplemented.

EMPLOYEESIIELDRESPONSIBLE FOR OUTPUTQUALITY:l-loldingemployees respora'bleforqualityatthcir
operatiransbyusingteclmiquesanchucommicefingtoemployeesthatdneyarenottopmondefecfivematedal,tying

238

pay to qmlity performance. etc.

EXCESS EQUIPMENT CAPACITY MAINTAINED: Excess capacity is maintained to accomnnodate demand
fluctuatiom.

FAILSAFING OR FOOLPROOFING (POKA-YOKE): Building into operations methock that either prevent mistakes
ordel'ects fmmoccmringorbeingpmedonmrinstamlydetectmistakesordefects.

mu: MANUFACTURING svsrms (FMS): Using an ms in prodnrction of your products.

PORWARDINTEGRATIONfl'hedegreetowhichyorufirmeontolsarndloroperatesthetfistributionchainmdmrlcets
for its products.

FUNCTIONAL INTEGRATION: Incredng formal and informal communication across functional lines (e.g.
marnrfacnuingarndmarketing.deaignundmarketing)withinthefirm.

GAINSEARING:Anhncandvepaysyflemhnwlfidnweryanneeivesadmdfiwvflmofcoadecmm

GROUPTECENOLOGY: A wduuquebywlfichpmdrmapanswithsimihrdnraaedsficsangrwpedhuodisina
families and machines are arranged to specifically produce a family of parts.

mom Foursome: Reducing m cons through me accurate rm.
msmcnonorrmsmmcoons: Materialaareinspectedbeforetheyareahippedtocustomera.
mmcnos OFIN-PROCESS worm: Materialsareinspectedatpointsintheproductionprocas.
INSPECTION or INCOMING MATERIALS: M]! are inspected upon arrival from suppliers.

INVOLVE SUPPLIERS IN PRODUCT DESIGN: Using suppliers‘ technical abilities arnd product knowledge in the
design stage of your products.

JUST-WINE(Jm:Pmmhmmmdsyamdedyndbmmfllds,mimmiuwmm
rerhrceWIPinventor-y.

LARGE BATCH PRODUCTION: Reducing unit coats through producing in larger lots.
LEVELWORKRELEASES:Rdeasingworktodnednpfloormalevdmmnerflnerebyeliudmdngboularecls.

LINEBALANCING:Aproceduefortividingudmwudymganployeeeuwaksadasmapromuacdhdu
hm

LOTSPLITTING:Splittingalotqmriityhflonmrednnanearfldundworkingonaarbhhndnerdmwddngfor
theentirelottobecompetedbeforebegimringproaeamthenen.”

MANWAWGRESOURCEHANNNGM:AWangmmdmdngM
MWMBabflmenmmdfimmmwpmmwflw.

MAIERIALREQUmmPLANNme:AmMudemadmmfmmfingWM
achedrlingatockreplenidnmentorders.

239

MEANANDRANGECEAR‘TS:Agraplucrepruentatimofdnevarisfimindnednnaenstiasbdngproducedbya
pmcaswhiehslmsdnammmtuflmhmofdflvafiafionbyfimemndic‘esaafistimlcmudorlackofinandenables

patterninterpretationarnddetectionofchangesinqoalitylevels.

MEASURING PRODUCT RELIABILITY: Most irnterested in total number of failures and total cumulative operating
time (in hours, days, cycles, etc.).

MIXEDMODEL PRODUCTION SCHEDULING: Aprorhrctionachedulethatisrepetitiveinslnortcyclesandismore
carducivetoarpplyingsomeofeachneededmodeleachchycloselyinlinewithcustomerrequirements.

OFTERLONGERTERMAGREEMEN’TS'IOSUPPIJERS:Movingawayfromshorttermeontractstolonger.more
stablecoraacts.

WWANCE:Amndmuhsdfiqudbdcdmfimdmfml
equipmentfailures.
PROCESS-FOCUSEDFAC’TORY:Anapproachwhichnarrowstherangeofhsksunddemandsplacedonthe
munrfacuaingmganindmbyfomsingefi’aumafimiwdmgeofproeesswdunlogiu. '

PRODUCTRELIABILITY IESTINGHInprobabifltyMaproduawillpufmmitshuandedfincfiasmderaawd
conditions for the specified time period. The following are techniques that me these elements to improve reliability.

PRODUCT SIMPLIFICA‘I'ION: A search for ways to unable a product to perform the same functiar, but with fewer
partsarndlessprocessingtimerequired forrmnufacturing.
PRODUCT STANDARDIZATION: Making products standardized to ease manufacture arnd increase efficiency.

PRODUCT-FOCUSEDFACTORY:Anapproachwhichnarrowsdnerangeoftsksanddemandsplacedonthe
maurfachuhgorgarflrfimbyfocrfingeffoflsmafimitedmmberofproducts

PROGRAMMABLETECENOLOGY: Ameunsofprothrcfionforwhichdnefrancfiansareeaarolledbycomplners,
mempamaflecafloflmdlwhgfumfickdungemabnodnfimdmtm

PROPRETARYIECWOIDGYHRWNMJMmqmeMMaM
firmtogainanadvuntageovercompetitors.

mommmcnovmwmmwmwmmymmmmm
processingctsts,etc.

QUALITYAUDIT:Adoamanedwfivitypefiamedmaecudncewithwfiuenmuchwkfinsmvuifydu
amfiweebmdwqmflq‘mmmmmmmwawefimyimflmm
aecorrhncewithspecifiedremriremarts.

QUALITYCIRCLES:Smilwukpwpsdflmedpuiodiaflymdismnsmysbimprweqmfitymrodmfivitxmdn
workenviruanent.
QUALITYEUNC’TIONDEPLOYMENTQI'D):Amechmiamusedtocapturecutomerdesiresandwantsmndassipn
functional reapansibilitytluoughomtlneomp-ry.

QUALITY OF WORK-LIFE (QWL) INITIATIVES: Aprogramaimedatimprovingtheworkenvironmerrtconsiaing
domameddnfdlwim:jobafichmamdmfinen,wmpaamminmbemfiu.mefings,ac

240

.REDUCE SIZE OF WORKFORCE: Reducingthesiuoftheworkforoe tsing layoffs,dismissalsandattrition.
REDUCINGSETUPTIMES:IImseacuvidesainwdatmducingdretimereqtnredbetweanprodmdmnms.

REDUCTION IN ENGINEERING CHANGE ORDERS: Reducing the number of engineering change orders allowed
toirncreasetlnestabilityofthepromnctionplan/schedule.

REDUCITONINFINISHEDGOODSINVENTORY:Practiceswln'chreducetheamountofprorhrctinfinishedgootb

REDUCIIONINRAWMATERIALS INVENTORY: Practiceswhiehrethoetlcamarntdrawmterialsininverlory.

REDUCTIONINTHROUGHPUTTIMES: Reducingtluurghpmstolowereostsinareassuchasinvemoriesundjob
latenes. arnd toimprove machineutilintion.

REDUCTION IN WORK-IN-PROCESS (WIP) INVENTORIES: Efforts to reduce the size of WIP inventory.
RELIABHJTYASSESSMFNT:flaggingmlWflwproUemsMghmardnmmnumba offailures,failure

mwmmfmhmmmmmmfiewmawmpdim‘snhfiw
relialility performance, and ctstorner or dealer complaints.

RELIANCEONAFEW,DEPENDABLESUPPLIERS:Awardingbrsinestoalimitedmrmberofsupplierstofoster
acooperativerelatiornship.

REVERSE ENGINEERING: Competitors‘ products are physically disassembled and impected to determine what
compauugdedgnspwmwhfumdmlnfacnuingmhwbeunmeduimprwedupat

SELF-DIRFBTED WORK TEAMS: Small groups of workers (5-15) rotating through jobs witlnout the presence of

supervnsors.

SMLHIEDMAIERIALFLOW:IIdeqmpmaumdwdngJMnngdmpfifydwflw
ofmaterial.

STATISTICAL PROCESS CONTROL (SPC): A collectiorn of process amlysis techniques including flowcharts, Pareto
unlydgfrdnbaneclnrnundeornuolclnrtstommitorprocessqmlity.

SUBCONIRACTING:Fuminganworkinhcavydemmdpuiodstofreeupcapacity.

SUPPLIERCERTIFICATION: Structuredprogramsthatusesupplierratingstoaward eertificationbasedonachievement
ofstated goals.

SUPPLIERSELECIIONBASEDONPRICE:Suppliersareclroaanprimrilyfortheirahilitytodelivcralow-eost
prorhrct.

SUPPIJERSELECTIONBASEDONQUALITY: Suppliersarechoaenprimarilyfordneirabilitytodeliveraqnlity
prothrct.

SYNCHRONOUSMANUFACTURmmAnWmdemmwbichdIdeefimm
involvedinthedesignundproductionofaproduct.

IIMELYFEEDBACKOFQUALITYDATA:vaidingfeedracktoworbrsanqmlityperformancetobeusedinthe
idemificatiunandcorrectionofqmlity problem.

241

TOTAL PRODUCTIVE MAINTENANCE (TPM): A full agenda of procedures that improve tine dependability of
cquiprncrnt. withemphmison maintaining equipment before itbrealrsdown; bestows primary resporsibility for Preventive
Maintenance on the equipment operator.

TOTAL QUALITY CONTROL (TQC): A comprehensive program to ensue qmlity throughout the orgarrintion;
includes planning arnd design, supplier arnd manufacturing interface, ctstomer service and 'quality at the source'.

WGNREECWVESANDMANAGmmmedegmmmquafiq,coemgem
productivity improvenent, team brrilcfing, etc., for executives.

TRAININGFOR WORKERS:flwmedufimngprogramin¢nfiq,coeemud,pMndfityhnprwemeu.ec.,fa
workers.

TRAININGPROVID-TOSUPPLIERS:Providingnsistenccintheareaofqmlityhnproveneuteclmicprestoymu
suppliers. -

VALUEANALYSIS:Admghexamimfimofexisfingprodrededgnspedfiafiaswithdndmdbwedngeoa.
typicallycenteredinthepurchasingorcngineeringdepartments.

VARIETYREDUCTION:Awdunqulfichdmpfificsdprmudrthmghmowingthebeseofpartsmnnd
toprodnrce.

VENDOR LEAD-TIME MANAGEMENT: Managing suppliers to ersure timely deliveries and working with suppliers
toreducelcadtimes.

VERTICAL JOB ENLARGEMENT: Bxpanrfing job design by allowing workers more involvemcrnt in planning activities
and supervision.

VISIBLE PERFORMANCE CHARTS: Placing pcrforrnarnce clnrtsand quality related datasothatall employecsare
abletoviewthem.

woumm:muammmmmmmmmmmfim
highefficiency.

WORKER MOTIVATION: Programs ainned at motivating the workforce using itenns such as mognition. bonmes,
cantests, rewards, etc.

WORKERSAFETY:hnmdngwmhrmfeymyaufaeofiemuwremeWuflmwmpenfim
premium

WORKERSPECIALIZAflON:Wulcrshddngmyspedafizdsfilkwmchdwambewqefiicieaua
limitednumberoftasks.

WORKPLACEORDERLINESS:Havhngweydingneededforprodmfianhnplacearxireelyforrsesodntfimis
notapentscarclningfortoolsornnteials.

-ODEFECT‘S:Apmgramaimedatmducingdnemmbeofproduedefectstozem.

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