Scott has been a faculty member in higher education for over 10 years. He holds an MBA in Management, an MA in counseling, and an M.Div. in Academic Biblical Studies.
Overview of the Cynefin Framework
The only thing more frustrating than a recurring problem is a recurring problem without a known cause or solution. This is where the Cynefin Framework can help. The Cynefin Framework is a systematic method for assessing problems. The framework can be applied to problems of all kinds, and using it's helpful in nearly any industry. In a broad sense, the purpose of using the Cynefin Framework to analyze problems is to ensure that leaders don't try to apply universal solutions to unique problems.
Domains of the Cynefin Framework
The Cynefin Framework is made up of five domains. Each domain is a category to which a problem can be assigned before the analysis begins. The person leading the effort begins the process of problem-analysis after determining in what domain the problem should be placed.
Let's look at the definition, characteristics, and an example of each domain in the Cynefin Framework.
Imagine that you're a restaurant manager. For the third time this year, you've been required to pay a worker's compensation claim that resulted from two servers colliding with each other while entering or exiting the kitchen. Is this a problem? Absolutely! But will it be difficult to analyze or fix? Probably not. When the problem, its cause, and its solution are all pretty easy to understand and resolve, the problem is in the domain of the obvious context.
In this domain, your problem's details are so readily apparent that you won't really need to study the issues or causes. To solve problems in the Cynefin Framework's obvious context, your organization needs to do little more than determine what other organizations like yours are doing in similar situations. This is known as a best practice.
The complicated context is marked by two key differences from the obvious context. First, the complicated context classifies problems that have the potential for multiple solutions that aren't apparent or agreeable to everyone involved. Second, the complicated context doesn't have a universal understanding of the problem's root cause, its solution, or both. In other words, it's, well, complicated!
Let's revisit the earlier example of worker's comp claims in the context of a complicated (rather than obvious) context. Imagine now that the injuries causing the claims aren't collisions while entering or leaving the kitchen, but instead the result of falls in the kitchen area. Falls can be caused by quite a few different things. Is your floor wet, covered in oil, or made of a surface that offers no traction? Is one of your employees spilling something on to the floor? Are the servers wearing good shoes? Since we don't understand the cause, we can't propose a solution just yet.
To address a complicated problem, experts may be necessary. These experts are the people who have a skill set and background to help answers the questions about both cause and resolution.
In the domain of complex context, problems don't just have an obscure cause or solution. In fact, they may have no known cause or specific solution. As a result, complex problems are nearly impossible to predict. This makes them difficult to solve. In many cases, complex problems can't be effectively addressed until you experiment a little. The necessary experiments are created to test different variables to see which one(s) seem to be causing the issue.
Returning once again to the employee fall example, how does the situation change if the pattern of falls included one collision with a co-worker, one slip-and-fall in the kitchen, and one fall after tripping on a chair in the dining room? Since there's no obvious causal relationship between the events, experimenting may be the only effective approach. A simple experiment relative to this Cynefin Framework domain might be to have servers try a specific type of shoe, and then observe if there was any change.
Chaotic context problems are emergencies. They're the situations in which there's no time to experiment, and there isn't enough time to perform experiments or analysis of a root cause. Problems in the chaotic context require immediate stabilization or rapid action to prevent further harm. Let's go back to your restaurant: a chaotic context problem would occur if four servers all slipped and fell in the kitchen simultaneously. Bad luck, right? This is a chaotic context problem because immediate action must be taken to ensure that no more servers are injured. The proper response might be to immediately mop the floor, but delay looking for a root cause until the danger has passed.
Finally, the disordered context is the polar opposite of the obvious context. In the obvious context the cause and solution are apparent, but in the disordered context it's impossible to even classify the problem into one of the other Cynefin Framework domains. In a disordered situation, all bets are off and you'll often have to resort to following your gut instincts to make decisions. An effort should be made to re-classify the problem to another domain as soon as it's practical to do so.
The Cynefin Framework is a methodology used to assess problems in a systematic, orderly way. The framework has five domains that function as categories to which a problem is assigned based on its characteristics.
Problems in the Cynefin Framework's obvious context are problem for which the cause and solution are apparent to all involved. In the complicated context, there are several apparent causes and/or solutions but further investigation is necessary to determine the right way to proceed.
Problems in the complex domain are issues for which a cause isn't readily apparent, and the connection between the problems and causes isn't solidly established yet. Chaotic problems are urgent issues for which a root cause and permanent solutions are held off until the immediate risk has passed.
Problems that can't be accurately placed in any of the first four domains are assigned to the disordered context by default.
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