Drifting to Low Performance
I recently heard a joke John Oliver told on one of his stand-ups. He travelled to Colorado and got a cab from the airport to take him to his hotel. He immediately asked the driver if he could tell him what was Colorado most famous about. After giving him some thought the driver said: "Well... we are the least obese state in the country!". Funny right? And when you'd expect a tip about sightseeing.
I found that retort tragic and very sad. The best thing that the driver could mention is that they are not as bad as everyone else. That immediately reminded me of one of the system traps that the Donella H. Meadows talks about in her book "Thinking in Systems". That trap is called Drift to Low Performance.
Drift to low performance
In system theory, the system structures that produce common patterns of problematic behaviour are called archetypes. These archetypes cause problems that have to be fixed or they will lead to the system's destruction. However, the obvious solutions to these problems are usually not the correct ones and very often backfire. That is why Donella Meadows calls them traps.
Drift to low performance is one such trap when by allowing standards to be influenced by past performance, especially when past performance is perceived as bad, sets up a reinforcing feedback loop of eroding goals that set a system drifting toward low performance.
We see examples of this all around us in people, governments, schools, companies and organizations in general. They set performance goals and aim for a state that is compared to the actual state. But if the current state of the system is not satisfactory then they allow the goals that are based on it to also erode. There are countless examples of this. Our neighbouring countries also have a lot of problems. The previous government was stealing much more than we did! No one jogs these days anyway. At least we are the least obese state in the country. And so on and so forth.
This kind of thinking and allowing goals to erode can lead to continuous degradation of the system's performance. And the worst thing is that it happens slowly and over time. It is very easy to go under the radar unnoticed until it is way too late.
Let us assume we have a huge heap of sand and we are allowed to only take a single grain of sand at a time. We take one grain. Do we still have a heap? Yes, we do. We take another grain of sand. Do we still have a heap? Yes, we do. And it goes on until there is a single piece of sand left. So, when did the heap stop being a heap? How did we let this heap erode?
The boiling frog theorem
Although biologically incorrect, this fable is well known to anyone. Put a frog in boiling water and it immediately jumps out. But put the frog in cold water and then gradually heat it up, the frog will boil to death happy in it's relaxing hot bath. If only the frog could remember how the water was at the very beginning, not only a second ago. Because, only a second ago, it wasn't that colder really.
How do avoid drift to low performance?
There are two ways advised in "Thinking in Systems". Keep standards absolute and set goals based on the best performances not based on the current state of the systems.
Stop the gradual theft of your sand heap. Jump out that water before it boils you to death.