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    Abductive Research

    Abductive Research is where one considers a series of apparently unrelated events on the suspicion they may be connected. It involves creating a Pre-hypothesis, hypothesis generation leading to other methods and objectivity based on numbers & distributed cognition.

    Aggregation and Summarization

    Humans make decisions on a first fit pattern match either with past, or hypothecated future experience. We do not scan all the information that is in front of us, typically 5-10%. Based on this partial scan we match against patterns stored in our long term memory and perform a first fit pattern match against those patterns. In human terms computers are autistic, they are simply very fast at what they do. We do have limited capacity information processing capability but it is not the basis of our intelligence. Our considerable capacity to utilise and blend patterns is the basis of our intelligence, and evolutionary adaptability is more associated with pattern utilisation than information processing. Our ability to link and blend patterns in unusual ways, known as conceptual blending (Fauconnier & Turner 2002), gives us ability to adapt rapidly to changing context and critically to innovate as well as to use that most powerful tool of explanation, knowledge transfer and teaching, metaphor. People will know things in the right context but not independently of that context. The traditional role of KM has been perceived as being to summarise, aggregate and reduce. But summary is actually specific to one’s context. Complexity is one of the physical ontologies, whose interface with other systems need interactive, iterative, recursive inquiry (as any connections between meta-systems do). (The worst thing you can do to complexity is to believe you can 100 percent measure/know it. You need to probe, sense, respond with it).

    An Emergent Framework

    (Referencing the Cynefin Framework) At its most sophisticated, and in full operational use, Cynefin starts life as a sense-making framework not a categorisation model. In a sense-making the framework emerges from the data, while in categorisation the model is pre-given. The advantage of categorisation is that it is efficient, the danger is that if the context shifts then it may result in significant category errors. Now this is best understood by describing the process by which it is constructed using the narratives of an organisations’ past perspectives and possible futures.


    The title of anthro-simulation emphasizes the human as opposed to the machine/agent environment of other types of simulation. The method incorporates aspects of war gaming. The method builds on the fact that people learn faster through partial tolerated failure and under conditions of uncertainty.

    Ashby’s Law of Requisite Variety

    The larger the variety of actions available to a control system, the larger the variety of perturbations it is able to compensate. (1) Ie a model system or controller can only model or control something to the extent that it has sufficient internal variety to represent it.


    Bounded Applicability

    The concept that different and contradictory things work in different bounded spaces


    Causality versus Dispositionality

    Complex adaptive systems are not causal but dispositional in that a false causality is not assumed – instead one works with the system’s dispositions; the systems are not causal in the sense of efficient or material cause.

    Cluster Points

    Cluster points are attractors, or the pattersn which form from the interactions of many connected entities.” In complexity, attractors are the results, not the cause.


    One of the features of Emergence: (2) coherence or correlation (meaning integrated wholes that maintain themselves over some period of time);


    A complex system is a system composed of interconnected parts that as a whole exhibit one or more properties (behavior among the possible properties) not obvious from the properties of the individual parts.[1]

    A system’s complexity may be of one of two forms: disorganized complexity and organized complexity.[2] In essence, disorganized complexity is a matter of a very large number of parts, and organized complexity is a matter of the subject system (quite possibly with only a limited number of parts) exhibiting emergent properties.


    Traditionally, in sociolinguistics, social contexts were defined in terms of objective social variables, such as those of class, gender or race. More recently, social contexts tend to be defined in terms of the social identity being construed and displayed in text and talk by language users.

    Crews (also see ‘Working Across Silos’)

    One of the radical alternatives I and others are working on here is the concept of crews as a way of ritualizing, and formalizing cross silo activity.

    A crew works because its members take up roles for which they are trained, and where their expectations of the other roles in the crew is also trained and to a large extent ritualised. This means that people can assemble into a crew without the common forming, norming, storming & performing cycle.

    A crew has cognitive capacity beyond the sum of its members, members occupy their roles for limited time periods, with people swapping between roles to allow for continuity. In addition crews can delegate power in context outside of the normal hierarchies.

    Crossing the Chasm

    Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers or simply Crossing the Chasm (1991, revised 1999), is a marketing book by Geoffrey A. Moore that focuses on the specifics of marketing high tech products during the early start up period. Moore’s exploration and expansion of the diffusions of innovations model has had a significant and lasting impact on high tech entrepreneurship. In 2006, Tom Byers, Faculty Director of Stanford Technology Ventures Program, described it as “still the bible for entrepreneurial marketing 15 years later”. The book’s success has led to a series of follow-up books and a consulting company, The Chasm Group.

    Culture and Complexity

    Culture is the patterning of our interactions with our environment and it is not susceptible to design principles appropriate to the creation of bridges or software programs. In organizations, we want the most efficient systems, on in which each component of the organization is optimized in order that the system as a whole can be optimized. However, human systems are not ordered systems and the path to their optimization is to allow sub-optimal behaviour in parts.

    The Cynefin Framework

    The Cynefin framework has five domains. The first four domains are:

    Simple, in which the relationship between cause and effect is obvious to all, the approach is to Sense – Categorise – Respond and we can apply best practice.
    Complicated, in which the relationship between cause and effect requires analysis or some other form of investigation and/or the application of expert knowledge, the approach is to Sense – Analyze – Respond and we can apply good practice.
    Complex, in which the relationship between cause and effect can only be perceived in retrospect, but not in advance, the approach is to Probe – Sense – Respond and we can sense emergent practice.
    Chaotic, in which there is no relationship between cause and effect at systems level, the approach is to Act – Sense – Respond and we can discover novel practice.
    The fifth domain is Disorder, which is the state of not knowing what type of causality exists, in which state people will revert to their own comfort zone in making a decision. In full use, the Cynefin framework has sub-domains, and the boundary between simple and chaotic is seen as a catastrophic one: complacency leads to failure. In conclusion, chaos is always transitionary and dynamics are a key aspect.



    Dialectic (also dialectics and the dialectical method) is a method of argument for resolving disagreement that has been central to Indic and European philosophy since antiquity. The dialectical method is dialogue between two or more people holding different points of view about a subject, who wish to establish the truth of the matter by dialogue, with reasoned arguments.


    The “DIKW Hierarchy”, also known variously as the “Wisdom Hierarchy”, the “Knowledge Hierarchy”, the “Information Hierarchy”, and the “Knowledge Pyramid”, refers loosely to a class of models, for representing purported structural and/or functional relationships between data, information, knowledge, and wisdom. “Typically information is defined in terms of data, knowledge in terms of information, and wisdom in terms of knowledge”. In addition to a hierarchy and a pyramid, the DIKW model has also been characterized as a chain, as a framework, and as a continuum. Cynefin also emerged as a counter to DIKW.


    Removal of intermediaries in a supply chain (in this context, an information supply chain from the ground to senior management)

    Distributed Cognition

    Move away from attempting failsafe design towards setting up safe-fail experimentation’. Because you cannot analyse the problem space fully in advance, and you have to be prepared to adjust systems interactively until you find that they work. // Distributed cognition is a branch of cognitive science that proposes that human knowledge and cognition are not confined to the individual. Instead, it is distributed by placing memories, facts, or knowledge on the objects, individuals, and tools in our environment. Distributed cognition is a useful approach for (re)designing social aspects of cognition by putting emphasis on the individual and his/her environment. Distributed cognition views a system as a set of representations, and models the interchange of information between these representations. These representations can be either in the mental space of the participants or external representations available in the environment.

    Dynamic Learning Cycle

    The dynamic learning cycle starts with the informal, looks to shift some knowledge from there to fthe domain of experts on a just in time basis. That knowledge is either stabilised into the formal (although links are maintained) or cyclically disrupted to prevent entrainment and ossification. Look at reference image.

    Dynamics of Knowledge Flow:

    See Information Flow



    Everything is Fragmented

    The more you structure material, the more you summarize (either as an editor or using technology), the more you make material specific to a context or time, the less utility that material has as things change. For years now I have asked this question at conferences around the world: Faced with an intractable problem, do you go and draw down best practice from your company’s knowledge management system, or do you go and find eight or nine people you know and trust with relevant experience and listen to their stories?

    With the odd exception (generally IT managers who have just spent a few million dollars putting a best-practice system in and think people should use it), everyone goes for the stories. So why for the last decade and more have we focused on chunking up best practice? These days I add a few references to the way I and others use blogs to link and connect to insight and learning. Increasingly unstructured material, blended in unexpected ways, provides a richer source of knowledge.



    The etic attribution of inherent value or powers to an object; Dave Snowden is against techno-fetishism, or the over-reliance on technology as a solution.

    Forms of Knowledge

    As seen through the ASHEN framework: A.S.H.E.N Framework

    Dave Snowden, the Chief Scientist of Cognitive Edge, has proposed A.S.H.E.N – which stands for Artifacts, Skills, Heuristics, Experience, and Natural talent – framework to identify knowledge assets. Artifacts are things that produced by people, which include documents. Skills are expertness, practised ability. Heuristics are methods that people used to do work. Experience is an ability that is acquired through time. and Natural talent is an ability that is difficult to emulate.

    Four Points Contextualisation

    This method, known as four points involves a pre and a post process and can be summarised as follows: Pre-process: generation of several hundred examples of exemplar narratives of key moments in the organisations own history, alternative histories and imagined futures. This can be done using another method Future Backwards , but it can also be achieved by brainstorming or, best of all, by a broad capture of identity micro-narratives using SenseMaker®. See detailed process in paper.

    Four Tables

    The Cynefin contextualisation: Four tables approach is illustrated here in respect of the Cynefin framework which is a primary sense-making model to understand the different types of system and associated decision models.

    Fragmented Micronarratives

    Narratives which are fragments that have been broken up into its source data and allowing messy, but coherent real time assembly in the context of need. Information carries too many assumptions to allow it to be context free, while data has more fluidity and adaptability.


    Goodhart’s Law

    Goodhart’s law, although it can be expressed in many ways, states that once a social or economic indicator or other surrogate measure is made a target for the purpose of conducting social or economic policy, then it will lose the information content that would qualify it to play that role.


    Human Sensor Networks

    Groups of people (usually connected through technology-enabled social media) that are able to pool their knowledge and interact better with those in their network. More specifically, social computing enables the content and online interactions to constantly shift so as to better reflect the knowledge, ideas, opinions, preferences and even aspirations of allcontributors. People are able to better develop a radar of what is happening across their network; human sensor networks provide higher levels of collaborative intelligence: a range of opportunities and outputs that could not be created by any number of individuals or small groups working alone.


    Impact Measures and Monitors

    Being able to measure success without defining success in advance; contrasted with outcome based targets. See Goodhart’s Law

    Information Flow

    Using the Cynefin model, Snowden demonstrates that a limited amount of codified knowledge can be fully separated from its owners and transferred to the best practice domain. On a cyclical basis, we disrupt the assumptions and models of the knowable domain of experts allowing new meaning to emerge. Knowledge is seen as flowing between different states, with different rules, expectations and methods of management.

    Information Processing by the Human Brain

    The assumption that the human brain is a computational device has led to an information focus in learning. There is a dominance of machine-type metaphors. We have been seduced by machines, leading to an education system dominated by input/output models (promoted by some types of systems thinking) and a view of the brain as an information-processing device. The human brain is a pattern processing intelligence not an information-processing machine. We need to avoid the pattern entrainment that results from group think. The human brain evolved to handle messy coherence, not structure and order. It allows us to innovate, have insights and see things in a different way.

    Intractable Problems

    Problems which are not easily governed, managed, or directed.


    Knowledge Disclosure Points

    KDPs are the points at which people use knowledge, and may be any combination or instatiation of decisions, judgments, problem resolution and learning

    Knowledge Taxonomies

    An approach to handle narrative, as well as other material by the adoption of a classification system, frequently hierarchical, assigning the material to a category. Within knowledge management the generation of a hierarchical taxonomy has been a frequent starting point; within Library Science the Dewy-Decimal. Lambe (2007) in his excellent summary of the role of Taxonomy in knowledge management points out that Taxonomy represents a form of artificial memory,In practice taxonomies have, due to the inherent limitations of card classification systems (which passed across into early computers) being hierarchical, required an item to be placed in a single unique category.


    Learning from Failure

    Tolerated failure imprints learning better than success. All human cultures have developed forms that allow stories of failure to spread without attribution of blame. Avoidance of failure has greater evolutionary advantage than imitation of success. It follows that attempting to impose best practice systems is flying in the face of over a hundred thousand years of evolution that says it is a bad thing.

    Low probability high impact

    In the majority of cases governments and industry assess risk based on a bell curve or Gaussian distribution. Now this works well for things like tossing coins, but when it comes to natural events such as earthquakes and floods its less effective. If we use a power law (or Pareto distribution) then a double log scale of size against frequency produces a straight line (shown below but wait for it), which matched on the the curve above shows a fat tail, as shown on the blue curve. So an outlier event, dismissed as an outlier on one distribution turns out to have a much higher probability if we use the more naturally occurring Pareto one.

    Net effect of all this is that so called Black Swan events, or better low probability high impact events have a much higher probably than we thought.


    Machine versus Human Intelligence

    Much work on search, retrieval and interpretation is caught between the Scylla of restrictive taxonomies and the Charybdis of the semantic web. Too much of IT practice is based on the assumption that the human brain is a “limited capacity information processing device” (A-Level psychology text book) and that language has a common structure and meaning.

    Dave Snowden and Cognitive Edge use semi-constrained signifier sets, allowing humans to tell and index their own material within a loose structure. This work enables the pattern basis of human intelligence to be augmented by information processing power, without losing the insights that are essentially human in nature.

    Messy Coherence

    A key aspect of living with complexity; The point is that you can the structure which was there, depending on the degree of disintegration it may or may not still fulfil its original purpose Its sticky, you can be woven into its pattern or you can fly through the gaps. It has beauty even as it disintegrates, it cannot be rebuilt but has to be replaced with something that will in its turn fade.

    The metaphor carries with it the concepts of transience, but is also of purpose and for a time solidity. Depending on the context they can last for days, months or even years before they have to be rebuilt. Its not the best metaphor for an organisation, but it is a good metaphor for thinking about degrees of coherence.


    Narrative Definition

    Narratives are at the heart of our day to day discourse and our sense-making abilities. They form a part of the common sense world in which intention, interpretation and interaction are all intermingled in any narrative. The narrator and listener assume shared context for any statement to have meaning. Stories carry with them ambiguity and their meaning can be interpreted in different ways in different contexts. Narratives create meaning, and are meaning-making toolsl for humans of all levels of literacy.

    Narrative Patterns

    Stories in organisations reveal patterns of culture, behaviour and understanding in a different and, frequently more effective way than interviews and questionnaire based approaches. Narrative techniques both reveal the patterns of an organisation and are in turn the means by which it can be patterned. Narrative is a powerful tool within organisations, but is not susceptible to the engineering approaches that have dominated management practice in the last few decades. Managers need to create an environment in which the patterns of narrative meaning and the patterning capability of narrative interventions are managed in the way a gardener manages a garden, not the way an engineer designs a machine.

    Narrativebased Research

    Narrative techniques both provide a complementary form of what we will call pre-hypothesis research, but further that the use of narrative research techniques produces, through a single intervention, quantitative conclusions supported by narrative context, fragmented knowledge databases, and a mechanism for measuring impact and more complex issues such as mapping ideation cultures.

    Naturalizing Sensemaking

    Dave espoused his theory on naturalizing sense-making. We should focus on how we make sense of the world so we can act in it. Knowledge management should be about decision-making and innovation.


    Organizational Resilience

    Refer to “Robustness vs Resilience


    Paradigm Shifts

    New approaches to risk that focus on resilience rather than robustness, allowing a degree a failure but focusing on early detection and fast recovery. Shifts in systems occur from applications to architectures, from planning towards an idealised future state to managing the evolutionary potential of the present.

    Pervasive Effects

    Using narrative as a pervasive element of the organization’s life through the creation of channels and patterns within which people can tell their own stories in a natural way as part of the day-to-day progress of their work environment. Pervasive use of narrative involves the creation of sustainable capability across the entire organization


    Phronēsis (Greek: φρόνησις) is an Ancient Greek word for wisdom or intelligence which is a common topic of discussion in philosophy. In Aristotelian Ethics, for example in the Nicomachean Ethics it is distinguished from other words for wisdom as the virtue of practical thought, and is usually translated “practical wisdom”, sometimes (more traditionally) as “prudence”,


    Praxis is the process by which a theory, lesson, or skill is enacted, practised, embodied, or realised. “Praxis” may also refer to the act of engaging, applying, exercising, realising, or practising ideas.

    Praxis Makes Perfect

    Praxis is the putting of theory into practice. In Dave Snowden’s context: is the shift from attempting to replicate what has worked for others with the inevitable confusion of correlation with causation and the failure to appreciate the criticality of context, to an approach in which sound theory is applied to practice. When we understand the principles of complexity, such as agent interaction, attractors etc. then we can apply that theory to a novel situation with some confidence of a good outcome. It will not replicate past success, but will be appropriate to the current context. That used to be called praxis and is I think at the heart of this new age, and a key and controversial skill so its adoption will not be easy. Back in the seventies we used to joke that praxis makes perfect. In an age of uncertainty that is not longer a joke, its a key opportunity.

    Protecting Mavericks

    Mavericks and accidents, not experts, are responsible for many advances in society and organisations. Dave Snowden warns that in complex situations, experts can fall victim to their own thinking, and fail to see innovative solutions to novel problems.


    Rendering Knowledge

    See 7 Principles of KM

    Research and Monitoring

    The use of prehypothesis research material to reveal weak signals that would otherwise be ignored, the use of narratives as originating raw material without the disintermediation of analysis or interpretation… We therefore have a research instrument, a method of knowledge discovery and a means of monitoring or detecting changes early in real time environments

    Robustness to Resilience

    The recognition that some failures are inevitable, hence a shift in focus to speedy detection and fast recovery. Resilience is then prized over robustness.

    One of the key strategic shifts in a complexity informed era. Early detection of weak signals, fast recovery and consequently an enhanced ability to exploit the new spaces that emerge. Not only is real risk and cost reduced if a system is built for resilience, the capacity to move forward is increased while others struggle to recover and/or hold commissions of enquiry to determine blame and fault.


    S Curves adapted with Moore/ Life Cycles

    The framework in the picture combines the well established ‘S’ curve with ideas from Moore’s seminal work, Crossing the Chasm. The basic idea is that new ideas and new ways of thinking gain early enthusiasm but quickly fall away as they challenge established orthodoxy. Those ideas which manage to cross this chasm (the small dip at the start of each curve), then become the dominant idea for a period of time, before we start to exhaust their utility. This exhaustion creates the space for the next idea to come into play, but the very dominance of the old idea makes this very difficult (life cycles). Refer to links for full explanation.

    SECI model

    The SECI (Socialization, Externalization, Combination, Internalization) model is a model of the knowledge creating process to understand the dynamic nature of knowledge creation, and to manage such a process effectively.

    There is a spiral of knowledge involved in their model, where the explicit and tacit knowledge interact with each other in a continuous process. This process leads to creation of new knowledge. The central thought of the model is that knowledge held by individuals is shared with other individuals so it interconnects to a new knowledge. The spiral of knowledge or the amount of knowledge so to say, grows all the time when more rounds are done in the model. SECI has always been challenged and Cynefin originated as a counter to SECI.


    Attaching meaning to a narrative through use of a semi-structured tagging approach, created by the researche or through an emergent process using a sample of the population if enquiry is more general.

    Social Complexity

    Contemporary definitions of complexity in the sciences are found in relation to systems theory, where a phenomenon under study has many parts and many possible arrangements of the relationships between those parts. At the same time, what is complex and what is simple is relative and may change with time.

    Social Network Analysis

    At its most basic, SNA works by identifying the various individuals within a network and then proceeds to ask each of those individuals questions about their relationships with the other individuals in the network. Answers are typically scored on a numerical scale and the results plotted at different levels of significance in the form of a network chart that demonstrates the relationships that exists. Typically it identifies individuals who act as connectors within the network, boundary spanners who connect networks, information brokers and people who are peripheral to the network. The Method Social Network Stimulation was developed as an alternative for SNA.


    The word swiftboating is an American neologism used to describe a political attack based on fabrication of the evidence


    Symbiosis is an interaction between two organisms living together in intimate association or the merging of two dissimilar organisms.

    Systems Dynamics to CAS

    Most systems thinking approaches focus on defining an ideal future state, then seek to close the gap. This is seen in Porter’s approach to strategy, BPR, Six Sigma and also Learning Organisation. These approaches also tend to focus firmly on changing individual behaviour – look at the books on competences, leadership behaviour etc.

    Complexity thinking on the other hand, recognising that complex adaptive systems are not causal (in the common meaning of the term) but are dispositional in nature should focus on describing the present, then acting in that situated now to test and enable the evolutionary potential of the system in multiple parallel safe to fail experiments. Complex approaches should also focus on building collective capability through ritualised forms such as crews and network creation with techniques such as social network stimulation.


    The Tacit Dimension

    Tacit knowledge can refer to knowledge in the form of skills possessed by individuals (experiences, intution, relationships, understanding etc). Important questions in the tacit dimensio incude:is it possible for the knowledge to be made explicit and should the knowledge be made explicit?

    Theory informed Practice

    The application of sound theory (which for Snowden means natural science in the main) and monitoring for emergence.

    Think Anew

    Complexity- based approaches are inherently messy in nature: we are dealing with non-linear problems and we need multiple methods and tools operating in different ways from which patterns can emerge that allow us to think strategically. In the area of scenario planning one of the key needs is to radically increase the number of participants and the diversity of perspective.

    Trust Tagged

    Trust tagging is a natural human phenomenon that is critical to knowledge transfer and the validation of authority as well as general problem solving. Here is an example. When you have a problem or need, you could contact a Jen, a colleague to see if she or anyone she knows can help. A day later you get a call from someone who knows Jen and he says he can help you. You have just been trust tagged in a network linkage.


    Working Across Silos

    A well-functioning team within an organisation is actually much like a well-designed silo: it concentrates its energy and expertise (and identity) into the tasks it is best suited for, yet maintains context-appropriate connections and flows that maintain its relationship with the entire farm complex. Silo design metaphorically corresponds not only to the internal functioning of the team, but also to its awareness of its place in the enterprise and its relationships with other teams and with the “fields” from which and to which its “content” lows in an unending rhythm. If we look at teams in this way, the most effective organisation is made up of teams that are not entirely “transparent” or entirely “knowledge sharing” but aware of and capable of constantly negotiating internal and external connections between identities – some strong, some weak – in ways that make them and the entire organisation more effective.