Download - Complex Knowledge
Complex Knowledge
Dave Snowden
Cynefin Centre for Organisational Complexity
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The three rules of Knowledge Management
Knowledge can only be volunteered, it cannot be conscripted• Camouflage – motivated by fear of abuse
• Conformity – motivated by time I only know what I know when I need to know it
• Human knowledge requires contextual stimulation
• The way that we know things is not the way that we say we know them, and that goes for decision making too
We always know more than we can say, and we will always say more than we can write down• Context Management
• Narrative Management
• Content Management
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Knowledge is the means by which we inform, not a higher order of information
Data
Information
Knowledge
Wisdom
Global Services© IBM UK Ltd 2003 COMMERCIAL IN CONFIDENCE
Knowledge is the means by which we inform, not a higher order of information
Data
Information
Knowledge
Wisdom
Global Services© IBM UK Ltd 2003 COMMERCIAL IN CONFIDENCE
Knowledge is the means by which we inform, not a higher order of information
Dat
a
Information
Knowledge
Wisdom
Context
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The model that launched a thousand failed KM initiatives: Nonaka’s SECI
Originally a paper on knowledge transfer in the consumer goods manufacturing industry in Japan
Rapidly generalised as a model for knowledge transfer in all sectors
Closely linked with Business Process Re-engineering
Used way beyond Nonaka’s original intent
Tacit Explicit
Exp
lici
tT
acit
Socialisation Externalisation
CombinationInternalisation
S E
CI
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ASHEN Modela meaningful question
ArtefactsAny thing made by people, processes, documents, tools in which knowledge is imbedded
SkillsAbilities that can be trained and measured without ambiguity, but remember the time issue
HeuristicsRules of thumb, the outcome of experience, the main repository of knowledge mostly unarticulated
ExperienceAccumulated experience of failure and success which allows the right pattern to be triggered in the right context
Natural TalentSome people are just better at doing things than other people – and they are often not the people you expect
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Knowledge Disclosure Pointsa meaningful context
Any event or activity which reveals knowledge through use• Decisions
• Problems resolution
• Solution creation
• Judgement
• Learning points Used to create the context in which the ASHEN question can be
asked Can be achieved through virtual and physical means
• Virtual allows anonymity and multi-persona techniques to be used
• Physical provides a different dynamic of interaction to vitual (not better or worse but virtual)
DO NOT judge or value or move to solution
First Exercise
Knowledge Disclosure Points
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Discovering KDP & ASHEN
Anecdote Circles• A group with cohesive experience• May use a structured task (e.g.
future history)• Stimulate Ditting• Use of Actors, Cartoonists etc • Use of Proxies
Mass Capture Techniques• Naïve Interviews• The Set up
Participative techniques• Field Interviews• Participative Observation• Deep Emersion
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From KDP to Knowledge Objects
HAA S
KDP CLUSTERS
ASK ASHEN EAA S
N
HAA S
ASHEN CLUSTERS
KN
OW
LE
DG
E
OB
JEC
TS
Global Services© IBM UK Ltd 2003 COMMERCIAL IN CONFIDENCE
From KDP to Knowledge Objects
HAA S
KDP CLUSTERS
ASK ASHEN EAA S
N
HAA S
ASHEN CLUSTERS
KN
OW
LE
DG
E
OB
JEC
TS
Communities and JIT Knowledge management
Using the natural flow patterns of an organisation
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Acceptable levels of Abstraction
Ab
str
acti
on
Cost of Codification
ULAA
LLAA
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The Cynefin sense making framework applied to knowledge management
High Abstraction
Low Abstraction
Teach
ing
Cu
lture
sLearn
ing
Cu
ltu
res
Communities of Practice
The Domain 150
Committees & Review BodiesBureaucracy
The Shadow OrganisationDomain of
15
Chaos the threat of the
newCrisis
management & opportunity
Global Services© IBM UK Ltd 2003 COMMERCIAL IN CONFIDENCE
The Cynefin sense making framework applied to knowledge management
High Abstraction
Low Abstraction
Teach
ing
Cu
lture
sLearn
ing
Cu
ltu
res
Communities of Practice
The Domain 150
Committees & Review BodiesBureaucracy
The Shadow OrganisationDomain of
15
Chaos the threat of the
newCrisis
management & opportunity
Global Services© IBM UK Ltd 2003 COMMERCIAL IN CONFIDENCE
The Cynefin sense making framework applied to knowledge management
Good Practice
Best Practice
Emergent Practice
Decisive Action
High Abstraction
Low Abstraction
Teach
ing
Cu
lture
sLearn
ing
Cu
ltu
res
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Communitiesan emergent model
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Communitiesan emergent model
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Social Network Analysis
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Knowledge Project MatrixK
NO
WL
ED
GE
OB
JEC
TS
!!!!
!!!!!!
!!
!!!!!!
5 2 4 1 3 7 6
THE THINGS DECISION MAKERS VALUE
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Knowledge Project Matrixeasy to sell, hard to implement
KN
OW
LE
DG
E O
BJE
CT
S
!!!!
!!!!!!
!!
!!!!!!
5 2 4 1 3 7 6
THE THINGS DECISION MAKERS VALUE
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Knowledge Project Matrixhard to sell, easy to implement
KN
OW
LE
DG
E O
BJE
CT
S
!!!!
!!!!!!
!!
!!!!!!
5 2 4 1 3 7 6
THE THINGS DECISION MAKERS VALUE
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Knowledge Project Matrixa portfolio of knowledge projects
KN
OW
LE
DG
E O
BJE
CT
S
!!!!
!!!!!!
!!
!!!!!!
5 2 4 1 3 7 6
THE THINGS DECISION MAKERS VALUE
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Creating a Knowledge Strategy“what” related to value, where and flow
KN
OW
LE
DG
E O
BJE
CT
S
!!!!
!!!!!!
!!
!!!!!!
5 2 4 1 3 7 6
THE THINGS DECISION MAKERS VALUE
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The history and context of knowledge management
The first generation before the SECI model• Information Management
• Technology supports human decision making The second generation the SECI period (corruption of Nonaka)
• Knowledge is tacit or explicit
• KM practice focuses on the conversion of tacit to explicit knowledge
• Closely linked to Business Process Re-engineering (BPR)
• Focus on maximising efficiency The third generation post SECI
the impact of complexity science• Knowledge is never wholly tacit or explicit
• Just in Time Knowledge Management
• A focus on effectiveness rather than efficiency
To improve the effectiveness (not the efficiency) of decision
making and to create the conditions for innovation
The purpose of Knowledge Management
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3rd Generation or Post SECI KM
Content Management Narrative Management
• Narrative representation, neither qualitative, quantitative but emergent• Archetypes & themes & & & &
• Narrative databases• Indexed on emergent, NPML and Demographic data• Enable Serendipitous encounter
• Myth Management• Fable Construction• Story Virus• Monitoring
Context Management• Social network stimulation• Expertise location• Narrative (metaphor)• JIT KM
Technology is a tool: if we pick it up and it fits our hand it is useful, if we have to bio-reengineer our hand to fit the tool something is
going badly wrong!
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Knowledge Managementthe final metaphor
How do you learn to ride a bicycle?
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The Cynefin Centre
Nasrudin found a weary falconsitting one day on his window-sill. He had never seen a bird like this before.‘You poor thing’, he said, ‘how ever were you to allowed to get into this state?’He clipped the falcon’s talons and cut its beak straight, and trimmed its feathers.‘Now you look more like a bird,’ said Nasrudin.
From Idries Shah, The exploits of the Incomparable Mulla Nasrudin & The subtleties of the Inimitable Mulla Nasrudin. Octagon Press, London 1985
The Cynefin Centre
A new paradigm in research and method development
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The presumptions of management science and consultant practice
The presumption of rational choice• human actors make a “rational” decision based on self interest• individual and collective behavior can be managed by manipulation of
pain/pleasure• education to make those consequences evident will change behavior
The presumption of intentional capability• the acquisition of capability indicates an intention to use that capability• actions from competitors are the result of intentional behaviour: every “blink” we
see is in effect a “wink” and act accordingly. • hypocrisy of intent, we have accidents, they don’t
The presumption of unitary and stable identity• organisations are aggregations of discrete individuals• categorisation and stereotyping• scalability – the rule of 15 & 150
The presumption of order• relationships between cause and effect capable of discovery and empirical
verification and in consequence, prescriptive and predictive models are possible
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Contextual Complexitythe landscape of management
Empirically KnownThe domain of
the actualCause and effect relationsCause and effect relations
repeating & predictablerepeating & predictable
Empirically KnowableThe domain ofthe probable
Cause and effect separatedCause and effect separatedover time & space but repeatover time & space but repeat
ComplexThe domain of many
possibilitiesCause and effect coherent in Cause and effect coherent in
retrospect, repeat accidentallyretrospect, repeat accidentally
ChaosThe domain of the
inconceivableNo cause and effect relationships No cause and effect relationships
generally perceivablegenerally perceivable
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Contextual Complexitydecision models
The domain ofthe actual
SenseCategoriseRespond
The domain ofthe probable
SenseSenseAnalyseAnalyseRespondRespond
The domain of many possibilities
ProbeProbeSenseSense
RespondRespond
The domain of the inconceivable
ActSense
Respond
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Contextual ComplexityIntervention types
Empirically KnownThe domain of
the actualLegitimate best practice
STANDARD PROCEEDURESPROCESS RE-ENGINEERING
Empirically KnowableThe domain ofthe probable
Analytical/ReductionistSCENARIO PLANNINGSYSTEMS THINKING
ComplexThe domain of many
possibilitiesPattern Management
PERSPECTIVE FILTERSCOMPLEX ADAPTIVE SYSTEMS
ChaosThe domain of the
inconceivableStability focused intervention
ENACTMENT TOOLSCRISIS MANAGEMENT
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Interpretation of state determined by preference for action
Known
Knowable
Complex
Chaos
DISORDER
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Crisis managementmulti-point attractors
Asymmetric Collapseexcessive order leads to the collapse of order – chaos
Single point attractorsthe charismatic dictator stabilise to order, with the danger of asymmetric collapse
Multi point attractorscreate several points of attraction (chaos to complexity) to seed possibilities
Select favourable patterns to exploit (Complex to Knowable)
Kill unfavourable patterns (but you don’t know which they will be
X
X
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Discovery and InterventionNetwork linkages
Strong centralStrong central
strong strong distributeddistributed
Strong centralStrong central
weak weak distributeddistributed
WeakWeak
centralcentral
strong strong distributeddistributed
WeakWeak
CentralCentral
weak weak distributeddistributed
Domain of the Actual
Domain of the ProbableDomain of Possibilities
Inconceivable Domain
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Diagnosis - principles
Domain of the ActualWe can teach people how to do We can teach people how to do things very quickly and ensure things very quickly and ensure
compliancecomplianceWe control the space and can
determine behaviourAny diagnostic is a simple check
against predetermined criteria
Domain of the ProbableWe have learnt how to solve this We have learnt how to solve this problem and are now in a stable problem and are now in a stable
situationsituationWe have been here before and any deviations are readily understood
Diagnostics can be separatedfrom intervention
Domain of PossibilitiesEvery time we think we have Every time we think we have
solved the problem it returns in a solved the problem it returns in a different formdifferent form
Minor, troublesome events occur but are easily rationalised Diagnostics are interventions –
they influence the patterns
Inconceivable DomainThis is a new situation in which This is a new situation in which we no previous experience and we no previous experience and
have no reflective timehave no reflective timeSomething completely unexpected at this time
There is no time or need for any diagnostic
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Intervention
Domain of the ActualStandard process with reviewStandard process with review
cycle & clear measurescycle & clear measures
Establish indicators to prevent Establish indicators to prevent catastrophic failurecatastrophic failure
SENSE – CATEGORISE - RESPONDSENSE – CATEGORISE - RESPOND
Domain of the ProbableAnalytical techniques to determine Analytical techniques to determine
facts and option rangefacts and option range
Create ritual/cyclical process to Create ritual/cyclical process to prevent entrainment of expertiseprevent entrainment of expertise
SENSE – ANALYSE - RESPONDSENSE – ANALYSE - RESPOND
Domain of PossibilitiesMultiple small and diverse Multiple small and diverse
interventions to create optionsinterventions to create options
Always have an exit strategy to the Always have an exit strategy to the ordered domains for exploitationordered domains for exploitation
PROBE – SENSE - PROBE – SENSE - RESPONDRESPOND
Inconceivable DomainSingle or multi point attractor(s) Single or multi point attractor(s)
to stabilise situationto stabilise situation
Avoid creating long term Avoid creating long term dependency on single attractordependency on single attractor
ACT – SENSE - RESPONDACT – SENSE - RESPOND
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The Cynefin Life Cycle
Licensed Methods
Comprise Components Models and ToolsWhich have Attributes and UsesAnd combine into Assemblies and RecipesInterface with Other bounded
techniques
Emergent Methods
Are Experimental Innovative and ChallengingThey are Sold at cost Using key staff and Aim to become
LicensedThey can Use the elements of
licensed method Create new elements
Discovery Programs
Address Intractable Problems Re-vitalising other
approachesComprise Catalytic and
Patterning Events Focused
Participatory Learning Streams
Emergent ResearchTypically Run over 3-6 months Are Multi-client