When we look at organizations, we don’t think about ‘chaos’ very often. After all, an organization is where there are rules to be followed, processes to accomplish tasks, and people who are responsible for these tasks. Come to think of it; one might assume that It is essentially a machine. A machine that can be optimized for maximum benefit, fixed if needed and its parts can be replaced for a more efficient outcome.
In this light, organizations seem like they are the antithesis of chaos; it is where everything seems under control.
But is it really? Are we in control of what happens in an organization on a broader scale? Is it possible to engineer how people act? Can we predict with certainty where the organization is going to be in the next ten years? Are we really in control of its destiny?
A realistic answer would be no. But our minds and subconscious work in a slightly different way because we share the basic assumption with classical science regarding our thinking about organizations. As James Gleick writes in Chaos, ‘given an approximate knowledge of a system’s initial conditions and an understanding of natural law, one can calculate the system’s behavior.’
We are prone to think that if we understand where our organization stands today and how things work, we can calculate the outcome, design the system, and control the ‘uncertainty.’
Where chaos begins, classical science stops.
Chaos Theory suggests otherwise. Here is an example of a simple double pendulum. We know how the law of motion works, but it is not enough for us to calculate the pendulum’s exact position in a given moment. That is because the system is chaotic. And with even small changes in the initial system, the results will differ significantly.
The reason why the pendulum acts this way is called sensitive dependence on initial conditions. Many systems around us are chaotic; there are too many variables that are intertwined, all of which can significantly change the outcome. These variables constitute a complex system so much so that no matter how better we get at calculating the conditions, we would probably be unable to tell its future.
Let’s think about weather forecasts. How many times did you look at the weather forecast, it showed sunny for the day, but the reality turned out to be the opposite? We cannot precisely predict what the weather will be like a week or even a day from now because there are simply too many variables. Temperature, humidity, wind, to name just a few. To get an exact prediction, you would need to measure every variable in the atmosphere over every half a meter. Even that 50 cm distance may cause significant outcomes that would not show up in your calculations. Therefore you’d make wrong predictions.
Chaos theory teaches us that we cannot rely solely on our calculations, but it also shows a way to navigate the uncertainty. Yes, we may not precisely predict events at the micro-level, but we can understand the system’s patterns. They are called ‘attractors,’ which give us a sense of itinerary of the system’s state, to where it will gravitate towards, and whether it will remain in that path unless its course somehow changed. So if we want to change the organization, we have to find out first what the attractors are.
Organizations as chaotic ‘living’ systems
Organizations in themselves are very chaotic. They, too, have many variables that are integrated. External and internal conditions, organizational culture, leadership styles, teams, and people in the teams — including their personality traits — can change the organization’s course. An excellent idea might be turned down when the leader is ‘not in the right mood’ or a simple misunderstanding can reshape the whole project. Even most of our day-to-day planning is a way to create a sense of control in an environment where random events can reshape the entire plan. Pretty chaotic, right? (Surely, a machine is not that chaotic while it is operating.)
This chaotic nature in organizations are very much like ‘living systems’ rather than a mechanic system from two points of view:
Organizations (and living systems) must be able to reach resources to survive in their environment.
Organizations (and living systems) must transfer the accumulated knowledge to the ‘next generation’ to keep surviving.
And a more in-depth look into these two factors might reveal the attractors for how organizations change.
Let’s look at number one: “reaching resources.” For an animal or a species, this might simply mean having access to food and water. For an organization, it is how you generate income. That is why most common business practice focuses on how to compete with organizations in the same sectors. In that approach, organizations will survive if they are doing better than their immediate competition — by any means necessary. That is correct, of course, until a disruptive innovation in the ecosystem happens.
If the organization can only see its competition, it will not see significant shifts happening and affecting them. It is like a predator focused on eliminating another predator without recognizing that the environment is changing drastically. The real reason an animal can survive in the long run is that it positively impacts the whole ecosystem. It is only then the ecosystem can thrive with balance, rather than face constant disruption and elimination.
So the first attractor **drum rolls here** is whether the organization has a purpose, which allows them to think beyond ‘sectors’ and to focus on having a positive impact. If their existence creates value and has meaning for all their stakeholders, they will guarantee access to the necessary resources in the long run.
The second one is even more interesting. To transfer the accumulated knowledge to the next generation, organizations develop standards and protocols that employees are expected to follow. Indeed, these help the organization to document its know-how. However, it does not truly enable the ‘next generation to accumulate knowledge. As procedures get longer and bureaucracy gets bigger, information gets stuck in the hands of experts and silos, only to become obsolete after some time.
However, in living systems, there are no manuals to follow. Species survive because they learn how to adapt, react, and change with their environment. They learn from the generation before how things are done and the natural instinct and skills needed, which will help them navigate the uncertainty.
From an organizational perspective, the only way to generate an instinct is by providing the necessary context and vision. And if the organization is to survive the uncertainty, the skills needed are creativity and collaboration. Whether the organization has required culture and structures that enable people to act creatively, collaborating easily towards a shared purpose might be attractor number two.
‘The machine’ does not make sense anymore.
What chaos theory teaches us is that organizations act more like living systems rather than mechanical structures. The myth that an organization can act as if it is a machine is why most organizations have a hard time implementing strategy, initiate change, and in the end, survive.
If we want to build better organizations tomorrow, we have to accept that they are more chaotic than we would like to admit. And it is okay because it is only natural.
James Gleick; Chaos: Making a new science; 1983
Daniel J. Svyantek and Richard P. DeShon; Organizational Attractors: A chaos theory explanation of why cultural change efforts often fail; 1993