An expert system for new product development projects
| Published date | 01 October 2000 |
| Pages | 317-324 |
| Date | 01 October 2000 |
| DOI | https://doi.org/10.1108/02635570010291784 |
| Author | R. Balachandra |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
An expert system for new product development
projects
R. Balachandra
Northeastern University, Boston, Massachusetts, USA
Introduction
Considering the fact that hardly ten out of
every 100 new product ideas achieve
commercial success (The Wall Street Journal,
1992), there has been a constant search for
indicators of success for new product
development (NPD) projects. The topic has
been examined from a variety of different
fields ± marketing, R&D management, project
management, and economics to name a few.
There is, however, no consensus on which
factors are really important for predicting
the success or failure of a NPD project. Some
studies list as few as three factors, while
others list over 12. Only a few factors appear
in more than one study, while many are
unique to a particular study. A recent review
of the available literature revealed the fact
that there are over 70 factors considered
critical for the success of a NPD project
(Balachandra and Friar, 1997). In addition,
some of these factors are actually composites
of further sub-factors.
The study also revealed that the effects of
some factors were contradictory and the
emphasis placed on different factors varied
in different studies. Some studies claimed the
presence of a project champion was very
important, while many did not even mention
a project champion. Some studies insisted
that a thorough marketing analysis was
necessary for success, while some others
claimed that market analysis was either
impossible or irrelevant. A thorough
analysis of the literature suggested that the
contradictions and anomalies were possibly
due to the fact that the studies were
considering different sets of projects.
Depending on the nature of the project, it is
possible that different factors become more
important. Such reasoning led to the
development of a contextual model for NPD
projects (see Balachandra and Friar (1997) for
a comprehensive discussion). This model
proposes three contextual dimensions ± type
of market, type of innovation and type of
technology. The relative importance placed
on different sets of factors while evaluating a
NPD project will depend on the specific
contextual factor combination of the project.
For example, if a project is of a radical
innovation, planned for a new market in the
high technology field, there is really no way
one could undertake a complete market
analysis ± the potential customers are still
not known. Even if the potential customers
are identified, they could not conceive of the
potential uses for the product. Market
analysis is almost impossible, and one has to
go with so-called gut feel. A recent pilot study
provided partial validation of this model
(Balachandra and Friar, 1998).
The contextual nature of the project also
affects how the project is managed. For
example, if the project is planned for an
existing market, and with incremental
innovation, then one needs to set up a more
organized project management with specific
time and cost schedules, as most of the steps
in the development phase are well known,
and the firm has experience. On the other
hand, one has to have a more flexible
organization for a project in the radical
innovation category in an unfamiliar
technology. The time and cost schedules may
have to be flexible in such a situation.
Identifying the contextual variable
combination of a NPD project is not easy in
many situations. One has to determine the
type of innovation, the nature of the market,
and the type of technology of the planned new
product. Even in some of the simplest
situations there are many subjective factors
needed to make such evaluations. Without
proper identification of the factors, one may
be led to incorrect classifications leading to
wrong factors being chosen as being
important; the management approach
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Industrial Management &
Data Systems
100/7 [2000] 317±324
#MCB University Press
[ISSN 0263-5577]
Keywords
Expert systems,
New product development,
Success,
Project management
Abstract
New product development (NPD)
project studies have attempted to
identify a common set of factors
that will indicate whether a NPD
project will succeed or fail. A
recent study has shown that there
is no universal set of factors; also
some factors have contradictory
effects on a project's success.
A framework that classifies NPD
projects into different contextual
groups explains these anomalies.
The grouping helps in determining
the appropriate weights for the
different success/failure factors,
and the type of management
organization and approach
suitable for the project. The many
subjective elements make
classifying NPD projects into their
appropriate contextual grouping
difficult. Describes a rule-based
expert system which classifies
NPD projects into their
appropriate contextual groupings,
suggests the level of emphasis for
different success/failure factors
and the right approach for
managing.
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