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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

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