Chaos Theory and Uncertainty

In the last 20 years, a whole new branch of science has emerged based on chaos theory. For the previous 300 years, science had been grounded in the theories of the mathematician Renee Descartes [1625] who suggested that everything could be gradually decomposed until such time as it was divisible no further and at this point it would be possible to scientifically explain its behavior and composition. Its corollary held that something that was not understood simply had not been sufficiently decomposed.

The principles of Descartes suggest that eventually everything is convergent when it is properly understood—alchemy becomes chemistry, astrology becomes astronomy. Science has taught us to believe that all things converge and do so to a singularity. For example, there is only one precise answer to the time it takes the Earth to orbit the sun. However, study of weather patterns has shown that there are things that do not converge on a singularity. No matter how many weather sensors are added to a weather prediction system, the accuracy will only ever be so good. Adding more sensors does not improve it further. This does not mean that the science of meteorology is divergent. It means that it does not converge on a singularity, rather it converges on an approximation—a value with a measure of uncertainty.

The principle of uncertainty has been known in physics for some time, having been postulated by the nuclear physicist Hiesenberg. The science of physics learned to live with uncertainty. The Theory of Constraints teaches the business systems methodologist how to live with uncertainty in other fields, such as production, project management, and enterprise resource planning.

Philosophically, an effect that is known to involve uncertainty is not necessarily divergent or uncontrollable. It is merely convergent on an approximation. It does not mean that something that is uncertain cannot be classified, codified, measured, or controlled. It simply means that our measurements must always reflect a degree of uncertainty.

Hence, this text is grounded in a basic assumption that planning and prediction are possible within some bounds of uncertainty. Financial predictions for the performance of a software development business are possible, but must always be couched with a degree of tolerance. Agile management is all about being able to cope with uncertainty.