Complex Adaptive Systems

Since the mid-1990s, concepts of Complex Adaptive Systems (CAS) have been used to try and explain how organizations work in an increasingly complex world (HIGHSMITH, 2002). Various leaders of the agile movement have based their ideas regarding management on theories that study this type of system. Scrum was created in this context, aiming at the development of complex products immersed in complex environments.

Below are two of the most common definitions for Complex Adaptive Systems:

Complex Adaptive Systems …are systems that have a large numbers of components, often called agents, that interact and adapt or learn (HOLLAND, 2006)

*…*consist of a number of components, or agents, that interact with each other according to sets of rules that requires them to examine and respond each other’s behavior in order to improve their behavior and thus the behavior of the system they comprise. (STACEY, 1996).

Since the behavior of Complex Adaptive Systems is emergent, it cannot be predicted based on a cause-and-effect analysis (“if you do this, that will happen”), nor from an individual inspection of their agents and their properties. That is, for any action, we do not know in advance what its results will be, and not even an understanding or analysis of the details of each of its agents will allow us to infer what will happen to the system as a whole.

Nevertheless, these agents in the system interact with each other, and from these interactions patterns emerge that increase the predictability of the system’s behavior in the short term. These properties of the system arise from the interactions of its parts. Given the absence of centralized control, the agents of Complex Adaptive Systems are self-organized: in frequent feedback loops, the system’s emergent behavior feeds back into itself and provokes an adaptation from its agents and the system as a whole. Hence these systems operate in a state of ordered instability – that is, an order that is emergent, unpredictable, and constantly changing. External stimuli can also provoke this readaptation, which causes the system to evolve and new patterns of behavior to emerge (JAIN; MESO, 2004).

As we will see in detail in this book, there are many elements of Scrum whose parallels can be easily identified in the theories of Complex Adaptive Systems, such as: the frequent feedback cycles, that guide construction of a product and enable the continuous improvement of work processes (inspection and adaptation), the self-managed work teams and the high level of interaction required between the parties involved in developing the product.