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Toby Sinclair

Cynefin Foundations Training – A Learning Journal by Toby Sinclair

Updated: Aug 6, 2020



A learning journal containing my ah-ha moments, puzzles and learning notes as I complete the Cynefin Foundations Online course


MODULE 1


Topics:

  1. Welcome & Overview

  2. Positioning the approach of anthro-complexity

  3. Complexity Theory and managing in complexity

  4. Exercises and Practice

3 Ah-ha Moments:

  1. Five Things – You can only manage five things in a complex system (see notes below). In particular I was intrigued by constraints and how different constraints respond to failure.

  2. Problem of Intermediation – There is a tendency by senior managers to treat complex problems as ordered. My learning is that this is driven by Intermediation. Senior Management are often far removed from the realities of teams. Complexity is hidden and they only see the world through order in power points, steering committees etc. More disintermediation is needed so that Senior Managers can be exposed to complexity to help shift away from everything appearing like an ordered problem. Managers need experience complexity in order to embrace it.

  3. Goal Setting – You cannot drive a complex system to a specific goal but you can experiment  towards a sense of direction. I had learned through systems thinking that systems have implicit goals. In particular that you can define a system optimisation goal. Now i’m starting to question that thinking. A complex system has a disposition or sense of direction but it cannot have a specific, fixed goal.

2 Unanswered Questions:

  1. If complex systems are dispositional, how do you identify the systems disposition?

  2. What examples of constraints exist within organisational systems?

1 Next Step:

  1. Perform Constraint Mapping within my Organisational System to understand better the different types of constraints that exist (See notes below)

 

Learning Notes:

Pitfalls with Systems Thinking

  1. It is different from Anthro-Complexity (Cynefin)

  2. It is driven by an engineering mindset

  3. It has value to limits

  4. It can create a belief that systems can be controlled if we just understand it enough.

  5. It can drive measurements which has negative effects.

  6. It can lead to retrospective coherence

  7. It can confuse correlation and causation

You can only manage five things in a complex system

  1. Constraints – containers, connections, context free, context specific (https://vimeo.com/128934608)

  2. Identity – Different identities in various contexts (husband vs employee) – Identity is an orientation. Identity highlights important of linkages

  3. Affordances – designing the environment and allowing others to make that design a reality. We talk about self-organising teams but we need to enable the ability to adopt it. If people don’t believe it will work they won’t do it, or just token adopt it. Diversity fits into affordances. Diversity is essential in complex systems. Tiger teams – three people with diverse backgrounds to tackle a complex problem

  4. Assemblages – a type of strange attractors – there is a pattern but not pathway used twice. Example: people get swept away in a story

  5. Attractors – you cant create them but you can catalyse them. Bounce the ball at a children’s party. The attractor might fail. If it works you want to amplify. If it fails you want to dampen

Constraint Types:


Resilient – survives changed (salt marsh)

  1. Permeable – salt marsh

  2. Mutating – Case law system – law can change over time

  3. Dark(Emergent) – You can see impact but you can’t find cause – taboo

Robust – survives unchanged (sea wall) – catastrophic failure

  1. Fixed – sea wall

  2. Elastic – exercise band

  3. Tethers – climbing rope

  1. Identify those which we can change

  2. Identify those which can be changed by other actors

  3. Complete a risk assessment on our and/or other actor changes

  4. Identify constraint changes that will minimise risk

  5. Commence parallel safe-to-fail experiments based on the above

Unique aspects of Human Systems:

  1. We make decisions based on patterns

  2. We create and maintain multiple identities

  3. We ascribe intentionality and cause where none necessarily exist

  4. We have learnt how to structure their social interactions to create order

Characteristics of Complex Systems (Professor Cilliers)

  1. Consist of a large number of elements that in themselves can be simple.

  2. The interactions are nonlinear.

  3. many direct and indirect feedback loops.

  4. Complex systems are open systems — they exchange energy or information with their environment — and operate at conditions far from equilibrium.

  5. Complex systems have memory, not located at a specific place, but distributed throughout the system. Any complex system thus has a history, and the history is of cardinal importance to the behavior of the system.

  6. Since the interactions are rich, dynamic, fed back, and, above all, nonlinear, the behavior of the system as a whole cannot be predicted from an inspection of its components.

  7. Complex systems are adaptive. They can (re)organize their internal structure without the intervention of an external agent.

Heuristics for complexity

3 Questions to ask (to focus)

  1. What can i change? Only 5 things (e.g. Constraints)

  2. How can i monitor the impact of change? Foolish to change without ability to monitor

  3. Where can i amplify or dampen result of change?

3 ways to manage

  1. Work in the small (Reduce granularity) – Focus on smaller experiments and see how they interact

  2. Involve Diverse thinking (Distribute cognition) – example: sense-making – Involve many diverse perspectives for insights

  3. Access Raw Data – Reduce layers between raw data and decision makers – Remove managers. Don’t summarise. Summarisation looses raw understanding.

3 things to avoid

  1. Retrospective Coherence – Hindsight doesn’t lead to foresight. Don’t use statements about the past to predict the future

  2. Risk with Systems Thinking – Looking back at what the system is doing today won’t predict what will happen in future

  3. Premature Convergence – People jump to solutions too quickly

  4. Pattern blindness – Gorilla experiment

Much research in management science makes a basic error in logic in assuming that because successful companies have certain types of organizational structure, strategic process or whatever, that the assumption of those organization structures or strategic processes by another company will lead to that company being successful. This is the confusion between properties and qualities taught in 101 philosophy: just because I see a Frenchman wearing glasses it does not follow that all Frenchmen wear glasses and even less so that if I put on glasses I will become French!
 

MODULE 2


3 Ah-ha Moments:

  1. There is a “pathway” to move through the domains. For example from Complex to Obvious. I hadn’t previously understood the nature of movement through the domains so this was good learning. Expanded further in notes below.

  2. Cynefin is a sense-making framework NOT a model

  3. A model seeks to represent reality. A framework is a way to look at reality

  4. Data should inform the framework. Avoid categorisation instead of sense-making

2 Unanswered Questions:

  1. What case studies/examples exist of organisations moving a challenge/solution through the domains?

  2. What indicators exist to inform what stage/section/level of the domain model you are in? For example, Heretics v Group Think

1 Next Step:

  1. Explore and experiment with movement throughout all the domains

 

Learning Notes:

Domain Models and Movement:

  1. Core to the Cynefin Framework is the movement between domains. For example, from Complex to Complicated and vice versa.

  2. In addition, there is movement within a domain itself. Within complex domain for example.

  3. This movement is described in 3×3 matrices for each domain. 

Complex Domain Matrix

Within the complex domain, to act you need :

  1. Some degree of evidence as coherence

  2. People have to buy in to some degree to allow you to do experiments.

Scale

  1. Nature of Evidence:

  2. Beyond reasonable doubt – Point where problem starts to transfer into complicated domain (Liminal state)

  3. Inductive –  Evidence it works in several cases it’s starting to go in the right direction

  4. Gut feel or intuition – May not pass coherence tests

  5. Degree of acceptance

  6. On a small number of people, a Cognoscenti really get this right, this is an elite

  7. Orthodox – accepted to most people come

  8. Synchrony – That means everybody is walking in step, and there’s no dissent anymore

Line of coherence

  1. The lowest energy route through the domain is : Safe-to-fail experiments > Projects and itiaitives > Ready for Exploitation.

“Stages” within the domain

  1. Heretics and Mavericks – Most good ideas end up here, a small group of people who know this is true, but nobody believes. These are people who actually do see a new way of working, but they have no way of explaining it to the wider organization, it’s the guy who created digital photography in Kodak, but Kodak doesn’t believe there’s any future of it. 

  2. Skunkworks – Work on secret projects to build coherence and ability to “tell the story” to convince others

  3. Coaching and Mediation – Find people with time, who have the trust of senior management. Because if you can convince them, their approval, will convince other senior managers.

  4. Break it up fast, zero tolerance  – Often where people have accepted a “management fad” with little of no evidence of it’s value. Key action here is to break up the group of “believers” before it gets more traction

  5. Groupthink – The belief of the group takes hold. High acceptance of ideas based upon group “gut feel”

  6. Challenge the evidence – 

  7. Portfolio of Safe to fail experiments – Highly novel ideas, only a small number of people understand it. And that’s where you run safety fail experimentation, or you do things like triplet programming prototyping.

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