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Complex Acts of Knowing: Paradox and Descriptive Self-Awareness

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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. 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. 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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IBM Global Services
July 2002
Complex acts of knowing paradox
and descriptive self-awareness
Dave Snowden
Director of the Cynefin Centre for Organisational Complexity
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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 business process reengineering (BPR) initiatives. Like BPR it
has substantially failed to deliver on its promised benefits.
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.
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.
IBM Cynefin Centre for Organisational Complexity
Membership of the Cynefin 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 Cynefin 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. It is about
engaging human organisational complexity in its many manifestations,
including the ancient collective and emergent patterns of narrative,
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ritual, negotiation of identity and truth, self-representation and
knowledge exchange. The Cynefin Centre is not about consultants or
academics conducting multiple interviews or observations and deriving
static hypothesises and models based on their outside expertise’. It
is about creating focused dynamic interactions between traditional
and unexpected sources of knowledge to enable the emergence of
new meaning and insight. The Cynefin 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 Cynefin 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.
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.
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 and 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:
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1. In 1991 process reengineering was still in full flow, by 1995 its failures
in respect of capturing knowledge were becoming more obvious.
2. By 1995 collaborative computing, increasing access to e-mail and the
growth in intra and extranets were becoming commonplace.
3. Early success stories from organisations such as Buckman, Dow,
Scandia and others were making the practice of knowledge management
more respectable.
An irony is that Nonaka and Takeuchi were only seeking to contrast
a claimed Japanese tradition of oneness’ with a rational, analytical
and Cartesian western tradition. Their work derived in the main
from the study of innovation in manufacturing processes where tacit
knowledge is rendered explicit to the degree necessary to enable
that process to take place it did not follow that all of the knowledge
in the designers heads and conversations had, should or could have
been made explicit. In partial contrast, early knowledge programmes
attempted to disembody all knowledge from its possessors to make it an
organisational asset. Nonaka attempted to restate his more holistic and
dialectical view of tacit and explicit knowledge when he republished
the model utilising the Japanese word ‘Ba, which is a ‘shared space
for emerging relationships,(Nonaka and Konno 1998), but by this
time the simple two by two of the SECI model was too well established
in business plans, software brochures and the structured methods of
consultants to be restored to its original intent.
The paradoxical nature of knowledge
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. 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). For all that this is an 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.
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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, 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.
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.
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:
1. Knowledge can only be volunteered it cannot be conscripted for
the very simple reason that I can never truly know if someone is using
his or her knowledge. I can know they have complied with a process or a
quality standard. But, we have trained managers to manage conscripts
not volunteers.
2. We can always know more than we can tell, and we will always
tell more than we can write down. The nature of knowledge is such
that we always know, or are capable of knowing more than we have the
physical time or the conceptual ability to say. I can speak in five minutes
what it will otherwise take me two weeks to get round to spend a couple
of hours writing it down. The process of writing something down is
reflective knowledge it involves both adding and taking away from
the actual experience or original thought. Reflective knowledge has
high value, but is time consuming and involves loss of control over its
subsequent use.
3. We only know what we know when we need to know it, human
knowledge is deeply contextual, it is triggered by circumstance. In
understanding what people know we have to recreate the context of
their knowing if we ask a meaningful question or enable knowledge use.
To ask someone what he or she knows is to ask a meaningless question
in a meaningless context, but such approaches are at the heart of
mainstream consultancy method.
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The three heuristics partially support Stacy’s view of knowledge as an
active process of relating’ (op cit). However it does not follow that we
have to abandon second-generation practice, but we must recognise its
limitations. We can encompass both Stacy and Nonaka if we embrace
paradox. Philosophers have long seen paradox as a means of creating
new knowledge and understanding. Physicists breaking out of the
Newtonian era have had to accept that electrons are paradoxically
both waves and particles if you look for waves you see waves, if you
look for particles you see particles. Properly understood knowledge is
paradoxically both a thing and a flow in the second age we looked
for things and in consequence found things, in the third age we look for
both in different ways and embrace the consequent paradox.
Context the dimension of abstraction
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.
Figure one levels of
acceptable abstraction
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1. A colleague with whom they have worked for several years asks
a question, a brief exchange takes place in the context of common
experience and trust and knowledge is transferred.
2. A colleague who is not known to the expert asks the same question.
The discourse is now more extensive as it will take longer to create
a common context, and when knowledge transfer takes place it is
conditional ‘phone me if this happens’ or lets talk again when you
complete that stage’ are common statements.
3. The expert is asked to codify their knowledge in anticipation of
potential future uses of that knowledge. Assuming willingness to
volunteer, the process of creating shared context requires the expert
to write a book.
Each level operates at a different level of abstraction, both implicit and
explicit. Figure one, contrasts the level of abstraction with the cost of
disembodiment, most frequently the cost of codification. The model
was originally inspired by the I-Space (Boisot 1995). High abstraction
either involves expert language, taught in universities, through books,
training programmes and so on, or shared experiential and cultural
referents.
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 and so on. 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:
1. The socio-cultural system or the pattern of residence and resource
exploitation that can be observed directly, documented and measured
in a fairly straightforward manner. The tools and other artefacts that
we use to create communities, the virtual environment we create and
the way we create, distribute and utilise assets within the community.
These are teaching cultures that are aware of the knowledge that needs
to be transferred to the next generation and which create training
programmes. They are characterised by their certainty or explicit
knowability
2. Culture as an …ideational system. Cultures in this sense comprise
systems of shared ideas, systems of concepts and rules and meanings
that underlie and are expressed in the ways that humans live. Culture,
so defined, refers to what humans learn, not what they do and make,
(Keesing and Strathem 1998). This is also the way in which humans
provide ‘standards for deciding what is, ... for deciding what can be,
.... for deciding how one feels about it, ... for deciding what to do
about it and ... for deciding how to go about doing it.(Goodenough
1961). Such cultures are tacit in nature networked, tribal and fluid.
They are learning cultures because they are dealing with ambiguity
and uncertainty originating in the environment, or self generated for
innovative purposes.
Both cultures are key to the flow of knowledge within an organisation.
We need to transfer to new members, in both society and the
organisation, knowledge that has been painfully created at cost over
previous generations. The mechanisms for learning are very different
from those for teaching. In the case of teaching there is little ambiguity
between teacher and taught, in learning such ambiguity is often a
necessary precondition of innovation. The costs and scalability are also
different, in the case of teaching the population of students can be
large, varying to some degree with the level of abstraction reliability,
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scalability and economies of scale are both realistic and sensible.
Learning is more about providing space and time for new meaning
to emerge, research facilities are not cheap and not all employees can
realistically be provided with space of learning, as opposed to the
application of what can be taught.
Cynefin – diversity over time and space
The dimensions of abstraction and culture create the sense-making
model, shown in figure two below.
Figure two Cynefin:
common sensemaking
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
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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.
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
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
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 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 she/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 organisations
culture, (Snowden 1999b). At its simplest manifestation this can be a
coded reference to past experience. ‘You’re doing a Margimay 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?
Uncharted/innovative learning, low abstraction
We now reach a domain in which we have neither the experience,
nor 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
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share knowledge, depending on speed of exploitation as the means of
maintaining competitive advantage, (Boisot 1998). Here we act to create
context to enable 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.
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.
Figure three Cynefin:
decision making
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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.
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 brother 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).
Two examples make this clearer:
1. Consider what happens in an organisation when a rumour of
reorganisation surfaces the complex human system starts to mutate
and change in unknowable ways and new patterns form in anticipation
of the event. On the other hand, if you walk up to an aircraft with a box of
tools in your hand, nothing changes.
2. A feature of a complex system is the phenomenon of retrospective
coherence in which the current state of affairs always makes logical
sense, but only when we look backwards. The current pattern is logical,
but is only one of many patterns that could have formed, any one of
which would be equally logical.
Organisations tend to study past events to create predictive and
prescriptive models for future decisions based on the assumption that
they are dealing with a complicated system in which the components
and associated relationships are capable of discovery and management.
This arises from Taylor’s application, over a hundred years ago, of the
conceptual models of Newtonian Physics to management theory in the
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principles of scientific management. Subsequently a whole industry
has been built between business schools and consultancies in which
generalised models are created from analytical study of multiple case
histories. Scientific management served well in the revolutions of
total quality management and business process re-engineering and
continues to be applicable in the domain of the complicated, however,
just as Newtonian Physics was bounded by the understandings of
quantum mechanics so scientific management has been bounded by the
need to manage knowledge and learning.
The second distinction is between a complex system comprising many
interacting identities in which, while I cannot distinguish cause and
effect relationships I can identify and influence patterns of interactivity,
with a chaotic system in which all connections have broken down and
we are in a state of turbulence or eternal boiling. It is dangerous, as too
many writers do, to confuse complex with chaotic. In a complex domain
we manage to recognise, disrupt, reinforce and seed the emergence of
patters and we allow the interaction of identities to create coherence and
meaning. In a chaotic domain no such patterns are possible, unless we
intervene to impose them, they will not emerge through the interaction
of agents.
The three types of system map on to the Cynefin model, with a
separation of complicated systems into those in which we know all of the
cause and effect relationships and those that are knowable if we had the
resource, capability and time. This is illustrated in figure four. Each of
the domains contains a different model of community behaviour each
requires a different form of management and a different leadership
style.
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. Too 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
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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 which 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.
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 interesting oligarchies are often less
innovative than the idiosyncrasies of feudalism.
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
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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.
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 in 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.
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
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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.
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
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shown in figure four.
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.
The sheer number of informal and semi-formal communities within
an organisation is too 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,
Figure four Cynefin:
knowledge flows
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and critically when we need to know it. Techniques for the informal-
formal just in time transfer include:
1. Flagging by subject matter. To take an example from the author’s
own experience, during the early stage of pioneering work on narrative
techniques for knowledge disclosure a private collaboration space was
created within IBMs network, but not as a part of a formal community of
practice. This contained a record of significant mistakes and associated
learning that would only be shared in a small trusted community. The
subject matter was flagged in the formal community under the more
colloquial label of organisational story telling’. This resulted in an early
trickle of e-mails until 1999 when an article on the use of story in 3M
was published in (Shaw et al 1998) story telling became fashionable
and e-mail volume increased to a painful level. At this point a document
answering the most frequently answered questions was written in self-
defence. The socialisation pressure of the ecology forced the voluntary
codification of knowledge and that same pressure, through the various
questions provides the context that allows the production of material
at an appropriate level of abstraction. A formal document prepared in
advance of those questions would have been far too time consuming to
produce and it might also never have been needed story might have
remained an esoteric technique.
2. Expertise location systems replace the second-generation technique
of yellow pages making connections between people and communities.
One example, tacit’ will trawl e-mail records to identify where expertise
lies, but allow the individual knowledge holder to determine if his or her
expertise is to be public. The knowledge seeker will then be directed to
people whose expertise has been made public, but will not gain access
to those who desire privacy in those cases the knowledge holder
will be notified that their knowledge is being sought and they have a
choice to volunteer. If the person making the request has a reputation
for trustworthy behaviour then knowledge will be readily volunteered
otherwise they will get no access. Several subtle things have happened
here an existing asset, e-mail, discloses what we know; the paradox of
privacy is respected, if you allow privacy people will share, if you insist
on sharing they will be private; knowledge in requested in such a way
that context can be created through conversation; we have ensured that
trustworthy behaviour results in better access to knowledge and thereby
build trust into the ecology of knowledge exchange. All in all we have
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reduced cost and increased effectiveness by recognising that we are
dealing with a complex not a complicated system.
3. We can use the complex domain as a means of creating communities
in the formal space. Clustering is the identification of like-minded or
like interested individuals within the organisation, who already form
the nucleus of a community. Software tools such as affinity mapping
and social network analysis (Cross et al) can also serve to identify the
natural focal points of a proto-community. Such clusters will have
already worked out the upper and lower levels of acceptable abstraction
and will have sufficient shared context to create a sustainable, low cost
formal community. Swarming is used where no naturally occurring
cluster can be found, either to create a cluster, or make one visible.
The metaphor of a swarm of bees is appropriate here if the beekeeper
can capture the swarm after it has left the hive, then it can be put in
a new hive and will become productive. Swarming involves creating
the equivalent of a bright light and seeing what comes to it a Web
discussion group, evening lecture series, an open competition there
are many ways of finding who is interested and will also volunteer.
Only if we cannot either find a cluster or a swarm do we build a formal
community with all the associated costs of creating something from
scratch reserving our financial and time investment for the number of
situations where a non-naturalistic intervention is necessary.
Organisations need to realise the degree of their dependence on
informal networks. The danger is of chronic self-deception in the
formal organisation, partly reinforced by the camouflage behaviour
of individuals in conforming to the pseudo-rational models. A
mature organisation will recognise that such informal networks are a
major competitive advantage and while ensuring scalability through
automated process and formal constructions will leave room for the
informal communities to operate.
Disruption from knowable to chaotic
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
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of thinking is a variation of the pattern matching nature of decision-
making (Klein 1998) that is a basic feature of human condition and one
which in normal circumstances is important.
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 more
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.
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.
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 ten years of social contact to ten
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months of voluntary activity (Snowden and Kurtz 2002) and an
increasing recognition that just in time requires greater openness to
‘suppliers’ to allow them to optimise supply in to the formal system will
also accelerate the process.
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. Just in time 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.
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
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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.
In the new, complexity informedbut 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.
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.
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The views expressed in this paper are those of the author and are not
intended to represent the views of either IBM or IBMs Institute for
Knowledge Management.
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Snowden D. & Kurtz, C. (2002)”Social Network Stimulationawaiting
publication - details from author
Stacy, R. (2001) Complex responsive processes in organizations:
learning and knowledge creation Routledge
Author
Dave Snowden is Director of IBMs newly created Cynefin Centre
for Organisational Complexity and was formerly a Director of IBMs
Institute for Knowledge Management. 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.
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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Ikujiro Nonaka e Hirotaka Takeuchi establecen una vinculación del desempeño de las empresas japonesas con su capacidad para crear conocimiento y emplearlo en la producción de productos y tecnologías exitosas en el mercado. Los autores explican que hay dos tipos de conocimiento: el explícito, contenido en manuales y procedimientos, y el tácito, aprendido mediante la experiencia y comunicado, de manera indirecta, en forma de metáforas y analogías. Mientras los administradores estadounidenses se concentran en el conocimiento explícito, los japoneses lo hacen en el tácito y la clave de su éxito estriba en que han aprendido a convertir el conocimiento tácito en explícito. Finalmente, muestran que el mejor estilo administrativo para crear conocimiento es el que ellos denominan centro-arriba-abajo, en el que los gerentes de niveles intermedios son un puente entre los ideales de la alta dirección y la realidad caótica de los niveles inferiores.