9261

JIEM, 2011 – 4(4):746-770 – Online ISSN: 2013-0953 – Print ISSN: 2013-8423
http://dx.doi.org/10.3926/jiem.334
– 746 –
A framework for successful new product development
Nadia Bhuiyan
Concordia University (CANADA)
bhuiyan@alcor.concordia.ca
Received February 2011
Accepted November 2011
Abstract:
Purpose: The purpose of this paper is to propose a framework of critical success
factors, metrics, and tools and techniques for implementing metrics for each stage
of the new product development (NPD) process.
Design/methodology/approach: To achieve this objective, a literature review
was undertaken to investigate decades of studies on NPD success and how it can
be achieved. These studies were scanned for common factors for firms that
enjoyed success of new products on the market.
Findings: The paper summarizes NPD success factors, suggests metrics that
should be used to measure these factors, and proposes tools and techniques to
make use of these metrics. This was done for each stage of the NPD process, and
brought together in a framework that the authors propose should be followed for
complex NPD projects.
Research limitations/implications: Several different research directions could
provide additional useful information both to firms finding critical success factors
(CSF) and measuring product development success as well as to academics
performing research in this area. The main research opportunity exists in
implementing or testing the proposed framework.
Practical implications: The framework can be followed by managers of complex
NPD projects to ensure success.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 747 –
Originality/value: While many studies have been conducted on critical success
factors for NPD, these studies tend to be fragmented and focus on one or a few
phases of the NPD process. To the authors’ knowledge, this is the first time a
framework that synthesizes these studies into a single framework.
Keywords: new product development, critical success factors, metrics, tools and
techniques
1 Introduction
The new product development (NPD) literature emphasizes the importance of
introducing new products on the market for continuing business success. Its
contribution to the growth of the companies, its influence on profit performance,
and its role as a key factor in business planning have been well documented (Booz,
Allen & Hamilton, 1982; Crawford, 1987; Urban & Hauser, 1993; Cooper, 2001;
Ulrich & Eppinger, 2011). New products are responsible for employment, economic
growth, technological progress, and high standards of living. Therefore, the study of
NPD and the processes through which they emerge is important.
In the last few decades, the number of new product introductions increased
dramatically as the industry became more aware of the importance of new products
to business. Correspondingly, managing the NPD process has become a challenge
for firms as it requires extensive financial and human resources and is time
sensitive. The harsh realities are that the majority of new products never make it to
market and those that do face a failure rate somewhere in order of 25 to 45
percent (Crawford, 1987; Cooper, 2001). For every seven new product ideas, about
four enter development, one and a half are launched, and only one succeeds (Booz,
Allen & Hamilton, 1982). Despite the extensive research on how to achieve success
in NPD, firms continue to deliver products that fail and therefore NPD ranks among
the riskiest and most confusing tasks for most companies. As the number of dollars
invested in NPD goes up, the pressure to maximize the return on those investments
also goes up. It becomes worse as an estimated 46 percent of resources allocated
to NPD are spent on products that are canceled or fail to yield an adequate financial
return.
In this paper, we propose a framework that identifies the critical success factors
(CSF) for each phase in the NPD process, metrics to measure them, and the tools
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 748 –
and techniques that can be used to evaluate each metric. Our study is based on an
extensive review of the NPD literature. The paper is presented as follows. In the
next section, we discuss the NPD process, followed by a discussion of critical
success factors and metrics. Our framework is then described in detail, and we
conclude with a discussion of our work.
2 New product development
The NPD process consists of the activities carried out by firms when developing and
launching new products. A new product that is introduced on the market evolves
over a sequence of stages, beginning with an initial product concept or idea that is
evaluated, developed, tested and launched on the market (Booz, Allen & Hamilton,
1982). This sequence of activities can also be viewed as a series of information
gathering and evaluation stages. In effect, as the new product evolves,
management becomes increasingly more knowledgeable (or less uncertain) about
the product and can assess and reassess its initial decision to undertake
development or launch. Following this process of information gathering and
evaluation can lead to improved new product decisions on the part of firms by
limiting the level of risk and minimizing the resources committed to products that
eventually fail. The NPD process differs from industry to industry and from firm to
firm. Indeed it should be adapted to each firm in order to meet specific company
resources and needs (Booz, Allen & Hamilton, 1982).
Many researchers have tried to develop a model that captures the relevant stages
of the NPD process (Ulrich & Eppinger, 2011; Wind, 2001; Cooper, 2001; Crawford,
1987; Scheuing, 1974). A number of detailed NPD models have been developed
over the years, the best known of which is the Booz, Allen and Hamilton (1982)
model, shown if Figure 1, also known as the BAH model, which underlies most
other NPD systems that have been put forward. This widely recognized model
appears to encompass all of the basic stages of models found in the literature. It is
based on extensive surveys, in depth interviews, and case studies and, as such,
appears to be a fairly good representation of prevailing practices in industry.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 749 –
Figure 1. Stages of New Product Development (NPD) (Booz, Allen & Hamilton,
1982)
The stages of the model are as follows:



New Product Strategy: Links the NPD process to company objectives and
provides focus for idea/concept generation and guidelines for establishing

screening criteria.
 Idea generation: Searches for product ideas that meet company objectives.



Screening: Comprises of an initial analysis to determine which ideas are
pertinent and merit more detailed study.



Business Analysis: Further evaluates the ideas on the basis of quantitative
factors, such as profits, Return-on-investment (ROI), and sales volume.



Development: Turns an idea on paper into a product that is demonstrable
and producible.



Testing: Conducts commercial experiments necessary to verify earlier
business judgments.

 Commercialization: Launches products.
Booz, Allen and Hamilton (1982) found that companies that have successfully
launched new products are more likely to have some kind of formal NPD process
and that they generally pass through all of the above stages. Our framework is
based on the BAH model, however, we exclude the commercialization stage; while
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 750 –
this stage represents an important area of concern, our study deals with the precommercialization stages of the NPD process.
2.1 Critical success factors
Over the last two decades, several studies have examined the determinants of NPD
success and identified many factors that distinguish successful products from
unsuccessful ones. Factors that are necessary and guarantee commercial success
are termed as critical success factors (CSF): it is imperative to reflect on how one
can benefit from each and how one can translate each into an operational aspect of
the NPD process. Daniel (1961) and Rockart (1979) proposed that organizations
need to identify factors that are critical to the success of that organization, and
they suggested that the failure to achieve goals associated with those factors would
result in organizational failure. In fact, it is even suggested that NPD itself is a CSF
for many organizations. Given that this is now a well-known fact, the idea is to
determine what factors in NPD are essential for success, and how to measure the
extent of this success. The challenge is to design a process for successful product
innovation – a process whereby new product projects can move quickly and
effectively from the idea stage to a successful launch and beyond.
2.2 Metrics
A metric tracks performance and allows a firm to measure the impact of process
improvement over time. Metrics can play an important role in helping companies to
enhance their NPD efforts and are important for at least three reasons. First,
metrics document the value of NPD and are used to justify investments in this
fundamental, long term, and risky venture. Second, good metrics enable Chief
Executive Officers and Chief Technical Officers to evaluate people, objectives,
programs, and projects in order to allocate resources effectively. Third, metrics
affect behavior. When scientists, engineers, managers, and other NPD employees
are evaluated on specific metrics, they often make decisions, take actions, and
otherwise alter their behavior in order to improve the metrics. The right metrics
align employees’ goals with those of the corporation; wrong metrics are
counterproductive and lead to narrow, short-term, risk-avoiding decisions and
actions.
Any metric that might be applied to NPD will often focus on one function or another
or on the entire NPD process. But no one function is the sole contributor to the
process that produces new products. A metric for the productivity of the R&D
organization, for example, may show constant improvement. In spite of this
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 751 –
improvement, however, there may be no improvement in the rate at which new
products reach the market (Beliveau et al., 2002). What is important to measure is
the effectiveness of the stages of NPD process in an interdependent fashion. A lack
of useful metrics is undoubtedly one reason that the success rate of NPD has not
improved appreciably over the past 40 years Crawford (1979, 1992). If companies
had reliable metrics to gauge their performance, then specific problem areas could
be addressed and managers might see the same improvement in their NPD efforts
that they come to expect from their quantifiable total quality management
programs (Lynn & Reilly, 2000).
3 Critical success factors and metrics for stages of the NPD process
In what follows, each stage of the NPD process and its respective CSFs, metrics,
and tools and techniques for measuring progress are explained in detail.
3.1 New Product Strategy
Prior to commencing an NPD project, companies must set objectives and devise a
clear new product strategy (NPS) to meet them (Wind, 1982). The purpose of this
stage is to provide guidance for the new product effort. It identifies the strategic
business requirements that the new product should comply with, and these are
derived from the corporate objectives and strategy of the firm as a whole. These
business requirements assign roles to be played by the new products, which in turn
are influenced by the needs of the industry (Booz, Allen & Hamilton, 1982).
CSFs for NPS
A firms’ strategy should provide a clear understanding of the goals or objectives for
the company’s new product program, and should indicate the return-on-investment
(ROI) expected such that the contribution of new products to corporate goals is
well-understood. Furthermore, clearly defined arenas, i.e., specified areas of
strategic focus, such as products, markets, or technologies, are needed to give
direction to the firm’s total new product program.
The problem at this stage is not only one of developing a clear strategy but also its
implementation, i.e., translating the strategy into terms that everyone understands
to bring focus to day-to-day actions, and communicating the strategy with other
members in the organization. Prior research suggests that companies that
recognize the importance of interventional coordination and effectively sharing an
NPS across departments will have more successful new products (Cooper, 1999).
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 752 –
The role of new products in achieving company goals was clearly communicated to
all in such firms. Thus, once a clear NPS is defined, the related confounding
problem is communicating clearly the needs, requirements, resources, and plans for
a new product effort – in essence, internalizing the strategy. This communication
must take place in multiple forms; however, a well-documented plan and
specification must serve as the foundation. In summary, the establishment and
communication of a clear plan and a strategy for an NPD project is a key requisite
for success. Businesses that have a well-articulated NPS fare much better than
those lacking in this aspect and they have 32 percent higher NPD success rates,
meet sales objectives 42 percent more often, and meet profits objectives 39
percent better (Cooper & Kleinschmidt, 1995).
Metrics for NPS
The return-on-investment (ROI) compares the company’s yearly income with the
investment in the asset. While the ROI is not too challenging, management should
understand how the ROI benchmarks have been calculate so that relevant
comparisons can be made for the project under evaluation. A company’s ROI
proves to be useful in setting the new product goals. This metric will help to
determine if the cost to develop a new product exceeds the resulting benefit, or if
the payback affects the corporate bottom line. The aim here is to compare the
return expected to be received from the project with some pre-established
requirement. This long-term metric set by the corporate objectives should be linked
with the NPS.
Tools and techniques for NPS
The Balanced Scorecard (BSC) provides the instrument the firm needs to navigate
to future competitive success (Kaplan & Norton, 1996). BSC translates an
organization’s strategy into a comprehensive set of performance measures that
provides the framework for a strategic measurement and management system. The
scorecard measures organizational performance drivers across four perspectives
which provide its framework: financial, customers, internal business processes, and
learning and growth. The objectives and the measures of the BSC are the collection
of financial and non-financial performance measures; they are derived from a topdown process driven by the strategy of the business unit. The measures are
balanced between the outcome measures – the results from past efforts – and the
measures that drive future performance. The scorecard is balanced between
objectives, easily quantified outcome measures and subjective performance drivers
of the outcome measures. Organizations should use the scorecard as a strategic
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 753 –
management system, to manage their strategy over the long run and use it for the
measurement focus of the scorecard to accomplish critical management processes,
including communicating and linking strategic objectives and measures.
The BSC strategic objectives and measures are communicated throughout an
organization via company newsletters, bulletin boards, videos, and even
electronically through groupware and networked personal computers. The
communication serves to signal to all employees of the critical objectives that must
be accomplished if an organization’s strategy is to succeed. Once all employees
understand high-level objectives and measures, they can establish local objectives
that support the business unit’s global strategy.
The organizational communication and education program should not only be
comprehensive but also periodic. Multiple communication tools can be used to
launch the BSC program: executive announcement, videos, meetings, brochures
and newsletters. This initial announcement should then be followed continually, by
reporting scorecard and outcomes on bulletin boards, newsletters, groupware, and
electronic networks. The design of such a program should begin by answering
fundamental questions:
 What are the objectives of the communication strategy?
 Who are the target audiences?
 What is the key message for each audience?
 What are the appropriate media for each audience?
 What is the time frame for each stage of the communication strategy?
 How will top management know that the communication has been received?
The BSC links financial objectives to corporate strategy. The financial objectives
serve as the focus for the objectives and measures in all the other scorecard
perspectives. Every measure should culminate in improving financial performance.
The scorecard starts with long-run financial objectives, and then links them to the
sequence of actions that must be taken with financial processes, customers,
internal processes, and finally employees and systems to deliver the desired long
run economic performance. Many corporations, however, use identical financial
objectives for all of their divisions and business units. This uniform approach is
certainly feasible, consistent, and fair since all business unit managers will be
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 754 –
evaluated by the same metric, but different business units may follow quite
different strategies.
3.2 Idea Generation
After setting a well-defined NPS for NPD, the idea generation stage begins, where
the search for product ideas is made to meet company objectives. The idea
generation concerns the birth, development, and maturation of a concrete idea.
After defining the markets and segments based on the NPS it wishes to target, the
firm must advance and nurture ideas wherever they occur to take advantage of the
identified opportunities. As per the study done by Booz, Allen and Hamilton (1982),
a firm has to generate at least seven ideas to generate one successful. Griffin
(1997) says that an average of 100 ideas must be generated in order to yield 15.2
successes.
The main purpose of this stage is to create a number of different ideas from which
the firm can select the most feasible and promising one(s). A greater likelihood of
achieving success depends in part on the number of ideas generated. Firms that are
effective at idea generation are those that do not focus solely on the first source to
generate ideas, i.e. ideas that are originated from inside the firm, but that
concentrate on all potential idea sources (Crawford, 1997). There is a multitude of
sources as well as many different methods to generate ideas. The firm can derive
new ideas from internal sources (i.e., employees, managers), external sources (i.e.,
customers, competitors, distributors, and suppliers), and from implementing formal
research and development. Brainstorming, morphological, analysis and gap analysis
are most commonly employed methods for generating ideas (Crawford, 1997).
Customers can be an especially good place to start searching for new product ideas.
The relatively high rate of success for product ideas originated from marketing
personnel and customers (Souder, 1987).
CSF for Idea Generation
Customer focused idea generation is a CSF for this stage as per studies done by
many researchers that show that a thorough understanding of customer’s needs
and wants is vital for new product success (Cooper, 1993; Crawford, 1987).
Successful businesses and teams that drive winning new products have a dedication
towards the voice of the customer. A strong customer involvement is necessary
right from the idea generation stage. According to Souder’s (1987) review of causes
of NPD success and failure, he concluded that internally generated ideas had lower
success rates then externally generated ideas. A relatively high rate of success is
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 755 –
achieved for project ideas that originated from marketing and customers as
compared to ideas originating from R&D, suppliers, and management.
Metrics for Idea Generation
Metrics to track idea generation and enrichment include: number of ideas
generated from the customer, number of ideas retrieved and enhanced from an
idea portfolio, number of ideas generated over a period of time, and the value of
ideas in idea bank. Among all of these metrics, the number of ideas generated from
the customer is the most associated with the CSF of the idea generation stage.
Firms must devote more resources to customer based idea generation activities,
such as focus groups with customers; detailed, one-on-one interviews with
customers; customer site visits, especially by technical people; the active
solicitation of ideas from customers by the sales force; and the development of a
relationship with lead users (Cooper, 1999).
Tools and techniques for Idea Generation
Understanding customer and market needs is a consistent theme for successful
product development in studies by Song and Parry (1996) and Cooper (1999).
There are many creativity and brainstorming techniques for enriching the idea
stream. Effective methods for enriching the customer based idea stream utilize lead
user methodology and ethnographic approaches.
The lead user methodology takes a different approach as compared to traditional
approaches in which ideas are generated based on customer input and usually
collect information on new product needs from a random or typical set of
customers. The lead user process collects information about both needs and
solutions from the leading edges of the target market and from markets facing
similar problems in a more extreme form. The rich body of knowledge collected
during this process continues to be useful during the remaining steps of product
development and marketing (Lilien et al., 2002).
An ethnographic approach is a descriptive, qualitative market research
methodology for studying the customer in relation to his or her environment
(Cooper & Edgett, 2008). Researchers spend time in the field observing customers
and their environment to acquire a deep understanding of customer’s lifestyles or
cultures as a basis for better understanding their needs and problems. In this
approach, observation, interviews and the documentation are done for traces that
people leave as they go about their everyday lives. Since it allows the use of
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 756 –
multiple converging perspectives – what people say, do, and use – it will always
reveal more and provide greater insight. This deeper level of understanding is
derived from customer to generate customer-based ideas.
3.3 Screening and Business Analysis
While the screening and business analysis are proposed as two different stages in
the BAH model, we consider the two stages as one for simplicity of the proposed
framework. In the screening stage, initial analysis is done based on the NPS,
resources and competition, while in the business analysis stage, ideas are
evaluated using quantitative performance criteria. After gathering enough new
product ideas through various sources from the idea generation stage, which ideas
to pursue will be selected based on the business value they bring. Making a good
selection is critical to the future health and success of the business. The point is
that product development costs rise substantially with each successive stage in the
NPD process (Booz, Allen & Hamilton 1982). The ideas that have been classified as
“Go” ideas must be screened further using criteria set up by top management
(Cooper & de Brentani, 1984; de Brentani, 1986). These ideas must be described
on a standard form that can be accessed by a new product committee. The
committee then assesses each idea against a set of criteria, which verify the
attractiveness and visibility of the idea as well as its fit with the company’s
strategy, objectives and resources. The ultimate result from screening and
evaluation is a ranking of NPD proposals, such that the resources can be allocated
to the projects that seem most promising (Crawford, 1997; Wind, 1982).
After screening, the business analysis is the detailed investigation stage that clearly
defines the product and verifies the attractiveness of the project prior to heavy
spending. According to Cooper’s NewProd studies of new product, it was shown that
weakness in the upfront activities seriously compromises the project performance.
Inadequate market analysis and a lack of market research, moving directly from an
idea into a full-fledged development effort, and failure to spend time and money on
the up-front steps, are familiar themes in product failures. The quality of execution
of the predevelopment steps is closely tied to the product’s financial performance
(Cooper, 1980).
In every successive stage of the NPD process, as estimates become more refined
and accurate, companies should continue conducting financial evaluation
throughout the NPD process, but at this stage it is critical. A review of a costs,
potential sales and profit projections of the new product are undertaken in order to
determine whether these factors satisfy the company’s objectives or not. If a result
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 757 –
from this stage shows that the product meets the objectives, then the new product
concept can move to the development stage. According to Griffin (1997) among the
firms taking part in study, 75.6% developed formal financial objectives against
which performance was measured. The final component of the business analysis
stage is the action plan. A detailed plan of action is created for the next stage and
tentative plans are developed for all subsequent stages. This critical stage opens
the door to a significant commitment of resources and to a full-fledged
development program based on financial analysis which forms the base for the CSF
and its metrics proposed for this stage.
CSF for Screening and Business Analysis
Up-front homework is a CSF for the screening and business analysis stage as too
many new product projects move from the idea stage right into development with
little or no early preparation (Rosenau et al., 1996). The results of this approach
are usually disastrous. Up-front homework includes activities such as financial
analysis, undertaking thorough market and competitive analyses, research on the
customer needs and wants, concept testing, and technical and operations feasibility
assessments. Solid pre-development work drives up new product success rates
significantly and is strongly correlated to financial performance. All of these
activities lead to solid business analysis prior to beginning serious development
work. Firms devote on average only seven percent of a project’s funding and 16
percent of the person-days to these critical up-front homework activities, which is
not enough to make a successful product according to the NewProd (1999) study.
The conclusion is that more time and resources must be devoted to the activities
that precede the design and development of the product.
As per a study done by Cooper et al. (2000), the most dominant method used by
40.4% of businesses for performance results is a financial approach, followed by
strategic approaches and scoring models. Using financial methods, profitability,
return, payback or economic value of the project are determined and projects are
judged and rank-ordered on these criterion.
Metrics for Screening and Business Analysis
Financial or economic models treat project evaluation much like a conventional
investment decision. The expected commercial value (ECV), net present value
(NPV), internal rate of return (IRR), and the profitability index (PI), are metrics that
are proposed as being most useful for measuring the success of the screening and
business analysis stage. These metrics should be used to rate, rank order, and
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 758 –
ultimately select projects. All metrics have their own advantages and
disadvantages. For example, the NPV method ignores probabilities and risk; it
assumes that financial projections are accurate and financial goals are important.
The ECV depends on extensive financial and other quantitative data. These metrics
together give clearer details about the project’s financial performance to help select
the best project from the group.
Tools and techniques for Screening and Business Analysis
The financial methods of evaluation for the proposed metrics and how they
measure the financial performance of each project are explained below.
The Expected Commercial Value (ECV) method seeks to maximize the value or
commercial worth of the project, subject to certain budget constraints, and
introduces the notion of risks and probabilities. The ECV method determines the
value or commercial worth of each project to the corporation. The calculation of the
ECV is based on a decision tree analysis and considers the future stream of
earnings from the project, the probabilities of both commercial success and
technical success, and both commercialization costs and development costs.
Therefore, the ECV measures the value of the project in terms of its expected
financial returns from the perspective of the company’s overall commercial strategic
objectives. In order to arrive at a prioritized list of projects, the ECV of each project
is determined projects are rank ordered accordingly.
The net present value (NPV) criterion for evaluating proposed capital investments
involves summing the present values of cash outflows required to support an
investment with the present value of the cash inflows resulting from operations of
the project. The inflows and outflows are discounted to present value using the
firm’s required rate of return for the project. If the NPV is positive, it means the
project is expected to yield a return in excess of the required rate; if the NPV is
zero, the yield is expected to exactly equal the required rate; if the NPV is negative,
the yield is expected to be less than the required rate. Hence, only those projects
that have a positive or zero NPV meet the criterion for acceptance.
The internal rate of return (IRR) is that rate which exactly equates the present
value of the expected after-tax cash inflows with the present value of the after-tax
cash outflows. Once the IRR of a project has been determined, it is a simple matter
to compare it with the required rate of return to decide whether or not the project
is acceptable. If the IRR equals or exceeds the required rate, the project is
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 759 –
acceptable. Ranking the projects is also a simple matter. Projects are ranked
according to the IRRs: the project with the highest IRR is ranked first and so on.
The profitability index (PI) is the ratio of the present value of the after-tax cash
inflows to the outflows. A ratio of one or greater indicates that the project in
question has an expected yield equal to or greater than the discount rate. The
profitability index is a measure of a project’s profitability per dollar of investment.
As a result, it is used to rank projects of varying costs and expected economic lives
in order of their profitability. Projects are rank-ordered according to this
productivity index in order to arrive at the preferred portfolio, with projects at the
bottom of the list placed on hold. In order to ensure that project ideas are carefully
screened, and that the business analysis is carefully carried out, these metrics are
certain to help select projects so as to maximize the sum of the values of all active
projects in the firm’s pipeline in terms of business objectives.
3.4 Development
Once the results of the business case of the new product conform to company
objectives, the new product team can move on to the development stage, which is
made up of activities that range from prototype development to volume ramp up
and test marketing. The interaction between the program and project manager is
no longer one of selling or buying the concept, but rather one of bringing the
product to market on time, within budget, and to the required specifications.
On average, one third of total NPD expenditures are committed during this stage
with 40 percent of total NPD time (Cooper, 1999). In the development stage,
business case plans are translated into concrete deliverables. What is critical for
success at this stage to move through development to launch as quickly as possible
and to ensure that the product prototype or final design does indeed meet
customer requirements, which requires seeking customer input and feedback
throughout the entire development stage. It is important to gain competitive
advantage and to enjoy the product’s revenues as soon as possible and it also
minimizes the impact of a changing environment. Thus, as the product proceeds
from one step of the development stage to the next, the new product team should
reassess the market, position, product, and technology in order to increase chances
of delivering a successful product (Cooper, 1993; Urban & Hauser, 1993).
Marketing and R&D functions in particular should collaborate because, while
marketing can express the needs of customers, R&D has the capacity of turning a
product concept into an actual physical entity. Therefore they should work together
to ensure the product meets customer requirements. Cross-functional teams are
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 760 –
widely used in companies to help in identifying and solving problems efficiently by
coordination of resources and ideas. Customer input and feedback is a critical
activity throughout development, both to ensure that the product is right and also
to speed development toward a correctly defined target.
CSFs for Development
Development of new products often takes years, and much that is unexpected can
occur during this time frame. The market may change partway through
development, making the original estimates of market size and product acceptance
invalid. Customer requirements may shift, rendering the original set of product
specifications obsolete. Competitors may introduce similar products in the
meantime, creating a less receptive market environment. These and other external
changes mean the original product definition and justification are no longer valid.
Reducing development time is a vital competitive weapon and yields competitive
advantage; it means that there is less likelihood that the market or competitive
situation has changed by time the product reaches the market and it means a
quicker realization of profits Cooper (1993, 1999, 2001). Companies that develop
products quickly gain many advantages over their competitors: premium prices,
valuable market information, leadership reputation with consumers, lower
development costs, and accelerated learning (Cooper, 2001). Therefore, the goal of
reducing the development time is critical. Most importantly, fast development
minimizes the impact of a changing environment. If the development time can be
reduced from eighteen months to nine, the odds of things changing are similarly
greatly reduced that makes the need to reduce the time during the development
stage. Most firms have reduced product development times over the past five years
with the average reduction being about the one-third. In short, the challenge here
is to shorten development time so as to minimize the chances that the development
target has changed.
Seeking customer feedback is a vital activity throughout development stage, both
to ensure that the product design is right and also to speed development toward a
correctly defined target. The original voice-of-customer research that was done
prior to development may not be enough to resolve all the design problems during
development (Cooper, 1999). Customer feedback is perhaps the most certain way
of seeking continual and honest customer input during the development phase.
Seeking customer input should become an integral part of the design team to speed
up and make development stage successful.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 761 –
Metrics for Development
Development time is defined as the duration from the start to completion of the
development stage, i.e., the length of time to develop a new product after passing
business case stage to initial market sales. Precise definitions of the start and end
point vary from one company to another, and may also vary from one project to
another within the company. How quickly the team moves through this stage is
critical for the reasons stated earlier, and as such, it is imperative that the team
measures their progress according to time.
A cross-functional team is defined as a team consisting of representatives from the
various functions involved in product development, usually including members from
marketing, R&D, and operations (and perhaps others, such as purchasing, as
needed). The most effective development teams also involve suppliers in the early
stages of development, and frequently rely on suppliers for a large portion of the
subsystem design (Clark & Fujimoto, 1988). Cross-functional teams have replaced
a more functional approach in which each team relinquishes project responsibility to
a down-stream function (e.g. the engineering team hands-off to the manufacturing
team). This paradigm requires frequent communication between functions
represented on the team and co-location greatly facilitates this process. Crossfunctional teams are essential for timely development, improving design quality,
and lowering development costs. Cross-functional integration that really matters
occurs when individual design engineers work together with individual marketers or
process engineers to solve joint problems in development. True cross-functional
integration occurs at the working level. It rests on the foundation of tight linkages
in time and in communication between individuals and groups working closely
related problems. How these groups work together determines the extent and
effectiveness of integration in the design and development of the product
(Wheelwright & Clark, 1992).
Related to the above is the degree to which team members are committed, or
dedicated, to the project. Since project team members’ time commitments are
typically spread across a number of projects at any one time because departmental
managers are vying for team members’ time, team members are often on and off
development projects. This creates a discontinuity and increases development time.
It is in this stage that it is crucial to have a team with dedicated team members. A
dedicated, accountable team leader- that is, not doing too many other projects or
other assignments at the same time, and held accountable for the result.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 762 –
Parallel processing involves activities that are undertaken concurrently (rather than
sequentially), thus more activities are undertaken in an elapsed period of time. The
purpose is to achieve product designs that reflect customer wants as well as
manufacturing capabilities and to do so in the shortest possible time. However, due
to the need for prerequisite information, not all activities or phases in the NPD
process can be overlapped with minimal risk. Therefore, the degree of parallelism
must be measured to ensure minimal downstream risk.
The degree of design effort on real customer needs is a qualitative in-process
metric which ensures as much as possible that the final design meets customer
requirements. This requires seeking customer input and feedback throughout the
entire development stage and thus the customer becomes an integral part of the
design team to overcome technical problems that arise and that necessitate product
design changes during the development stage. Customer needs and wants
assessment must be a vital and ongoing activity throughout development, both to
ensure that the product is designed right and also to speed development toward a
correctly defined target.
Tools and techniques for Development
The literature review has shown that there exist a number of tools and techniques
to reduce development times that are consistent with sound management practice.
Dynamic time to market is a tool which can be useful in predicting the end date of
the said project as well as in tracking the progress of a project. It works in the
following way: when a schedule prediction is made, the prediction date is plotted
against the date the prediction was made. By assessing dynamic time to market,
the team members will get an early warning of potential late delivery and
appropriate action can usually be taken by the team to maintain schedule integrity.
Thus projects are kept on schedule to achieve timely product development.
The degree of team cohesiveness gauges the growth of the team as a working
group and it is a function of length of time that a team has worked together in a
past or present project (Balakrishnan, 1998). It is the extent to which team
members are attracted to the team and motivated to remain in it.
Overlapping means doing various activities in parallel rather than doing them
sequentially. By overlapping activities, the cycle time, i.e. the total time taken to
complete the product development from concept until the product reaches market,
can be greatly reduced. Overlapping activities saves time due to 1) parallel
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 763 –
processing of activities, 2) better and more timely identification of design problems,
and 3) improved communication earlier and throughout the team. This metric
serves as an indicator of the degree of concurrency in the process. In general, the
higher the number of overlapped activities, the higher the degree of concurrency
and the shorter is the development time. A lower number of overlapped activities
indicates a lower degree of concurrency in the process and may also indicate
opportunities for improving the process to achieve objectives.
3.5 Testing
The purpose of this stage is to provide final and total validation of the entire
project: the commercial viability of the product, its production, and its marketing
(Cooper & Kleinshmidt, 1987). Design and testing go hand in hand, with testing
being conducted throughout the development stage. Information obtained during
testing is used in developing the product. This phase is extremely important in that
it may dramatically decrease the chances of failure in launch, since it has the
capacity of revealing flaws that could cause market failure (Urban & Hauser, 1993).
Studies by Cooper (1998, 1999) show that a test phase that is customer oriented is
the critical factor – whether it is done and how well it is executed – is significantly
correlated with the new product success. Different types of testing, i.e. concept
testing, prototype/development testing, and test marketing, should be conducted in
this stage Cooper (1993, 1998, 2001). It should be noted, however, that testing
should not be solely restricted to this stage; it must be conducted throughout the
NPD process (Ulrich & Eppinger, 2011).
CSF for Testing
Product functionality is critical for the testing stage as the aim here is to see
whether a product with the attributes called for has been produced. It must be
proven that claimed attributes exist and the causes for missing attributes must be
found.
Customer acceptance is critical for this stage to gauge whether the product is
acceptable to the customer, to measure the customer’s level of interest, liking,
preferences, and intent to purchase, and to determine those benefits, attributes,
and features of the product to which the customer responds. Not only must the
product work right in the lab or development department, but, more importantly, it
must also work right when the customer uses it. The product must excite and,
indeed, delight the customer; who must find it not only acceptable but actually like
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 764 –
it better than what he or she is currently buying. In short, the customer reaction
must be sufficiently positive so as to establish purchase intent.
Metrics for Testing
The performance of a product is how well the product achieves the functionality
desired. Product performance is usually measured in such ways as testing physical
features, perceptual features, functional modes, and perceived benefits. Feature is
those aspects of an offering that create the benefits; they are typically a focal point
of NPD. Perceived benefits are the best point in the needs continuum on which to
focus conversations with customers because they represent customer-oriented
perceptions but are still close enough to supplier-oriented features to permit that
linkage to be made by the product developer. Validation and user testing
techniques are used to gather data on product performance. These primary
research techniques generate quantitative results. At this stage in the NPD process,
these are the types of research results necessary to make final critical decisions
and reduce the risk of possible failed launches.
Customer-perceived value is measured to determine whether the customer is
willing to purchase the tested product or not and to gauge whether the product is
acceptable to the customer. Important metrics for this stage are: perceived relative
performance, customer satisfaction (Like/Dislike), and the preference score to
determine the nature of the competitive situation. These are qualitative metrics,
but are very important nonetheless to record the basic likes/dislikes of the
customer early before the product gets launched into the market. Based on the
qualitative data, managers can take action to make changes in the product.
Tools and techniques for Testing
Validation testing is of a product model that closely resembles the final product that
will be manufactured and sold, and is often called system testing and usually takes
place in-house. The purpose of the testing process is to ensure that all product
performance requirements and design specifications have been met. The validation
test is normally conducted late in the development process to ensure that all of the
product design goals have been met. This includes usability, performance, and
robustness. Validation tests normally aim to evaluate actual functionality and
performance, as is expected in the production version and so activities should be
performed in full. It is probable that the validation test is the first opportunity to
evaluate all of the component elements of the product together, although elements
may have been tested individually already. Thus, the product should be as near to
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 765 –
representing the final item as possible, including packaging, documentation and
production processes. Also included within validation tests will be any formal
evaluation required for certification, safety or legislative purposes.
Data from a validation test is likely to be quantitative, based on measurement of
performance. Normally, this is carried out against some benchmark of expected
performance or criteria set before. Usability issues may be scored in terms of
speed, accuracy or rate of use, but should always be quantified. Issues such as
desirability may be measured in terms of preference or user ranking. Data should
also be formally recorded, with any failures to comply with expected performance
logged and appropriate corrective action determined.
User and field testing is performed by real users or customers, and in some cases,
this testing must precede product shipment. This is not to be confused with
marketing customer testing, where certain strategies regarding sale and marketing
of the product are explored. The purpose of testing is to understand how the
product performs in the end-user environment. Customer based testing is indeed
complex, and there is no way it can be simulated in laboratories, where use is
isolated from users’ mistakes, competitive trashing of the concept, and objections
by those in the user firm or family whose work or life is disrupted by the change.
Products that are entirely new to the market should receive beta testing because
there is no base of data on which to judge customer acceptance.
Test protocols are produced by the company and can range from rigorous to
nonexistent. In the first case, the developer closely monitors and follows up the
beta test with in-house staff or contracted staff from a specialty testing company.
In the second case the developer may simply contact the customer by phone or has
an group or individual contact to ask for opinions on the product. The test results
attempt to confirm that the user feels the same toward the prototype as toward the
verbal concept discussed earlier in the NPD stage. The results of the testing either
confirm that the product meets its requirement or show the areas where the
product is deficient, and is therefore a critical stage to be considered in the
development process.
3.6 Framework of CSFs, metrics and tools and techniques for NPD
The CSFs, metrics, tools and techniques proposed for successful NPD discussed in
the previous sections are all summarized in the framework proposed in Table 1.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 766 –

Stage

Critical Success
Factor

Metrics

Tools and Technique

New Product
Strategy

Clear Strategy

Return on Investment

Financial Analysis

Well Communicated
Strategy

Degree of Communication

Balanced-scorecard as
a Communication Tool

Idea
Generation

Customer Focused
Idea Generation

Number of Customer
Focused Ideas Generated

Lead User Methodology

Ethnographic Approach

Screening and
Business Case

Up-Front Homework

Expected Commercial Value
(ECV)

Financial Method of
evaluation

Net Present Value (NPV)

Internal Rate of Return
(IRR)

Productivity Index (PI)

Development

Speed

Development time

Team Cohesiveness

Customer feedback

Degree of functional
integration

Dynamic Time to
Market

Degree of team commitment

Degree of Parallelism

Concurrency of activities

Degree of design effort on
real customer priorities

Testing

Product Functionality

Product Performance

Validation Testing

Customer Acceptance

Customer-Perceived Value

User and Field Testing

Table 1. Critical Success Factors and Metrics for Stages of NPD Process
For each stage of the NPD process, the factors that are essential for success for
each stage, metrics which can be used to measure the performance of those
factors, and tools and techniques to implement the metrics are all detailed in the
framework. As a preliminary proposed framework, we believe that any complex
NPD project that follows this framework will have an increased chance at success.
4 Discussion and conclusions
New product success still remains the critical challenge for companies. Many
companies are aware of the major role new products must play in their future and
quest for prosperity: companies are constantly searching for ways to revitalize,
restructure and redesign their NPD practices and processes for better results.
This framework proposes that to achieve success, NPD firms should have a clear
and well communicated new product strategy. These firms should have well defined
new product arenas along with long term trust, with clear goals. Successful
businesses and teams of NPD have a dedication towards the voice of the customer.
It is critical that firm should gather as many ideas as possible and a large number
of these should come from customers so that the firm can be in a position to design
and develop winning new products. Up-front homework prior to the initiation of
product design and development is found to be a key factor in a firm’s success. The
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 767 –
quality of execution of the predevelopment steps – initial screening, preliminary
market and technical studies and business analysis – is closely tied to the products
financial performance. Firms should try to shorten the development time so as to
minimize the chances that the development and customer needs have changed
when the product comes into the market. It is important to verify and validate
product performance requirements and design specifications along with customer’s
acceptance before launching the product into the market via validation and user
field testing.
This paper explored and analyzed the NPD process and attempted to identify ways
in which firms can improve their performance when developing new products,
mainly through the study of factors that are critical to success. These factors were
identified through an extensive study of the practices and performance of
successful firms presented in the NPD literature. The CSFs which have been
described in the literature are generally defined for the overall development
process, rather than specifically addressing each stage. To overcome this problem,
this paper sought out CSFs for each stage of the process. Presumably, no other
study to date has developed such a framework, which can be crucial for NPD
success.
Several different research directions could provide additional useful information
both to firms finding CSF and measuring product development success as well as to
academics performing research in this area. The first research opportunity exists in
implementing or testing the proposed framework. This would be useful to do over
the longer term both among the community of NPD companies and through
academic research to determine the impact of this research on both practice and
research.
References
Balakrishnan, A. (1998). Concurrent engineering: Models and metrics. Master
dissertation, McGill University, Canada.
Belliveau, P., Griffin, A., & Somermeyer, S. (2002). Meltzer, R. in The PDMA
toolbook for new product development, New York: John Wiley & Sons.
Booz, Allen, & Hamilton. (1982). New product management for the 1980’s. New
York: Booz, Allen & Hamilton, Inc.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 768 –
Clark, K., & Fujimoto, T. (1988). Product development in the world auto industry:
Strategy, organization, and performance. Boston: Harvard Business School.
Cooper, R. (1980). Project NewProd: What makes a new product a winner? Quebec
Industrial Innovation Centre.
Cooper, R.G., & Kleinschmidt, E.J. (1987). New products: What separates winners
from losers?. Journal of Product Innovation Management, 4(3), 169-184.
http://dx.doi.org/10.1016/0737-6782(87)90002-6
Cooper, R. (1993). Winning at new products: accelerating the process from idea to
launch (1st Ed.). Massachusetts: Perseus Publishing.
Cooper, R. (1998). Product leadership: Creativity and launching superior new
products. Massachusetts: Perseus Books, Reading.
Cooper, R. (1999). From experience: The invisible success factors in product
innovation. Journal of Product Innovation Management, 16, 115-133.
http://dx.doi.org/10.1016/S0737-6782(98)00061-7
Cooper, R., Kleinschmidt, E., & Edgett, S. (2000). New problems, new solutions:
Making portfolio management more effective. Research Technology Management,
43(2), 18-33.
Cooper, R. (2001). Winning at new products: Accelerating the process from idea to
launch (3rd Ed.). Massachusetts: Perseus Publishing.
Cooper, R., & Edgett, S. (2008). Maximizing Productivity In Product Innovation.
Research Technology Management, 51(2), 47-58.
Cooper, R., & Kleinschmidt, E. (1995). Benchmarking the firm’s critical success
factors in new product development. Journal of Product Innovation Management,
12, 374-391. http://dx.doi.org/10.1016/0737-6782(95)00059-3
Cooper, R., & de Brentani, U. (1984). Criteria for screening new industrial products.
Industrial Marketing Management, 13, 149-156. http://dx.doi.org/10.1016/0019-
8501(84)90027-0
Crawford, C. (1979). New product failure rate- facts and fallacies. Research
Management, 9-13.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 769 –
Crawford, C. (1992). The hidden costs of accelerated product development. Journal
of Product Innovation Management, 9(3), 188-199. http://dx.doi.org/10.1111/1540-
5885.930188
Crawford, C. (1987,1997). New product management. (2nd Ed. & 5th Ed.). Illinois:
Richard D. Irwin.
Daniel, R. (1961). Management data crisis. Harvard Business Review, Sept-Oct,
111-112.
de Brentani, U. (1989). Success and failure in new industrial services. Journal of
Product Innovation Management, 6, 239-58. http://dx.doi.org/10.1016/0737-
6782(89)90077-5
Griffin, A. (1997). PDMA research on new product development practices: Updating
trends and benchmarking best practices. Journal of Product Innovation
Management, 14(6), 429-458. http://dx.doi.org/10.1016/S0737-6782(97)00061-1
Lilien, G., Morrison, P., Searls, K., Sonnack, M., & Hippel, E. (2002). Performance
assessment of the lead user idea generation process for NPD. Management
Science, 8(8), 1042-1059. http://dx.doi.org/10.1287/mnsc.48.8.1042.171
Kaplan, R., & Norton, D. (1996). The Balanced Scorecard, Boston. Massachusetts:
Harvard Business School Press.
Lynn, G., & Reilly, R. (2000). Measuring team performance. Industrial Research
Institute Inc., March-April 48-56.
Rockart, J. (1979). Chief executives define their own data needs. Harvard Business
Review, 57(2), 238-241.
Rosenau, M., Griffin, A., Castellion, G., & Anschuetz, N. (1996). The PDMA
Handbook of New Product development. John Wiley and Sons, Inc.
Scheuing, E. (1974), New product management. Hinsdale: The Darden Press.
Song, M., & Parry, M. (1996). What separates Japanese new product winners from
losers. Journal of Product Innovation Management, 13, 422-439.
http://dx.doi.org/10.1016/0737-6782(96)00055-0
Souder, W. (1987). Managing new products innovations. Massachussetts: D.C.
Health and Company.
Journal of Industrial Engineering and Management – http://dx.doi.org/10.3926/jiem.334
– 770 –
Ulrich, K.T. & Eppinger, S.D. (2011). Product Design and Development. McGrawHill.
Urban, C., & Hauser, J. (1993). Design and marketing of new products. New
Jersey: Prentice-Hall.
Wheelwright, S., & Clark, S. (1992). Revolutionizing product development. New
York: The Free Press.
Wind, Y. (1982). Product policy: Concepts, methods, and strategy. Reading, Mass:
Addison-Wesley.
Journal of Industrial Engineering and Management, 2011 (www.jiem.org)
Article’s contents are provided on a Attribution-Non Commercial 3.0 Creative commons license. Readers are allowed to
copy, distribute and communicate article’s contents, provided the author’s and Journal of Industrial Engineering and
Management’s names are included. It must not be used for commercial purposes. To see the complete license
contents, please visit http://creativecommons.org/licenses/by-nc/3.0/.