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Chaos theory in organizational development
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Applications and pitfalls
The primary goal of an organizational development (OD) consultant is to initiate, facilitate, and support successful change in an organization. Using chaos theory as the sole model for change may be far too risky for any stakeholder buy-in. The concept of uncertainty on which chaos theory relies is not an appealing motive for change compared to many alternative “safer” models of organizational change which entail less risk. By careful planning and management of disorder a successful intervention is possible, but only with a truly dedicated arsenal of talented and creative resources. By permitting or actively forcing an organization to enter a chaotic state, change becomes inevitable and bifurcation imminent; but the question remains, “Will the new direction be the one intended?” In order to account for the direction of the new thrust, most planning attention should be focused on attractors instead of the initiation of disorder.
Although chaos eventually gives way to self-organization, how can we control the duration, intensity, and shape of its outcome? It seems that punctuating equilibrium and instilling disorder in an organization is risky business. Throwing an organization off balance could possibly send it in a downward spiral towards dissemination by ultimately compromising the structural integrity (i.e. identity) of the system to the point of no return. The only way to reap the benefits of chaos theory in OD while maintaining a sense of security is to adjust the organization towards a state of existence which lies “on the edge of chaos”.
By existing on the edge of chaos, organizations are forced to find new, creative ways to compete and stay ahead. Good examples of such learning organizations are found throughout the field of technology as well as the airline industry, namely organizations such as Southwest Airlines, which used re-invention not just for survival, but also to prosper in an otherwise dismal market. In contrast, there are organizations which, due to extended periods of equilibrium, find themselves struggling for survival. Telephone companies, for instance, were once solid and static entities that dominated the communication market. While the rest of the world was developing new communication technology, telephone companies did not creatively grow at the same rate. The result is an organization that is battling to stay alive unless they embrace the element of chaos due to crisis, and allow creative adaptability to function freely so that self-organization and re-invention can occur.
Viewing an atom as a complex system in itself, and magnifying the interactional effects of sub-atomic particles and waves to reflect the interactions of different elements making up a complex system, such as an organization, assists us in seeing parallels between quantum physics (namely chaos theory) and organizational relationships. What must be pointed out, however, is that these “parallels” between organizations and the sub-atomic particles exist largely in terms of analogy (metaphorically) between two very different domains of activity; the interactional effects of sub-atomic particles, in quantum mechanics, are expressed in terms of math; bringly these theories into the domain of human activity can be seen as problematical. Although these parallels are easily witnessed in regard to complex organizational systems, it is difficult to see evidence of irrational quantum-effects in everyday life. If you roll a ball forward, it rolls forward in the general direction intended. As a whole, Newtonian principles of interaction stand solidly within the bounds of macrophysics. But at the sub-atomic level, things do not act as expected. “At the subatomic level, the objectivity found in classical physics is replaced by quantum subjectivity.” (Shelton, 2003) The introduction of chaos theory brings the principles of quantum physics to the pragmatic world. These complex systems have a rather random appearance and, until recently, have been labeled and discarded as chaotic and unintelligible. With the advent of computer systems and powerful processors, it has become easier to map chaotic behavior and find interesting underpinnings of order. The newly discovered underlying order to chaos sparked new interest and inspired more research in the field of chaos theory. The recent focus of most of the research on chaos theory is primarily rooted in these underlying patterns found in an otherwise chaotic environment, more specifically, concepts such as self-organization, bifurcation, and self-similarity.
 Elements of organization
Self-organization, as opposed to natural or social selection, is a dynamic change within the organization where system changes are made by recalculating, re-inventing and modifying its structure in order to adapt, survive, grow, and develop. Self-organization is the result of re-invention and creative adaptation due to the introduction of, or being in a constant state of, perturbed equilibrium. One example of an organization which exists in a constant state of perturbation is that of the learning organization, which is “one that allows self-organization, rather than attempting to control the bifurcation through planned change.” (Dooley, 1995) Being “off-balance” lends itself to regrouping and re-evaluating the system’s present state in order to make needed adjustments and regain control and equilibrium. By understanding and introducing the element of punctuated equilibrium (chaos) while facilitating networks for growth, an organization can change gears from “cruise” to “turbo” in regard to speed and intensity of organizational change. While maintaining an equilibrial state seems to be an intuitively rational method for enabling an organization to gain a sense of consistency and solidarity, existing on the edge of a chaotic state remains the most beneficial environment for systems to flourish develop and grow.
For instance, two competing organizations that differ in regard to their levels of homeostasis will not be in competition for long. Generally speaking, the organization with the less-stable structure will come out ahead while the constant stability of the latter will eventually lead to its own demise. Although quite similar, small differences in homeostasis levels are enough to make a tremendous difference in future outcomes for each organization. The notion of similarity in origin vs. dissimilar results comes to fruition with the emergence of bifurcation.
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