Most organizations adapt their best practices based of the experinces they gather over the years. Naturally, they learn from their market and competitors and try to mimic their operations and success factors. The Assembly line created by Henry Ford is still used today. Today, thanks to technological advancements such as constant available internet connections and online platforms like Facebook, people around the world can get in touch with each other instantly. This new worldwide connectivity has increased the complexity of markets and organizations significantly and created additional areas of complexity:
Besides technologically, the world changed also in social, economical and political dimensions. In short: The world is not the same anymore.
As individuals and organizations we are generally striving for certainty. But the world does not work like this anymore. Due to a constant adapting and dynamic environment, the way traditional organizations were built, is challenged. It is impossible for only a few individuals to understand all of the effects and connections involved. We are swamped by the lack of predictability and uncertainty.
New ways of cooperation with more focus on customer experience, value delivery and in general effectiveness, such as Lean, Design Thinking or with the Agile mindset require a fundamental understanding on how the world has been developed over the last 40 years. One way to look at complexity is Cynefin: Dave Snowden developed it in 1999 as a knowledge management or sense making model for complexity. Consequently, it can help us as a reflective tool on problem-solving based on the context you are in. With the Cynefin framework, Dave Snowden divided your context into 4 different domains. Those domains describe the environments an organization potentially navigates in. The solutions is to understand your own context to find your own solution:
Cynefin: Making sense of complexity
One way to look at complexity is Cynefin. Dave Snowden developed it in 1999 as a knowledge management or sense making model for complexity. Consequently, It can help us as a reflective tool on problem-solving based on the context you are in. He divided the Cynefin framework 4 domains, which describe the environments an organization navigates in. The solutions is to understand your own context to make sense of what is happening around you:
ObviousWhen things appear obvious, cause and effect are always connected in a straightforward way: If A happens, B will always be the result. For example: If you hold a pen and you let it loose, it always will fall to the floor. This is a proven theory, which works: Therefore, we can apply our proven best practices to avoid the pen getting broken .
ComplicatedIn a complicated environment the relation between the relationship between cause and effect is visible with expert knowledge. Research or Experience will help us to make the relationship more visible: these are good practices. An expert sales person will know, how many sales calls he would need to get how much of sales revenue. A novice would need to develop this expertise first.
ComplexIn a complex environment it is impossible to make the connection between cause and effect visible in advance. We need to try a solution first and test, if that works. Then we learn from the experience and improve our solution. Empirical process such as Scrum are based of an understanding of complex environments. We do not know, what we do not know. So, we need to test it.
ChaoticIn chaotic environments there is no relationship between cause and effect, therefore we cannot know, what we do not know. We can only react to developments, challenges and problems as soon as possible. If you have ever been in a firefighting situation in your organization, you might understand, that a ,lot of times, what you do then, does not make sense for you, but you do not have a chance to do it anyways.
Most of the time, we are in a state of disorder: A situation, where we did not understand the area we are in and therefore applied the wrong measure.
Consulting Services for Complexity Thinking
- July 8, 2020
- February 19, 2020