Complex Adaptive Systems

Conceptual Overview

The field of organization studies regularly sees new theories emerge to a fanfare. The promise is usually that some new theoretical perspective will shed light on key problems and will help us to understand our organizations anew. In recent years, theories explaining the behavior of complex adaptive systems (CAS) have attracted just such attention. Devotees of this new theoretical perspective argue that we should accept that organizations exhibit many (or all) of the features of CAS and that radical insights flow from this observation. This short contribution seeks first to place CAS theory in context, and then to discuss the potential benefits and limitations of studying organizations as CAS.

The recent emergence of CAS theory can be traced back to the development of systems theory in the 1940s and 1950s. Starting from general systems theory, some argued that particular types of systems displayed properties that might be described as complex. It is important to be clear about the language employed here: A complex system is not the same thing as a system that is complicated. A complicated system may [Page 224]involve many, many components that interact in simple ways.

A complex system is usually described as being composed of a large number of interacting components. While the interactions of individual components may be simple or complicated, the combined effect of the interactions render issues such as prediction or control problematic. Hence, the system is complex in that one cannot tell what will happen as the system's behavior unfolds over time. The science of complexity theory (and the related but distinct field of chaos theory) developed around the study of such systems in fields as diverse as chemistry, biology, laser physics, zoology, and economics.

Significant breakthroughs began to occur in each of these fields when researchers began to discover what David Bohm calls “implicate order.” A commonly cited illustration is the flocking behavior found in some species of bird. The behavior of a large flock of birds may be described as complex because it is generated through the densely interconnected interactions of many hundreds or thousands of birds. Nonetheless, these interactions produce emergent patterns that are not controlled by any individual bird, though they are observable as the flock swoops back and forth avoiding things like buildings, trees, or predators. Researchers noticed that one could produce such outwardly complex behavior using a very simple set of instructions or order-generating rules:

Rules of Flocking

• 1.
  Follow the bird directly in front of you.
• 2.
  Remain equidistant from the birds on either side of you.
• 3.
  Match the velocity of the birds around you.

Searching the Internet for the word “boids” will direct you to sites that offer computer simulations that use these, or similar, rules to reproduce complex behavior. Each individual bird is interacting locally with a limited number of other birds in its immediate vicinity. Collectively, however, the flock portrays complex and emergent behaviors. Scholars became excited at the revelation that seemingly complex behaviors could be generated from such simple algorithms.

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