Command and Control (C2)

Command and Control (C2)

How can technologies and systems enable organizational agility and adaptation? How can technologies and systems prevent agility and adaptation?

In the information era, rapid technological changes, extensive globalization, and intense competition have created significant pressures on organizations. The agile organization is an appropriate alternative to the bureaucratic model under these conditions. When building an agile organization, one of the most essential issues is how to build an organization that can respond rapidly to the changing business environment. Organizational researchers have long recognized the value of formal models- mathematical, logical, computational - for examining organizational behavior in general and organizational adaptation in particular. However, it is still challenging to identify the organizational adaptation and examine the optimal organizational structure that adapts to the environment change.

Research into organizational adaptation is a complex issue because the relationships are intricate, multiple participants are involved in multiple interactions over time and interactions are nonlinear. Nonlinear phenomena, with their feedback loops, are difficult to study with the classical inductive case methods or with standard statistical techniques. Furthermore, these phenomena are becoming of increasing academic interest as theoretical developments move from cross-sectional and equilibrium perspectives to dynamic ones. Additionally, networks composed of multiple agents are inherently computational since they have a need to scan and observe their environment, store facts and programs, communicate among members and with their environment, and transform information by human or automated decision making. (Weick 1993, p. 20)

Consequently computer-based simulation can be used for theory development and hypothesis generation. Simple, but non-linear processes often underlie the team and group behavior. Computational analysis enables the theorist to think through the possible ramifications of such non-linear processes and to develop a series of consistent predictions. Simulations are also particularly valuable when we seek to explain longitudinal phenomena that are challenging to study using empirical methods because of their time and data demands.

With computational models, Carley found that organizations often alter their structure in response to their performance, however, altering the organizational structure in response to minor shifts tends to limit organizational performance (Carley 1995, p.88). Carley (1995) and Lee also found that change is more important than the amount of change, if organizations are to be adaptive. In this research, performance was used as an indicator of the effectiveness of the change or adaptation. If performance degraded after the change, the change was not considered an adaptation. Additionally, focusing on military C2 (Command and Control) structural adaptation, Carley and Lee developed a computational model tool that is suitable for analyzing the impact of different types of organizational learning on the organizational adaptation (Carley and Lee 2004, p.74). Carley and Svoboda also applied a simulated annealing algorithm to find the optimal organizational adaptive structure, which is represented by span of control and size. (Carley, and Svoboda 1996, p.32)

Particularly, agent-based simulations can give insights into the 'emergence' of macro-level phenomena from micro-level actions, and enable examination of how sensitively the simple local rules affect the final results using sensitivity ...