Cynefin Framework

For a given problem in this domain, we sense the problem, fit it into a category and respond with a standard solution.
This leads to true best practice solutions at any given point in time.
Many design patterns have the ability to safely fail or extend as required built in. This allows for complex behaviour to emerge safely. For example, the abstract factory pattern lets you add other kinds of items as you find out what they are; rollback lets you release and if it’s wrong you get to roll back.

There may be many solutions to the same problem, hence good practice, instead of best practice.

Complex systems still have causality; however, it is not possible to correlate that causality upfront. It is only possible with hindsight.
There are light constraints on agents who can modify the system. Cause and effect are only obvious after the event.
In practice, this means to

1. form multiple hypothesis that are often conflicting. Then
   
2. create multiple small safe to learn (fail) experiments within the problem domain and
   
3. view the results. We then
   
4. amplify, or dampen the results with more experiment
   

complexity requires us to run experiments in parallel.
The practices and results emerge from the data. We have emergent practices.
The challenge is that we like to form conclusions too quickly and expect that the correlations we have identified will hold true if we repeat. However, this is not always true and quickly we can find ourselves getting different results when doing the same thing.
We must probe first and then sense.
A complex adaptive system is a “complex macroscopic collection” of relatively “similar and partially connected micro-structures” formed in order to adapt to the changing environment and increase its survivability as a macro-structure.
They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive in that the individual and collective behaviour mutate and self-organize corresponding to the change-initiating micro-event or collection of events.
A complex adaptive system is a community of relatively “similar and partially connected people” formed in order to adapt the business model to the changing environment and increase its survivability as a viable product.

No cause and effect relationship can be found. Patterns can emerge, but they do not repeat or stay in a stable state. We cannot correlate cause and effect until we’re out of chaos
Chaos is only ever temporary and constraints must either be formed in a constructive way, or stability will form seemingly automatically from other forces, and may or may not be beneficial. Therefore, when a system moves to a chaotic state it only stays in that state temporarily. It will stabilise into one form or another
To increase the chances of the outcome being beneficial, it is necessary to act first, then sense, and respond, mainly because of time criticality.
Chaos can be used to find innovation, and having an innovation team, that works in tandem with the crisis management team to provide learnings that might never have happened is recommended by the framework.

The central space is for when you do not know which of the domains that you are operating in. When we do not know what domain we are operating in, we default to using the method that we are most familiar with.
These domains are not categories. The model is not a quadrant model, and each domain requires a different leadership model, tools, and mind-set.
You may enter voluntarily to create aporea

The problem never leaves the complex domain
The individuals or teams constantly evolve and change the problem definition and solutions over time.

Agile → complex adaptative problems are iterated over, and then once a solution for a small period of time is found, teams can develop and deliver with a reasonable consistency for a period of time. Then the environment/feedback/stakeholder changes
There is a series of windows of opportunity where it becomes possible to either remain in the complicated domain, or become commoditized and move towards the obvious/clear domain

If a problem is solved with tools applicable to the complicated domain and then the constraints applied are too tight or not reviewed through complacency, then the problem may re-occur as a crisis and temporarily move to the chaotic domain.

If a problem is moved to the Obvious domain too soon, and constraints applied too heavily, and the environment changes or the constraints were not appropriate, then again, through complacency, the problem may fall over the Obvious/Chaotic cliff, and the team, individual or organisation may experience catastrophic failure.
This may or may not be recoverable.

Chaotic ↔ missing in action ↔ projects & initiatives ↔ ready for exploitation ↔ complicated

• 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.
  
• Skunkworks
  Work on secret projects to build coherence and the ability to “tell the story” to convince others
  
• 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.
  
• Break it up fast, zero-tolerance
  Often where people have accepted a “management fad” with little or no evidence of its value. The key action here is to break up the group of “believers” before it gets more traction
  
• Groupthink
  The belief of the group takes hold. High acceptance of ideas based upon group “gut feel”
  
• Challenge the evidence
  
• Portfolio of Safe to fail experiments
  Highly novel ideas, only a small number of people understand them. And that’s where you run safety fail experimentation, or you do things like triplet programming prototyping.
  

This is a good place to start and not a bad place to be.
They start with Orthodoxy, meaning many but not all people support them, and they are supported by business cases.

We are moving closer to the Complicated domain, where we can start to add constraints and so ’exploit’ the solution by standardisation and perhaps mass production or commoditisation.
This square is within the Synchrony space so we have mass agreement, and it is also within the Beyond Reasonable Doubt space, so we are pretty sure we can apply the right constraints for exploitation.

This square is within the Cognoscenti space, meaning only a few people understand or follow what is going on.
It is also in the ’Gut Feel’ space, meaning that a few people have gone off on a gut feel hunch; hence ’missing in action’.
This is not a problem, as it is on the red line, and perhaps real insight and understanding will come from this team.
In this space, we need to manage risks, and apply the ’Safe to Fail’ approach to problem solving and innovation.
If this team is not managed, or the risks too high, or other problems occur, then the problem may move to the Chaos domain.

Synchrony space, meaning everyone is in agreement. It is also in the Gut Feel space, meaning there is no data to back it up.
The solution to come out of this square (behaviour) is to break it up.

In direct response to the square at the top of the model representing ‘Group Think’.
Breaking up the group think with zero tolerance refers to adding more people and diversity to the problem and referring back to real data and case studies.
Hopefully this should ‘ground’ the thinking and create more open minds and allow different hypothesis to try for new experiments.

This square is in the Beyond All Reasonable Doubt space and also only believed by a few. These are the heretics and mavericks.
The advice here is listen to them and positively move to ‘Coaching and Mediation’, otherwise the behaviours and problem will move towards ‘Hide It’.

Actionrequired when there are ‘Heretics and Mavericks’ who understand their version of truth beyond all shadow of a doubt but no-one is either listening or able to understand.
Those in the know need to be able to relay their information in a way which a larger audience can understand and then take action or mitigate the risk. Therefore the ‘Heretics and Mavericks’ need coaching and their discussions with others may need mediation.
Left unchecked, the ‘Heretics and Mavericks’ will give up, and then the problem and organisation will lose the chance to understand this important point of view.

If ‘Heretics and Mavericks’ are not heard for whatever reason, then the problem will be hidden. This may happen because no one wants to speak up through frustration and fear of conflict. Or perhaps because those who are trying to listen give up as they cannot understand the problem in the way expressed.
In this state, the organisation thinks there is greater consent for a solution than there really is and therefore moves prematurely into using tools and solutions for the Complicated domain. This can set the organisation into Dynamic 3, the move through Chaos.

Anyone who links Six Sigma with Lean doesn’t understand Lean because Lean is about eliminating the waste that Six Sigma techniques created in the first place.

Organizations like 3M have abandoned Six Sigma for all but core manufacturing because it destroys their ability to innovate or have a relationship with the customer.

Definition and schools of sense-making

knowledge management properly understood is about helping people make better decisions and creating the preconditions for innovation
Is not about making tacit knowledge explicit because that’s impossible

naturalizing comes from philosophy and it means to root what you’re doing in the natural sciences, not in the social sciences
cognitive science, complexity theory, material engagement theory, biological anthropology rather than social science
what do we know about how people make decisions about how people create communities about how they interact with each other and the nature of systems: we work with that trying to work rather than trying to work against it

1. get multiple perspectives you need people from different cultural, educational, gender, … backgrounds
   
2. looking at the same situation in parallel without collusion and then
   
3. look at patterns in all of those responses to find outlier responses
   
   1. Draw them as contour maps (Fitness landscapes) and identify blobs: overlapping blobs, isloated blobs that see something everybody else is ignoring
      
   2. This creates a Human Sensor Network
      using the whole of your workforce to create a real-time decision support environment where knowledge can be deployed in the context of a specific question or need rather than having to be codified in advance
      you can do real-time situational assessment and real-time ideation and novel solutions you don’t rely on databases you rely on multiple levels of human interaction so that’s kind of like one bit of science and one set of implications
      

we make sure there’s a happy ending but the stories that we enjoy are actually extended stories of failure not stories of success
evolutionary reason → avoidance of failure is a more successful strategy than imitation of success
the stories that spread most rapidly around an organization and not stories of best practice stories but stories of failure
we use fiction because fiction often contains far more truth than fact
best practice stories tend to elicit “well my case is different” type response

not so-and-so equipped is some harness safety harness to the gantry and perform the job satisfactory with no accidents: they’re about somebody who didn’t do that who fell off the gantry and luckily fell on another person who broke his leg but they both lived: everybody knows that story and it gives you better warning and knowledge than anything else

everything is connected with everything else and the sheer number of connections
means that it’s impossible to create a predictive model and the same thing will only happen again the same way twice by accident not by design
the only thing I can say with absolute certainty about a complex adaptive system is that whatever you do will produce unintended consequences and once you know that you’re sort of ethically responsible for them. You can only do three things:

1. Change boundary conditions and constraints
   
2. Probe/experiment to see what happens, do them in parallel
   If you don’t do them in parallel you may get into the Hawthorne effect, where you get an improvement because of the novelty itself
   Also because of confounding variables
   
3. Energy Amplification: if something starts to grow, you give it more energy and viceversa
   

https://youtu.be/-GIp_cNZio0?t=1028

1. Knowledge can only be volunteered it cannot be conscripted.
   You can’t make someone share their knowledge, because you can never measure if they have. You can measure information transfer or process compliance, but you can’t determine if a senior partner has truly passed on all their experience or knowledge of a case.
   http://web.archive.org/web/20200929194409/http://oldsite.cognitive-edge.com/blog/entry/4524/volunteer-not-conscript/
   If you ask someone, or a body for specific knowledge in the context of a real need it will never be refused. If you ask them to give you your knowledge on the basis that you may need it in the future, then you will never receive it.
   
2. We only know what we know when we need to know it.
   Human knowledge is deeply contextual and requires stimulus for recall. Unlike computers we do not have a list-all function. Small verbal or nonverbal clues can provide those “aha” moments when a memory or series of memories are suddenly recalled, in context to enable us to act. When we sleep on things we are engaged in a complex organic form of knowledge recall and creation; in contrast, a computer would need to be rebooted.
   
3. We always know more than we can say, and we will always say more than we can write down.
   This is probably the most important. The process of taking things from our heads, to our mouths (speaking it) to our hands (writing it down) involves loss of content and context. It is always less than it could have been as it is increasingly codified.
   
4. In the context of real need few people will withhold their knowledge.
   (Counter to 1.)
   A genuine request for help is not often refused unless there is literally no time or a previous history of distrust. On the other hand ask people to codify all that they know in advance of a contextual enquiry and it will be refused (in practice its impossible anyway). Linking and connecting people is more important than storing their artefacts.
   
5. Everything is fragmented.
   We evolved to handle unstructured fragmented fine-granularity information objects, not highly structured documents. People will spend hours on the internet, or in casual conversation without any incentive or pressure. However creating and using structured documents requires considerably more effort and time. Our brains evolved to handle fragmented patterns not information.
   
6. Tolerated failure imprints learning better than success.
   When my young son burnt his finger on a match he learnt more about the dangers of fire than any amount of parental instruction cold provide. 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.
   
7. The way we know things is not the way we report we know things.
   There is an increasing body of research data which indicates that in the practice of knowledge people use heuristics, past pattern matching and extrapolation to make decisions, coupled with complex blending of ideas and experiences that takes place in nanoseconds. Asked to describe how they made a decision after the event they will tend to provide a more structured process oriented approach which does not match reality. This has major consequences for knowledge management practice.
   

https://youtu.be/-GIp_cNZio0?t=1063
Deeply embodied knowledge → Narrative → Explicit Knowledge

SenseMaker in its Genba version allow access to those stories without the need for excessive codification
we found things in narrative research that we just didn’t find through conventional interviews (distributed ethnography)

it’s not i didn’t want to share what i knew but i knew if i codified it and put it into that system i couldn’t codify it properly.
i did what you always do in a large bureaucracy i said okay don’t worry i’ll codify, no problem, and then just didn’t do anything. Most problems went away in IBM if you took that approach but this time it didn’t so they linked it in with my bonus
i didn’t want to share my knowledge so i wrote a (obscure) 16-page paper
it was actually designed not to say “here’s my knowledge” but to designed to say “I know something about this come and talk with me”
to codify all the possible answers to all the possible questions i’d have to write a series of books and that’s too much time

what you generally find is people either undercodify or overcodify

if you have to spend a dollar on knowledge management send one one cent on technology and 99 cents on connecting people and that’s still true today

in any large corporate if you codify something people will steal it without attribution unless it doesn’t work at which point they’ll attribute it to you fully
fear of abuse is a far more significant reason for knowledge retention than is the whole traditional idea of power

if your knowledge management system is effectively focused on written information with search engines which rely on text analysis you’re dealing at best with about 10 percent of the knowledge of the company

This often leads to a distinct separation:

• Managing tacit knowledge through networks
  
• Managing explicit knowledge in the more traditional focus on Communities of Practice, information systems, search engines, graph databases…
  
• This leaves out the critical intermediary stage of people’s stories
  

https://youtu.be/-GIp_cNZio0?t=1430
If there’s anything, any lesson they learned, any idea they’ve got, any anomaly they spot, they either take a picture, record or voice, or write something down or any combination, and it goes directly into a narrative database which is based on what’s called high-abstraction metadata

If you wait until people have finished something and do a lessons learned review or a peer review the way people remember things after the event is different from the way they remember at the time. Retrospective “lessons learned” are actually quite limited in what they achieve regardless of the sophistication of the techniques you use.
people describe the past in terms of the political context of the present, and success/failure affects because people are holding all the possibilities open (for example do a “lessons learned” the day after a big event)
What we do is we capture material in the field and the fire

SenseMaker Genba version
once you’ve got a body of narrative you can start to determine what should be codified and you don’t start with that and
what can’t be codified because it’s based on experience or knowledge or social connections or whatever

i still got a huge body of experience because i’ve worked in hr i’ve worked in finance i’ve worked in strategy i’ve written code i’ve been a systems architect i’ve done ux design and i’ve been in r d and so
when i go in and talk with a hr director i kind of like know where they’re coming from and i can focus my questions and what i propose to them based on that rich understanding of context and i can actually do it quite quickly and that ability to understand context is absolutely key because it reduces the cost of actual sharing

https://youtu.be/-GIp_cNZio0?t=1703
informal networks are more important than formal networks in the way ibm worked
who you knew mattered more than what part of the structure you played
the ratio between formal and informal communities was about 1 to 64.
people in informal networks trust each other: you share all your failures, when it becomes an official group you spend a lot of time removing anything you don’t want other people to know

if you want to measure the effectiveness of the company in terms of knowledge sharing, the degree of ease of sharing failure stories is actually more important than best practice

Silos: educational, class
In Singapore Military Service creates networks across these silos, in the UK informal networks at the government come from a few elite schools/universities and they don’t cross silos

you can’t break silos down because silos allow people to share knowledge at the right level of abstraction
if i have to share my knowledge with everybody regardless of their educational background, it’s just too hard

Triads are groups of three people and entangled is a variation on this that brings together people from radically different backgrounds with no prior interaction but with a common purpose. This entangling leads to a more extensive and diverse exploration of the issue at hand which may lead to new ideas that can be explored. The 3 are kept together by a shared purpose and by well-crafted set of actions which ritualise the exchange of knowledge and lead to new possibilities.

If you do that sort of exercise on about 40 or 50 percent of the workforce at least twice a year then within two years everybody is within two phone calls of everybody else and at that point you’ve got a healthy ecosystem: you’ve focused on the way in which things flow not what things are

https://thecynefin.co/library/complex-acts-of-knowing-paradox-and-descriptive-self-awareness/
managing the flow is more effective / easier than managing the stock
Is Hermeneutic Despair (Luhmann) the origin of this division?
If you could peek inside the mind of somebody you could transfer knowledge (figuring out the translation between some representation in one mind and some representation in another mind without loss of information)

to use a requirements definition is not to send out an analyst who will only see what they expect to see what we do instead is we maybe create 15 20 trios

• a systems architect
  somebody with a picture of the entire system
  
• a bright young coder
  
• the user trained to talk to IT people
  it’s a lot easier to train users to talk to IT people and train IT people to understand users
  
• Creates a lot of small, diverse conversations, running multiple experiments in parallel to map what’s possible within the system
  

https://youtu.be/-GIp_cNZio0?t=2053
Improve onboarding process
this is one of the ways you capture knowledge from senior executives
when somebody joins the company for the first six months they’re required to keep a daily genba type journal at the start and end of each day what they’ve learned and what they expect to learn
it tells you the common stories, things that everybody has to know

https://youtu.be/mkNhsGR7c3E?t=2022
weak signal detection in a project
if we got multiple fragmented reports coming in continuously from all agents including the micro anomalies
we can identify when a project is starting to go off track way before the project manager will see it
ability to intervene early when you’ve got early signs of change

https://youtu.be/-GIp_cNZio0?t=2077
senior people will talk to junior people but not to middle managers or consultants

art comes before language and human evolution
so cave paintings and music are before coherent language
it started as an accident but its development has evolutional utility
high levels of abstraction disconnect you from the material so you see connections that you didn’t see before
store knowledge at the right level of abstraction so it can be combined and recombined very quickly

If we want to manage complex environments, we need to stop talking about how things should be in the distant future, and start changing things in the here and now. Move from lofty long term goals to mapping where you’re at and making small changes and monitoring what’s happening.

We decide on what direction we want to go in, map the system’s current state, run experiments to shift in that direction, measure the system’s state again and assess what interventions might be most useful. This is an iterative process that incorporates feedback and allows for continually taking stock of a dynamic environment so we can take advantage of new opportunities as they arise.

Genba is the Japanese word for “the real place.”, In business, genba is used to denote the “place where work is done.”
The true meaning of conducting a genba walk is to be one with your process and the team that performs in it. Through this, refining processes will take your business on a journey towards success.

generally the role of leadership is to coordinate but not decide unless there’s a crisis when
you make decisions very quickly not to solve the crisis but to increase the option space for other people to explore and find solutions
sotfware architecture is about keeping your options as open as possible, creating boundaries between things that change at a different rate
Predicting software changes is complex because it involves “predicting” how your users will use the software and will they request
Microservices follows a complex aproach dividing into modules and then scaling as needed, because the workloads are non-preditable, complex

https://thecynefin.co/max-boisot-1943-2011/
Statistics - Probable/possible/plausible

If you have to write your values down you just lost them
If you have to codify your purpose then you’re purpose less
the minute you write your values down you just lost them
now everybody knows what language to use regardless of what they’re actually doing and corporate survivors have learned how to do with them
explicit knowledge can be gamed

Affordance → Assemblage → Agency
Can’t be changed → Can be changed with difficulty → Easier to change
What do you give agency to is probably the most important question, rather than who do you give authority to

• Natural science as counter-factual - The Cynefin Co
  
• https://cynefin.io/wiki/Assemblages
  Cynefin template: Assemblages - Cynefin.io
  
• https://cynefin.io/wiki/Affordance
  

https://youtu.be/iMlO-xuMrms?t=261
Don’t try to introduce it as a transformation, introduce it as a differentiator on something which people already know they want and want to buy
Don’t try and get a revolution, add to something people are already familiar with, so they get to learn it as they go along
If you want to introduce something new, find the thing that people know the old techniques don’t work for and offer something which is risk free which might solve the problem
https://youtu.be/iMlO-xuMrms?t=3524

when something is really in the early days the people who buy things are intelligence military and pharma
if you want to do something new you’ve got to be prepared to work with “evil people” because they do the interesting things
https://youtu.be/zlCJnNQXWN0?list=PLyVQIUns7rp9H6Fd5iSGUzyAr0jYJ0By6&t=1168

https://youtu.be/zlCJnNQXWN0?t=2035

https://youtu.be/mkNhsGR7c3E?t=613
ritual transfer based on making a mistake owning up to it

we had a new engineer and he’d been trained by correspondence course so he knew about ties in theory but he’d never seen him in practice and in his first job he tied a floating crane to the dock and didn’t allow for the tide:
crane goes in wrecked, his manager phoned me up and said “we’ve probably got to fire him but he might be redeemable”
I took him out for lunch and realized he was actually quite good
I told him he was now a real engineer because he’d lost his first crane and I told him what would happen if he ever did it again

https://youtu.be/mkNhsGR7c3E?t=701

https://youtu.be/mkNhsGR7c3E?t=1898
you basically have a minimal viable product, a maximum achievable product, a minimum available resource and a maximum available resource
you have an end date and the team have autonomy to vary the delivery or vary the resource within those two constraints but they must deliver on the date

the date-based dependency is key in a large project environment

non-accountable early weak signal detection
look guys, there’s two reports: there’s a formal report you give me every month to which I will write up
and send upstairs, and there’s the informal report you’ll write every week and I will never punish you for that and never pass it on because if so I’ll be fired because I’m not allowed to do this: so this is the actual report of what’s happening

I read a lot so at any one time I’ve probably got a scientific textbook, a history book and a science fiction book
You don’t want to go to the management literature, the management literature in this field is is with a few exceptions pathetic
I’ve yet to see a good popular book about complexity theory other than scientific books
I would read up on things read up on epigenetics, Gary Klein - How People Make Decisions, read up on constructor theory and physics

There is also an interesing discussion at the end of the other episode
https://youtu.be/mkNhsGR7c3E?t=4112
If you look at the maturity models they all go back Piaget and all of Piaget’s experiments have been disproved: he didn’t allow the context

PKM is an atomistic and aggregative approach which ignores the primacy of social systems. Individuals act within such systems but not as free agents.
Community-based collaborative knowledge sharing that skilled individuals can participate in can and should actively direct, to meet their own knowledge requirements:
what we refer to in this chapter as Social Knowledge Networking

• If you enable the right sort of ecology then knowledge sharing will tend to happen naturally
  
• The blogosphere as an artifact of distributed cognition - The Cynefin Co
  
• Two reasons
  
  • Blogs work at a lower level of fine granularity: highly fragmented, ad hoc and unstructured ⇒ matches the way the human brain has evolved to handle data (prefers multiple fragmented stimuli such as surfing web or socializing vs sitting reading a book)
    
  • Meaning in the blogosphere comes through social interaction over time: it is not predetermined. Works via links (amplify/dampen through linking, your own RSS builds a network, both input/output)
    

In the old days he would have had two choices.

1. library each month, skim the journals, hope to find useful information.
   
2. employ a summarization service ⇒ not trust summarizers to get the essence of the knowledge
   

Bloggers act as a scanning and filtering device ⇒ you only need the blog to get relevant references.
Bloggers become part of your network when you learn to trust them over several months.
Other people might not trust them in the same way, since they just think the way you do

Snowden has RSS feeds from about 35 science blogs coming in daily or weekly. It takes an hour a day to go through the RSS feeds
Snowden has effectively got all the things he feels he needs to know about in this one space, all populated by people who have proved themselves as sources.
Every six to nine months Snowden tidies the whole thing up, often when he downloads for free a new RSS package to meet his changing needs or out of boredom.

What Snowden is doing here is handling fragmented material, building stuff naturally and structuring his universe into a hierarchy.
Every six to nine months he dissolves the hierarchy and reforms it which gives him an adaptive capacity which does not exist in a traditional KM system.
It is a fragmented, unstructured, trust-based network.
Moreover because he blogs that gives him access to more blogs. His blog is referenced and he references other people.
So he became part of this community of people who are sharing and contributing knowledge to a learning environment which is equivalent to the staff common room at university where it is possible to interact with people one did not expect to interact with.
you do not necessarily know people as individuals; you know them as identities. They are people who cluster together around areas of interest

the blogosphere on the whole verges on being a chaotic system made up of unconstrained agents. Everything is independent of everything else, with different people using different ways and means to do the same things. People do not find the things they expect to find. However, it is possible, as shown above, to build or join trust-based networks where you can find things quickly.
As the connections increase, light constraints come into play and the system becomes complex which allows meaning to emerge.
for the most part the blogosphere ends up as a series of clusters of people who think in similar ways. Occasionally they interact with another group and there is some transference or linkage but it is not a universally connected system. It resembles a series of isolated villages.

What differentiates the online environment from face-to-face interactions is that an individual can possess multiple identities

By creating a definitive version of the method with full transparency not only do we have an authoritative source but that source is also publicly visible. It is also a strategic move with my being consistent to the flexuous curve framework which provides a contextual approach to strategy. I’ll probably elaborate on that in a future post or write one of the retrospectively coherent books in a decades time!

• Flexuous curves - Cynefin.io
  
• You searched for flexuous - The Cynefin Co
  
• The Ystwyth-curve continued - The Cynefin Co
  

This week in Canberra teaching the mapping of situations for the EU Field Guide (a simplified form of the substrate paper which is morphing into Estuarine Framework) I started to realise that it’s something I’ve taken a little for granted, assuming that people understand the idea and importance.

• Estuarine framework - Cynefin.io
  
• Entanglement: empathy via abduction - The Cynefin Co
  
• The process of strategy 3 of 3 - The Cynefin Co
  
• The process of strategy 2 of 3 - The Cynefin Co
  
• The process of strategy 1 of 3 - The Cynefin Co
  
• Estuarine mapping first edition - The Cynefin Co
  
  • Some principles, based on three key aspects of working with complex systems:
    
    1. Initiating and monitoring micro-nudges, lots of small projects rather than one big project so that success and failure are both (non-ironically) opportunities
       
    2. Understanding where we are, and starting journeys with a sense of direction rather than abstract goals
       

    3. Understanding, and working with propensities and dispositions, managing both so that the things you desire have a lower energy cost than the things you don’t
       Another way of thinking: aim to create an ecosystem in which good things are more likely to happen than bad ones and that also requires balance in the system – rewilding.
       Rather than take the engineering approach, assuming a green field site and just building it in the hope people will come, you start by understanding where you are, you
       

       1. build some boundaries,
          
       2. create some novel linkages,
          
       3. put somethings into the shade or eradicate them while giving energy to others.
          

       An ecologist who uses engineering, rather than an engineer who sees the ecosystem as something to conquer.
       

  • Estuarine mapping – outline process
    
    1. map the constraints
       
    2. energy cost of change and time to change
       every constraint is placed on a grid between the energy cost of change against the time to change. In that process, they are also clustered and if the process is manual then impact is indicated by colour coding or overlay. Clusters may be relabelled as needed.
       
    3. the counter-factual border
       A line is then negotiated (shown in red above) where everything to the top right of the line is very unlikely to change. In other words, the energy cost or time horizon of change means that it is out of consideration within the time horizon for strategy or planning. It has been fascinating watching people at this stage, as the act of drawing the line creates a rich discussion in which things are moved backwards and forwards, and frequently broken up or redefined in the process.
       Once this is done monitors are created for the line, and/or indicator or early warning constraints are described.- if unexpectedly things start to change you need to know fast.
       I’ve also started to create a set of layers of warning here. All of this creates a set of micro-projects.
       
    4. vulnerability border
       
    5. acting on constraints and constructors
       
    6. set a direction of travel
       
    7. combine the micro-projects into portfolios
       
  • Key to all of this
    The domain between the lines is the effective area in which you can act. The domain of strategic and operational possibilities. And the philosophy is simple: find out where you are and what is possible before you leap into the whole vision and goals thing.
    
• Estuarine Mapping, some additions - The Cynefin Co
  
  1. Clear separation of constraints in stage five into boundaries and constructors, shifting from constraints. Constructors produce consistent outputs, we bounce off boundaries. I still need to get attractors into this domain but its not there yet. The Hexi kit for this will have overlay transparencies for both types along with a keep/amend/destroy option. There will also be a set of forms like the Cynefin Action forms here, currently in design.
     
  2. The identification of constraint clusters that act as forward indicators or/scouts/ thatcan be monitored for deviance as a possible forward indication of a threat to the counterfactual line.
     
  3. Run flexuous curve checks on some constraint clusters to create indicators of when the energy cost of change is about to go through a phase shift in energy cost. Having these checks in place gives first mover advantage
     
  4. The constraint mapping phase uses the typology labels as triads (as shown) one for resilience and the other for robustness. This encourages people not to see them as categories.
     
  5. It is also possible as the opening gambit of a workshop to get people to define their own metaphors for all types. This has the additional advantage of socialising meaning before people fully engage in the process with their own data.
     
• The three frameworks - The Cynefin Co
  
  • Estuarine Mapping
    focuses on the energy gradients and counterfactuals that tell you what domains you can actually play in, regardless of where you would like to be.
    timing is everything: walks that are possible in summer are barely passable in winter and so on.
    
  • The Flexuous Curves framework
    building on market life cycle theory with complexity added on for good measure focuses on when you can do things.
    Trying to break a dominant pattern in its growth phase is impossible, once it starts to fail or becomes commoditised, then the opportunity can present itself
    
  • Cynefin
    starts with the nature of the system you are in, or more importantly the nature of the transition you want to achieve, and which then determines the type of decision you can make.
    

• Combining Cynefin, Flexous Curves and Estuarine Mapping
  

  Cynefin

  what type of system I have? → What type of decision can I make?
  

  Flexuous curves

  What’s happening to competitors in the market? When can I make change?
  

  Estuarine mapping

  Where are we? Where can we go next?
  

  Flexuous curves

  Action(?)
  

  Cynefin

  What type of project/solution I have? (Like in the EU Field Guide)
  

  They use to do Cynefin→Flexous→Estuarine but now they are doing Estuarine→Flexous→Cynefin, as Estuarine is more approachable (explainable in 10 minutes)
  

• Welcome & Keynote: People Driving Knowledge Sharing: Sense- Making Frameworks, Tools, & Strategies
  
  • Cynefin
    What type of decisions you can make is dependent on the type of system you are in
    
  • Flexuous Curves
    To every thing there is a season, and a time to every purpose
    
  • Estuarine (Moryd)
    What is the domain (strategic, operational or tactical) in which we can even make changes?
    
• Connection with types of time? Chronos, Kairos and Aion
  
  • Flexous ↔ Kairos (clearly)
    
  • Cynefin ↔ Aion (because it has dynamics)
    
  • Estuarine ↔ Chronos
    
• Estuarine mapping - joapen
  
• A trip into the estuary - Tom Kerwin
  

https://youtu.be/zlCJnNQXWN0?t=711
Hexagons with all the methods and tools/frameworks: you pick the ones you’re actually using: that’s where we are and then you start to say well we could do this as well or we could do that differently, so you have these evolutionary conversations about the way you’re going (Vector theory of change)

1. multi-methods, multi-vendors
   
2. start with where you are identify what you can change
   
3. allow people to engage in different solutions at different parts of the organization
   

A significant problem with Agile is that it codified without necessary abstraction, a sin it shares with many a previous fad. One of the things I didn’t do with Cynefin was to rush into premature codification, which is now happening as the final abstractions have been worked out and that has taken time,
Infantilization of the receiver
Loss of integrity
If you can handle a highly abstract language then communication is so much easier and frequently more productive

Instead of saying What will we do if X leaves the organisation we can instead say How do we replace the combination of artefacts, skills, heuristics, experience and natural talent that X brought to the organisation. It also allows a better sense of the level of vulnerability to loss. If the balance is towards artifacts and skills then we are at less risk than if the balance is towards experience and natural talent. […]
One of the other uses of ASHEN in knowledge mapping was to challenge the idea that all of the knowledge could be codified.

When you make that decision, what artifacts did you use? What skills are necessary and how are they acquired? What heuristics or rules of thumb or practices make it easier to make a decision? What experience is necessary in terms of time and context? What makes some people better at this than others and who are they?
The results of that get mapped, clustered and there is a general principle that the more you are dependent on artifacts and skills the less you have to worry about knowledge retention, the more it is experience and natural talent the more you need to panic.

https://youtu.be/zlCJnNQXWN0?t=913

1. people brainstorm constraints
   
2. you then cluster those constraints and map them onto a grid with energy costs of change against time to change
   
3. anything in the top right hand box is called a counterfactual: draw a line around that and say “they ain’t going to change” and you shouldn’t even talk about it
   What’s theoretically possible may not be politically acceptable
   
4. anything bottom left is highly volatile highly dangerous
   
5. the middle is our zone of operation: which of these constraints is producing predictable outcomes? Those are called a constructor. It’s stabilizing the space and anywhere else you run the safe to fail experiments
   

—

• Tables, not walls
  
  • on a wall one or two people dominate the space. If you have a long thin table then people can work on both sides of the table and more people can engage and it spreads out more
    
  • people aren’t worried about them peeling off, it also means we can pre-print two-sheet paper
    
  • Easier to move in a table than in a wall
    

• https://thecynefin.co/ligne-de-fuite-1-of-3/
  
• https://thecynefin.co/ligne-de-fuite-1-o2-3/
  
• https://thecynefin.co/ligne-de-fuite-3-of-3/
  
  1. Change perspective
     If I look at the forest from above or below then it is no longer a series of branches that have sprung from a trunk, but a deeply entangled system with multiple levels of connection. If you look down on a system from above then you can see and perceive patterns that are not on the ground.
     
  2. Change the lens
     You may not know this but most mammals other than primates, can see into the ultra-violent. If we can expand the spectrum then we will see things (sic) in a different light. One of the functions of Cynefin is to provide a new lens and new language so that a system can be perceived afresh. One of my first encounters and engagements with the power of computers was when we took satellite images in 64 shades of grey and used enhancement of those images to see the landscape in very different ways.
     
  3. Change the actors or the actor interacton
     Who, or what is observing the system can make a difference. The phrase Through the eyes of child occurs in many traditions. Remember it is a young person who is prepared to say that the Emperor has no clothes.
     

Key here is to vary all three before you make an irrevocable decision and to determine if you want/need to transit out of the liminal aspects which is an essential and ongoing aspect of rhizomatic systems. If you do decide to exit then it is worth remembering that there is always a tendency for the system to return to its prior state so you have to make the return path difficult to follow, but that, of course, implies risk.

• Differentiation and Cynefin
  
• Deliberate Discovery
  
• Real Options
  
• Diversity and Chaos
  

Default of purchase (which was represented as a boolean), asked specifically loads of time → are you sure this is should be the default?

Waltzing with bears
Every projects has something about it which is completely different to what has already happened before, and that’s where the risk is

7:57

• commodities (complicated) → things you need to have just to play the game
  
• differentiators (complex) → where the risk is
  
• expediting (from kanban) (chaotic) → things you need to do really really urgently (overrides flow)
  
• katas (simple)
  
• value trumps flow, flow trumps elimination of waste
  

Genesis

where new ideas are created or exapted - R&D and new innovations

Custom

where new products emerge, are adapted to the needs of and find momentum with clients - selling what the client will buy; or internal products where no other commercial offer exists and where they are integral in support of the organisation’s differentiation

Product / Rental

where there is sufficient repeatability to consolidate and scale the products/services - selling ready-made solutions

Commodity

a place of intense competition where there are fewer possibilities of differentiation, and competition involves scaling and dominating the market. This is also the place of platform strategies and enabling technology.

5. Nobody in the world has ever done this before.
   
4. Someone in the world did this, but not in our organization (and probably at a competitor).
   
3. Someone in our company has done this, or we have access to expertise.
   
2. Someone in our team knows how to do this.
   
1. We all know how to do this.
   

We can also measure this complexity across multiple axes: people, technology, and process.
If we’ve never worked with someone before, or we’ve never made a stakeholder happy; if there’s a UI or architectural component that’s unusual; if there’s something we’d like to try doing that nobody has done; these are all areas in which the outcome might be unexpected, and in which – as with Cynefin’s complex domain – cause and effect will only be correlated in retrospect.

software devs → automatize complicated things into complex/simple things, but there is the danger of moving to chaos
(It is not clear whether automation makes complicated things complex or simple)

Feature Injection
Mechanism to know who you should be talking to at different levels of scale

• Start with a primary stakeholder
  
  • Makes money
    
  • Saves money
    
  • Protects money (prevent your users from leaving, replacing legacy systems to have more options)
    
  • Have clear your differentiator and use metrics
    
• Incidental Stake-Holder
  Its goal must be met to go live
  
  • New regulations
    
  • Things that are needed, not wanted
    
• Capability
  
  • Users can achieve a business outcome
    
• Feature
  
  • User Interface component which enables a capability
    

Story

• A slice through a feature to enable faster feedback
  
• To have a better understanding as software devs to what it is they’re trying to deliver
  

• Scenario
  
  • An example of how the system might behave from a user perspective
    
  • Dev,test,analyst
    
• Code
  
  • Turn ideas into reality
    

Vision ⇒ Goal ⇒ Capability ⇒ Feature ⇒ Story ⇒ Scenario ⇒ Code

Analysis, breaking things down only works on predictable stuff, not complex stuff
Real projects are full of “oh crap!” moments, discoveries

Agile manifesto
We are uncovering (discovering) better ways of developing
software by doing it and helping others do it.
We’ve been delivering software for decades
We are making this explicit. Knowledge discovery is what happens in knowledge work

• Where the knowledge discoveries activities are?
  
• Where the feedback loops are?
  

Differentiators → Differentiate requirements through experiments

“We can’t accept this into our backlog without clear acceptance criteria”
People go for the certain stuff and delay the uncertain stuff
If you make this discoveries at the end you got no time or options to respond

Deliberate Discovery

• Assume ignorance
  
• Assume second order ignorance
  This is going to be in the new stuff
  
  • New stakeholder with new goal we’ve never met before
    
  • New capability that the business has never had
    
  • Experiments to deliver that feature. If you have a limited time frame, run lots of experiments at once: Set-Based Concurrent Engineering (SBCE): Why should you be interested? – Lean Analytics Association
    
  • Told the story that’s never been told
    
• Optimize for discovery
  
• Risk (Newest Stuff) First
  

Deadline

like Christmas, nobody is going to move it, if you don’t get it done by Christmas the opportunity dies, people are usually pragmatic about it

Sadline

no opportunity will die but if you don’t make it somebody somewhere will be sad

Visibility on the top, stabilty on the
Genesis, Custom Built, Product (+rental) Commodity (+utility) Evolution

https://en.wikipedia.org/wiki/Start_with_Why