Cynefin has long been one of the most useful tools in my own toolkit. It helps explain so much about the world, and why things that work in some situations don’t work in others. But I think Cynefin is hampered by how difficult it is to get your head around, and how tricky some of the terminology is.
Continuing my series on sense-making, today I try to explain Cynefin for the rest of us. This takes the series from meta posts about sense-making itself towards some more practical tools that you can actually use in your day-to-day lives – ways of actually practising sense-making.
This week’s article
Perhaps the most influential sense-making framework, Cynefin is deservedly popular – but can be a little hard to get your head around
Despite – or perhaps because of – its curious name, Cynefin is one of the most popular and talked-about tools within sense-making. Its creator, Dave Snowden, reckons “Cynefin” (pronounced kuh-NEV-in) might be the most widely known Welsh word outside of Wales. An undeniably beautiful word, “Cynefin” lacks a direct translation but Snowden defines it as “the place of your multiple belongings”, a definition that emphasises the subtle and intertwining influences of our environment, history, culture and personalities on the way we act and react.
Sense-making is about action: about deciding what to do, based on your understanding of “what’s going on”. There’s no one-size-fits-all approach to that sort of decision-making. How you decide what to do depends on what sort of situation you’re in. For example, deciding what to do when making a cake is quite different to deciding whether to raise interest rates, which is again quite different to deciding how to respond to fighting a fire in a burning building. The way you make interpret the world, the extent to which you rely on past experience, the extent to which the “right choice” is obvious; all of these are very different in each of those scenarios.
The central usefulness of Cynefin is that it gives us a way of identifying what kind of decision-making situation we’re in, and therefore what sense-making tools to use. It’s not a method or a process, it’s a set of concepts and terminology that enable thinking and decision-making in many different organisations and scenarios.
I love Cynefin, but it suffers from two things. First, it aims to be general-purpose, and so leans more towards the abstract than the concrete. That can make it hard to understand for newbies; there are (deliberately!) no simple steps to follow or cookie-cutter approach to take. And second, it’s the creation of a fantastically smart and well-read person whose knowledge transcends disciplines and who loves to play with language and meaning, which means it’s full of words and phrases like “dispositional”, “abductive”, “a state of aporia”, “liminal zones”, “phase shifts”, “exaptive practice”, “bounded applicability”, and so on. All wonderful, but also intimidating to the outsider.
So, how do we simplify things and make Cynefin as straightforward as possible?
For me, the central idea within Cynefin is the idea of domains. Domains describe particular types of situations we might find ourselves in, and suggest ways of making decisions once we’re in them. Cynefin tell us that there are three types of situation: ordered, complex, and chaotic.
In a situation that’s ordered, the relationship between cause and effect is known. The future is predictable, so long as things remain stable.
That doesn’t mean things are easy; a modern computer processor is ordered, but only a small number of experts fully understand it. So Cynefin distinguishes between ordered situations that are clear (where causal relationships are self-evident to any reasonable observer) and ones that are complicated (where the relationship between cause and effect requires expertise or analysis to discover).
Examples of clear situations might include baking a cake, mass-producing a familiar product, or playing a musical instrument. These scenarios have straightforward and obvious mechanics that would appear obvious to a lay-person: the cake is dry in the middle when it’s cooked; the nut goes on the bolt; the piano key makes a noise when you press it.
In a clear situation, we follow “best practice” and we get the best results.
Examples of complicated situations might include setting up a new computer network in an office, an accountancy problem, or translating text from one language to another. All of them are technically straightforward, but require specialist knowledge and experience to understand and explain clearly.
In a complicated situation, there’s no singular best practice; there are many ways to skin a cat. We can either take the time to learn what “good practice” looks like, or we can consult an expert.
In a situation that’s complex, cause and effect are unknown, and are only possible to determine in retrospect. We’re not dealing with total randomness: things are interconnected and entangled, and patterns can emerge over time. But it’s not the case that “if we do X, then we always get Y”.
Examples might include things like weather forecasting, managing a country’s economy, and marketing a new product. All of these scenarios contain too many interconnected variables to make predictions, and none of them have “best practice”.
In a complex situation, we can only probe and experiment, making small changes to the system and seeing how it responds and what patterns emerge.
In a situation that’s chaotic, cause and effect are totally unclear. Snowden writes that, in a chaotic situation, “a leader’s immediate job is not to discover patterns but to staunch the bleeding”.
Examples of chaotic situations tend to be dramatic: hostage situations, burning buildings, and so on.
In a chaotic situation, we have to act: we evacuate the burning building, we put out the worst of the fire. In doing so, we might make the situation merely complex, rather than chaotic, at which point we can begin to understand what’s going on.
Cynefin sets these domains out into a diagram with four quadrants, with fluid lines between them that demonstrate the interplay between the domains (and much more besides):
Basic usage of Cynefin involves understanding the domain one is in and adapting one’s decision-making accordingly. But more advanced usage sees the situation as dynamic, moving between domains as it unfolds, and indeed capable of being deliberately moved from one domain to another by us. But that – and many other things about Cynefin – will be the subject of a future article. For now, Cynefin can be of some immediate use to us if we can just get our heads around the idea of domains, and the sense-making approaches we need to take in each situation.
This week’s five interesting links
From my blog over at Orso, a post on understanding the natural variation inherent in data. How do you know if a change in a metric is a cause for alarm, or just business as usual? #
Tim Hwang with a great post on long-term scientific experiments:
“If you’re not already familiar… I highly recommend that you immediately stop what you’re doing and visit the Wikipedia page for ‘long-term experiment’. Then, check out Sam Arbesman’s collection of Long Data. Then, Michael Nielsen’s list of long projects.
“If you’re anything like me, the scientific efforts that appear on these lists are deeply compelling. That’s due in part to their relative rarity. It’s hard to find cases of an experiment or a data collection effort that grinds away on the scale of decades, and easy to appreciate the uncommon dedication and focus they represent.
“These efforts are also compelling on an epistemological level. They suggest that there is a wealth of valuable knowledge to be gleaned from even fairly humble explorations that operate over a long, long period of time.”
Tim reckons that such experiments are under-performed, especially given how simple and cheap they can be relative to the insights they can deliver. He suggests a new way of funding them:
“One approach could be to popularize a style of grant that I call TILT – tiny investment, long term. Under a TILT grant, a foundation or government agency would award grantees a relatively small stream of money spread out over an extremely long period of time, say twenty or thirty years.”
A useful tool from Jay Acunzo, which helps to define how an idea differs from the competition that’s already out there:
“Unfortunately, most of us get stuck playing comparison games. I think that’s because most of us are quick to spoil the possibilities for ourselves. We can’t wait to see the score. We can’t wait to look in the box at the cat. We can’t wait to figure out the best practice, or else we spend too much time consuming things inside our echo chamber. We adopt a narrow view right from the beginning instead of considering endless possibilities — which should be the hallmark of any creative person. As a result of being so anchored to our peers and competitors, when it’s time to pitch our premises, it sounds like a comparison.”
A sobering post from Mark Hadfield, whose “Meet the 85%” agency speaks to real people up and down the UK, seeking to understand what’s going on in their lives. He’s piercing the bubble that lots of businesses and marketers live in.
“Yet the unfortunate reality is that burying your head in the sand is not an option any more. As our good friend Richard Huntington says: ‘Hope is not a strategy.’
“Reality is here to stay. And for the foreseeable future – whether you like it or not, regardless if it doesn’t align with your brand onion – the reality people are living now and for a while is pretty grim.”