modified stage-gate® regimes in new product development

Modified Stage-GatesRegimes in New Product Development

�

John E. Ettlie and Jorg M. Elsenbach

The purpose of this research was to explore the nature of the Stage-Gates process

in the context of innovative projects that not only vary in new product technology

(i.e., radical versus incremental technology) but that also involve significant new

product development technology (i.e., new virtual teaming hardware-software sys-

tems). Results indicate that firms modify their formal development regimes to im-

prove the efficiency of this process while not significantly sacrificing product novelty

(i.e., the degree to which new technology is incorporated in the new offering). Four

hypotheses were developed and probed using 72 automotive engineering managers

involved in supervision of the new product development process. There was sub-

stantial evidence to creatively replicate results from previous benchmarking studies;

for example, 48.6% of respondents say their companies used a traditional Stage-

Gates process, and 60% of these new products were considered to be a commercial

success. About a third of respondents said their companies are now using a modified

Stage-Gates process for new product development. Auto companies that have

modified their Stage-Gates procedures are also significantly more likely to report

(1) use of virtual teams; (2) adoption of collaborative and virtual new product

development software supporting tools; (3) having formalized strategies in place

specifically to guide the new product development process; and (4) having adopted

structured processes used to guide the new product development process. It was

found that the most significant difference in use of phases or gates in the new prod-

uct development process with radical new technology occurs when informal and

formal phasing processes are compared, with normal Stage-Gates usage scoring

highest for technology departures in new products. Modified Stage-Gates had a

significant, indirect impact on organizational effectiveness. These findings, taken

together, suggest companies optimize trade-offs between cost and quality after they

graduate from more typical stage-process management to modified regimes. Impli-

cations for future research and management of this challenging process are dis-

cussed. In general, it was found that the long-standing goal of 50% reduction in

product development time without sacrificing other development goals (e.g., quality,

novelty) is finally within practical reach of many firms. Innovative firms are not just

those with new products but also those that can modify their formal development

process to accelerate change.

�Stage-Gates is a trademark of Product Development Institute and Innovation Management U3. Work in this area was supported in part by theTechnology Management Center of the College of Business at Rochester Institute of Technology and by Systems Applications and Products (SAP)America. The opinions in this article are those of the authors.

Address correspondence to: John E. Ettlie, College of Business, Rochester Institute of Technology, 107 Lomb Memorial Drive,Rochester, NY 14623-5608. Tel.: (585) 475-7789. Fax: (585) 475-7055. E-mail: [email protected].

J PROD INNOV MANAG 2007;24:20–33r 2007 Product Development & Management Association

Introduction

Many a fan and proponent of the Stage-

Gatesprocess for managing the new prod-

uct and new service development process

has argued that it has promoted speed up, better qual-

ity, greater discipline, and overall better performance

for all concerned (e.g., Cooper, 1993). But rarely has

the question of the impact of Stage-Gateson innov-

ation in new product development (NPD) been raised

or investigated in the context of adoption of new hard-

ware-software systems for virtual engineering. There

are some hints in the more recent empirical literature

delineating how the Stage-Gatesprocess might impact

innovation. For example, Busby and Payne (1998)

found that engineers’ predictions about activity dur-

ations varied significantly by circumstances and con-

text. This is potentially quite important because the

more innovative projects often do not meet deadline

targets, partly because the learning required to accom-

plish tasks is not figured into original estimates.

Busby and Payne (1998) studied a large defense

contractor of complex weapons systems using inter-

views of engineers and found that judgments of ac-

tivity duration were influenced broadly by whether or

not the project was a top-down, target-cost-framing

exercise or a bottom-up, detailed task-breakdown-

driven project. One important finding of the study

was that the engineer making estimates of project

activity times is not always the same engineer who

actually works on the project. They also found that

the more experienced engineers were less optimistic in

their predictions of activity time duration, more likely

to allow for rework, less detailed in decomposition of

tasks, and more likely to consult others. In general,

expertise in engineering does not amount to expertise

in planning for projects. The implications of these

findings are that the management of the NPD process

often proceeds quite independently of the technical

challenges of the work setting and might be quite

strongly influenced by context, especially by the in-

novation agenda of the firm.

Shaw et al. (2001) applied the Stage-Gatesmethod-

ology to the chemical industry and found that company

personnel often confronted with vague, generic gate,

and stage definitions evoked the ‘‘not-invented-here’’

excuse for lack of progress. Actual application of the

Stage-Gatesprocess required a collaborative effort be-

tween plant planners and plant engineers. Further, they

found from case studies in chemical manufacturing that

the Stage-Gatesprocess can result in significant time

savings, but no longitudinal data are as yet available to

test their idea that the process does not compromise

innovative solutions to plant problems. That is, the

Stage-Gates framework might enable the ability to

package innovative tools and methods, giving a ‘‘hol-

istic approach to project development underpinned by

a variety of novel option generation and evaluation

tools’’ (Shaw et al., 2001, pp. 1133–5).

Smaller companies have also tried to apply the

structured NPD methodologies, and Skalak, Kemser,

and Ter-Minassian (1997) studied four cases of con-

current engineering in firms with 300 to 500 employees.

They found considerable variance in application of

concurrent engineering across these four companies,

influenced most by resources, product type, and scope.

Baback and Holmes (1999) studied six automotive

and two aerospace companies for three years and

found that at least four structured approaches to

new product development were possible, including

Stage-Gates (the third type), also called the concur-

rent product definition model. The other three

approaches were the (1) sequential model, where

products pass through various functional areas; (2)

the design-centered model, usually using significant

up-front planning with a lightweight project-manager

approach; and (3) the dynamic model, which relies

BIOGRAPHICAL SKETCHES

Dr. John Ettlie is the Madelon L. and Richard N. Rosett Professor

of Business Administration and director of the Technology Man-

agement Center at the Rochester Institute of Technology. He earned

his Ph.D. at Northwestern University in 1975. Dr. Ettlie has pub-

lished over 70 refereed journal articles, 85 trade articles, and book

chapters and has made over 100 professional presentations world-

wide on the management of technological innovation. He has

authored six books, including Managing Innovation, 2d ed. (Elsevi-

er, 2006). His current research projects include new products and

service innovation as well as managing new information technolo-

gies. Dr. Ettlie has been the consultant to numerous corporations

and government projects, including the Saturn Corporation, Allied-

Signal Corporation, Caterpillar Tractor, Inc., PACAR Reynolds

Metals, Kodak, and Delphi Corporation. He is associate editor of

Journal of Operations Management and Production and Operations

Management Journal.

Dr. Jorg M. Elsenbach is associate professor and chair of corporate

management and production and logistics at the Technical Univer-

sity of Munich. He earned his Ph.D. at the Technical University of

Munich in 1998. His current research projects are the role of the

radiofrequency identification technology in supply chain event man-

agement, an investigation of reverse supply chain management, idea

reservoirs and new product commercialization, and supplier foot-

print optimization to low-wage countries. Previously Dr. Elsenbach

was senior manager for Accenture in Strategic & Business Archi-

tecture Serviceline and vice chair of a European car logistics service

provider.

MODIFIED STAGE-GATEs REGIMES IN NEW PRODUCT DEVELOPMENT J PROD INNOV MANAG2007;24:20–33

21

heavily on information technology enablers, when

greater integration—especially downstream—is re-

quired in the concurrent, Stage-Gates model.

In a review of the literature, Hauser, Tellis, and Grif-

fin (2005) suggested two alternatives to a strict Stage-

Gatesprocess. The first is the spiral process, which puts

a premium on speed but still requires cross-disciplinary

input to the process; the second is overlapping stages, in

which an example might be the testing of product ideas

before fully released from previous stages. In both in-

stances, the emphasis is on speeding up without loss of

quality of solution, or the optimization of the process.

This suggests an avenue by which the Stage-Gates

process is often modified by companies practicing de-

sign-process management. Breakthrough projects were

more likely to be managed using the dynamic model

whereas low-risk, incremental technology projects used

the sequential approach or the concurrent engineering

(i.e., Stage-Gates) process regime.

This helps to frame hypothesis development by de-

fining the contexts that typically require Stage-Gates

modification and if these contexts require more in-

novative project demands or contexts. Therefore, the

overall objective here is to explore the nature of the

Stage-Gates process in the context of innovative

projects that not only vary in new product technolo-

gy (i.e., radical versus incremental technology) but

that also involve significant NPD technology (i.e.,

new virtual teaming hardware-software systems).

Hypothesis Development

There is considerable appreciation for the need to

consider alternative regimens in new product devel-

opment. For example, in Cooper, Edgett, and Klein-

schmidt (2002a), the first of a two-part article on what

they called optimizing the Stage-Gates process, they

suggested that the way to modify this regimen for

breakthrough ideas is to add a discovery stage to the

front of the process. This discovery stage includes

building mechanisms for idea capture, working with

innovative users, generating scenarios, and camping

out with customers. By constructing their Stage-

Gates modification in this way, Cooper, Edgett,

and Kleinschmidt (2002a) were in general agreement

with the literature reviewed in the introduction, and

this leads to the first hypothesis for testing.

H1: Companies adopt a modified Stage-Gates process

for radical as opposed to incremental technology new

product development.

To their credit, Cooper, Edgett, and Kleinschmidt

(2002b) continued in their second article with modi-

fications to the standard Stage-Gates process by sug-

gesting that the hit rate of new products can be

improved by better go/kill decision points. The prob-

lem, accordingly, is that too many companies cannot

say no, so they are working on too many projects at

once. This lack of discipline comes from key customer

requests, no accepted mechanism to kill projects, no

criteria for killing projects, difficulty in getting senior

managers involved when they are needed, and getting

them involved appropriately. They observed that

companies do fast-track lower-risk projects and use

the full-blown Stage-Gate for more risky projects with

high hurdles at the decision points. These clearly de-

fined gates are business case check-offs, clear product

definition, and target market identification.

However, this does not sound like a high-risk new

product development, which is quite rare in most com-

panies’ experience. Furthermore, the engagement of

top management as opposed to enforced delegation

and not taking on appropriate projects in the first

place would seem like better advice, even in the ab-

sence of theory. The more typical experience is that

projects are changed by top management in a way that

often is not satisfying to new product team members.

Travel pressures, in particular, are no longer an excuse

to miss project meetings that are critical gate passages

with collaborative technology and virtual teaming

software available to most firms today (Buhman,

2003). This leads to the second hypothesis for testing.

H2: Companies using modified Stage-Gates develop-

ment processes are also significantly more likely to

adopt advanced enabling systems for new product

development like collaborative engineering hardware-

software to enable virtual team implementation.

Radical new products require radical new produc-

tion processes, especially in mature industries (Ettlie,

Bridges, and O’Keefe, 1984). A logical extrapolation

of this relationship is that radical new products re-

quire not only departure from traditional gating

methods but also new hardware-software systems as

well. For example, Ettlie (1997) found that computer-

aided design (CAD) systems were part of the NPD

adaptations in successful introduction of durable

goods products. Further, Cooper, Edgett, and Klein-

schmidt (1997) suggested the use of a product port-

folio approach to help make critical decisions and

ration scarce resources, which is consistent with find-

ings that companies integrate customer needs and

22 J PROD INNOV MANAG2007;24:20–33

J.E. ETTLIE AND J.M. ELSENBACH

competitive pressures (Ettlie and Johnson, 1994). In

fact, the latter study began with the same contention

as Cooper, Edgett, and Kleinschmidt (2002b), arguing

that the front end of the Stage-Gates process is to

accommodate differences in technology (e.g., radical

versus incremental, disruptive versus sustaining).

However, it seems now that changing the front end

of the new product development process alone is in-

sufficient to account for the existing observed variance

in use of Stage-Gates and NPD practices generally

(Adams and Boike, 2004; Griffin, 1997).

Taken together, this suggests an alternative justifi-

cation for modification of a well-accepted and discip-

lined process like a stage or phase gate in that a

method can be optimized only after it is introduced

through learning. This is akin to the notion long held

in operations management that one sets a level of ser-

vice to meet external goals (e.g., customer needs) and

then minimizes the costs to deliver this service level. It

follows that only after a method is supported by a

formalized strategy can optimization follow through

modification of this and other processes. The follow-

ing hypothesis is offered for testing.

H3: Formalized new product development processes

(i.e., formal strategies and structures) are likely to be

able to allow companies to adopt a modified Stage-

Gates regimen.

The rationale for this hypothesis is that the notion

that companies can leap-frog their competitors in de-

veloping new capabilities for more efficient and more

effective product and services launches is rare in prac-

tice, not supported by theory (cf. Pfeffer and Salancik,

1978), and strategy–structure sequencing in compa-

nies (Amburgey and Dacin, 1994). Further, there is no

empirical evidence that leap-frogging actually occurs

in practice, and if anything, it is the opposite: The rich

get richer (Adams and Boike, 2004). There has also

been accumulation of evidence for nearly 15 years

now that discipline actually promotes success in new

product development (e.g., Adler et al., 1996; Ettlie

and Stoll, 1990; Sosa, Eppinger, and Rowles, 2004),

which supports the notion that formalizing the pro-

cess is the preferred route to higher performance out-

comes.

Finally, based on this same accumulated theory

and evidence (e.g., Cooper, Edgett, and Kleinschmidt,

2002a, 2002b; Ettlie and Stoll, 1990) it was necessary

to creatively replicate a well-known idea that

Stage-Gates and modified Stage-Gates firms were

more likely to be successful at NPD process improve-

ment. This in turn would improve overall firm

performance.

Particularly striking were two studies, one pub-

lished in the marketing literature and one in the

operations management literature. In the marketing

literature, Ittner and Larcker (1997) found little evi-

dence in a comparative study of the United States,

Canada, Germany, and Japan that faster product-

cycle time alone improves organizational performance

(e.g., return on assets, pretax return on sales), and

only when this is combined with use of cross-

functional teams and use of advanced design tools

can any impact on organizational effectiveness be ob-

tained. In the operations literature, Ettlie (1997)

found for a sample of 126 U.S. durable-goods new

products that first-mover strategy had its major im-

pact on commercial success through indirect impact

on the development process and only secondarily on

early market introduction. Both of these studies

suggest that improvement in the process of new prod-

uct development has the ultimate organizational

effectiveness impact.

H4: Stage-Gates new product development discipline

indirectly promotes organizational effectiveness.

H4a: Modified Stage-Gates is coincident with the

adoption of advance development tools like virtual

team technology (H2), which in turn promotes overall

new product development success.

H4b: Overall new product development success pro-

motes organizational effectiveness.

The idea of H4 and its two parts is to explore the

direct and indirect impact of adoption of Stage-

Gates and modified Stage-Gatesmethods on organ-

izational effectiveness. Although there is evidence of

the positive impact of Stage-Gates on outcomes of

superior new products (Davis, 2002; Soh, Mahmood,

and Mitchell, 2004) and NPD creativity (Stevens,

Burley, and Divine, 1999), there is not much in the

literature on the causal mechanism of how this occurs.

There are findings on job specialization in the NPD

process between middle and top management (Ettlie

and Subramaniam, 2004), modified Stage-Gates

usage (Cooper, Edgett, and Kleinschmidt, 2002b),

successful case studies from companies like 3M

(Stevens, 2004), and others (Phillips, Neailey, and

Broughton, 1999). However, the causal sequence still

remains to be systematically tested.


23

Methodology

The goal of this study was to shed some light on the

challenging and often elusive issue of the relationship

between evolving nature of the new product develop-

ment processes and innovation—product and process

alike. A survey of 72 automotive engineering manag-

ers involved in supervision of the NPD process was

the primary method of this study. All the major com-

panies were represented in the sample: the largest

assemblers like GM, Ford, DCX, Honda, Toyota,

Subaru, Nissan, and Fiat/Alpha Romeo, as well as the

large first-tier suppliers like Delphi, JCI, Visteon,

Lear, Magna, Bosch, and Siemens, representing a

total of 60 firms (company employment and results

were not correlated).

Measures

First a measure of modified Stage-Gates was devel-

oped as used by auto companies (see itemthat fol-

lows), and this variable was coded as 15 adoption of

modified Stage-Gates and 05 other. A second ques-

tion was used to scale the NPD process. The item ap-

peared as follows on the questionnaire/interview

format protocol:

Do you use a traditional form of the Stage-Gates pro-

cess for developing and introducing new products or a

modified form of Stage-Gates (e.g., we allow back-

tracking through a gate if warranted)?

(a) No process

(b) Informal process

(c) Traditional Stage-Gates

(d) Modified (please describe modifications)

A scale was then developed to measure adoption of

collaborative engineering systems, and this was also

validated by other items on the surveys. This was a six-

item scale (CAD neutral or universal translator was

the only item that dropped out), including audio and

video conferencing, virtual team support software with

and without CAD collaboration, and integrating these

engineering systems with enterprise resource planning

(ERP). Cronbach’s alpha for this scale was .75 for the

automotive sample, with acceptable internal consist-

ency. A limited evaluation of construct discrimination

was done by evaluating correlations with other items

on the scale and then in the follow-up interviews with

the automotive industry and additional survey infor-

mation. Scale validation is taken up separately.

Two single-item response formats to capture for-

malization of the NPD process were used.

(1) Our organization has a specific

strategy for its new product activities

which directs and integrates the entire

new product program.

Yes No

(2) Our organization tends to follow

a well-defined, structured process for the

development of most or all of our

innovative new products.

Yes No

As before, yes responses were coded 1, and no re-

sponses were coded 0. Although these two items were

significantly correlated (Table 1) and a scale could

easily have been developed, they were kept separate in

this study because of the early stage of hypotheses

development.

The questionnaire included a probe on whether or

not NPD was done with virtual teams, again with

codes 15 yes and 05no, with the following results:

33 respondents (46%) reported virtual team use, and

39 respondents (54%) said they do not use virtual

teams. This item, which appeared on the first page of

the instrument, was validated with another asking for

the proportion of NPD done in virtual teams, and the

two responses were significantly correlated: r5 .339,

p5 .005 (n5 67).

Easily forgotten, but a great construct of

innovativeness was that originally introduced as a

three-dimensional form by Bigoness and Perrault

(1981). The authors argue that innovativeness is a

relative construct, relative to time, content (e.g., the

firm may be innovative to production process but

not product), and reference domain (internal vs. ex-

ternal), that is, as compared to the firm’s various

units, the industry, industry in general, or other

countries or economic regions. This construct was

used to guide measurement of innovativeness. The

persistent item format that has survived many empir-

ical outings (Ettlie, 1997; Ettlie and Rubenstein,

1987), including this study, to capture product nov-

elty, is as follows:

Was the product (circle one):

(a) new to the world

(b) New to the industry

(c) new to the company

(d) a significant upgrade, existing product

(e) minor modification, existing product

(f) other



Table1.CorrelationMatrix

Correlation

Modified

Stage

Gate

Used

Virtual

Teams

Last

New

Product

Was

R&D

Ratio

Specific

Strategy

forNP

Structure

Process

forNew

Product

Adopt

Collaborative

Technologies

Improved

NPD

Process

New

Product

Profitable

Percent

Modified

StageGate

PearsonCorrelation

1.334��

.147

.088

.331��

.319��

270�

.257�

�.013

Sig.(2-tailed)

.005

.227

.535

.005

.008

.048

.036

.925

N70

70

69

52

70

69

54

67

59

usedVirtualTeams

PearsonCorrelation

.334��

1�.018

.083

.112

.084

.208

.147

.113

Sig.(2-tailed)

.005

.884

.549

.350

.489

.124

.227

.386

N70

72

71

54

72

71

56

69

61

lastNew

ProdWas

PearsonCorrelation

.147

�0.18

1.209

.254�

.200

.337�

.033

.113

Sig.(2-tailed)

.227

.884

.130

.033

.096

.012

.789

.390

N69

71

71

54

71

70

55

68

60

R&D

Ratio

PearsonCorrelation

.088

.083

.209

1.066

�.005

.129

�.013

�.281

Sig.(2-tailed)

.535

.549

.130

.634

.969

.421

.929

.053

N52

54

54

54

54

54

41

52

48

SpecificStrategyForN

PPearsonCorrelation

.331��

.112

.254�

.066

1.616��

.510��

.302�

.298�

Sig.(2-tailed)

.005

.350

.033

.634

72

.000

.000

.012

.020

N70

72

71

54

72

71

56

69

61

structureProcessForN

PPearsonCorrelation

.319��

.084

.200

�.005

.616��

1.325�

.362��

.152

Sig.(2-tailed)

.008

.489

.096

.969

.000

.015

.002

.243

N69

71

70

54

71

71

56

68

61

AdoptCollaborativeTechnologies

PearsonCorrelation

.270�

.208

.337�

.129

.510��

.325�

1.232

.295�

Sig.(2-tailed)

.048

.124

.012

.421

.000

.015

.091

.042

N54

56

55

41

56

56

56

54

48

improvedNPDProcess

PearsonCorrelation

.257�

.147

.033

�.013

.302�

.362��

.232

1.147

Sig.(2-tailed)

.036

.227

.789

.929

.012

.002

.091

.268

N67

69

68

52

69

68

54

69

59

NPProfitablePercent

PearsonCorrelation

�.013

.113

.113

�.281

.298�

.152

.295�

.147

1Sig.(2-tailed)

.925

.386

.390

.053

.020

.243

.042

.268

N59

61

60

48

61

61

48

59

61

��Correlationissignificantatthe0.01level

(2-tailed).

�Correlationissignificantatthe0.05level

(2-tailed).


25

Respondents were asked to indicate the proportion of

sales they spent on research and development (R&D)

(R&D ratio) with a resulting median of 5%, standard

deviation (SD)5 12%, and archival data are compar-

able. The period from 1997 to 2002 reveals the follow-

ing approximate industry averages in R&D intensity

(percentage of sales spent annually on R&D). Data for

1993 to 1997 are from Schonfeld & Associates (1998,

pp. 136–140, 330); data for 2002 are budgetary plans

from Schonfeld & Associates (2002) (Table 2).

Ultimate performance outcomes were investigated

with four questions on the survey concerning the

overall NPD development process and its outcomes

(All of these items were used with permission from the

Product Development & Management Association

[PDMA] benchmarking survey; Griffin, 1997).

For each statement, please mark the box that best

describes the performance (cost, quality, innovation)

of your new product development process relative to

your major competitors (Table 3):

(1) For your new products program please estimate:

Past 5 years

New Product Sales as a % of Total sales: ______%

New Product Profits as a% of Total profits ______%

(2) Based on your organization’s definition of a suc-

cessful new product (e.g., some multiple of return

on investment), about what % of all new products

introduced into the market during the last 5 years

were successful? ______%

Other outcomes were evaluated as well, such as quality

improvement, but none was significantly correlated

with the study variables. For example, the correlation

between Stage-Gates usage and overall development

costs was r5 .003 (n.s.). More of these nonsignificant

relationships are reported in the results section.

Response Bias Tests

Comparisons were then made between the Hoover’s

archive compiled on the Fortune 1000 and the sample.

Comparisons were made on a random sample of non-

responding automotive companies from the mailing

with the respondent companies using these archival

data on both sets of companies (two independent

sample t-tests). No differences were found on sales

(t5 1.66, n.s.), sales growth (t5 1.67, n.s.), employees

(t5 1.66, n.s.), R&D expenditure (t5 1.72, n.s.), re-

turn on equity (ROE) (t5 1.72, n.s), and current ratio

(t5 1.70, n.s.). ROE is defined as ‘‘the accounting

ratio which measures net income to common equity.

The reports ratio tells how well investors are doing in

an accounting sense’’ (Brigham and Ehrhardt, 2002,

p. 86). Current ratio ‘‘provides the best single indica-

tor of the extent to which the claims of the short-term

creditors are covered by assets that are expected to be

converted to cash fairly quickly. It is the most com-

monly used measure of short-term solvency and is

calculated as current assets divided by current liabil-

ities’’ (Brigham and Ehrhardt, 2002, p. 76). R&D ex-

penditure was entered into the analysis as reported by

Hoover’s. The dollar value that the firm spent on

R&D for 2002 was recorded. Sales were an absolute

dollar value from 2002, and sales growth was deter-

mined as the percent change in reported total sales

from the previous years (both values from Hoover’s

Online). The tentative conclusion is that response bias

was minimal and that this study’s sample was repre-

sentative of the target population of automotive firms

involved in new product development.

Scale Validation

To standardize the study’s data collection, items were

borrowed (with permission) from a set of questions

from a benchmarking survey conducted by the

PDMA (Ettlie, 1997; Griffin, 1997; Visions, 2004),

primarily on performance outcomes, so reasonable

comparisons could be made later. A summary from

selected highlights of the study’s statistically signifi-

cant results for the automotive survey follow.

First, creative replication of the findings of dozens

of previous studies (Ettlie, 1997) of the NPD success

rate resulted, defined as the percentage of new

products that return some multiple of the investment

to companies. In the current study, the average

percentage of successful new products introduced

in the last five years for auto assemblers and sup-

pliers was 60%, which is essentially identical to the

national average This suggests that the other find-

ings of the survey were likely to be very representative

Table 2. Progression of R&D Ratios in the AutomotiveIndustry

Auto Parts (SIC 3174) Auto Assemblers (SIC 3711)

1993: 2.2% 1993: 4.3%1997: 3.8% 1997: 4.2%2002: 3.9% 2002: 3.8%



of current practices and outcomes of the NPD

process.

Second, adoption of collaborative engineering

tools and technology (e.g., Web-based development

systems for virtual team coordination) was signifi-

cantly correlated with NPD profitability (r5 .295,

n5 48, p5 .042). However, these same companies

reported lagging competitors in cost performance

(r5 –.311, n5 55, p5 .021), which might be a primary

driver in the adoption of systems that require little or

no travel to develop new products.

Third, the proportion of new product development

done in virtual teams (average5 25%, n5 67) was

significantly correlated with superior commercializa-

tion of new products (r5 .414, n5 66, p5 .001). The

number of virtual team pilot programs was also sig-

nificantly correlated with superior commercialization

as compared to competitors (r5 .278, n5 55,

p5 .040). Pilot programs for virtual teams and full-

scale implementation of pilot programs were signifi-

cantly intercorrelated (r5 .916, n5 54, po.001).

Fourth, the proportion of new product develop-

ment done in virtual teams was significantly correlat-

ed with improvement in the NPD process relative to

competitors (r5 .323, n5 65, p5 .009).

Fifth, new products scale had the following fre-

quency distribution: five reported new to the world

(7%); 20 said new to the industry (28%); 15 said new

to the company (21%); 27 said significant upgrade

(38%); and 4 said a minor modification (6%).

In a recent survey of 45 new products nearly iden-

tical percentages were found: at 6.7% for new-to-the-

world products, 31% new to the industry, 24% for

significant upgrade, existing product, but in the other

survey, only 9% for new to the company and 29% for

minor modifications of existing products was ob-

tained (Ettlie and Elsenbach, 2004). These percent-

ages are nearly identical for the first two—most im-

portant—categories for this study, indicating good

reproductibility.

In summary, the adoption of collaborative engi-

neering tools that allow product development to be

seriously undertaken at a distance, between different

time zones, and in the absence of face-to-face inter-

action has had a significant and substantial impact on

the outcomes of the NPD process in the auto industry.

Results

Earlier findings from the PDMA benchmarking sur-

vey were replicated (Adams and Boike, 2004; Griffin,

1997) in the study’s distribution of Stage-Gates

usage: about half (48.6%) of respondents said their

companies used a traditional Stage-Gates process,

20% (7þ 8 respondents) said they had no formal or

an informal Stage-Gates process, and nearly 30% of

respondents said they used a modified Stage-Gates

process. What made the last group different?

To investigate this question, Stage-Gates re-

sponses were correlated (e.g., modified scored 4)

with other constructs and measures with the follow-

ing results summarized in Table 1: (1) use of virtual

teams (r5 .334, p5 .005, n5 70); (2) adoption of col-

laborative and virtual NPD software supporting tools

(r5 .27, p5 .048, n5 54); (3) formalized strategies in

place specifically designed to guide the NPD process

(r5 .331, p5 .005, n5 70); and (4) structured pro-

cesses used to guide the NPD process (r5 .319,

p5 .008, n5 69).

These results represent strong support for H2

and H3. Given the apparent emerging importance

of modified Stage-Gates in the NPD process,

Table 3. Overall Performance of Self-Reported Items

Worse thanCompetitors Neutral

Better thanCompetitors

1. Overall Development Costs2. Efficiency of Product Development Investment3. Lead Times4. Superiority of Commercialization5. Improvement in Product Functionality/Quality6. Improvements in Elements of Product Technologies7. Major Innovation in Product Technologies8. Major Innovation in Products as a whole9. Creation of New Product Concepts

10. Improvement in NPD Process11. Reduction in Quality Problems12. Surprise or Delight New Product Customers


27

closer examination was required of how companies

report changing this reasonably well-accepted means

of promoting new product development. Results

follow.

All 21 respondents who said their companies used

modified Stage-Gates explained how they did this.

Also, the frequency distribution of types of modifica-

tions (see Table 4 for raw data) indicates a hierarchy

of reasons for breaking the discipline of Stage-Gates

and some explanation will be required, given the na-

ture of these responses. The most common way of

modifying the Stage-Gates process is allowing back-

tracking (cases bolded in Table 4). That is, in some

instances, gates can swing both ways, depending on

the circumstances; 9 of the 21 respondents said this.

Interrater reliability for coding of back-tracking be-

tween the first author and graduate assistant on this

project was Phi5 .72 (po.001).

The second most common reason given for modi-

fying the Stage-Gates process was that program or

project management dictates often overrule Stage-

Gates , including guidelines for continuous improve-

ment. For example, one of the eight respondents in

this category said ‘‘continuous improvement specific

to our process.’’ Another said, ‘‘modified depending

on resources required, market . . . perceived oppor-

tunity.’’ A third said, ‘‘Internal program management

process.’’

Finally, in earlier pilot-study interviews and follow-

up visits to nearly a dozen of these firms it was found

that collaborative engineering tools are allowing

substantial improvement of the Stage-Gates . For ex-

ample, one manufacturer of diesel engines said that

virtual teaming software has almost eliminated the

need for program reviews and has prevented delays

on projects by implementing ‘‘anytime, anywhere’’

program review processes. Managers typically do not

delegate sign-off on design reviews in this industry, and

delays often occur under the old methodologies when

team members miss face-to-face meetings. Mini re-

views have streamlined the process significantly in this

industry, making promises of reduced time to launch

by 50% a reality since they were an initial aspiration a

decade and a half ago (cf. Ettlie and Stoll, 1990).

To test H1, correlations were run between adoption

of modified Stage-Gates methods, R&D ratios report-

ed by respondents, and the product novelty (i.e., the

degree to which the company’s last major new product

was new to the world or just a follow-up to existing

offerings). Results are reported in Table 1 and Table 5.

Novelty of historical product offerings were not signifi-

cantly correlated with current Stage-Gates choices

(r5 .147, p5 .227, n5 69, two-tailed test), nor was

modified Stage-Gates significantly correlated with

reported R&D ratios (r5 .088, n.s., n552),

although the last result had considerable missing data.

Table 4. Modified Stage-GatesOpen-Ended Responses

a

ID Case Survey Question: if modified, how?

(Individuals selected ‘‘Modified, please describe’’)3995 omodified4 gates/or product development launch3949 Depends on product scope, smaller programs allow for minor back-tracking3951 Continuous improvement specific to our process4144 We break the rules when we want to1986 Fast version of Stage-Gate1008 Delay final product decisions as long as feasible within Stage-Gate2515 Some back-tracking/ sometime constrictions3066 Allow back-tracking if warranted3680 Even though the process is stopped at the gate, development continues4559 Gates are targets, but we often allow late changes in order to maximize flexibility1001 Back-tracking allowed1314 (type of) phase project plan1211 In past Stage-Gate, not any more3724 Internal program management process4449 Back-tracking frequent, but only after assessment of risk1740 Gate deliverables may vary depending on extent and timing. More??2409 The (Co.) System provides odifferent4 timing dep. on complexity of . . . changes.

Gates are flexible as long as items are documented for next stage1839 Back-tracking allowed

. . . modified depending on the resources required, market . . . perceived opportunity.4751 (Co.) . . . milestones: are a) Idea b) Prototype, c)Prod. Tool d) release4722 Executive, risk, or competitive forces may warrant changes.

aOnly complete cases appear. Backtracking (Inter-rater reliability 5 .72, po.001).



In Table 5, the cross-tabulation of last new product

technology (55new to the world) and Stage-Gates

usage status (15none, 25 informal, 35Stage-Gates ,

45modified Stage-Gates ) is presented. Note that for

both new-to-the-world (n5 4) and new-to-the-industry

(n5 26) cases, normal Stage-Gates usage exceeds

modified Stage-Gates usage. When it comes to new-

to-the-firm products, modified Stage-Gates exceeds

normal Stage-Gates by one case (6 versus 5).

Based on these two historical indicators of innov-

ation—novelty and technology departures in prod-

ucts—there is no direct support for H1, which predicts

that radical product technology is more likely to be re-

ported by firms using modified Stage-Gatesnew prod-

uct development processes, at least based on history.

To what extent do firms order themselves on prod-

uct novelty in the NPD categories? One-way analysis

of variance tests (Table 6) on the departure of new

products from existing offerings by grouped category

of Stage-Gates (15none, 25 informal, 35 Stage-

Gates , 45modified Stage-Gates ) showed sig-

nificant effects, with F5 3.9 (p5 .012, df5 3.65).

Significant multiple comparisons showed that groups

2 (informal, with mean 2.35) and group 3 (normal

Stage-Gates , mean new product score5 3.45) are

significantly different. The new product mean score

for modified Stage-Gates was 2.9, which is greater

than the first two groups (no process and informal

process) but not significantly different than any

group. Analysis of variance tests for R&D ratio

were not statistically significant by Stage-Gates cat-

egory (F5 .33, n.s., not shown).

These results indicate that companies using more

formalized NPD processes (i.e., Stage-Gates and

modified Stage-Gates firms) have a more aggressive

new product introduction history. Again, there is no

direct support for H1, which predicted modified

Stage-Gates firms were more likely to introduce

higher-technology products new to the world or in-

dustry, at least based on new product introduction

history of product success not withstanding.

To test H4, the relationship between Stage-Gates

usage and 12 outcomes was evaluated. Two were statis-

tically significant: NPD process improvement (Table 1)

(r5 .257, p5 .036, n567) and superiority of commer-

cialization (not shown in Table 1) (r5 .244, p5 .036,

n568). Further, adoption of collaborative engineering

hardware-software systems, which are significantly re-

lated to Stage-Gates adoption (Table 1), was in turn

correlated with new product profitability (r5 .295,

p5 .042, n548), shown in Table 1. This is strong sup-

port for H4, which predicts that Stage-Gates usage will

indirectly promote new product success by acting

through intervening outcomes.

Regression results controlling for these various se-

quential effects reinforce these findings. Tables 7a, 7b,

Table 5. Product Cross-Tabulation Novelty�Stage-Gatesa

Count

Stage-Gates

(15 none,25 informal,

35Stage-Gates ,45 modifiedStage-Gates

Total1 2 3 4

Product Novelty(55New to the world,45New to the industry)

1 2 1 0 2 52 1 5 8 6 203 2 1 5 6 144 2 1 17 6 26

5 0 0 3 1 4

Total 7 8 33 21 69

aR5 .147, n.s.; Kendall Tau c5 .072, n.s. The last two categories ofeach measure are in bold for ease of comparison.

Table 6. One-Way Analysis of Variance (Product Novelty by Stage-Gates Usage Groups)a

95% ConfidenceInterval For Mean

Maximum

Between-ComponentVariance

Product Novelty �Stage-Gates Usage N Mean

StandardDeviation

StandardError

LowerBound

UpperBound

15None 7 2.57 1.272 .481 1.39 3.75 425 Informal 8 2.25� .886 .313 1.51 2.99 435Stage-Gates 33 3.45� .971 .169 3.11 3.80 545Modified Stage-Gates 21 2.90 1.091 .238 2.41 3.40 5Total 69 3.06 1.097 .132 2.79 3.32 5Model Fixed Effects 1.032 .124 2.81 3.31

Random Effects .295 2.12 4.00 .207

aF5 3.933, p5 .012 (df5 3.65) overall between group evaluation. Significant differences are also in bold.�po.05 (Scheffe multiple comparisons).


29

and 7c present three summaries, modified Stage-

Gates as a predictor of collaborative engineering

(replicates H2), Stage-Gates , and collaborative engi-

neering as predictors of NPD process improvement

and, finally, all three of these variables as predictors of

NPD profitability percentage, respectively. Collab-

orative engineering adoption is the only significant

predictor of overall, NPD profitability (Table 7c,

beta5 .323, p5 .044), and modified Stage-Gates is

a significant correlate of collaborative engineering

(Table 7a). What appears to be bypassed in this causal

sequence is the failure to account for NPD process

improvement (Table 7b), although the zero-order cor-

relations are all significant in the predicted direction

(Table 1).

It is also worth noting that the other outcomes as

compared with competitors were not significantly cor-

related with Stage-Gates usage for this auto sample,

such as overall development costs (r5 .003, n.s.), ef-

ficiency of the NPD process (r5 .074, n.s.), lead times

(r5 –.086, n.s.), improved quality (r5 .011, n.s.), im-

proved elements (r5 .039, n.s.), major innovation

(r5 .044, n.s.), major innovation overall (r5 .097,

n.s.), create NPD concepts (r5 .027, n.s.), reduction

of quality problems (r5 –.017, n.s.), and surprise and

delight (r5 .182, p5 .143, n.s.).

Overall, results show strong support for three of

the four hypotheses. Stage-Gates usage and modi-

fications were found to be significantly related to

formalization of NPD strategies and structures, use

of virtual teams, and adoption of collaborative

engineering systems. Outcomes were also positively

affected: better collaborative engineering, superior

commercialization, and, indirectly, new product prof-

itability. There was no direct evidence, however, that

Stage-Gates usage with modifications was more like-

ly to be associated with a history of new-to-the-world

or new-to-the-industry product launches. Modified

Stage-Gates is primarily used to improve the NPD

process in auto firms sampled in this study, not taking

on significant new technology products. Exploration

of the implications of these results and case illustra-

tions follow.

Subsequent Cases Studies

In the spirit of Ittner and Larcker (1997) a search was

undertaken for comparative case-study examples of

the present study’s major survey and interview find-

ings to illustrate how organizations modified existing

Stage-Gates processes to eventually improve organ-

izational effectiveness. A brief report of four com-

parative case studies is given here: two from the

United States and two from Germany.

The first case from the United States involves a ma-

terial technology and products division of a major pet-

rol-chemical firm involved in packaging science for the

Table 7a. Regression Summary to Predict Adoption ofCollaborative Engineering Systems

Model

Coefficientsa

UnstandardizedCoefficients

StandardizedCoefficients

B Std. Error Beta t Sig.

1 (Constant) 2.134 .898 2.377 .021Stage Gate .572 .283 .270 2.021 .048

aDependent Variable: collaborate. Regression Summary: R2 5 7.3%,F5 4.1, p5 .048, df5 1.52.

Table 7b. Regression Summary to Predict NPD ProcessImprovement

Model

Coefficientsa




1 (Constant) � .438 .323 � 1.358 .181collaborate .066 .048 .195 1.363 .179stageGate .113 .102 .158 1.107 .274

aDependent Variable: improvedNPDProcess. Regression Summary:R2 5 8.1%, F5 2.15, p5 .128(n.s.), df5 2.49.

Table 7c. Regression Summary to Predict NPDProfitability Percentage

Model

Coefficientsa




1 (Constant) .487 .177 2.758 .009Collaborate .055 .027 .323 2.082 .044ImprovedNPD Process

.065 .069 .141 .941 .352

StageGate � .050 .055 � .142 � .915 .365

aDependent Variable: NPProfitablePercent. Regression Summary:R2 5 12.5%, F5 1.96, p5 .136(n.s.), df5 3.41.



food and related industry applications. Five years ago,

this division embarked on a major strategic shift to im-

prove R&D efficiency and ultimately to improve the hit

rate of their new product efforts by increasing resources

available for development. One of the outcomes of this

strategic shift was the back-tracking at gates later in the

development process when both development resources

increased significantly (e.g., prototype launch or ramp-

up) and performance of the process declined signifi-

cantly, often due to unforeseen problems. This back-

tracking to previous stages has resulted in significant

improvement in the NPD process and organizational

effectiveness and replicates findings reported earlier.

The second U.S. case involves a truck manufactur-

er engaged in the adoption and prove-out of collab-

orative engineering hardware-software systems design

to allow virtual-team collaboration with major cus-

tomers as well as across divisions of the company

(e.g., drive train and chassis design and production).

In the past, this company had encountered an accu-

mulation of delays in the NPD process due to travel

by team members and delay of design reviews at sig-

nificant gates in the process. Management in this div-

ision, learning from the experience of the drive train

group, insisted that key members not be bypassed by

the process, and if used properly virtual engineering

enables 24-hour development cycles. As a result, team

member travel during the development process no

longer has to slow things down. Furthermore, as the

teams learned how to collaborate at a distance, often

around the world, most of the work that formerly was

done during design reviews in terms of critical deci-

sions, was done before the design review meetings,

rendering these meetings truly as reviews and speeding

up the process significantly with improved quality and

knowledge sharing for the next product launch.

The first case from Germany deals with a well-

known automotive company, OEM. In 2004, one of

the vehicle divisions decided to add a discovery stage

to the front of the NPD process for idea capture,

especially with innovative users and engineering ser-

vices companies and was in support of the formalized

cost-cutting strategy. This was not the first use of this

approach, but earlier results fell short of targets. In

this early stage of development, the target market

identification had to be finalized and the product con-

cepts clear to promote decisiveness. There was delib-

erate effort to integrate this early stage with strategic

planning, resulting in a formalized link to the innov-

ation roadmap to consider future opportunities and

risks. This replicates and illustrates findings presented

already (H3, Table 1). A council structure was adopt-

ed to monitor the achievement of the Stage-Gatess .

One year later, on-time performance was encour-

aging, cutting time to date in half.

The second case from Germany is an example of a

NPD in mature industries: agribusiness. A German

tractor manufacturer was taken over by a U.S. com-

pany more than five years earlier; merger activities

included efforts to standardize the development pro-

cess. Virtual teams were introduced to maximize use

of company-wide technical resources. The advantage

of the jumping time zones in development, as before,

was also sought. The U.S. company had already used

a CAD system and wanted to share this technology,

but the software was new to the German part of the

firm. Therefore, an integrating software was adopted

and the traditional Stage-Gates process had to be

modified and structured to use this new system to in-

tegrate new electronic components for gearboxes and

air-conditioning and other systems. This was a chal-

lenging task in an industry where the link between

mechanical and electrical engineering was not typical.

The development of the new electronic gearbox was a

major success because it is now being copied by the

auto industry.

Discussion

A survey was conducted of 72 automotive engineering

managers involved in supervision of the NPD process

and it was found that the companies adopting mod-

ifications to the traditional Stage-Gates process are

also more innovative related to process but are nearly

the same as normal staging or phasing companies re-

lated to product innovation. In particular, they adopt

virtual teaming software tools and operate in more

formalized NPD strategy environments. Perhaps it is

this sustaining and focusing value of common goals

and well-defined structure that propels these compa-

nies to the next level of innovation, and this has been

the penchant for balancing cost against performance.

The adoption of these tools seems to allow continuous

improvement in this disciplined gating process, often

eliminating or streamlining design reviews significantly.

There was no direct evidence that firms historically

more likely to report new product launches that were

new to the world or industry were also more likely to

use a modified Stage-Gates NPD process. However,

Stage-Gates usage was significantly related to NPD

process improvement and was indirectly but signifi-

cantly related to new product profitability. Apparently,


31

companies use modified Stage-Gates processes to

optimize their development process rather than as

way to further introduction of radical new technology

products per se. Alternatively, the NPD process can

be improved without sacrificing product novelty (i.e.,

the degree to which new technology is incorporated in

the new offering). This is a very significant finding

with far-reaching implications because it suggests that

just using staging- or phasing-process discipline alone

will not necessarily propel a firm into optimization of

the NPD process.

Companies that have gone into the modified zone

of new product development no longer have to always

argue that a trade-off between quality, cost, and de-

livery is the norm. In fact, for the first time, the vaunt-

ed and venerable 50% reduction in development time

with no sacrifice in quality is now achievable and is

not just words in presentations or a dream that gen-

eral managers thought would never actually be ob-

tained. The 50% barrier has finally been broken—not

just by a few firms but by many. In interviews with

these firms, some report that they actually find design

reviews at gates redundant to the process now. All the

real work is done on line, in the virtual war room.

This study, like all empirical research, is not per-

fect. There is a method variance explanation for the

lack of support for the radical product technology-

modified Stage-Gates process that cannot be ruled

out as yet. This possible methodological issue is that

companies do not really adopt Stage-Gates before

they respond that they have modified this method.

That is, they have actually adopted an informal pro-

cess, similar to an earlier stage of development. This

suggests that survey methods need to be augmented

with in-depth comparative cases. This will be a meth-

odological challenge for future research in this arena.

The methodological implications of these prelim-

inary findings for research seem quite clear. Richer,

in-depth study of Stage-Gates modifications in

everal innovation variant contexts would appear to

be one of the next steps of this research stream. If

more innovative companies are more likely to modify

Stage-Gates , does the way in which these modifica-

tions proceed follow a much more complex causal

model? For example, do products group by industry,

which in turn predicts back-tracking as opposed

to project management modified Stage-Gates

processes? Further, the extent to which both product

and process innovation is evident in projects might

also influence how Stage-Gates is modified. What is

missing in this scenario is whether or not these con-

tingent approaches have outcome implications as sug-

gested by anecdotal evidence.

The implications for management of the NPD pro-

cess also appear to follow a pattern. More innovative

firms are more creative with the Stage-Gates process.

Information technology and strategy for new product

development are very much a part of this pattern.

Clearly, there is a role for all levels of management

based on these results. General managers orchestrate

strategies, and project managers modify Stage-Gates

accordingly. The great challenge now, for which this

study does not have an answer, is how complex enter-

prise systems will be integrated with these virtual engi-

neering support technologies. This research lies ahead.

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modified stage-gate® regimes in new product development

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