Tom Graves

Several people asked me to cross-post to other ‘economics’ sites the previous post on ‘Whuffie’ and currencies‘. I wasn’t comfortable doing so without editing-out the comments about the ‘Ready? Fire! Aim…’ syndrome, which were specific to the conversations to which that post referred: hence the re-work in this post here. I’ve also taken the opportunity to extend some parts, to link it more strongly to my ‘day-job’ of enterprise-architecture.

So: what can we learn if we tackle economics as enterprise-architecture? In other words, as if it was just another exercise in whole-of-enterprise architecture, the same as we would do for any large organisation (such as described in my book ‘Doing Enterprise-Architecture‘)? After all, ‘the economy’ is just another enterprise – it happens to be at a very large scale, but the exact same principles should apply.

(This’ll be another long one, hence I’ll place a ‘Read more…’ link here.)

Read more…

(This series of posts explores a concept of ‘context-space’ which in part draws on a categorisation immortalised in a certain well-known diagram. It must be emphasised that this is not about ’That Welsh Framework‘ (aka twf) which that diagram illustrates: for details on twf, please contact this company. I apologise for these absurd aliases, but regrettably their necessity has been forced upon us by others.)

We seem to be iterating steadily towards a full description of what I’ve termed context-space mapping (as a more permanent name than the temporary label ‘tinc‘). For example, there’s been some very useful discussion on the previous post, especially by enterprise-architects Paul Jansen and Sally Bean. Paul Jansen followed this up with another Tweet:

@tetradian May the ‘chaotic approach’ be the key to #tinc? http://bit.ly/amJa1o

In fact this leads to what is probably the fundamental difference between twf and context-space mapping (aka tinc): the role of the Chaotic domain. This particularly applies in terms of the respective views of repeatability within the context.

In the hope of preventing yet more repercussions, I won’t say anything about twf’s approach at this point, other than to express my opinion that, in the terms of context-space mapping, its focus is primarily on the Complex domain, which in turn leads to an emphasis on contexts that are ‘partly-repeatable’ in highly complex ‘unordered’ ways.

Context-space mapping, however, needs to cover all repeatability-types. As twf’s proponent indicates, the Simple domain of presumed-repeatability is covered by Taylorism et al.; the Complicated domain of analysed-repeatability by hard-Systems Thinking and the like; and the Complex by twf and so on. But there’s so far been little or nothing to cover the Chaotic domain of ‘barely-repeatable’ events and processes. So in practice it’s likely that that’s where whole-of-scope techniques such as context-space mapping will have the most impact.

The central theme in the Chaotic domain of practice is low- to zero-repeatability: some part(s) of the practice cannot be repeated, either because the conditions have changed – including the awareness and experience of the person doing the work. Conventional ’scientific-analysis’ approaches (Complicated-domain) rely on repeatability, so they’re actually not all that much use in the Chaotic components of any real-world task – in fact will often be misleading because they provide an illusion of predictability. In a way, the same is true of many Complex-domain techniques: they give us a much more reliable picture of an overall uncertain context, but we can’t reliably apply that in reverse to tell us what to do for a specific ‘market-of-one’, such as a specific medical diagnosis.

Ability to engage appropriately in the Chaotic-domain in this sense is almost a definition of skill. It’s also a key component of almost all knowledge-work – which is why this concern is coming much more to the fore, as knowledge-work becomes an increasingly important part of the overall economy.

At the business-process level, one of the key figures is Sigurd Rinde, whose concept of ‘barely-repeatable processes’ is the focus for his Thingamy business-process-execution software. The whole point of Thingamy is that the processes themselves are made up as they go along, by the people doing the work, expressing and applying their expertise. Underneath this, however, is a consistent Simple structure that records every decision, every artefact, every transfer of responsibility – which makes it possible to create any required reports from the process, including conventional statistical analysis. The result is nicely summarised on Sig’s other website, 30megs.com – so-called from his tag-line “Here’s 30 Megs. Now go run Germany”, which in principle is entirely feasible with this kind of decision-support/decision-tracking software. Sig is not alone in this, of course – for example, Stafford Beer developed something similar that in effect ran the entire economy of Chile for a while, way back in the early 1970s – but Thingamy is probably the best example of a software package available today that is designed for true Chaotic-domain processes.

Context-space mapping is part of what needs to happen before we settle on any technique or tool such as Thingamy. It’s about mapping the options available to us, and the decisions that we make within ’solution-space’, as part of an overall process of sensemaking in order to arrive at appropriate actions for the context. One of the key points in this is an awareness that we are part of the context, part of the ’solution’: in the classic Chaotic-domain sense, there is a boundary, and there is no boundary, always in the same moment.

We always start from ‘reality’ – that which in twf is termed the ‘disorder’ domain. (Everything does in fact take place within that domain: any purported subdivisions – such as Simple, Chaotic and suchlike – are sensemaking-abstractions that we place onto that domain, but are not actually ‘real’ as such.) From there, we would move into some kind of recursive OODA loop (Observe/Orient/Decide/Act), where sensemaking itself forms one or more of the earliest iterations. In those terms, context-space mapping would typically proceed as follows:

• Observe: What is ‘the context’ here?
• Orient: How do I make sense of what I’m seeing?
  1. What parts of the context appear to be unique (Chaotic), unordered or ‘wicked-problem’ (Complex), complicated but repeatable (Complicated) or universal (Simple)? Using that categorisation, map out the ‘problem-space’.
  2. Given that categorisation, what cross-maps would be useful for sensemaking?
     Note: There are an infinite number of cross-maps that could be used: some examples shown in this series include:
     • here: repeatability and action-tactics; domains and tetradian asset-dimensions; time versus focus; Jungian domains
     • here: twf tactics and types of practice; timescale versus ‘bindedness’; development of embodied ‘best-practice’
     • here: repeatability and ‘truth’; marketing versus sales; the ‘plan / do / check / act’ cycle
     • here: ISO-9000 quality-model; skill-levels; automated versus manual processes; asset-types; data, information, knowledge, wisdom
     • here: cause/effect relationships; decision-mode, timescale and level of abstraction
     • here: nature of boundaries between domains
     • here: phases of matter
  3. Using the categorisations from the cross-maps, what available tools and techniques are ’situated’ in what regions of the maps’ ’solution-space’? What can we learn from this?
• Decide: Given what I have learned from sensemaking, what should be my ‘action-plan’?
  1. Select from the available tools/techniques.
  2. Decide on a plan as to how, why, when, where, by whom, with what, and in what order each of the selected tools or techniques should be used.
• Act:  What am I doing as I am doing, and what do I see as I am doing?
  1. Enact the desired action.
  2. Apply the same overall OODA-loop to the action taken – recursively, where appropriate – for review, further sensemaking, decision and action.
• Repeat as appropriate.

(Some people might suggest that this kind of OODA-loop fits more within a twf-style Complex-domain mode than Chaotic-domain. True, there are important similarities, such as the shared focus on ‘unorder’ versus the Complicated/Simple notion of ‘order’. But the key distinction is that this acts on a single, individual, specific context rather than a Complex-domain collective – and is often also much closer to real-time than most Complex-domain decision-making.)

The above is a start towards how we would use context-space mapping, anyway. I’ll leave it there for now: any constructive comments, ideas and suggestions would be most welcome, as usual – over to you?

Previous posts in this series:

• Complexity, chaos and enterprise-architecture
• More on chaos and Cynefin
• Alternatives to the ‘Cynefin’ term, please?
• Solution-space: beyond Cynefin?
• On meta-methodology
• Using ‘Cynefin-like’ cross-maps
• More ‘Cynefin-like’ cross-maps
• And more ‘Cynefin-like’ cross-maps
• More on meta-methodology
• ‘tinc’ – a Temporary Inconvenience
• Context-space mapping and enterprise-architecture

Related:

• ‘Two Cryptic conversations‘

(This series of posts explores a concept of ‘problem-space’ versus ’solution-space’ which in part demonstrates alternative uses and interpretations of the Simple / Complicated / Complex / Chaotic categorisation originally described in the Cynefin diagram. It must be emphasised that this is not about the Cynefin Framework; for details on Cynefin, please contact Cognitive Edge.)

This post represents yet another attempt to describe certain fundamental differences in approach from twf (aka ‘That Welsh Framework‘ – so-called because we’re no longer allowed to use its official name at all) and to find an alternative term that might reduce the ongoing friction in that quarter.

To do this, we need to go right back to first-principles: the core concept of context-space, which eventually leads us to context-space mapping.

(Another long-ish post: more after the ‘Read more…’ link.)

Read more…

(This series of posts explores alternate uses of the Simple/ Complicated / Complex / Chaotic categorisation originally described in the Cynefin diagram. This discussion is not about the formal Cynefin Framework; for details on the Cynefin framework proper, please contact Cognitive Edge. The term ‘beyond-Cynefin’ is solely a placeholder to indicate this separation of concerns.)

Back to theory again – apologies… – following on from comments on the previous posts, especially ‘On meta-methodology‘.

The aim of this post is to try to create a bit more clarity around the notion of ‘problem-space’ versus ’solution-space’. To do this, I’ll draw on a variety of sources, ranging from dowsing to enterprise-architecture, Sigurd Rinde’s work on ‘barely-repeatable processes’, activity/response-models such as OODA and PDCA, and much more besides.

Will again be long, hence more after the ‘Read more…’ link.

Read more…

(This is part of an ongoing series that explores alternate uses of a generic conceptual categorisation originally described in the well-known Cynefin diagram. This discussion is not about the formal Cynefin Framework; for details on the definition and use of the Cynefin framework proper, please contact Dave Snowden at Cognitive Edge. The term ‘beyond-Cynefin’ is here used solely as a placeholder to indicate this separation of interests.)

Here’s another collection of ‘Cynefin-like’ cross-maps that I’ve found useful for sensemaking in enterprise-architecture and related work:

• ISO-9000 quality-model
• Skill-levels
• Automated versus manual processes
• Asset-types
• Data, information, knowledge, wisdom

More details after the ‘Read more…’ link.

Read more…

(This is part of an ongoing series that explores alternate uses of a generic conceptual categorisation originally described in the well-known Cynefin diagram. This discussion is not about the formal Cynefin Framework; for details on the definition and use of the Cynefin framework proper, please contact Dave Snowden at Cognitive Edge. The term ‘beyond-Cynefin’ is here used solely as a placeholder to indicate this separation of interests.)

Another collection of ‘Cynefin-like’ cross-maps that I’ve found useful in various aspects of my enterprise-architecture work:

• Repeatability and ‘truth’
• Marketing versus sales
• The ‘Plan / Do / Check / Act’ cycle

More details after the ‘Read more…’ link.

Read more…

(This is part of an ongoing series that explores alternate uses of a generic conceptual categorisation originally described in the well-known Cynefin diagram. It should be emphasised that this discussion is not about the Cynefin Framework, which is a distinct body of practices based on scientific research. For details on the definition and use of the Cynefin framework proper, please contact Dave Snowden at Cognitive Edge. As this broader usage of the categorisation does not yet have a specific name, the term ‘beyond-Cynefin’ is here used solely as a temporary placeholder to indicate this separation of interests.)

‘Cynefin-like’ cross-maps

I first started using what we could describe as ‘Cynefin-like’ models several decades ago, such as in my book Inventing Reality (first published 1986, current print-edition available here). I’ve found them immensely valuable in a very wide range of applications, especially in disciplines such as enterprise-architecture that necessarily cover the entire scope of a context. The key to its usefulness is that the model’s categorisation provides a consistent base-map for all manner of cross-maps, each of which provides new insights about the context.

Typical characteristics of a ‘Cynefin-style’ base-map include:

• universality: the model purports to cover the entire scope of a given context
• sensemaking: the purpose of the model is to guide sensemaking and decision-support, rather than (for example) design and implementation of a specific ’solution’
• simple partitioning: the model divides the context into a small number (typically 4-5) of regions or ‘domains’ (e.g. the Cynefin set of ‘Simple’, ‘Complicated’, ‘Complex’ and ‘Chaotic’), and often including a ‘none-of-the-above’ region (e.g. the Cynefin central region of ‘Disorder’)
• fluid boundaries: the boundaries between regions are not rigidly fixed (as they are in e.g. a two-axis matrix), and may be allowed to move, blur and/or be somewhat porous
• usage-dependent layout: the layout of the model may not be semantically significant (as it is in e.g. a two-axis matrix) – layouts are often two-dimensional, but may be single-dimension horizontal or vertical, or multi-dimensional such as the four-axis/three-dimension tetradian

(More after the ‘Read more…’ link.)

Read more…

(This is part of an ongoing series that attempts to resolve problems in (mis)interpretation of the Cynefin framework, and in particular the commonly-used Cynefin diagram. For the correct interpretation and use of the Cynefin framework and Cynefin techniques, please contact Dave Snowden at Cognitive Edge.)

The standard Cynefin diagram is as follows:

Diagram by Dave Snowden, Cognitive Edge (image: public domain)

As the Wikipedia article states, “The model provides a taxonomy that guides what sort of explanations and/or solutions may apply.” Unfortunately, this is a generic model that lends itself to multiple interpretations, only one of which is ‘correct’ Cynefin. There are also multiple uses of the concepts and conceptual space summarised in the model’s taxonomy and pathways, of which, again, only a specific subset may legitimately be described as Cynefin.

It is therefore important to state that what follows is not ‘Cynefin’, yet necessarily uses what is in essence much the same taxonomy (see ‘Framework role and purpose’ and ‘Similarities to Cynefin’ in the previous post ‘Solution-space: beyond Cynefin?‘).

The central theme in this ‘not-Cynefin’ framework is the concept of ‘problem-space’ and ’solution-space’.

Problem-space is the context of the problem. Part of this is repeatability, or perceived cause-effect relationships, which can usefully be mapped using the same ‘Cynefin’ taxonomy:

• Simple: very high perceived repeatability, in accordance with simple linear cause-effect rules
• Complicated: linear (repeatable) cause-effect relationships, but may involve multiple factors, delays and feedback-loops
• Complex: cause-effect relationships are context-dependent – for example, where the effect itself becomes the cause
• Chaotic: no perceived cause-effect relationships

(The central region of ‘Disorder‘ is always ‘chaotic’, by definition, because it is the starting-point before any cause-effect relationships can be determined; the Chaotic-domain of problem-space applies where some or all of the problem continues to show no perceivable cause-effect relationships.)

Solution-space is the context and characteristics of the solution – i.e. the methods used to resolve the perceived problem. This too can be usefully mapped using the same taxonomy:

• Simple: the solution uses rules based on linear cause-effect logic
• Complicated: the solution uses analytic algorithms allowing for feedback, delays, etc, but are ultimately based on linear cause-effect logic
• Complex: the solution uses context-sensitive heuristics, guidelines and iterative re-assessment, in which the problem is continually ‘re-solved’ rather than ’solved’
• Chaotic: the solution uses principles to guide creation of uniquely context-dependent results

(Note: these are only one-line summaries, not formal definitions!)

The process of finding an appropriate solution to a specified problem can be mapped as a pathway across solution-space. To succeed (i.e. to be effective), the ultimately-selected solution(s) must map appropriately to the context of the problem in problem-space. Note that although in some cases a problem may be situated in just one specific location in problem-space, it is more common for it to occupy a region or even to have components that spread out across multiple regions. For example, a context might be mostly resolved by a rules-based automated process (Simple) but also ’special cases’ that may need to be ‘escalated’ to an algorithmic system (Complicated), a manual review (Complex) or specialist expertise (Chaotic) for a ‘one-off’ incident. The overall solution must resolve all components in problem-space.

The core concept in the use of this framework is recursive meta-methodology. For example:

• a method in solution-space acts on the problem in problem-space
• a methodology selects an appropriate method
• a meta-methodology selects an appropriate methodology
• a meta-meta-methodology selects an appropriate meta-methodology

…and so on. A methodology is a path within solution-space; a meta-methodology is a path in another layer of solution-space; in effect, the layers may be nested indefinitely, but must ultimately all resolve to a set of methods that address the actual problem in problem-space.

The ultimate aim of all of this is to find methods that are appropriate and effective for any given problem, in any business context (such as my primary field of enterprise-architecture), or in any other field, as required.

I’ll stop here for now, but will give more explanation and illustrative examples in later posts in this series.

Previous posts in this series:

• ‘Complexity, chaos and enterprise-architecture‘
• ‘More on chaos and Cynefin‘
• ‘Alternatives to the ‘Cynefin’ term, please?‘
• ‘Solution-space: beyond Cynefin?‘

The previous posts on ‘chaos and Cynefin’ were intended to contribute to an ongoing debate about how to use concepts from the published Cynefin framework and the like, and particularly to underpin a systematic exploration of what many Cynefin aficionados would describe as the ‘Chaotic domain’. It’s evident that there’s a real perceived need there, because overall I’ve so far had several hundred reads, several dozen re-Tweets (particularly via knowledge-management thought-leader David Gurteen and management-consultant Paul Jansen, for which many thanks), and a lot of constructive comments and feedback – all of which have been very helpful.

Unfortunately, as can be seen from his comments to those posts, one person who was definitely not happy about such ideas was the originator of Cynefin, Dave Snowden. So there’s evidently a major problem for us there.

What is clear is that, whether Dave likes it or not, a substantial community already uses Cynefin concepts and Cynefin terminology to describe a kind of meta-methodological ’solution-space’ within which various methods, methodologies and tactics can be situated, and their respective appropriateness for specific contexts can be assessed. What’s also clear is that, as far as Dave is concerned, we are no longer permitted to use the term ‘Cynefin’ for this ‘framework-that-occupies-much-the-same-conceptual-space-as-Cynefin’: we do need to find an alternative term for this.

In short, to describe that ’solution-space’, it seems we now need to move beyond Cynefin.

To do that, we need to identify:

• the role and purpose of this ‘not-Cynefin framework’
• how it draws from the published Cynefin framework and/or common usages of that framework
• how it extends and/or differs from the published Cynefin framework
• summarise how this framework would be used in practice

Once we’ve done that, we can perhaps start looking for an appropriate alternative term to describe it.

This is again going to be long, so I’ll stop here for a moment with a ‘Read more…’ link.

Read more…

Courtesy of a link by fellow enterprise-architect Sally Bean, I’ve just spent the past couple of hours viewing and then reviewing an online seminar on complexity by one of the thought-leaders on complexity-theory and practice, Dave Snowden:

From Induction to Abduction: a new approach to research and productive enquiry

This seminar will provide a summary of both the theory and practice of a new approach to research based on the large scale capture of self-interpreted micro-narrative.  The approach has been described as the first technique for distributed ethnography and has been developed over the past decade with project based funding from the US, UK and Singapore Governments in the context of risk assessment, horizon scanning, cultural mapping and weak signal detection.  It allows the linkage of research with knowledge management and impact based measurement.  Current projects involve measuring the impact of development projects in Africa, narrative based knowledge management for the US Army in Afghanistan and cultural mapping of various inner city communities within the UK.

The theoretical origins lie in the application of complex adaptive systems theory to social systems together with new understanding about the nature of human decision making from the cognitive sciences. The seminar will summarise the theory, but will also use a series of projects to combine theory with practice.  One of the goals is to create learning systems that work on continuous capture of material in the field as it happens linked with a capacity for feedback loops and sophisticated representations that allow people to learn by doing, building on the micro-narratives of day to day experience.  Narrative forms of knowledge lie between the experiential and the symbolic, allowing complex interactions and interventions in multiple social situations.

Abductive reasoning is, as Dave explains, “the logic of hunches”, and plays a key role in helping to develop understanding of how themes emerge in social contexts such as in business and elsewhere. It’s all fascinating stuff – very strongly recommended. The depth and versatility of the techniques will be a real eye-opener to anyone who hasn’t previously seen Dave’s work, and its applicability to whole-of-enterprise architecture and the like should be self-evident.

Read more…