The Cynefin Framework

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Decision Making in challenging situations isn’t easy.  The decision on how to approach and respond to a problem varies depending on the circumstances. Decisions necessitate a tailored approach, which should help avoid making a fatal decision with irreparable consequences.

The Cynefin Framework is a model to assist in making effective decisions in dynamic contexts.  It is a structured way to understand complex problems and make informed judgments.  The model does that by analyzing possible elements of a circumstance and the factors that influence individuals’ thoughts and decisions in ways that they are unaware of.

The word “Cynefin” takes roots from the Welsh language, meaning a habitat, place, or familiar.  The framework was introduced by the researcher, Dave Snowden, while working as the European director of the IBM Institute of Knowledge Management in 1999.  He later became the founder and director of the IBM Cynefin Center for Organizational Complexity.  Dave Snowden developed the Cynefin Framework as a tool for managing knowledge in complex environments.

The framework is grounded in concepts from Knowledge Management and Organizational Development.  Over time, the Cynefin Framework evolved into a broader sense-making model applicable to various domains, including Business, Management, Leadership, Marketing, Product Development, Corporate Strategy, and emergency situations.  The model emphasizes the need for flexibility, adaptability, and a deeper understanding of complex systems.

The Cynefin Framework categorizes situations into 5 contexts or domains (or 5Cs simply), each representing a different level of complexity.

1. Clear: A context where cause and effect and options are obvious to everyone.
2. Complicated: In this context, problems are still solvable, require expertise or analysis to understand the cause-and-effect relationships.
3. Complex: Problems, here, have multiple interdependencies, influenced by emergent patterns.
4. Chaotic: Situation is highly unpredictable and unstable, without clear cause-and-effect linkages.
5. Confused: This context represents a state of ambiguity and uncertainty where it is difficult to determine which of the other domains are at play here.

The 5 situational domains of the Cynefin Framework are governed by cause-and-effect relationships.  Let’s us now dive a bit deeper into the first 3 domains.

Domain 1. Clear

In the first context, there are procedures and predetermined rules in place, and nothing is left to chance. In this domain, cause-and-effect relationships are known and can be addressed through best practices and established processes.  The clear domain represents situations where there is a high level of predictability and the answers or solutions are known or easily obtainable.

This domain involves known knowns, where both the problems and the solution are clearly understood.  The solutions are often based on past experiences and procedures.  It is a domain of order where the emphasis is on efficiency, consistency, and repeatability.

Domain 2. Complicated

This domain is characterized by situations where the cause-and-effect relationships are not as obvious as in the Clear domain but can still be determined through analysis and expertise.  The problems are still solvable but require expertise or analysis to identify their cause and effect.

There is a sense of predictability and “known unknowns,” but it requires a deeper level of investigation and assessments to uncover underlying patterns and find effective solutions.  There might be multiple valid approaches to solving a problem, and different experts may offer various perspectives.  Examples of situations that fall into the “Complicated” domain include diagnosing a complex illness, developing a detailed project plan, or solving a technical problem.

Domain 3. Complex

Complex systems are dynamic, characterized by multiple interacting elements, non-linear relationships, feedback loops, and interdependencies that lead to unexpected outcomes.  In this domain, there are no clear cause-and-effect relationships.  Solutions emerge only through experimentation, learning, adaptation, and collaboration.

Complex environments are unpredictable and in such situations experimentation facilitates potential viable solutions.  Any failures should be allowed and taken as part of learning.  It is important to observe and identify patterns to gain insights into the system’s behavior, engage diverse viewpoints, and encourage collaboration to understand the system from different angles and uncover potential solutions.

Interested in learning more about the other domains or contexts of the Cynefin Framework? You can download an editable PowerPoint presentation on the Cynefin Framework here on the Flevy documents marketplace.

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