Understanding Complexity: an example
Using the Cynefin framework can help executives sense which context they are in so that they can not only make better decisions but also avoid the problems that arise when their preferred management style causes them to make mistakes.
-Dave Snowden
Too often, organizations tend to plan for a Lean / Agile / Digital Transformation. There are 2 fundamental flaws on this approach (or anti-pattern):
The first point should be simple and evident. Continuous Improvement is a key element in Lean (Kaizen) and instead of aiming for perfection, the goal is to get better every day.
If you are perfect, you cannot improve. Remember: getting better beats being perfect.
The second one instead, is too often not so well understood and this is why I wanted to share here an example that came out during a conversation, when talking about a couple of events that have been in the news worldwide:
The first case, is what in the Cynefin model is called "Complicated". It is clearly not simple, but there is a reasonable level of confidence in the success of the mission (otherwise, nobody would accept to be an astronaut) and cause-consequences are well understood.
Finding the vaccine for the COVID-19 virus instead, is a Complex situation:
We will only know that we found it ... once we found it.
Understanding the nature of the situation we are dealing with is essential in order to use the right strategy. Like Dave Snowden explains on his article on Harvard Business Review:
The framework sorts the issues facing leaders into five contexts defined by the nature of the relationship between cause and effect. (...)
Using the Cynefin framework can help executives sense which context they are in so that they can not only make better decisions but also avoid the problems that arise when their preferred management style causes them to make mistakes.
In short, a common mistake is to approach a complex situation as if it were complicated.
Please note that we are talking about the approach and not the results. Crossing the street is simple and yet, we can die doing that. This does not make it complex or complicated.
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Now, if we will only know what works after we have tried it out ... how to plan for that?
Basically, you follow a time-boxed approach, to limit the scope & risk of the experiments. You can read more in the previous post: "How & Where Control Happens in Lean"
And this is the whole point of this post, in understanding complexity.
A traditional mindset trying to find a vaccine for the COVID-19 for example, could say: "Let's optimize resources. We should unify all efforts into a single program, so there is going to be one single Universal Vaccine Advanced Research Program -UVARP-".
The consequence will be a bureaucratic, immense and inefficient organization where egos are more important than results. People will continue dying and excuses will flourish. The only way out is to move forward, meaning to continue adding budget on top of failing initiatives until they succeed ... or the whole program collapses.
Instead, a decentralized approach, where multiple autonomous experiments can take place, permits continuous funding of the most promising experiments with minimum overhead and upfront planning. What becomes relevant here is not the initial plan but the results delivered.
Also SpaceX followed this approach, with multiple failing launches, before collecting enough knowledge and experience, to move from Complex to Complicated.
There is time to learn. And there is time to perform.
Eduardo Brice?o explains this very nicely and it is also a good way to understand the point.
In a Complicated scenario, you focus on performing.
In a Complex situation, you first focus on learning.
Update: more recently, I found this short fragment of a presentation by Dave Snowden, that makes the point in a beautiful way. Just connect what he is saying with Toyota Kata, and many things will start falling in place. Enjoy!!
Last but not least, when you are learning, your experiments are (by definition) small.
Please remember (if you did) to "like" this article ;-)
Delivery Lead | Scrum Master
4 年"In a Complicated scenario, you focus on?performing. In a Complex situation, you first focus on?learning." and in that learning, move from the complex to the complicated. IMO really good point made clear, you are trying to get out of the complex, you want to (need to) learn in this space, but not solve ‘here’ but move to the complicated space. Perhaps that's why the solution can often be seen, in retrospect, more difficult than the original problem....