Chaos of leadership
When considering how complex systems organize and operate or how innovations occur, Russ Marion offered what seems to be a simple answer: “interaction.” However, the theories that explain complex interacting systems are far from simple. Chaos theory explains interacting systems, while complexity theory explains the interacting and adaptive systems. A science of turbulence, chaos theory shows how unpredictable behavior may not be random. Attempting to use a computer model to predict the weather, Edward Lorentz (1963) found that slight differences in initial condition greatly impacted how events unfold. This “sensitive dependence on initial conditions” (Gleick, 2008, p. 23) would become known as the Butterfly Effect and served as the foundation for chaos theory.
The ideas of interconnectedness and chaos were familiar with ancient philosophy and religion. Still, they were new concepts to scientists who viewed reality as Newtonian clockwork. Traditional science attempted to identify and explain the predictable while dismissing irregularities as errors in measurement or anachronisms. That is until researchers like Lorentz started to notice universal patterns in irregularities. Using computer models, Lorentz was able to identify structure and patterns in turbulent systems. Where once was chaos and unpredictability, computers helped scientists see that stability and unpredictability coexist.
Like most revolutionary discoveries in science, Lorentz’s observations were hardly original. His unique contribution was that the same kind of sensitivity to small changes can affect even simple systems. Chaos theory helps to show how chance appears in a deterministic world; predictability requires perfect knowledge of the universe and exact laws of nature. Even in the unlikely case that all laws become clear, humanity will not likely ever know the state of the entire universe (Strogatz, 2008). As stated by Lorentz (1963), “any physical system that behaves non-periodically is unpredictable” (Gleick, 2008, p. 18).
A vital concept that chaos theory offers for leaders is that understanding the current state of an organization will provide little information about its state tomorrow. The more complex a system, the less predictable it becomes because the relationship between cause and effect is not constant. The weakness of chaos theory for leadership applications is that it accounts for neither adaptation nor intelligent behavior. In her attempt to apply chaos theory to leadership, Wheatley (2006) offered an analogy of a river that can adapt to and change the environment. She suggests that the river knows how to make things happen because it has a “need to flow.” The river holds a clear mission and multiple strategies for dealing with obstacles because it “realizes” that many ways exist for reaching the ocean and has the “faith” that it can achieve its mission (p. 16).
Anthropomorphizing a river to define leadership applications of chaos theory has an important limitation: a river is neither human nor conscious. The river’s environment is a natural system, not a social system. Marion (2002) suggested that chaos theory helps to explain phenomena in environmental systems, like fluid turbulence and weather. However, it does not account for adaptation and intelligent behavior. Although chaos theory initially offered interesting metaphors for leadership applications, it has limited relevance to human social interactions.