A problem-solver’s best friend: the Cynefin Framework
The Cynefin Framework changed the way I solve problems; it can do the same for you.
Developed by David J. Snowden, its central theory is this: to effectively solve a problem, we first need to identify the type of problem we’re dealing with.
In Snowden’s framework, pronounced “kuh-nev-in”, all problems can be sorted into four types: simple, complicated, complex and chaotic.
- Simple problems are just that. With clear instructions, anyone can solve a simple problem because the relationship between cause and effect is linear: if you do X, you can expect Y. An example of a simple problem might be how to correctly build and test your weekly newsletter. Solve simple problems by making checklists for staff and document your processes.
- Complicated problems require more expertise. The cause and effect relationship exists, but data analysis may be required to understand it. In this case there could be a range of correct answers. An example of a complicated problem is running a successful Instagram account. Social media tips and best practices can help guide you, but they can’t guarantee engaged followers. To solve a complicated problem you’ll need to look at the data and apply your expertise.
- For complex problems, throw the rulebook out the window. If the system you’re working in is variable, there is no wisdom to fall back on. Complex problems require experimentation, learning and iteration. Consider an advocacy campaign aimed at changing environmental laws with policy makers. Experience is helpful but the political, social and cultural variables are always changing. So, you must experiment and keep learning and iterating as you go.
- The final problem type is called chaotic. Here, there’s no time to think, you just need to act to prevent damage and restore order as quickly as you can. A chaotic problem might be a hacker breaching your client’s website.
Why is it important to understand problems this way? Because identifying whether a problem needs a simple checklist, an extensive experimentation phase or all-hands-on-deck is critical to solving it effectively, with right-sized resourcing. Something we see too often at Capulet is complex problems branded as complicated. Clients are looking for experience and best practices when experimentation and iteration is what’s really needed.
When Capulet worked with the BC Chapter of Canadian Parks and Wilderness to create Precipice, an art show about biodiversity loss and the climate crisis, we were working in the complexity sphere. We knew building influence for climate action was critical, but we also understood that politicians were tired of going to the same old reception events and that potential supporters weren’t inspired by the usual tactics: tabling, petitions and emails.
So, to respond to this complex problem, we experimented; we created an immersive art experience. No one was expecting an environmental nonprofit to invite them to an art show! The invite caught the eye of BC’s Minister of Minister of Water, Land and Resource Stewardship who came to Precipice to speak with Indigenous leaders and environmental campaigners. Local media also attended to interview artists and advocates.
Ultimately, Precipice was an experiment on how best to influence decision makers who can move the needle on biodiversity loss in BC. We knew this to be a complex problem, with a need for learning and iteration. Precipice provided the learning opportunity our client was looking for.
The Cynefin Framework is like a pair of glasses that helps you see challenges more clearly. If you want to do a better job solving problems, the Cynefin Framework just might be the system you’ve been looking for.
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