Evolving innovation proficiency with a corporate mind
Machiel Emmering, Walter Baets
Nyenrode University, NOTION
Straatweg 25
3621 BG Breukelen
The Netherlands
email: {m.emmering}{w.baets}@nyenrode.nl
Abstract
Many innovations fail, and as innovation is required for organizational survival, organizations
should improve their capacity to do it. Scientific
support has limited practical value, as it is too
normative and simple, it does not account enough
for individual differences, and the body of
knowledge is highly dispersed, which imposes
problems on selection. A scientific way to support
the individual organization is by means of a corporate mind, consisting of a memory and a reflexive
capacity. The memory can support first order innovation, by helping to ‘remember’ what seemed
(not) to work well within a certain frame of the innovation practice. The reflexive capacity can support second order innovation, by facilitating a critical but productive reflection on the frame in
which the organization innovates, as to optimize
innovation trajectories case by case, rather than
adopting one single innovation frame.
1
Introduction
This is a position paper of a research on innovation. The
research aims at making a practical model annex methodology by which organizations can learn to develop their
proficiency with respect to new product development
(NPD), as to make NPD trajectories more efficient, and to
increase the chance of a product’s success. It will try to
overcome the shortcomings of former research on innovation, thereby contributing to the body of knowledge. § 2
sets out what problem is addressed. This is done from the
practical point of view in § 2.1, as to address why it is
indeed a problem. In § 2.2 it is done from the theoretical
point of view, as to address what science has done up till
now, and what can be improved. § 3 focuses at the research: in § 3.1 it is set out what the research tries to accomplish; in § 3.2 it is set out how this initially will be
approached. In section § 4 an attempt is made to support
some credibility.

NOTION is Nyenrode’s sponsored research institute
for Knowledge Management and Virtual Education
2
Innovation as a problem domain
2.1
Innovation in practice
Assessment of the success of strategic innovations - i.e.
the ones that are new to the company as well as to the
world - yields a rather heterogeneous picture. A combined research e.g. by Ernst & Young, AC Nielsen and
Global Client Consulting states that 5% of all innovations
is successful, while other research by AC Nielsen in the
same year (1999) shows that 10% is successful, whereas
Hultink [1998] states that about 60% of innovations succeed. From these differences two preliminary conclusions
can be drawn: success is an equivocal notion, and / or the
way of measuring influences the outcomes. It seems that
different methods, variables and norms affect the outcome thoroughly. From this it follows that judging success is in itself a problematic exercise. A third conclusion
derives from comparison of the outcomes: although results vary highly, it is clear that a great part of all attempts to innovate successfully fails.
A low capability to innovate successfully is not just an
inconvenient loss of investments; it is a flaw that threatens viability, specifically on the somewhat longer term.
Viability means being capable of maintaining one’s identity (in the first place: existence) independently of similar
organisms within a shared environment [Beer, 1989]. For
organizations this means that they have to obtain and
maintain an adequate fit with their environment. Thereto
they have to produce the behavior and output that is to be
supported by a critical mass of relevant stakeholders. This
support can come from e.g. political, ideological, or legal
sides, but specifically important for commercial organizations is support from the market. The market is by nature
subject to change to some extent. New technologies and
products from other companies, the economic climate,
scientific breakthroughs, cultural and fashionable preferences and whatever more may lead to changes in market
needs. And when the environment changes, the conditions underlying a certain fit with that environment in
terms of the capability to fulfil market needs may also
have changed. This means that in order to restore or to
improve the fit that leads to viability, an organization will
have to be equipped with a capacity to change itself. It is
therefore not surprising that Langerak et al [2000] found,
that there is a significant correlation between on the one
hand the expertise to innovate and the success of new
products, and on the other between success of new products and organizational success. So organizational success (i.e. viability) depends to an important extent on
proficiency with respect to product innovation.
Considering that innovations fail often, and that they are
crucial to organizational viability, it makes sense that the
Marketing Science Institute has proclaimed product innovation, or NPD, to be a research domain of top priority
[Hultink, 1998]. This raises the question in what respect
science has contributed to NPD up till now.
2.2
Innovation in Academia
Innovation / NPD is in itself of course not a new topic of
investigation. Innovation as a general term can apply to
several subjects, such as products, processes or markets.
Our primary interest is in product innovation. NPD can in
a narrow sense be seen as a part of a product innovation,
if literally understood as the activity of creating a new
artifact. In a broader sense however NPD and product
innovation are synonyms; activities such as marketing are
then also taken into account. This is the sense in which
NPD is used in the research. Scientific contributions on
NPD are abundant. Hands-on help typically comes from
phase models that try to offer grip on NPD-projects, by
setting out which steps are to be taken. Examples are:
Ulrich and Eppinger [1995] – design, manufacturing,
marketing; Marquis [1969] – recognition, idea formulation, problem solving, solution, development, use; or
Christiansen [2000] – idea generation, funding, development (launch, post launch). These models are sometimes
elaborated per phase. When the available resources are
appropriately distributed, and when one observes discipline in execution, such models should be helpful. Of
course, it is in these models neither known, nor considered relevant what the product is. The assumption is that
for any innovation some general activities and development phases can be identified. Therefore the activities
and phases are expressed in abstract terms, like the ones
mentioned above. The elaboration, number and detail of
phases, activities, or sub-output may differ, but categorizing them, one can discover three general phases of NPD:
variety amplification, variety reduction, and coupling. In
the first phase, variety in terms of what could be done is
created. This phase ends with the choice for a concept of
a product. In the second phase, variety in terms of what
will be done is reduced. This is done by the execution of a
functional decomposition of the job to be done, coupled
to a time-frame that also contains the moments on which
to make specific choices for further crystallization. The
output of this phase is the product. In the third phase,
what has been done must enter the world, in order to
generate the fit that (re)assures the company’s viability.
The output of this phase is the marketed product. This
corresponds with Langerak’s [et al, 2000] classification
of theoretically modeled steps in pre-development, development and commercializing activities. Abstract phase
models provide generic insight in innovation as a process,
allowing one to acquire basic innovation expertise, or to
prepare NPD-activities, as ‘checklists’ that assure that all
basic stages have been thought of. A first critique on such
theory is that the categories are too general to be of practical value. Van de Ven et al [2000] go after thorough
research much further in their critique. They conclude
that phase models are too simple, linear, normative and
theoretical. There is a persistent mismatch between such
theory and reality.
Other literature offers the widest range of specific topics.
For (probably) every phase, activity, line of business,
discipline, and whatever dimension one can think of,
some literature with a scientific approach is written to go
in detail. The large amount of literature and its highly
varying quality obscures a proper overview of the field of
innovation, which troubles selection. Moreover, as the
contributions have a more or less general character, the
relevance will have its limit. Nelson and Winter [1977]
conclude that these two observations are the fundamental
problems of theory of innovation: the body of knowledge
on innovation lacks an integrative framework, so that
individual contributions about a specific topic appear to
be arbitrary, and theory does not account for individual
differences.
We now can see that the problems of scientific support
relate to quality, specificity and relevance. The limited
specificity and relevance of scientific support is in its
very nature, as science cannot account for singularities,
when it comes to describing how innovation works. As
Beer [1989] says, science is a variety reducing activity. It
tries to uncover invariant properties of the phenomena
under study by means of homomorphic mapping; it does
not give isomorphic descriptions of all the cases that were
studied. So invariant characteristics are derived from the
omission of all that is singular, thereby transcending individual, specific, contingent situations. It is however exactly that situation in which the innovator would like to
be supported. In that respect, apart from the problem of
quality, science has intrinsic restrictions in helping an
innovation manager to identify what is relevant, let alone
in offering possible solutions that account for his specific
situation. This means that the NPD-manager remains
dependent upon himself with respect to his own situation.
Taking a particular innovator’s earlier experiences and
specific situation as a starting point, this research will try
to develop a model that accounts for these problems of
relevance and specificity.
3
Research attempt
3.1
Problems of innovating
Now that it is clear what the research aims at both in the
practical as well as in the academic sense, it is time to
assess what the model ought to support. This has to do
with invariant problems of innovation.
Organizational operations are about producing something
in a certain way; about what and how. The more experience and insight there is in dealing with a specific what
(product) and how (process), the more crystallized are the
conditions under which to come to the best products and
processes, thus to satisfying effectiveness and efficiency.
Routine operations are controlled by organizational functions, structures, practices and means that have been chosen for having proved to work in an assumed optimal
way. The in that order prescribed business process can be
seen as a coherent unity of embedded decisions, which
provide the organization with a capacity of routine regulation. Organizing an innovation trajectory is more difficult: the process of innovation requires to some extent
non-routine regulation, as an immanent feature of innovation is, that what and how are at least to some extent not
clear yet. The more strategic and thus the newer the innovation is, the less there are equivalents of the thing to be
developed that could serve as an example, and thus the
less there are references in what and how exactly to develop. In this process of inventing future reality, the organization is the only responsible party for making decisions required for doing so. As has been shown, this ends
up more frequently in failure than in success. Nevertheless organizations realize (whether explicitly or implicitly) that it is crucial to viability, so that they have to do it.
Moreover, the more important innovation is against the
background of the competitive environment, the stronger
one will probably realize that the innovation preferably
should be distinctive within that environment. A strategic
innovation initially yields a monopoly on it. But success
entails competitors’ mimetic behavior (a basic rule of
economics), diminishing the market potential of one’s
successful original. So the harder it is to copy the product, i.e. the more the new product is tied to competencies
characteristic for the organization that invented it, the
better. The innovator’s dilemma is now clear: in order to
remain viable, one has to initiate practices that put one’s
overall strength of viability at stake. It then becomes
clear, that innovations are experiments with viability, as
Achterbergh [1999] puts it. In this experimental function,
the organization must make decisions that give direction
and progress to innovation. It is not clear in terms of efficiency how the organization can best get to a certain
point, nor is it clear in terms of effectiveness if this point
will support its viability. If the proficiency and decisions
are inadequate, the risk of ineffectiveness or inefficiency
of the innovation project increases, resulting in respectively developing the wrong thing or developing a thing
in the wrong way.
Unpredictability of the future and inexperience with activities never carried out before point to risky uncertainty
as the core problem of NPD. The basis for sensible behavior dealing with uncertainty is a cognitive capacity,
that allows for accurate simulation of the situation beforehand in the form of planning, and adequate selection
of behavioral options in the real situation, as to control.
The behavior that shapes the course and appearance of
the innovation is crucial, and this behavior is preceded by
decisions steering that behavior. Ideally, these decisions
match project requirements with organizational resources.
Therefore, knowledge inducing the best decisions can be
seen as a fundamental condition to be successful in innovation. Such knowledge should be at a project manager’s
disposal. Those in charge of NPD have on the account of
their proficiency as managers certain a priori ideas about
how to approach a specific innovation and how to deal
with it while it evolves. But however good project managers have proven to be, they will always face limitations
concerning relevant knowledge. Categorizing the field of
mental capacities in terms of specific subjects, one may
be:
1. consciously capable
2. unconsciously capable
3. consciously incapable
4. unconsciously incapable
Table 1: knowledge consciousness, based on Ayas, 1997
The category of knowledge in the first column is the
knowledge potential of the NPD manager, that gives him
the proficiency to operate on the basis of his expertise.
Under 1 are explicit distinctions, which are deliberately
involved in a manager’s decisions. This knowledge plays
an active role in considerations; it is about topics that are
explicitly paid attention to. In this category, the manager
‘knows what he knows’.
Under 2 are implicit distinctions, which are unconsciously involved in a manager’s decisions. This knowledge is
highly internalized, and the manager is not actively aware
of these distinctions as being the basis for certain decisions. To this extent, the manager acts on routine. In this
category, the manager ‘does not know what he knows’.
There is a limit to knowledge in all possible respects: one
could not have full insight in the organization’s available
capacities, in the organizational history of NPD experiments, etc. The knowledge flaws are categorized in the
second column.
Under 3 is problem awareness, which can be seen as
knowledge about or awareness of certain knowledge that
is missing in order to do something right. Knowing this,
one can try to obtain the missing knowledge (either by
learning it, or by involving someone having the required
knowledge). In this category, the manager ‘knows what
he does not know’.
Under 4 is the cognitive blind spot, as Von Foerster
[1984] calls it. This is the situation in which the manager
is not aware that he misses specific knowledge that could
lead him to better decisions. In this category, the manager
‘does not know what he does not know’.
So, under 3 the problem is ‘not knowing’, but this problem is limited, in the sense that the fact that it is clear that
some knowledge is missing implies that some light is
shed on what knowledge to look for to overcome this
problem. Under 4 however the problem is not ‘not knowing’, but ‘not knowing about not knowing’, in other
words, not knowing that you have a problem.
Now, in order to complement a manager’s NPD proficiency and the project information that is available as to
make the most satisfactory decisions, he might be served
by means that help him to acquire relevant knowledge
(category 3), and that make him aware of possibly relevant knowledge that he had not thought of (category 4).
With such an instrument, one can optimize decisions, e.g.
about possible action when faced with a problem, or
about establishing the best possible organization in the
NPD-project, both by which the proficiency in NPD practices is amplified. This knowledge may be derived from
experiences of the company that are recognized as relevant corporate knowledge. That would make the
knowledge base characteristic for the company. It could
be seen as the company’s mind, facilitating the manager
to draw upon the organization’s memories that may be
relevant for his situation. In more systemic terms it means
facilitating a subsystem to make use of the larger system’s variety potential. This implies, as Baets [1998]
says, that the process of decision-making rather than the
decision itself becomes the focal point of attention, which
has to do with learning and knowledge building.
This research is aimed at developing an instrument that
serves as a corporate ‘mind’. This mind would consist of
a memory and a reflexive capacity. The memory would
operate in order to recall what might be relevant in a specific situation and how the organization currently can
deal or earlier has dealt with that issue. The reflexive
capacity would help to be critical in a productive way
about NPD practices that are accepted as given. If management starts to extend its expertise with a corporate
mind, the company as a whole starts to build up a capacity to deal with complexity, in order to optimize its interaction with the environment on the basis of earlier experiences and on relevant knowledge available throughout
the company. Doing so, it starts to build a capacity that
continuously enhances the proficiency in NPD activities.
3.2
Initial approach of the research
The ideas of the research will be tested in a company in
fast moving consumer goods with the pseudonym Code.
Code has a mission to be an innovator, but also struggles
with an unacceptable failure rate; moreover NPD projects
proceed too often in a troublesome way. Code has established a standardized NPD process, so new products are
developed in an assumed best, fixed trajectory of specified steps.
Project 1
Project 2
Project 3
Project 4
Result 1
Result 2
Result 3
Result 4
idea
concept
develop
Decisions are based on the one hand on explicit or implicit distinctions about what matters and what doesn’t, a
set of perceptions that differs to some extent per manager.
On the other hand, the decision on specific action depends on the behavioral options available, which suggests
knowledge of one’s own (organizational) capabilities, and
this is particularly problematic in large organizations.
Different perceptions of relevance and knowledge about
organizational capabilities lead to decisions that are likely
to yield different results, the ones being more desirable
than the others. If these ‘decision determinants’ are gathered and the more interesting are preserved, the basis on
which to come to decisions can be organizationally optimized. Therefore, to speak with Baets [1998], the need
for consolidation of perceptions in order to decide properly is evident. The broader the collective base of possibly
relevant distinctions, the broader the potential to come to
the best thinkable decision. So, development of a device
as a corporate mind, complementing managers’ ability to
make adequate decisions, based on distinctions that
proved (not) to be of relevance in some specific situation,
would be an adequate research-direction to follow, in
view of the earlier mentioned convocation to research
NPD. This device should support the manager’s proficiency in a scientifically sound way to be dependent upon
himself.
launch
market
= step of innovation trajectory
= experience per step
Figure 1: A model of application of Code’s NPD model
In this picture the (simplified) set of steps is depicted in
the boxes. Application of this approach to different NPD
projects leads to different experiences (ovals) per modeled step, yielding different overall results, as reality
proves.
In order to build a corporate mind that can recall these
experiences, the experiences have to be collected and
analyzed in terms that can be interpreted in an evaluative
frame of reference. The terms to be compared are any
variable that one chooses in order to describe experiences. This selection has to be limited, since not everything
can be described, nor is it relevant to remember everything. However it has to suffice to be of value, so we
have to be very prudent in our selection. An additional
problem of selection is the explanatory strength of the
relation between a variable chosen and the phenomenon
to be remembered. It may be that an outcome is (partly)
falsely ascribed to some variable, for instance because the
phenomenon in fact only occurred as a contingent ultimate rather than as a comprehensible immediate effect of
the variable. This is all too common: we know from chaos theory that small energy flows may have the largest
and most unpredictable consequences. Broader interpretation implies that influences generally reach further than
the direct environment and than intentions. This leads
some to state that everything is related to everything else,
so the search for causes and origins must be discontinued
[Kilduff and Mehra, 1997]. Although this viewpoint may
be too skeptical, it is clear that we have to be cautious
while identifying the variables that seem to matter most.
Two actions help to account for this problem. In the first
place we will identify variables from within Code, rather
than e.g. make an external selection of so called critical
success factors as described in the literature. Therefore
the variables relate to a specific organization by definition. In the second place, through time we will select the
more appropriate variables, along the co-evolving result
of innovating and learning.
Now, two of all possible reasons that the effectiveness
and efficiency of Code’s innovations are sub-optimal are:
1) One does not make the best possible use of Code’s
potentials to ‘fill in’ the modeled steps of the trajectory (sub-optimal performance within the frame);
2) The innovation model itself (the selection of what is
explicitly indicated as relevant) may not be the optimal one (sub-optimal performance of the frame).
Ad 1 Sub-optimal performance within the frame
Application of the model means creating settings, in
which in every step of every NPD project real people will
have to be doing real activities, to get to the best possible
result. Although the steps in all projects may be the same
on the abstract level of generalization, they will lead to
different experiences and results in their factual situation.
Experiences with (parts of) settings should be recorded in
such a way that allows one to evaluate them against (a)
result, (b) each other, (c) the variables in the modeled
setting. Evaluation of a (part of a) setting against result
means trying to rate its contribution to the project’s result. As success is usually measured by financial indicators, this evaluation will require a differentiation of an
overall evaluation as ‘success’ or ‘failure’, as such a statistical attribute does not clarify the contribution of a
specific variable such as somebody’s expertise to it.
Evaluation of the settings against each other makes it
possible to determine what appears to be the better setting
for a specific need within a project. The company can
consequently try to reinstall that setting in a new project.
Innovation then comes to follow an evolutionary trajecto-
ry, selecting step by step the best known setting as recorded in the corporate mind, thereby optimizing the use
of an organization’s potential. Evaluation of the settings
against the NPD model means that the experiences obtained per step of the model in return may say something
about that model, thereby feeding its refinement. This
would lead to sophistication of the organization’s NPD
model and obtained experiences by ever better use of inhouse capabilities in terms of the explicit organizational
innovation distinctions, in a continuous upward spiral.
So an instrument that helps to systematically gather, analyze and feed back experiences would allow a company
to optimize the use of its in-house capabilities, in terms of
the variables in which the experiences are described. This
is the organizational memory. The conscious employment
of specific capacities, following from building and applying this organizational memory will enhance proficiency
in NPD projects in that specific organization, as the experiences and capacities are the organization’s own. The
expression of a set of variables as factors that seem to be
successful for that company thus may lead to a set of
‘idiosyncratic generalizations’, a hard to copy set of specific competencies and comparative advantages. Protracted development of the corporate mind leads to tailormade science for the individual company.
This part of NPD, about making the best possible use of
capacities, is about optimizing a road to innovation with
the help of a memory. It can be seen as first order innovation. The research is in the first place aimed at designing
this instrument.
Ad 2 Sub-optimal performance of the frame
The general model in use describes a more or less fixed
approach to develop new products. It expresses the organizational distinctions about how to innovate, and thus
functions as a norm for project management. This model
is accepted as given. As different theories and practices
apply different sets of distinctions (meaning that they
apply different norms), it may be said that innovations
can be developed along different valid trajectories. It is
not unlikely that the one yields on average better results
than the other, which may also depend on specific typologies of organizations or environments, as Nelson and
Winter [1977] suggest. It may also be the case that NPD
projects should in fact not be approached in a standardized way at all, or that the organization should be better
of with a different general model. So apart from the
above-mentioned under-utilization of the organizational
potential within the frame of a standardized NPD model,
an entirely different reason for sub-optimal effectiveness
and efficiency of NPD projects can be that the frame of
distinctions to approach them with is in itself not optimal.
A company would thus be helped with an instrument that
supports a reflexive capacity to evaluate the model that
prefigures NPD projects, thereby assessing the organization’s assumptions underlying its approach of innovation
projects. The instrument should also facilitate this critical
reflection on the selected NPD model.
This part of NPD, about optimizing approaches of NPD,
is about innovating the road to innovation with a reflexive
capacity. It can be seen as second order innovation. The
research will develop the basic structure of an instrument
that supports evaluation and improvement of a company’s
assumed best predisposition of NPD projects.
4
Credibility
It may appear ambitious or contradictory that the aim is
to develop a model that has a practical value by accounting for individuals’ situations, while also overcoming
certain flaws of theory on innovation in general. This
indicates that some academic credibility is required.
Moreover, the approach may appear somewhat abstract.
This indicates that some practical credibility is required.
From the theoretical point of view, the research can be
located in the field of systems theory, cybernetics, and
related fields. More in particular, it will apply principles
of evolution. The idea is that if a way of doing proved to
be successful (in the different terms one could think of),
that way is reused in new projects. Doing so, the capabilities to act more accurately and to differentiate ways of
doing over different types of projects (rather than sticking
to one fixed phase model) may improve. Organizations
can try to create a positive feedback loop by building
forth on proven successes. The use of ideas of the fields
mentioned should assure academic rigor, while not losing
the requirement of individual application possibilities.
From the practical point of view, one of the outcomes
will be that lessons from NPD projects can be drawn, and
should be remembered in certain new projects. Project
teams should be given the lessons that give them the possibility to refine their approach, on the basis of what may
be relevant, and of what appeared (not) to work in the
past. This should eventually be done by the organization
itself, since the mind is to be filled with its own experience. The research is not that far. However, there is some
proof that the idea is appealing. Within Code, several
projects were analyzed and learnings were drawn. Recently a team was assigned for a new project that had
many similarities with two projects in the past that both
failed. I was invited to present the learnings that I considered relevant to the team. The team was highly enthusiastic and the overall opinion was that many issues would
probably not have been accounted for without that reflection on earlier experiences. An other piece of evidence is
that reflection upon a set of aggregated learnings made
Code to refine its NPD frame.
Concluding remarks
The research annex model under construction should
improve NPD success in practice, by supporting better
use of organizational knowledge within an NPD approach
and by improving that approach itself. The outline that
has been set out should account for the general problems
of specificity and relevance that more regular scientific
support entails. Both the first order and the second order
focus account for the specificity of individual situations,
with a mind of which the content is a specific organization’s own. The application area can be anything; the
choice to test in the field of NPD project management is
contingent. All in all, the result aimed at has in principle a
wide application range and is relevant for many systems
and types of problem areas.
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