Agile Management - Complexity Thinking View more presentations from Jurgen Appelo.
When people don’t understand the nature of complex systems, they tend to make assumptions that don’t make sense from a complexity perspective. For example, people often assume that the variation in size of customer requests follows a normal distribution, or Bell curve. When plotted in a graph this distribution looks like my belly, when viewed from above.
The assumption people make is that, when considering change requests or feature requests from customers, they can identify the “average” size of such requests, and calculate “standard” deviations to either side. It is an assumption (and mistake) I noticed again in John Seddon’s book Freedom from Command & Control.
There is no “average” size of earthquakes. There is no “average” size of personal income. There is no “average” size of blog posts. There is no “average” size of organisms. And there is no “average” number of false assumptions in books by systems thinkers.
Events in complex systems tend to follow the exponential or Pareto distribution. Also known as Zipf’s law, the 80-20 rule, the power law, etc. It looks like my foot, when viewed from the side.
In complex systems there are many occurrences of small events. Like tiny earthquakes, low wages, small blog posts, microscopic organisms, and slightly erroneous books on systems thinking. But there are also few occurrences of big events. Like catastrophic earthquakes, excessive salaries, gigantic blog posts, huge organisms, and complete idiots among systems thinkers. In complex systems this is all normal. It is a pity that mathematicians named the Bell curve the “normal” distribution, because, in the real world, the Pareto distribution is more ubiquitous and normal than the normal distribution.
I am convinced that the needs of your customers also follow the Pareto distribution. Most customers have only small needs. Few of them have big needs. Most of them have small budgets. Few of them are excessively rich. Most are quite reasonable. A few are minions from hell.
Of course, you can calculate the average of a number of specific occurrences that happened in the past. But your “average” has only little predictive value. With limited experience, your “average” is likely to include only the very common events, not the uncommon ones. Yet, in a complex environment, all events are normal. Both the common ones and the uncommon ones.
Customer demand is, by nature, an non-linear thing. If you assume that customer demand has an average, based on a limited sample of earlier events, you will inevitably be surprised that some future requests are outside of your expected range. You may call them “outliers” or “unexpected” or “black swans”. But fact is, you made the wrong assumption. You’re painting a distorted picture of customer demand. Like a picture of my face, when viewed from the rear.
The existence of rare events in complex systems is quite expected. Like me. Happily uncommon, but quite normal.
p.s. I do not mean there are no black swans, or unpredictable events. I just mean common thinking is no excuse for calling the uncommon events “unexpected” or “not normal”.