How the understanding of complexity leaders aids leadersIntroductionA deeper understanding of the key concepts embedded in complexity science generates an understanding about the dynamics and processes of change that are found in various biological and physical phenomena. Complexity science is described as a collection of prepositions, principles and ideas, most of which have been shaped by other fields of knowledge. It addresses characteristics of the living systems that are understated or neglected in the traditional approaches. It is apparent that most of the challenges that we face in the contemporary world have been largely influenced by the escalating complexities (Westley et al. , 2006).
For instance, the continuing innovations in information and communication technology are enlarging the scope and connectivity of the current engineered systems. However, managing the resulting complexity is major challenge for many industries and governments (Chapman, 2004). In essence, the whole concept of complexity is not new, but what is considered new is the fact that contemporary leaders are required to make informed decisions in the faster paced world, and increase adaptability to turmoil, globalization and knowledge breakthroughs (Warner, 2000).
Furthermore, increased attention is now focusing on how complexity can enable leaders and researchers understand and control economic, political and social phenomena. Such efforts are directed towards ensuring leaders realize the importance of complexity science and how this can be applied when it comes to change management (Westley et al. , 2006). This paper seeks to explore and provide an explanation of the key concepts of complexity science, illustrating the reasons why complexity science is important, and demonstrates how an understanding of complexity science aids leaders. The paper seeks to enhance the understanding about organization and leadership. Key concepts of complexity scienceComplexity science is viewed as a multi-disciplinary subject encompassing subjects such as biology, social science and industrial applications.
However, mathematical modeling and development approaches from physics can be applied to provide a better understanding concerning these systems (Cutler, 2002). Complexity science describes a set of concepts, propositions, principles and ideas that have appeared and clustered together from the beginning of the twentieth century (Gribbin, 2004). It is not a distinct theory, but incorporates more than just one theoretical framework. It is highly interdisciplinary, looking for explanations about fundamental issues concerning changeable systems, adaptations and living (Flynn Research, 2003).
However, concepts of complexity science are classified into three sets. The first concept covers complexity and systems, and applies concepts such as interconnectedness and interdependence within the aspects and dimensions of a system. Gribbin (2004) highlights that complexity is based on interconnections that occur between the simple parts, which in turn make up the whole system. Change is influenced by the feedback processes, and emerges from the interaction of parts in that; the whole change is attributed to the changes that have taken place in the parts.
Feedbacks are vital to the manner in which systems operate, and change in one element of the system always alters the whole system. The second set of concepts regards complexity and change. Complexity in this case is described as nonlinear since it is disproportionate and unpredictable. Feedback processes taking place within the interconnected elements generate relationships that view change as being nonlinear, dynamic and unpredictable. This change is termed as being sensitive to initial conditions such that small differences in a system’s initial state may lead to considerable changes at a later stage.
It is also apparent that complex system exhibit random behaviour and this is often described as chaos and edge of chaos.