- Disruptive Technologies
- High Change
- No Silver Bullet
- Are Organizations True Complex Adaptive Systems?
- Requisite Variety
- Project Ecosystems
- Simplicity and Complexity
- Summary
This chapter is from the book
This chapter is from the book
This chapter is from the book
Are Organizations True Complex Adaptive Systems?
Good managers fail because their management practices were developed to solve complicated problems, but their problems are much more than complicated; they are complex.
Altering fundamental assumptions about how organizations and projects should be managed is a difficult assignment. By using the theory of complex adaptive systems to help convince managers of better solutions for their problems, we move closer to accomplishing our goal, but it also forces us to analyze whether or not organizations are, in fact, complex adaptive systems, or whether CAS is merely a useful metaphor.
Ralph Stacey’s compelling argument that organizations are complex adaptive systems begins with an analysis of the properties of non-linear deterministic networks, which underlie much of the chemical and physical world. According to Stacey, analysis of these physical, deterministic systems has shown that self-organization and emergence occur under certain conditions. Stacey maintains that even if organizations were as deterministic as these physical realms, “[W]e can get such a system to do what we want only if what we want is an endless repetition of what it has already done” (Stacey96, p. 71). Predictability, even in deterministic systems, isn’t as predictable as we may think.
Stacey continues his point by detailing the characteristics of complex adaptive systems, which he differentiates from deterministic systems by the addition of a purpose. A deterministic system (for example, a chemical reaction) has no purpose or goal, but even the simplest living system has a goal (to live or to reproduce, for example) and a set of internal rules of behavior it uses to achieve that purpose. Stacey identifies the general features of complex adaptive systems that are shared by human systems. These were first identified in Chapter 1, naming a complex adaptive system as an ensemble of independent agents,
- who interact to create an ecosystem,
- whose interaction is defined by the exchange of information,
- whose individual actions are based on some system of internal rules,
- who self-organize in nonlinear ways to produce emergent results,
- who exhibit characteristics of both order and chaos, and
- who evolve over time.
The final building block in Stacey’s carefully constructed case is his identification of the characteristics that differentiate human systems from other CAS, and his analysis of whether those differences invalidate the comparison. He contends that the primary difference is a human’s internal structure—consciousness, emotions, and self-awareness—which makes humans and their organizations complex and, therefore, good examples of complex adaptive systems.
Stacey concludes that organizations and the individuals who compose them are, in fact, complex adaptive systems. What we learn about CAS topics such as emergence, nonlinear networks, self-organization, interactions in ecosystems, and adaptability is, therefore, perfectly applicable to how we manage complex adaptive organizations. The Adaptive Management Model and, in fact, Adaptive Software Development in its entirety are built upon this premise.