The Cynefin framework

In real life, when it comes to decision making...

There is no Marvel heroes, neither an ultimate plan for every situation.

When it comes to decision making, in every aspect of life that matters, it has to be a certain mechanism each one of us works with to deal with all kinds of disorders.

That’s why we will be introducing to you today a new kind of decision making, a good one. For most chaotic persons on earth, this could be a game-changer. We hope you read these words with an open mind.

Most people tend to make mistakes when they get themselves into something unknown, unusual or a certain disorder they haven’t been into ever or just by accident. Simply because every situation needs to be treated with a certain approach.

When you feel that weird confidence in a situation you’ve never experienced before, know for sure that you’re all the way wrong my friend. Instead of being confident, you must be realistic in order to realize that you really need to understand what’s going around you, by that we mean all the parameters that create the context.

Use Cynefin framework to know where you are

We are going to introduce you to a framework that will help you categorize what you know, what you know that you don't know, and what you even don't know that you don't know.

Dave Snowden’s Cynefin concept came up in 99s as the first framework described as a “sense-making” device. Nowadays, it is considered a great agile practice for operational management and strategic alignment.

First of all, let’s see the key distinctions between a framework (like SAFe per example or Scrum) and a methodology (like XP or Agile). This table summarizes everything you need to know about the difference between the two.

Difference between a framework and a methodology.

Cynefin is a framework that actually throws light on many theories: systems theory, complexity theory, network theory and learning theories. It was used by IBM developers in policy-making, product development, market creation, supply chain management, branding and customer relations.

The idea behind this framework is to differentiate between 4 decision-making contexts: Simple, complex, complicated and chaotic. Depending on the context or the situation, every domain has a certain approach to follow and when it is mostly adequate.

Here is a clear view to what all this is about:

The 4 contexts of the Cynefin framework

HOW TO TAME THE CHAOS AND COMPLEXITY?

In Agile methodologies, or frameworks such as SCRUM, SAFE, LESS, Agile@Scale, XP, Lean, Desing thinking, etc. We try to handle the unknown by adding few constraints to the game as:

• Market research to identify personas and possible market fits.
• Prototyping the product and getting feedback from our target audiences before developing it.
• Iterative and incremental development a process by which we can manage a project or a product by breaking it up into several stages and involving constant collaboration with stakeholders to improve it continuously at every iteration.

The ultimate objective is to transit from the chaotic to the simple passing by (or not) the complex and/or the complicated.

Cynegin framework

We hope this short introduction to the Cynefin framework was insightful and made you curious about the detailed practices that we will talk about sooner.

If you want to talk about it in detail with our experts, contact us!

<!-- ai-angle -->

Where AI fits: clear, complicated, complex

Cynefin is one of the best tools to decide where AI belongs and how to govern it.

• Clear domain: repetitive, rule-based work. Classic automation and AI agents deliver fast, measurable gains.
• Complicated domain: expert analysis. AI becomes a copilot that drafts, compares and checks, while experts keep the decision.
• Complex domain: strategy, change, new markets. AI supports exploration with scenarios and synthesis, but the approach must stay experimental: small probes, fast feedback, safe-to-fail.

Treating a complex AI transformation like a complicated IT project, with a fixed plan and a big-bang rollout, is the most common reason it stalls.

This is how we work at JediSquad: see our AI transformation approach and the Agile AI Product Triangle.