I have rewritten this post numerous times, I have deleted it and republished it. This is typically a sign of that I have a gut feeling about what I want to write but I haven’t yet been able to put words to that gut feeling. The rest of this post is my latest (but perhaps not last) attempt to find those words.
Everybody is looking for quick fixes to complex problems, especially if the problem initially doesn’t look all that complex and a fix is needed yesterday. Unfortunately quick fixes (with emphasis on the “fix” part) to complex problems are rare. A couple of examples of problems and their corresponding quick fixes:
- Something important is falling between the cracks in an organization. The quick fix is to create a new role or position that has the responsibility for exactly the thing that is being neglected. Perhaps a new coordinator (whatever that means) or even a new manager or vice president.
- A production stop is caused by a poor quality component. The quick fix is to appoint an ad-hoc task force for trouble-shooting.
Some cures, like the ones above, turn out to be worse than the illness. The new role in the first case above might end up having responsibilities that are already partially allocated to some other role resulting in confusion. The new role may also conceal the real problem.
The task force in the second example may take on the responsibilities that would otherwise belong to the product support organization that for the moment is understaffed. If the product support organization isn’t exposed to the issue it will not be able to take corrective action to prevent similar problems in the future. Also the resource shortage may not be exposed as one of the root causes.
Many methods such as Toyota Production System’s A3 [1] stress the need for a thorough root cause analysis when solving problems like this. But fixing the organization or the work processes on a more fundamental level, taking into account all process interfaces and the responsibilities of all roles may turn out to be quite complex. The simple reason is that reality can sometimes be dauntingly complex; a space ship requires rocket science – less will not get it off the ground.
These are the phases I often see in the problem solving process:
- “How hard can it be?”: The symptoms of the problem are in front of us. We start trying to make sense of it. It all looks simple because we haven’t started to scratch beneath the surface.
- “Are we making this too complicated?”: Fatigue and impatience is setting in as more and more factors and dependencies are revealed. If we stop here and don’t get the complexity on the table and understand it, then the solution may well be simple but it is also likely to be wrong. Simple solutions are desirable but simple and good solutions can only be created once the complexity is understood.
- “Over the complexity maximum”: If we have made it past the previous step then we are starting to get all the bits and pieces on the table. Our mental model of the problem is still complex but we begin to see patterns and connections. We see that that part over there is really the same as this part over here, that existing role already has almost the responsibilities that we at first were tempted to assign to a new role. And so on. We can start simplifying our solution from a position of understanding.
- “The simple and good solution”: Having done all the simplifications in the mental model, we are ready to design the simplest possible solutions. But not simpler.
In a complex world, a simple and elegant solution can only emerge once the messy and initially inelegant complexity has been understood. One has to have the stamina and determination to climb Mt Complexity. Drilling a tunnel through the mountain might get you into the Valley of Despair.
Links
[1] The Toyota Way. Jeffrey K. Liker.
Note
I’m indebted for the term complexity maximum to Anna, with whom I worked at a client more that ten years ago. She had many other interesting ideas too including the habit to take a new seat at the table after every break during a long meeting. She claimed it would keep us all flexible and ready for fresh thinking. She might have had a point although I must confess I found it quite annoying.