Dave Snowden is Director of IBM's newly created Centre for Action Research in
Organisational Complexity (CAROC) and was formerly a Director of IBM's
Institute for Knowledge. He is a fellow of the Information Systems Research
Unit at Warwick University. He can be contacted via e-mail at
snowded@uk.ibm.com
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Keywords
This article will be published in a Special Issue of the Journal of Knowledge
Management - Vol 6, No. 2, 2002 (May) The agreement of the publishers to
distribution at this conference is gratefully acknowledged.
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Abstract
We are reaching the end of the second generation of knowledge management, with
its focus on tacit-explicit knowledge conversion. Triggered by the SECI model
of Nonaka, it replaced a first generation focus on timely information provision
for decision support and in support of BPR initiatives. Like BPR it has
substantially failed to deliver on its promised benefits.
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The third generation requires the clear separation of context, narrative and
content management and challenges the orthodoxy of scientific management.
Complex adaptive systems theory is used to create a sense-making model that
utilises self-organising capabilities of the informal communities and
identifies a natural flow model of knowledge creation, disruption and
utilisation.
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However the argument from nature of many complexity thinkers is rejected
given the human capability to create order and predictability through
collective and individual acts of freewill. Knowledge is seen paradoxically, as
both a thing and a flow requiring diverse management approaches.
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The Cynefin Centre
Membership of the Centre, which focuses on action research in organisational
complexity is open to individuals and to organisations. It focuses on
high-participation action research projects seeking new insights into the
nature of organisations and markets using models derived from sciences that
recognise the inherent uncertainties of systems comprised of interacting
agents. However, the Centre is not about attempting to apply physical or
biological models to organisations wholesale without attention to the uniquely
human capacities of free will, awareness and social responsibility.
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It is
about engaging human organisational complexity in its many manifestations,
including the ancient collective and emergent patterns of narrative, ritual,
negotiation of identity and truth, self-representation and knowledge exchange.
The Centre is not about consultants or academics conducting multiple interviews
or observations and deriving static hypothesises and models based on their
outside "expertise".
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It is about creating focused dynamic interactions between
traditional and unexpected sources of knowledge to enable the emergence of new
meaning and insight.
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The Centre is based on a model of networked intelligence,
creating a broad and loosely structured coalition of academics, industrial and
governmental organisations to create new insight and understanding for its
members into the complexity of managing in a new age of uncertainty. The basis
of all Centre programmes is to look at any issue from multiple new perspectives
and to facilitate problem solving through multiple interactions among programme
participants. Programmes run on a national, international and regional basis
and range from investigation of seemingly impossible or intractable problems to
pragmatic early entry into new methods and tools such as narrative databases,
social network stimulation and asymmetric threat response.
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Introduction
The contention of this paper is that we are entering a third age in the
management of knowledge. Further, that the conceptual changes required for
both academics and management are substantial, effectively bounding or
restricting over a hundred years of management science in a similar way to the
bounding of Newtonian science by the discoveries and conceptual insights of
quantum mechanics et al in the middle of the last century. These changes are
not incremental, but require a phase shift in thinking that appears
problematic, but once made reveals a new simplicity without the simplistic and
formulaic solutions of too much practice in this domain. A historical
equivalent is the phase shift from the domination of dogma in the late medieval
period, to the Enlightenment; moving from esoteric complication to a new
simplicity based on a new understanding of the nature of meaning.
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The first age: Information for decision support
The first age, prior to 1995 sees knowledge being managed, but the word itself
is not problematic, the focus is on the appropriate structuring and flow of
information to decision makers and the computerisation of major business
applications leading to a technology enabled revolution dominated by the
perceived efficiencies of process reengineering. For many, reengineering was
carried out with missionary enthusiasm as managers and consultants rode
roughshod across pre-existing "primitive" cultures with the intent of
enrichment and enlightenment that too frequently degenerated into rape and
pillage. By the mid to late nineties a degree of disillusionment was creeping
in, organisations were starting to recognise that they might have achieved
efficiencies at the cost of effectiveness, they had laid off people with
experience or natural talents, vital to their operation, of which they had been
unaware. This is aptly summarised by a quote from Hammer and Champy, the
archpriests of reengineering: "How people and companies did things yesterday
doesn't matter to the business reengineer" (1993). The failure to recognise
the value of knowledge gained through experience, through traditional forms of
knowledge transfer such as apprentice schemes and the collective nature of much
knowledge, was such that the word knowledge became problematic.
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1995: the transition to the second age
To all intents and purposes knowledge management started circa 1995 with the popularisation of the SECI model (Nonaka & Takeuchi 1995) with its focus on the movement of knowledge between tacit and explicit states through the four processes of socialisation, externalisation, combination and internalisation. The concept of tacit and explicit knowledge was not new; its roots in the recent past derive from Polanyi (1974). However, where Polanyi saw tacit and explicit as different but inseparable aspects of knowledge, the de facto use of the SECI model was dualistic, rather than dialectical. The SECI model had been published four years earlier (Nonaka 1991) but without the same impact, for three reasons:
Some of the basic concepts underpinning knowledge management are now being
challenged: "Knowledge is not a "thing", or a system, but an ephemeral, active
process of relating.
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If one takes this view then no one, let alone a
corporation, can own knowledge. Knowledge itself cannot be stored, nor can
intellectual capital be measured, and certainly neither of them can be
managed." (Stacy 2001).
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For all that This extreme position he does bring out
that mainstream theory and practice have adopted a Kantian epistemology in
which knowledge is perceived as a thing, something absolute, awaiting discovery
through scientific investigation. Stacy accurately summarises many of the
deficiencies of mainstream thinking, and is one of a growing group of authors
who base their ideas in the science of complex adaptive systems. That new
understanding does not require abandonment of much of which has been valuable,
but it does involve a recognition that most knowledge management in the post
1995 period has been to all intents and purposes content management.
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In the third generation we grow beyond managing knowledge as a thing to
also managing knowledge as a flow. To do this we will need to focus more on
context and narrative, than on content.
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The question of the manageability of knowledge is not just an academic one.
Organisations have increasingly discovered that the tacit and explicit
distinction tends to focus on the container, rather than the thing contained
(Snowden 2000a). Three heuristics illustrate the change in thinking required
to manage knowledge:
The issue of content and context, which runs through all three heuristics, is key to understanding the nature of knowledge transfer. To illustrate this we can look at three situations in which expert knowledge is sought.
At the highest level of abstraction, where I share knowledge with myself there
is a minor cost; I may keep notes but no one else has to read them. On the
other hand if I want to share with everyone the cost becomes infinite, as the
audience not only need to share the same language, but also the same education,
experience, values etc. In practice there is a very narrow zone between the
Lower and Upper Levels of Acceptable Abstraction in any knowledge exchange.
Expert communities resent any knowledge below the lower level as it involves
reengaging in a level of conversation which they have passed some time ago:
they will visit to teach, but not to collaborate. In contrast, a broad cross
organisation community needs to ensure that it does not exceed the upper level;
the lower level is of less importance. The upper and lower levels represent
the range of shared context and therefore the range of possible knowledge flow.
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Context: the dimension of Culture
Abstraction is one dimension of context; the other is culture. Keesing and Strathern (1998) assert two very different ways in which the term culture is used:
The dimensions of abstraction and culture create the sense-making model, shown in Figure 2. below
Cynefin (pronounced kun-ev'in) is a Welsh word with no direct equivalent in
English. As a noun it is translated as habitat, as an adjective acquainted or
familiar, but dictionary definitions fail to do it justice. A more poetic,
definition comes from the introduction to a collection of paintings by Kyffin
Williams, a distinctively Welsh artist whose use of oils creates a new
awareness of the mountains of his native land and their relationship to the
spirituality of its people: "It describes that relationship: the place of your
birth and of your upbringing, the environment in which you live and to which
you are naturally acclimatised." (Sinclair 1998). It differs from Nonaka's
concept of Ba, in that it links a community into its shared history -- or
histories -- in a way that paradoxically both limits the perception of that
community while enabling an instinctive and intuitive ability to adapt to
conditions of profound uncertainty. In general, if a community is not
physically, temporally and spiritually rooted, then it is alienated from its
environment and will focus on survival rather than creativity and
collaboration. In such conditions, knowledge hoarding will predominate and the
community will close itself to the external world. If the alienation becomes
extreme, the community may even turn in on itself, atomising into an incoherent
babble of competing self interests. Critically it emphasises that we never
start from a zero base when we design a knowledge system, all players in that
system come with the baggage, positive and negative derived from multiple
histories.
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Cynefin creates four open spaces or domains of knowledge all of which
have validity within different contexts. They are domains not quadrants as
they create boundaries within a centre of focus, but they do not pretend to
fully encompass all possibilities. The fifth central space has significance,
but is beyond the scope of this paper.
Bureaucratic/Structured: teaching, low abstraction
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This is the formal organisation, the realm of company policy, procedures
and controls. It is a training environment. Its language is known, explicit
and open. It is the legitimate domain of the corporate intranet and its shared
context is the lowest common denominator of its target audience's shared
context.
Professional /Logical: teaching, high abstraction
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Commonly professional individuals, who through defined training
programmes, acquire a specialist terminology; codified in textbooks. The high
level of abstraction is teachable given the necessary time, intelligence and
opportunity. This is one of the most important domains as knowledge
communication is at its most efficient due to the high level of abstraction; in
second generation thinking this is the domain of communities of practice
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Informal/Interdependent: Learning, high abstraction
In this domain we have the abstraction of shared experiences, values and
beliefs. This is the domain of the shadow or informal organisation, that
complex network of obligations, experiences and mutual commitments without
which an organisation could not survive. Trust in this domain is a naturally
occurring phenomenon as all collaboration is voluntary in nature. Examinations
of primitive symbolic or pictorial languages reveal some relevant facts.
Primary of among these is the ability of symbolic languages to convey a large
amount of knowledge or information in a very succinct way. Each symbol has a
different meaning according the combination of symbols that preceded it. The
problem is that such languages are difficult to comprehend and near impossible
to use unless you grow up in the community of symbol users. In some primitive
societies the symbols are stories, often unique to a particular family who
train their children to act as human repositories of complex stories that
contain the wisdom of the tribe. The ability to convey high levels of
complexity through story lies in the highly abstract nature of the symbol
associations in the observer's mind when s/he hears the story. It triggers
ideas, concepts, values and beliefs at an emotional and intellectual level
simultaneously. A critical mass of such anecdotal material from a cohesive
community can be used to identify and codify simple rules and values that
underlie the reality of that organisation's culture (Snowden 1999b). At its
simplest manifestation this can be a coded reference to past experience.
"You're doing a Margi" may be praise or blame -- without context the phrase is
meaningless, with context a dense set of experiences is communicated in a
simple form. Is the common understanding of the symbol structure and its
sequence that provides shared context in this domain
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Uncharted/Innovative: Learning, low abstraction
We now reach a domain in which we have neither the experience, not the
expertise because the situation is new, the ultimate learning environment. The
organisation will tend to look at such problems through the filters of past
experience. The history of business is littered with companies who failed to
realise that the world had changed. In hindsight such foolishness is easy to
identify, but at the time the dominant language and belief systems of the
organisation concerned make it far from obvious. This is particularly true
where the cost of knowledge creation within the organisation is high as this
tends to knowledge hoarding and secrecy that in turn can blind the organisation
to new and changed circumstances. Other organisations deliberately share
knowledge, depending on speed of exploitation as the means of maintaining
competitive advantage (Boisot 1998). Here we act to create context to enables
action, through individuals or communities who have either developed specific
understanding, or who are comfortable in conditions of extreme uncertainty.
Such individuals or communities impose patterns on chaos to make it both
comprehensible and manageable
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The third age: complicated, complex and chaotic
The above description of the Cynefin model relates to its use in the context of
communities, and it originally developed from a study of actual, as opposed to
stated knowledge management practice in IBM (Snowden 1999a) but has since been
validated in other organisations and applied to strategy, innovation, culture,
trust and communication. It is based on an understanding of the
distinctiveness of three different types of system: complicated, complex and
chaotic, best understood through two distinctions. The first distinction is
that between complex and complicated. An aircraft is a complicated system; all
of its thousands of components are knowable, definable and capable of being
catalogued as are all of the relationships between those components. If
necessary it can be taken apart and examined to discover the nature of the
components and their relationships. Cause and effect can be separated and by
understanding their linkages we can control outcomes.
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Human systems are complex; a complex system comprises many interacting agents,
an agent being anything that has identity. We all exist in many identities;
the author can be son, father or bother in different contexts; similarly with
work group identities, both formal and informal along with various social
groupings. As we fluidly move among identities, we observe different rules,
rituals, and procedures unconsciously. In such a complex system, the
components and their interactions are changing and can never be quite pinned
down. The system is irreducible. Cause and effect cannot be separated because
they are intimately intertwined (Juarrero 1999).
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Two examples make this clearer:
In Known space is the only legitimate domain of best practice. Within known
limits we can both predict and prescribe behaviour. Humans, acting
collectively can make systems that might otherwise be complex or chaotic into
known systems; we impose order through laws and practices that have sufficient
universal acceptance to create predictable environments. Two many thinkers in
complexity take models from insect behaviour and attempt to impose them onto
human interactions: while humans often behave like ants they are capable of far
more, they can direct, structure and limit inter-activity to make it
predicable. Such activity is not only desirable, but also essential in a
modern organisation or society where provides a predictable framework for
employees and citizens. On the negative side, the imposed structure can
continue beyond its useful life. In this domain we categorise incoming
stimulus, and once categorised we respond in accordance with predefined
procedures. Leadership tends to a feudal model, with budget having replaced
land as the controlling mechanism.
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Knowable space is the domain of good practice. We do not yet know all the
linkages, but they can be discovered. This is the domain of experts, whose
expertise enables us to manage by delegation without the need for
categorisation. Again there is a human imposition of order but it is more
fluid than in the space of the known. A major issue in the space of the
knowable is entrainment of thinking. There are many examples in history of a
refusal by established experts to accept new thinking: the trial of Galileo,
the thirty-year rejection of clocks as a means of measuring Longitude, the
Maginot Line in the second world war, the list is endless. The very thing that
enables expertise to develop, namely the codification of expert language in
turn leads inevitably to entrainment of thinking. Exhortations to remain open
to new ideas are unlikely to succeed. Management of this space requires the
cyclical disruption of perceived wisdom. The common context of expertise is
both an enabler and blocker to knowledge creation and from time to time context
must be removed to allow the emergence of new meaning. In this space we sense
and respond based on our expert understanding of the situation, the leadership
models are oligarchic requiring consent of the elders of the community and
interestingly oligarchies are often less innovative than the idiosyncrasies of
feudalism.
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The nature of the Complex domain is the management of patterns. We need
to identify the early signs of a pattern forming and disrupt those we find
undesirable while stabilising those we want. If we are really clever then we
seed the space to encourage the formation of patterns that we can control.
These patterns are, to use the language of complex adaptive systems theory,
emergent properties of the interactions of the various agents. By increasing
information flow, variety and connectiveness either singly or in combination we
can break down existing patterns and create the conditions under which new
patterns will emerge, although the nature of emergence is not predictable. This
is fluid space of varying stabilities over time and space. Most humans make
decisions on the basis of past or perceived future patterns not through
rational choices between alternatives (Klein 1998), an understanding of
patterns is therefore key to managing behaviour within organisations and in
relationship to markets and environmental factors. In a complex space we
cannot sense and respond, but must first probe the space to stimulate pattern
understanding or formation, then sense the patterns and respond accordingly.
Entrepreneurs manage in this space instinctively while large organisations find
it more uncomfortable. In this domain leadership cannot be imposed, it is
emergent based on natural authority and respect but it is not democratic, it is
matriarchal or patriarchal
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Chaos represents the consequence of excessive structure or massive change, both
of which can cause linkages to sunder. As such it is a space that requires
crisis management and is not comfortable, or entered with any enthusiasm by
other than the insane. However it is one of the most useful spaces, and one
that needs to be actively managed. It provides a means by which entrainment of
thinking, the inevitable consequence of expertise can be disrupted by breaking
down the assumptions on which that expertise is based. It is also a space into
which most management teams and all knowledge programmes will be precipitated;
regular immersion in a controlled way can immunise the organisation and create
patterns of behaviour that will pay dividends when markets create those
conditions. We also need to remember that what to one organisation is chaotic,
to another is complex or knowable. In the chaotic domain the most important
thing is to act, then we can sense and respond. Leadership this domain is
about power: either the power of tyranny, or that of charisma. Both models
impose order, and if order is imposed without loss of control, then the new
space is capable of being used to advantage.
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The Knowledge Spiral and Cynefin
The purpose of the Cynefin model is to enable sense making by increasing the
awareness of borders and triggering with a border transition a different model
of decision making, leadership or community. It argues strongly against single
or idealised models, instead focusing on diversity as the key to adaptability.
The law of requisite variety is well understood in ecology; if the diversity of
species falls below a certain level then the ecology stagnates and dies.
Excessive focus on core competence, a single model of community of practice or
a common investment appraisal process are all examples of ways in which
organisations can destroy requisite variety. It has always amused the author
to see the amount of work in large organisations that goes into making the
system work once a decision had been made, without any consideration being
entertained that the system itself should be changed to accommodate what is
common sense to those involved. It also creates a sub-class of people who add
no value to the organisation, but are skilled in its arcane workings and
without whose co-operation nothing happens.
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Nonaka and his various co-authors see knowledge creation as a spiral of SECI
resulting in the progressive transfer of knowledge from individual, to group,
to organisation and beyond. This is a clear view of knowledge as a thing to be
managed; that at some stage in its life cycle will be explicit. Earlier an
explicitly contradictory model was identified in which knowledge was seen as an
"ephemeral, active process of relating" (Stacy 2001). We also suggested that
this was not a contradiction but a paradox in which knowledge is simultaneously
and paradoxically both a thing and a flow. The Cynefin model allows us to see
knowledge in both its aspects and this allows us to continue to use the
insights and practices of scientific management, while embracing the new
learnings and insights from the new sciences of complexity and chaos. Cynefin
focuses on creating the conditions for the emergence of meaning: in its two
complicated domains these are rationalist and reductionist: the SECI model
works. In the complex and chaotic domains new science and new approaches are
required. The range of possible flows within the Cynefin model across its
various boundary transformations is large and has been partially described
elsewhere (Snowden 2000b), here we will look at an idealised model of knowledge
flow involving three key boundary transitions: the disruption of entrained
thinking, the creation and stimulation of informal communities and the just in
time transfer of knowledge from informal to formal. These transitions are
shown in figure 4.
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Just in Time Knowledge Management: from complex to knowable
For many years stock was held on the factory floor in anticipation of need at a
high cost and risk of redundancy. Eventually it was realised that this was a
mistake and significant levels of stock were pushed back to suppliers entering
the factory on a just in time basis thus minimising costs. Second-generation
knowledge management made all the same mistakes. In the third generation we
create ecologies in which the informal communities of the complex domain can
self-organise and self manage their knowledge in such a way as to permit that
knowledge to transfer to the formal, knowable domain on a just in time basis.
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The sheer number of informal and semi-formal communities within an organisation
is to great to permit formal management. In one study within IBM Global
Services the ratio between informal and formal communities was in excess of
1000:1 and that only represents those communities who chose to use virtual
collaboration (Snowden 1999a) so the actual ratio is probably well in excess of
this. The informal, complex space contains much knowledge that never needs to
be an organisational asset; the issue is that even if we knew what we know, we
cannot distinguish in advance what we need to know as an organisation, and
critically when we need to know it. Techniques for the informal-formal JIT
transfer include:
The second key transition is to provide cyclical disruption of the entrained
thinking in expert communities. Exhortations to be open to change and new
ideas rarely work. The history of science, ideas and markets proves the
contrary; for any radical change revolution resisted by the establishment seems
the only way forward. This entrainment of thinking is a variation of the
pattern matching nature of decision-making (Klein 1998) that is basic feature
of human condition and one which in normal circumstances is important.
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Perspective shift, when necessary is not easy to achieve and needs to be
handled with care if operational efficiency is to be maintained. However there
are various techniques that do work, taking deep experts in one field and
linking them with experts in a radically different field, which will challenge
their assumptions, is one. An actual example being the exposure of marketing
experts in a Retailer to individuals involved in the design of ballistic
missile defence systems, combined with pressure and a degree of starvation of
resource, critical to creativity powerful results can be obtained (Snowden
2001). Such disruption does not need to take such an extreme form and is best
managed as a ritual and expected process. Often it is sufficient to take the
leadership of a community into a chaotic environment, it does not have to be
the whole community. The ritual is important; humans manage boundary
transitions through rituals that both create awareness of the transition, but
equally awareness of the new roles, responsibility and social mores associated
with the new space. If the disruption is cyclical and expected, then we are
closer to a learning ecology, we have also to some degree immunised the group
in respect of involuntary moves into the chaotic space.
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Creating new identities and interactions: from chaotic to complex
We use the domain of chaos to disrupt in advance of need, in order to break
down inappropriate or over restrictive models, combined with constrained
starvation, pressure and access to new concepts and ideas. As a result we
create radically new capability within the ecology, which will both transform
the knowable domain of experts and stimulate the creation of new networks,
communities and trust/experience relationships. While new alliances and
relationships form from the creative stimulus of chaos.
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The chaotic space is not of itself the only source of natural communities, new
people join the organisation, existing projects create new informal communities
and trusted links; the normal day to day interaction of human agents is a
constant source of new communities. Chaos is particularly productive, but is
not the only source. New thinking in third generation knowledge work is
starting to look at Social Network Stimulation as means to accelerate 10 years
of social contact to 10 months of voluntary activity (Snowden & Kurtz 2002) and
an increasing recognition that JIT requires greater openness to "suppliers" to
allow them to optimise supply in to the formal system will also accelerate the
process.
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The natural flow of knowledge
We can now see the sensible patter of flow of knowledge within an organisation.
Communities form naturally in the complex domain, and as a result of activity
both voluntary and involuntary within the domain of chaos. JIT techniques,
including cluster and swarming allow us to use the complex domain to create
through a process of formalisation, more natural and sustainable communities in
the knowable domain. We can also commence operations here, but the cost will
be high. A limited amount of codified knowledge can be fully separated from
its owners and transferred to the best practice domain, that of the known. On
a cyclical basis we disrupt the assumptions and models of the knowable domain
of experts allowing new meaning to emerge. From this perspective we see
knowledge as flowing between different states, with different rules,
expectations and methods of management. We do not have to choose between views
and approaches, but we bound those approaches to their appropriate domains.
The Cynefin model allows the creation of multiple contexts.
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Conclusion
This paper has argued that the focus on tacit-explicit knowledge conversion
that has dominated knowledge management practice since 1995 provides a limited,
but useful set of models and tools. The paper rejects both the assumed
universality of tacit-explicit conversion and recent arguments that the phrase
knowledge management is an oxymoron. This is achieved by embracing the
paradoxical nature of knowledge as both a thing and a flow. The basis of the
argument is for the adoption of different tools, practices and conceptual
understanding of the four spaces of the Cynefin model: known, knowable, complex
and chaotic. This model has been made possible by key understandings drawn
from the science of complex adaptive systems. However a key distinction is
made between human complex systems, and those that are observed in nature.
Humans, acting consciously, or unconsciously are capable of a collective
imposition of order in their interactions that enables cause to be separated
from effect and predictive and prescriptive models to be built. The mistake of
scientific management is to assume that such imposed order is an absolute or
universal structure. Its stability and accordingly its usefulness are based on
common will and a stable environment. When conditions of uncertainty are
reached, the order can break down or artificially persist beyond its
usefulness. By implication it is argued that the dogma of scientific
management, hypothesis based consulting and the generalisation of best practice
from multi-client or multi project studies are inhibiting factors in
progressing to the new levels of conceptual understanding required in the
modern world.
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In the new, "complexity informed" but not "complexity constrained" third
generation, content, narrative and context management provide a radical
synthesis of the concepts and practices of both first and second generation.
By enabling descriptive self awareness within an organisation, rather than
imposing an pseudo-analytic model of best practice, it provides a new
simplicity, without being simplistic, enabling the emergence of new meaning
through the interaction of the formal and the formal in a complex ecology of
knowledge
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Acknowledgements
Some parts of this paper were originally published in the conference proceedings of KMAC at the University of Aston, July 2000. The idea of "knowledge" becoming a problematic concept comes from J C Spender.
The views expressed in this paper are those of the author and are not intended to represent the views of either IBM or IBM's Institute for Knowledge Management.
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