Enabling continuous and discontinuous innovation learning from the private sector

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Enabling Continuous and Discontinuous Innovation:
Learning From the Private Sector
John Bessant a b
a Professor of Innovation Management , Cranfield University
b AIM Public Service Fellow , ESRC
Published online: 15 Mar 2010.
To cite this article: John Bessant (2005) Enabling Continuous and Discontinuous Innovation: Learning From the Private
Sector, Public Money & Management, 25:1, 35-42
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35
PUBLIC MONEY & MANAGEMENT JANUARY 2005
All organizations face the challenge of innovation.
Their survival and growth depends upon their
capacity to renew what they offer the world
(product/service innovation) and the ways in
which they create and deliver that offering
(process innovation) (Tidd et al., 2001). Through
what is essentially a trial-and-error process they
learn to organize and manage the activities
needed to carry through this innovation task on
a continuing basis. Over time, particular
behaviour patterns are rehearsed and reinforced
until they become firm-specific routines and these
give rise to structures, policies and procedures
which embed them in the firm and define the
way it approaches innovation (Nelson and Winter,
1982; Pavitt, 2002).
Although much of the reported research has
been on the private sector (and within that,
biased towards manufacturing) the core process
of innovation has equal relevance for public
organizations. This article looks at how innovation
is organized and managed, at the routines needed
to accomplish it and the challenges posed by
different types of innovation under ‘steady-state’
and ‘discontinuous’ conditions.
Innovation as a Generic Process
There is a core renewal process in innovation
which is common to all organizations. This
involves a series of linked activities:
•Searching—scanning the environment (internal
and external) for, and processing relevant
signals about, threats and opportunities for
© CIPFA, 2005
change.
•Selecting—deciding (on the basis of a strategic
view of how the enterprise can best develop)
which of these signals to respond to.
•Implementing—translating the potential in the
trigger idea into something new, and
launching it in an internal or external market.
Making this happen is not a single event but
requires attention to acquiring the knowledge
resources to enable the innovation (for
example by creating something new through
R&D or market research, or acquiring
knowledge from elsewhere via technology
transfer or strategic alliance); launching the
innovation and managing the process of initial
adoption; and sustaining adoption and use in
the long-term, or revisiting the original idea
and modifying it (re-innovation).
•Learning—enterprises have (but may not always
take) the opportunity to learn from
progressing through this cycle so that they can
build their knowledge base and can improve
the ways in which the process is managed.
These core activities do not take place in a
vacuum but are influenced by a set of contextual
factors which can be classified under the headings
of innovation strategy, innovative organization
and innovation linkages.
Good Practice Model for Innovation
Management
In the strategy domain there are no simple recipes
for success, but a capacity to learn from experience
John Bessant is
Professor of
Innovation
Management at
Cranfield University
and an ESRC AIM
Public Service
Fellow.
Enabling Continuous and
Discontinuous Innovation:
Learning From the Private Sector
John Bessant
Much of the research on innovation to date has been on the private sector (and,
within that, biased towards manufacturing) but the processes involved are equally
relevant to the public as well as the private sector. This article looks at how
innovation is organized and managed, at the routines needed to accomplish the
task and at challenges posed by different types of innovation under ‘steady-state’
and ‘discontinuous’ conditions. It argues that there is a strong case for learning
across public and private sectors, not just in terms of transferring well-proven
lessons (adaptive learning), but also for ‘generative learning’—building on
shared experimentation and comparison of experiences around discontinuous
innovation.
Downloaded by [University of Newcastle (Australia)] at 09:12 30 September 2014

36
Table 1. Sources of discontinuity in the innovation environment.
Triggers/sources of discontinuity Explanation
New market emerges Most markets evolve through a process of growth, segmentation etc. But at
New technology emerges Step change takes place in product or process technology—may result from convergence
New political rules emerge Political conditions which shape the economic and social rules may shift dramatically
Running out of road Firms in mature industries may need to escape the constraints of diminishing space for
Sea change in market Public opinion or behaviour shifts slowly and then tips over into a new model, for
sentiment or behaviour example the music industry is in the middle of a (technology-enabled) revolution
Deregulation/shifts Political and market pressures lead to shifts in the regulatory framework and
in regulatory regime enable the emergence of a new set of rules, for example liberalization, privatization
certain times completely new markets emerge which cannot be analysed or predicted in
advance or explored through using conventional market research/analytical techniques
and maturing of several streams (for example industrial automation, mobile phones), or
as a result of a single breakthrough (for example LED as white light source)
(for example the collapse of communism meant an alternative model—capitalist,
competition, as opposed to central planning, and many ex-state firms could not adapt their
ways of thinking)
product and process innovation and the increasing competition of industry structures by
either exit or by radical reorientation of their business
in delivery systems from buying records, tapes and CDs to direct download of tracks in
MP3 and related formats
© CIPFA, 2005
and analysis is essential. Research and experience
point to three essential ingredients in innovation
strategy:
•The position of the firm, in terms of its products,
processes, technologies and the national
innovation system in which it is embedded.
Although a firm’s technology strategy may be
influenced by a particular national system of
innovation, it is not determined by it.
•The technological paths open to the firm given
its accumulated competencies. Firms follow
technological trajectories, each of which has
distinct sources and directions of technological
change and which define key tasks for strategy.
•The organizational processes followed by the
firm in order to integrate strategic learning
across functional and divisional boundaries.
Within the area of linkages, developing close and
rich interaction with markets, with suppliers of
technology and other organizational players, is
of critical importance. Linkages offer
opportunities for learning—from tough
customers and lead users, from competitors,
from strategic alliances and from alternative
perspectives. The theme of ‘open innovation’ is
increasingly becoming recognized as relevant to
an era in which networking and inter-organizational
behaviour is the dominant mode
of operation.
Finally, innovation depends on having a
or deregulation
Fractures along ‘fault lines’ Long-standing issues of concern to a minority accumulate momentum (sometimes
through the action of pressure groups) and suddenly the system switches/tips over, for
example, social attitudes to smoking or health concerns about obesity levels and fast foods
Unthinkable events Unimagined and therefore not prepared for events which—sometimes literally—
change the world and set up new rules of the game
Business model innovation Established business models are challenged by a reframing, usually by a new
entrant who redefines/reframes the problem and the consequent rules of the game
Shifts in ‘techno-economic Change takes place at system level, involving technology and market shifts. This
paradigm’—systemic changes involves the convergence of a number of trends which result in a ‘paradigm shift’
which impact whole sectors where the old order is replaced
or even whole societies
Architectural innovation Changes at the level of the system architecture rewrite the rules of the game for
those involved at component level

37
supporting organizational context in which creative
ideas can emerge and be effectively deployed.
Building and maintaining such organizational
conditions are a critical part of innovation
management, and involve working with
structures, work organization arrangements,
training and development, reward and
recognition systems and communication
arrangements. Above all, the requirement is to
create the conditions within which a learning
organization can begin to operate, with shared
problem identification and solving and with the
ability to capture and accumulate learning about
technology and about management of the
innovation process.
Learning to Manage Innovation
Although all organizations face the same basic
challenge it becomes clear that some develop
routines which are more effective than others
with dealing with the generic tasks of innovation—
for example, how they search their environments
for potential triggers to the process, how they
allocate limited resources in strategic fashion,
how they acquire and absorb new knowledge
(Van de Ven et al., 1989; Rothwell, 1992; Cooper,
1999). Although innovation remains an uncertain
and inherently risky process, their ability to
manage the process in more consistently
successful fashion makes them targets for other
firms to imitate (Baden-Fuller and Pitt, 1996;
Kanter, 1997; Dodgson, 2000; Gundling, 2000).
As a consequence we have an emerging model of
‘good practice’ based on convergent patterns of
behaviour which appear to be associated with
successful management of innovation (Chiesa et
al., 1996; Dodgson, 2000; Tidd et al., 2001).
Enterprises trying to develop innovation
management capability face two challenges, both
linked to the question of organizational learning.
The first is to ensure that they have routines in
place to enable the process, provide strategic
support, supportive organizational context and
pro-active linkages. The second is about adapting
those routines to create firm specific advantage
through a process of experimentation and
consolidation. This pattern of continuous
learning and sharpening up of innovation
management capability conforms to what Senge
calls ‘adaptive learning’ and Argyris and Schon
term ‘single loop learning’ (Argyris and Schon,
1970; Senge, 1990).
For most innovative activity such learning is
associated with ‘doing what we do but better’—
improvement innovations—and approximates
to a kind of steady state in innovation in which
organizations push the boundaries of their
current products and processes. This corresponds
© CIPFA, 2005
to the conditions termed ‘mature phase’ by
Abernathy and Utterback in which there is a
high degree of imitation and an essentially
incremental pattern to innovation. (Abernathy
and Utterback, 1978; Utterback, 1994). Successful
firms in mature industries have developed
sophisticated suites of routines which they can
constantly modify through an adaptive learning
process to retain competitive edge (Baden-Fuller
and Stopford, 1995; Graham and Shuldiner,
2001). Even in relatively high velocity
environments this pattern can provide a
systematic mechanism to maintain continuous
product innovation (Eisenhardt and Brown,
1997).
The Challenge of Discontinuous Innovation
Although such routines are demonstrably
successful under steady-state conditions, they
may be ineffective or inappropriate when the
firm confronts situations outside of its ‘normal’
operating conditions. Discontinuities can take a
number of forms—for example a step change in
technological development, the emergence of a
totally new market or a dramatic shift in the
political/regulatory environment; table 1 gives
some examples.
The problem lies less in the absolute scale of
novelty or dislocation but, rather, in the firm’s
experience of these conditions as something
which takes it beyond its normal operating
envelope. Since such conditions do not emerge
every day (they are essentially discontinuous)
established firms are often unable to deal with
them effectively. It is usually new entrant firms
who are able to exploit the ‘fluid phase’ in terms
of developing innovations to take advantage of
these conditions, while existing incumbents do
badly (Tushman and Anderson, 1987;
Christensen, 1997; Foster and Kaplan, 2002).
Significantly, the threat is posed most to
those well-managed firms which have developed
effective steady-state routines for innovation.
They work closely with customers and suppliers,
they make use of sophisticated resource allocation
mechanisms to select a strategically relevant
portfolio of projects, they use advanced project
and risk management approaches in developing
new products and processes and so on. These
routines are the product of well-developed
adaptive learning processes which give the firm
a strong position in managing innovation under
steady-state conditions—but they also act as a set
of barriers to picking up signals about, and
effectively responding to, innovation threats and
opportunities associated with discontinuous
shifts. Christensen’s work on ‘the innovator’s
dilemma’ highlights this problem of a virtuous

38
© CIPFA, 2005
circle which operates in a successful firm and its
surrounding value network, and describes in
detail the ways in which their markets become
disrupted by new entrants (Christensen, 1997).
Working ‘out of the box’ requires a new set
of approaches to organizing and managing
innovation—for example how the firm searches
for weak signals about potential discontinuities,
how it makes strategic choices in the face of high
uncertainty, how it resources projects which lie
far outside the mainstream of its innovation
operations etc. Established and well-proven
routines for ‘steady-state’ conditions may break
down here: for example, an effective ‘stage gate’
system would find it difficult to deal with high
risk project proposals which lie at the fringes of
the firm’s experience. Developing new
behaviours more appropriate to these conditions,
and then embedding them into routines, requires
a different kind of learning—‘generative learning’
(Senge, 1990) or ‘double loop’ (Argyris and
Schon, 1970).
The problem is further compounded by the
networks of relationships the firm has with other
firms. Typically, much of the basis of innovation
lies at a system level involving networks of
suppliers and partners configuring knowledge
and other resources to create a new offering.
Discontinuous innovation is often problematic
because it may involve building and working
with a significantly different set of partners than
those the firm is accustomed to working with.
Whereas ‘strong ties’—close and consistent
relationships with regular partners in a network—
may be important in enabling a steady stream of
continuous improvement innovations, evidence
suggests that where firms are seeking to do
something different they need to exploit much
weaker ties across a very different population in
order to gain access to new ideas and different
sources of knowledge and expertise (Granovetter,
1985).
A key challenge is thus to develop alternative
routines for discontinuous innovation (‘do
different’ routines), which can sit alongside those
for steady-state ‘do better’ innovation (Francis et
al., 2003).
Medproducts—A Case Example
It will be useful to focus this discussion by reference
to a case example. Medproducts is a highly
profitable and increasingly global player in the
medical products field. Founded in Denmark in
1957 the company has grown through a series of
innovations which combine a deep
understanding of a specialist medical field with
strong and focused technical competencies.
Innovation is seen as a core strategic value and
their efforts have been regularly recognized;
most recently the Danish newspaper Berlingske
Tidende and the national Patent and Trademark
Committee together awarded them the 2002
Danish Innovation Prize.
In terms of our discussion of routines this is
a firm in which competitive advantage is
increasingly built on the ability to manage the
steady-state innovation process effectively, fine
tuning and extending a repertoire of established
and proven routines. The two examples which
follow help clarify this.
Developing Active User Involvement in the Product
Innovation Process
One of the key lessons about successful innovation
is the need to get close to the customer. Users can
become a key part of the innovation process by
feeding in ideas and improvements to help define
and shape the innovation (Von Hippel, 1988;
Herstatt and von Hippel, 1992; Moore, 1999).
In the case of Medproducts this pattern was
established from the outset when a nurse
developed a prototype and then found someone
who could make it and gradually improve it.
Medproducts builds such insights by consulting
panels of users, specialist nurses and other
healthcare professionals located in different
countries. So the firm has information from
those involved in care and treatment and also
about needs which might be difficult or
embarrassing for an individual patient to explain.
By setting up panels in many countries, differing
cultural attitudes and concerns can also be built
into product design and development.
The concept for this approach emerged in
the early 1990s and is essentially a series of
product development activities carried out with
a small group (10 to 15 people; called a ‘board’)
of key professionals. From an initial five boards
in Denmark, the UK, the Netherlands, France
and Spain, Medproducts now has 24 boards in
17 countries. Each Board meets twice a year with
a one to two day agenda, which is set by the
company but designed to promote extensive
interaction and experience sharing.
The core objective of the boards is to try and
create a sense of partnership with key players,
either as key customers or key influencers.
Selection is based on an assessment of their
technical experience and competence but also
on the degree to which they will act as opinion
leaders and gatekeepers—for example by
influencing colleagues, authorities, hospitals and
patients. They are also a key link in the clinical
trials process. Over the years Medproducts has
become quite skilled in identifying the people
who will make good board members—for

39
example, by tracking people who author write
articles or who have a wide range of experience
across different operation types. Their role is
mainly to help with two elements in innovation:
•Identify, discuss and prioritize user needs.
•Evaluate product development projects from
idea generation right through to international
marketing.
The TIM Process for Progressing Ideas into Products
Another area which represents good practice in
innovation management is the use of some form
of organized and accepted process for managing
risk and progressing projects from initial selection
through to strategic commitment of resources
(Bruce and Bessant, 2001; Cooper, 2001). Such
portfolio management/stage gate models are
essential in organizations with multiple product
and process innovation projects. In the case of
Medproducts the process developed was called
TIM (Taking Ideas to Market) and provided a
clear and widely accepted framework to take
ideas and progress them through to successful
products launched in the marketplace. TIM’s
purpose is to:
•Provide common rules of the game for product
development within Medproducts.
•Make clear decisions at the right moment.
•Clarify responsibility.
Much of the work in product development is
carried out by project teams consisting of selected
specialists from marketing (from both product
divisions and subsidiaries), R&D, clinical affairs
and manufacturing. Each project team works
under a project manager, and the TIM process
defines the rules to be followed by the project
team.
The TIM process divides the development
of new products into five stages. Each stage
contains a number of parallel and co-ordinated
activities designed to refine the definitions of
customer needs and to develop technological
solutions and capacity for efficient
manufacturing. Each stage is followed by a ‘gate’,
a decision point at which the project is reviewed
by ‘gatekeepers’—senior managers who have
authority to keep worthy projects moving ahead
quickly. The gates serve as the critical quality
control checkpoints between the stages. A ‘go’
decision is made when the gatekeepers decide
that a project is likely, technically and
economically, to meet the needs of the customers
as well as to comply with Medproducts’s
requirements for return on investment, quality
and environmental impact.
© CIPFA, 2005
Limitations of the Steady-State Routines
Despite the apparent strength of its innovation
capabilities, Medproducts recognizes the
limitations of some of its routines in dealing with
‘discontinuous’ conditions. For example the close
links with their users via the boards is an excellent
mechanism for identifying and testing new
concepts—provided these fall within the general
‘envelope’ of current operations. These are the
very best people to ask for input to maintain a
development trajectory—but, as Christensen
(1997) found with his studies of disc drive
companies, they represent a problem in terms of
exploring completely new concepts. The ‘virtuous
circle’ becomes a ‘vicious circle’, which does not
support the entry or active evaluation of
alternative concepts but is primarily about
reinforcing the existing ones.
In similar fashion, the TIM process is not
well-suited for dealing with risky new concepts
about which information is limited. Yet it is
precisely these ‘weak signals’ which represent
the early warning of what may form the basis for
a major new opportunity or, if introduced early
by a competitor, a significant threat to a business.
Some example statements from a recent
‘innovation audit’ of the company indicate a
concern that something different will be needed
for discontinuous conditions. For example, in
referring to the TIM process:
…sometimes it is a too heavy process, because you
have ideas they stop on the way because you have to
fill in all these forms, so it kills initiative and maybe
innovation from time to time
I think we do too little for the radical side—but
Medproducts is too busy.
The sense of needing to look outside—or risk
being surprised by something from outside—is
also well-expressed:
…sometimes what you need is radical, out of the
box—you need a separate kind of structure for that
because it can’t fit the optimizing one.
…if we don’t get outside the box, then somebody
outside the box will step in and do it…that will ruin
our business in the long term.
Developing ‘Ambidextrous’ Innovation
Management Capability
The case of Medproducts is typical of successful
firms which need to confront a major
organizational development challenge. How can
they build, alongside existing and proven
successful routines for innovation, a new

40
© CIPFA, 2005
and complementary set which help them
deal with the challenges of discontinuity?
The firm is now engaged in a ‘learning-by-doing’
process of experimentation with new
structures (such as a joint discovery/business
development team acting as ‘scouts’ for new
options), new processes (such as a revised
more open-ended version of the TIM
approach) and new underlying beliefs (like
the need to accept high levels of failure in
risky ventures, but to balance this by failing
early and learning quickly from mistakes).
There is clearly considerable scope for
learning between firms and across sectors
under these conditions and one part of
Medproducts’ strategy is to build such
learning networks with a variety of different
organizations.
In more general terms, this example
illustrates a core challenge in innovation
management: is it possible to create
organizations capable of both steady-state
and discontinuous innovation? Neither is
good or bad in an absolute sense but, rather,
the question is one of appropriateness to
external conditions for innovation. New
entrants exhibit a fluid and flexible approach
better suited to these conditions, but they, in
turn, need to develop a steady-state mode to
help them manage under more stable
conditions. Existing incumbents are well-suited
to exploit steady-state conditions but
often falter when the rules of the game
change.
This raises an important question. Is it
possible to operate both archetypes under
the same organizational roof and develop
the ability to switch between them—an
approach described as ‘ambidextrous’ by
some commentators (Tushman and O’Reilly,
1996)? Or does successful management
under different sets of conditions require
setting up completely new organizations—
for example spinning off a completely new
company to exploit new opportunities under
discontinuous conditions (Christensen and
Raynor, 2003)?
The ambidextrous approach poses
formidable challenges, but a number of
mechanisms have been tried—for example
various forms of corporate entrepreneurship
structures, ‘skunk works’ and
‘intrapreneurship’ schemes (Pinchot, 1985;
Rich and Janos, 1994; Gundling, 2000;
Buckland et al., 2003). Although difficult, these
have the advantage that the existing firm can
leverage its financial, experience and
knowledge assets to help exploit new
opportunities.
Unlike steady-state innovation where an
emergent good practice model exists,
discontinuous innovation routines are less
well-specified. But we can identify some of
the emerging principles around which such
learning can take place, based on the
experience of organizations experimenting
in this way. These are shown in table 2,
which maps them against the elements of the
‘steady-state’ model outlined earlier.
Conclusions
The learning process associated with
embedding and refining ‘steady-state’
routines is one of ‘adaptive’ learning, while
that needed for discontinuous innovation
requires a more ‘generative’ learning
approach. These complementary learning
themes are a key part of the dynamic
capability critical to innovation success.
Learning to manage innovation is a key
challenge for the public sector with increasing
pressures to offer new kinds of services and
improve process efficiencies in their delivery.
Although this article focused on the private
sector, the experiences and practises
described read across to the public sector.
While there is a body of experience-based
knowledge about effective innovation
management of the ‘steady state’, this has
not yet found widespread recognition or
application in the public sector. So there is
considerable potential for cross-sector
learning from the private sector, transferring
‘good practice’ tools and techniques (such as
project selection and risk management
approaches to deal with the challenge of
building and running a portfolio of
innovation projects).
There is also scope for learning about
the challenge of managing discontinuous
innovation from and with the private sector.
The issues are similar—and in many ways
the public sector has had a great deal of
experience in trying to deal with
breakthrough innovations, which often
change the rules of the game across the
whole sector, or with managing the
conflicting demands of multiple
stakeholders. The difficulties of working
within established frameworks, or risk
aversion, of selection and resource allocation
mechanisms which favour the status quo, are
common to both sectors alike—the quotations
in this article from the Medproducts’
employees could just as easily have come
from a number of public sector organizations.

41
Element in Emerging routines
innovation model
Search Search at the periphery—pick up and amplify weak signals (Day and Schoemaker, 2004)
Use multiple and alternative perspectives (Allen, 2001)
Manage the idea generation process—enable systematic and high involvement in innovation
(Bessant, 2003)
Develop an external scanning capability; use technological antennae to seek out potential new
technologies
Tune in to weak market signals, for example working with fringe users, early trend locations
(such as chat rooms on the internet) (Moore, 1999)
Develop future exploring capability—scenario and alternatives (de Geus, 1996)
Explore at periphery of firm—subsidiaries, joint ventures, distributors as sources of innovation
Bring in outside perspectives
Strategic choice Build pluralism into decision-making processes
and portfolio Create ‘markets for judgment’ (Hamel, 2000)
management Decentralize seed funding for new ideas, for example via internal venture funds or development
budgets
Build dual structures for innovation development and decision-making (Buckland et al.,
2003)
Develop ‘fuzzy front end’ approaches (Koen et al., 2001)
Implementation Build flexible project development organizations—emphasise probe and learn rather than
predictive project planning
Work actively with users on co-evolution of innovation (Von Hippel, 1988; Prahalad, 2004)
Build parallel resource networks (Leifer et al., 2000)
Innovation strategy Explore alternative future scenarios and consider parallel possibilities (de Geus, 1996)
Identify strategic domains within which targeted hunting can take place
Build capacity for ambiguity/ multiple parallel strategies
Actively explore ‘how to destroy the business’ to enable reframing (Welch, 2001)
Innovative organization Build a culture which supports and encourages diversity and curiosity-driven behaviour
Pro-active linkages Develop non-committal exploratory supply relationships in addition to longer term strategic
Table 2. Emerging routines for managing discontinuous innovation.
Set up appropriate incentive structures (McKelvey, 2004)
Enable complex knowledge flows
alliances—‘strategic dalliances’
Explore and develop parallel ‘weak ties’
Learning and Enhance absorptive capacity (Cohen and Levinthal, 1990)
capability development Encourage heterogeneity in learning group (Allen, 2001)
There is similarly a strong need in both
sectors to explore and experiment, trying to
develop ways of managing effectively under
these conditions.
For these reasons there is a strong case for
learning across the two sectors, not just in
terms of transferring well-proven lessons
(adaptive learning) but also for ‘generative
learning’ , building on shared experimentation
and comparison of experiences around
discontinuous innovation. ■
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