03.03.2022

Created by Karen Krogel

#favouritemodel No. 24 – Dealing with complex tasks

When was the last time you said to an employee who came to you with a problem: “Well, I understand your problem 100% and can tell you: if you do exactly XY, you’re guaranteed to solve the problem.”?

And that solved the problem? Well then, congratulations! Because this type of problem is dying out. There are fewer and fewer problems that we can solve with just the right specialist knowledge. At the same time, there are more and more tasks with a degree of complexity that we need several brains just to get through. If I try to solve such complex problems using the “expert approach” – i.e. assuming that I only need the right knowledge or the right person with the right knowledge – I will probably fail miserably. My solution will probably only target 1-2 aspects of the problem, whereas it actually has around 250. Which means that I have ignored the complexity with this approach. Perhaps I have also deliberately “reduced” it. We often talk about the need to reduce complexity. But how effective is that? If I reduce some aspects of an issue in order to understand it better, they have not disappeared in reality. So would I have to add them back later and would my solution still be sufficient? Probably not.

So what do I need to be able to deal with complexity? Our first suggestion is: don’t try to do it alone! Invite several perspectives to work through the problem with you. This can get quite confusing and feel overwhelming at first and not at all like a solution. Yet we are all so geared towards finding solutions. This is exactly what we have to endure! That the complexity may even increase because we allow different perspectives on it without already knowing in which direction the solution lies. In the course of the process, we then agree on which aspects we will focus on more and which we will put on the back burner. We should constantly review the hypotheses that guide us. We define parameters for the next decisions, knowing full well that these are only the next steps and that the complete path to the goal is not yet known.
After the initial decision for an action and its implementation, we observe closely and then enter the next reflection and learning loop. This iterative approach makes it possible to quickly recognize errors and unexpected effects and integrate them into the next step towards a solution. In our model, we often describe the process of opening up and “enduring” complexity as “open – explore – close”. At the beginning, when opening up, the original complexity may even be increased again because I obtain many perspectives and examine the task from different angles. The first challenge in the solution process is to filter out the relevant aspects and consciously put some of them to one side – always bearing in mind that they could become important later. This is followed by the phase of exploration, investigation, discussion and evaluation of information and parameters in order to be able to make the subsequent decision. In closing, we condense these and define the next step, our action, which we observe closely in order to learn from it and go through the process again.

How does my #favoritemodel help you?

In our increasingly interconnected and interdependent world, we cannot escape the growing complexity. Ignoring it also helps emotionally at best – because it relieves us if we simply ignore aspects of it. But as one of my participants once remarked so aptly: “Complexity doesn’t care whether you acknowledge it or not – it’s just there! So let’s face it with all our diverse expertise, our different perspectives, experiences, feelings and thoughts and bring them to maximum fruition by:

  • Ask open questions that create space for new perspectives
  • Consciously invite counter-speech
  • Invite more than one “expert
  • Making information accessible and transparent for everyone
  • never commit ourselves too quickly to one option
  • prefer to plan smaller steps
  • learn from the previous steps and rather add one more learning loop to the process
  • always assume that we could also be wrong


What experience have you gained in solving complex problems? What other ideas do you have for dealing with them? Feel free to write to me if you would like to discuss this. By email or on LinkedIn.

Author

Karen Krogel
Consultant