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Product and Process Innovation
A System Dynamics-Based Analysis of the Interdependencies
Peter M. Milling and J oachim Stumpfe
Industrieseminar der Universitat Mannheim
D - 68131 Mannheim, Germany
Phone: (++49 621) 181-17 50
Fax: (+449 621) 181-15 79
pmilling@ is.bwl.uni-mannheim.de
jstumpfe@ is. bwl.uni-mannheim.de
ABSTRACT
Innovation is regarded as a crucial factor for survival and competitive strength of
organizations. For industrial companies innovations of the product system and particularly
innovations of the processes generating these products are essential. The majority of the
scientific literature focuses either on product innovation or on process innovation. In many
cases the interaction between product and process innovation is not explicitly taken into
consideration.
Referring to the complexity and the inherent dynamics of the industrial innovation process
decision-making in innovation management is a challenging job. In addition to numerous
interactions with the environment the complexity of innovation processes in industrial
companies results from interactions between product and process innovation. An effective
innovation management has to take these interdependencies into account coming to a
congruent implementation of the different types of innovation.
In complex environments consequences of actions are often highly intransparent for decision
makers. This paper provides a System Dynamics approach reflecting the interdependencies
of the product-process innovation system. The System Dynamics model gives a first insight
into the dynamic consequences of actions in innovation management and allows to test
different innovation strategies. Finally, conclusions concerning the implementation of
product and process innovations in industrial companies can be drawn.
The Management of Innovation as a Complex Problem
Innovation is regarded as the focal point of an organization’s strategy and a crucial factor for
it’s competitive strength and survival. Organizations develop innovations to adapt to their
external environment and to react to perceived changes inside or outside the organization.
Innovations can be implemented in the organization’s outcomes, it’s structure, and it’s
processes in order to maintain or to improve the level of performance or effectiveness
(Damanpour, Gopalakrishnan 1999).
Various types of innovations can be differentiated: social, organizational, administrative or
technical, incremental or fundamental, product or process. In any organization a large number
of objects of the innovation process can be named. This paper examines product and process
innovations of industrial companies.
The management of innovation is located in a highly complex and dynamic environment.
There exists interaction inside the organization and interaction between the organization and
it’s environment. The underlying interdependencies are numerous and not always transparent.
Due to the complexity and the dynamic behavior of the system under investigation there is a
time gap between an action/decision and the evidence of it’s consequences what makes the
decision process even more difficult. Very often decisions which are crucial for an
organization’s survival have to be generated under lack of time. Due to this facts decision-
making in innovation management is a very difficult and risky task. Any approach providing
support and leading to more rational decision-making is welcome.
Decision-making at this level of complexity cannot be automated, but it can be substantially
supported by formalized models. A Decision Support System based on the System Dynamics
approach would be able to cover the complexity and inherent dynamics off the innovation
process. A thorough understanding of the system and it’s dynamic behavior is essential to
come to an effective and efficient management of the entire innovation process. A
comprehensive and causal approach to model building is required to explain and to help to
understand why specific behavior occurs (Milling 1996). A System Dynamics model can give
an idea of the dynamic consequences of actions in innovation management and allows testing
different innovation strategies. The objective is to come to coordinated and coherent policies
instead of isolated operations. The congruency and the synchronous adoption of different
innovation types is an important factor for organizational adoption (Damanpour,
Gopalakrishnan 1999).
Product and Process Innovation in Industrial Companies
In this paper special interest is drawn to the innovation process of manufacturing companies.
Innovation is regarded as a crucial factor for the survival and the competitive strength of any
industrial firm. Industrial firms have to adapt to increasing global competition and dynamics.
This results in a large number of innovative products, processes and services developed by the
companies. The part of new products in the companies’ product portfolio increased in the last
years. For industrial firms the development of new products and services is the engine of
growth. The firm’s competitive position is determined by the ability to innovate it’s product
portfolio and the time required to bring new products to the market. Firms have to launch
new sophisticated products in increasingly fast cycles and their ability to ramp up to full scale
production volume rapidly is crucial for success (Pisano 1997). With product life cycles
getting shorter it becomes even more essential to expand commercial production process
capacity rapidly to generate sales revenues and recoup development investments.
Innovation is the focal point in the business strategy of any industrial firm. Industrial
Companies are complex and dynamic systems showing numerous interactions with their
environment. The management of successful adoption of innovations in these companies is a
complex and difficult venture which has to take into account a large number of intemal and
extemal factors. Purpose of this paper is the investigation of the mutual interactions and
consequences of product and process innovations in manufacturing companies.
For industrial companies innovations of the product system and particularly innovations of the
related processes are essential. Due to technological facts there is a tight relationship between
technical products and the processes implemented to generate these products. Developing
innovation strategies management has to take into account the underlying product-process
interactions. Changes in the product system have significant consequences for the firm’s
manufacturing system and for technical and administrative processes (Utterback, Abernathy
1975; Hayes, Wheelwright 1979 a, 1979b; Kim et al. 1992). Before introducing new
products changes in process requirements have to be considered.
The tightness of the relationship between product and process features varies with the
industrial sector. In the process industries like chemicals, pharmaceuticals, and biotechnology
(“Process Driven”, “Process Enabling”, Pisano 1997) an extraordinary close relationship
between products and production process can be noticed. The investigation in this paper
focuses on the innovation process in manufacturing industries. Innovation management in
manufacturing companies is asked to create integrated innovation and manufacturing
strategies. An improved performance of manufacturing companies can be expected from
tighter linkages between product and process innovation (Kim et al. 1992). “Managing this
product-process connection is one of the top challenges of the era” (Ettlie 1995, p.1224).
For a development of integrated innovation and manufacturing strategies considering the tight
product-process interaction an investigation of the interdependencies of product features and
the related production processes seems to be useful.
Linking Product and Process Innovation
For industrial companies innovations of the product portfolio as well as innovations of the
processes generating these products are essential. In many cases the scientific literature
focuses either on product innovation or on process innovation without explicitly taking into
consideration the interaction between product and process innovation.
The product-process life cycle theory of Utterback and Abernathy (Utterback, Abernathy
1975) provides a useful model helping to understand the pattern of many industrial innovation
processes. This model succeeds in encompassing the mutual relationships between the stages
of a product's life cycle, the related production process’ stages of development and
competitive strategy.
By identifying, and then separating, process and product innovations the industrial innovation
pattem could be related to three different stages of the innovation process: the uncoordinated,
the segmental and the systemic. Utterback and Abernathy notice that the rate of product or
process innovation depends on the present stage of the product's life cycle. It has to be
mentioned that this concept can refer to the life cycle of a single product line and it’s
manufacturing process as well as to a specific product generation and the growth of a whole
industrial branch related to this generation of products. The process of substitution by a
completely different, sophisticated kind of products is not in the focus of investigation. Figure
1 reflects the typical pattern of product and process innovation, including the three different
stages.
Rate of innovation
Product Innovation
fo Se .
\\. Process Innovation
uncoordinated segmental systemic
Figure 1: Utterback/Abernathy’s model of industrial product and process innovation
(Utterback, Abernathy 1975, p. 645; modified)
The first stage of the innovation process—the uncoordinated stage—is characterized by
frequent changes in product design and low productivity of the related process. In this stage
competition is merely based on product performance, a dominant product design has not
evolved yet. Due to the uncoordinated and low integrated production process (technological
and organizational) there are low constraints for product improvements. These frequent
changes of product features inhibit process standardization efforts, which results in higher
production costs.
After the emergence of a dominant product design, the firm—or the industrial branch—
gradually enters the segmental stage. Specialized production equipment is introduced, the rate
of innovation related to the production process increases, and the process becomes more
coordinated. In this stage product innovations requiring radical changes in the production
process are voided, the rising of the product innovation rate diminishes. Production costs
decrease which leads to increasing sales and higher production volume.
In the systemic stage complex, highly integrated technological solutions are implemented in
the firm, the production system is further standardized while cost minimization becomes an
important goal. Tighter linkages between product and process features occur. Product and
process changes are highly interdependent which must be taken into consideration by
management. The process of standardization reduces the probability of further fundamental
innovations in both the product and the process system. Due to these constraints both the
product and the process innovation rate decrease.
As Utterback and Abemathy relate the three identified stages to the competitive strategies
performance maximization, sales maximization, and cost minimization their approach has as
well descriptive as normative attributes. The model provides explanations about systematic
variations in the innovation process of industrial companies— fundamental ideas of possible
and plausible cause and effect relationships— suitable for the generation of a System
Dynamics Model. Implementing the fundamental ideas of the Utterback/Abernathy approach
into a System Dynamics model specific adaptations taking into consideration the recent
advances in sophisticated flexible production systems and computer aided manufacturing are
necessary. These technological innovations in the recent years permit a higher degree of
product variation at later stages. Nevertheless the fundamental ideas of this concept can be
found in current literature (e.g. Ettlie 1995, Damanpour, Gopalakrishnan 1999) and the
concept still appears to be valid for many industrial settings (Butler 1988).
Following the concept of Utterback/Abernathy, Hayes and Wheelwright suggest a two-
dimensional product-process matrix linking product life cycle stage and process life cycle
stage and reflecting a company’s position in the interrelated product-process system (Hayes,
Wheelwright 1979a, 1979b). The matrix represents the interaction of both the product and
the process life cycle. The process life cycle-rows of the matrix represent the process
structure with increasing standardization towards the systemic form. The product life cycle-
columns represent the product structure going from great variety to highly standardized
products. This matrix is helpful in describing industrial companies’ strategic options
particularly with regard to the manufacturing function. The Hayes/Wheelwright matrix
concept provides substantial support in determining the direction and timing of innovation
decisions in the light of a company’s manufacturing capabilities.
Building on the ideas of Hayes/Wheelwright and the generic strategy typology proposed by
Porter an ongoing conceptual framework is provided by Kotha/Orme. Using the dimensions
“product line complexity” and “process structure complexity” this framework suggests a link
between several critical elements in manufacturing competitiveness (Kotha, Orne 1989). It
considers both the content of fit and the process of fit between structure, strategy, technology
and performance. It recognizes that the execution of the more generic business unit strategy
inherently involves manufacturing and postulates the fit of between business-level strategy
and manufacturing structure.
Kotha/Ome relate high process structure complexity in manufacturing and lower product line
complexity to the strategy of cost leadership while the strategy of differentiation is related to
higher product line complexity and lower process structure complexity. The company’s
“process structure complexity” is characterized by the level of mechanization, systemization
and interconnection of the production process while “product line complexity” is mainly
characterized by the end product’s complexity and variety and it’s maturity in the product life
cycle.
The frameworks of Utterback/Abernathy, Hayes/Wheelwright and Kotha/Orne represent
integrative approaches all succeeding in illustrating the tight interconnections between
product, process and strategy in manufacturing companies. Applied to industrial innovation
management these synthesized frameworks give valuable hints for the development and
implementation of specific types of innovation. They provide support for decision-making
concerning the specific type, the timing and the extent of innovation in relation to maturity in
product life cycle, manufacturing structure as well as in relation to manufacturing strategy and
competitive strategy.
Considering Product-Process Interaction in Decision-Making:
A System Dynamics-Based Approach
The frameworks described in the section above provide fundamental ideas giving substantial
support for the generation of a System Dynamics model focusing on the process of innovation
management in manufacturing firms. The description of patterns of innovation and the
analysis of interaction between the elements structure, technology, strategy, and performance
identifies essential underlying cause and effect relationships. A synthesis of these ideas is a
suitable foundation of a System Dynamics model covering the complexity and the inherent
dynamics of the industrial innovation process.
Objective of this modeling approach is to enable insights into the specific dynamic behavior of
the system and to offer a virtual environment to test different scenarios of innovation. A
taxation of consequences of managerial decisions concerning investments into development,
the rate, timing and implementation of certain types of innovations becomes possible in
relation to specific product or process features. In it’s final state the model can serve as
support tool for rational decision-making and strategy generation in innovation management
for manufacturing companies with a focus on product-process interdependencies. The
objective is to support the development of coordinated and coherent policies instead of
isolated operations.
The analysis refers to the characteristics of a process segment and a single product line’s life
cycle of one firm. At this level the transition to completely new product generations is not
included.
&
‘mowledgeprod
4
fh
: \ } LiMmpRoocEN
cconversioncoeffprodinn , ee
esR&Dpd mn, matuttypd,
Ah a oa |
ba \ ——_needforprodinug——~ | 4
\ NO \O a=
RESOURCES ~ Pact = cpg SRAPEPROD
~ je ~exproc# —~_
/ INTERCONPROC ae
Ay
y _-necdorationalizatiny
sR&Dpme we ee. LIMITPROCTYPE
i — /
conversioncoeffprocina——~
| \
q [ie = eos
em
nowiedgeproe
Nes jh
Figure 2: Simple System Dynamics model for analysis of product-process interaction
A simple System Dynamics model as depicted in figure 2 serves as a first approach integrating
the concepts described above linking the basic ideas together into a feedback structure. In this
first step the model only covers four sectors (R&D sector for product and process and
implementation sector for product and process innovations) in a simplified manner. Dominant
variable is the conversion coefficient product innovation and it’s analog for process
innovation which characterize the achievements in innovation implementation including
promoting factors and constraints for the implementation of specific types of innovations.
(For an explanation of further model variables see appendix.)
The model runs illustrate different scenarios forcing several process innovations leading to
more flexible and less interconnected processes at the one hand (see figure 3) and product
innovations leading to more complex products on the other hand (see figure 4). This behavior
in general is confirmed by similar results indicated by the investigations of Kim et al. (Kim et
al. 1992) and it is consistent with the concepts described above.
Implemented Product Innovations
Rate of Innovation Product
0 15 30 45 60
Time/Month
Figure 3: Number of implemented innovations in the product line and rate of product
innovation over time (with process flexibility rising from Run A to Run C)
A higher rising product innovation rate (see figure 3, Run C) is related to a business strategy
more dominated by the marketing function. This strategy can be boosted by the acquisition of
more versatile or flexible process equipment (Kim et al. 1992, p. 56 f.) in combination with a
more flexible organization and administrative processes that enable frequent changes in the
product line.
Implemented Process Innovations
Rate of Innovation Process
Figure 4: Number of implemented innovations rationalizing the process system
and rate of process innovation over time (product line complexity rising
from Run D to Run F)
Conclusions and Further Research
The System Dynamics model presented here links—in a first step—the cycle of product
innovation with the innovation of the related manufacturing process. Until the model can
serve as a strategy support tool it requires further steps of development. Nevertheless at this
state it is able to give an impression of the dynamics of product and process innovation in
manufacturing companies and illustrates their mutual constraints. These constraints are
essential and to be taken into consideration in the process of strategy generation. The
importance of process flexibility and flexible administrative practices and the influence of high
product line complexity is illustrated.
From the feedback perspective all relevant interactions with focus on strategic implications of
product-process interaction which cause the behavior of the system “industrial innovation”
have to be represented. Further sets of variables reflecting for example customer’s and
competitor’s behavior, learning curve effects and relevant managerial leverage points to
control the industrial innovation process have to be included in following steps of model
development.
The significance of technological and organizational product- process integration in the focus
of manufacturing strategy and corporate strategy is recognized in recent literature
(Damanpour, Gopalakrishnan 1999; Pisano 1997; Ettlie 1995; Kim et al. 1992; Prahalad,
Hamel 1990). In these investigations it is verified that manufacturing companies focusing on
integrated product-process development with a regimen of policies, practices and structures
are more successful. In contradiction to these approaches sometimes the notion that
companies’ product and process development capabilities are mutually exclusive can be found
in the literature. Empirical results indicate that integrated strategies— if implemented in a
coordinated and coherent manner—can boost both the corporation’s product development
capabilities and it’s process development capabilities (Milling 1998; Pisano 1997). Success is
significantly correlated to early and tight manufacturing involvement in product R&D taking
into consideration the constraints as showed above.
Further development stages of the model are likely to provide substantial support for the
generation of more effective decisions in manufacturing companies. In a next step practices
for an achievement of compressed innovation implementation cycles by integrated product-
process strategies will be investigated.
References
Butler, J.E. (1988). Theories of Technological Innovation as Useful Tools for Corporate
Strategy, Strategic Management Journal, Vol. 9, 15-29.
Damanpour, F., Gopoalakrishnan, S. (1999). Organizational Adaptation and Innovation: The
Dynamics of Adopting Innovation Types, in Brockhoff, K., Chakrabarti, A., Hauschild, J.
(eds.), The Dynamics of Innovation, Springer, Berlin, 57-80.
Ettlie, J.E., (1995). Product-Process Development Integration in Manufacturing, Manage-
ment Science, Vol. 41, No. 7, 1224-1237.
Hayes, R.H., Wheelwright, S.C. (1979a). Link Manufacturing Process and Product Life
Cycles, Harvard Business Review, Jan.-Feb. 1979, 133-140.
—— (1979b). The Dynamics of Process-Product Life Cycles, Harvard Business Review,
Mar.-Apr. 1979, 127-136.
Kim, J.S., Ritzman, L.P., Benton, W.C., Snyder, D.L. (1992). Linking Product Planning and
Process Design Decisions, Decision Sciences, Vol. 23, 44-60.
Kotha, S., Ome, D. (1989). Generic Manufacturing Strategies: A Conceptual Synthesis,
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Milling, P.M., (1996). Modeling Innovation Processes for Decision Support and Management
Simulation, System Dynamics Review, Vol. 12, No. 3, 211-234.
—— (1998). Strategy Support Systems for Product and Production Innovation Management,
Paper presented at the Korean Academic Society of Business Administration Meeting, May
1998, Seoul
Pisano, G.P. (1997). The Development Factory: Unlocking the Potential of Process
Innovation, HBS Press, Boston, Mass.
Prahalad, C.K., Hamel, G. (1990). The Core Competence of the Corporation, Harvard
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Innovation, Omega, The Int. Jl of Mgmt Sci., Vol. 3, No. 6, 639-656.
Appendix
Explanation of the model variables:
Imp]Prodinn
Imp]ProcInn
PotentialProdinn
PotentialProcInn
innrateproduct
innrateprocess
knowledgeprod
knowledgeproc
conversioncoeffprodinn
conversioncoeffprocinn
maturityprod
maturityproc
needforprodinn
Number of implemented innovations in the product line
Number of implemented innovations in the manufacturing
process referring to the product line
Number of potential innovations of the product line
Number of potential innovations of the manufacturing process
Rate of innovation in the product line
Rate of innovation in the manufacturing process
Rate of knowledge generation suitable for product innovations
Rate of knowledge generation suitable for process innovations
Conversion coefficient for product innovations,
characterizes achievements in innovation implementation in the
product line
Conversion coefficient for process innovations,
characterizes achievements in innovation implementation in the
manufacturing process
Maturity in the product life cycle
Maturity in the process life cycle
Need for innovation of the product line
needforrationalization
complexprod
flexproc
resR& Dprod
resR& Dproc
RESOURCESR&D
FRACT
SHAPEPROD
INTERCONPROC
LIMITPRODGEN
LIMITPROCTYPE
Need for rationalization of the manufacturing process
Complexity and variety of the product line
Flexibility of the manufacturing process
Resources for product R&D (capital, human capital, available
technological knowledge)
Resources for process R&D (capital, human capital, available
technological knowledge)
Resources for R&D (capital, human capital, available
technological knowledge)
Division factor
Product features referring to it’s complexity
Process features referring to the level of systemization
and interconnection
Superior asymptote of the technology-S-curve
Superior asymptote of the technology-S-curve
Notice
Further information on the System Dynamics model (model equations) and subsequent steps
of model development are available on request.
