Leadership insights harvard business review pdf

An overview of the complexity leadership literature is provided. This includes a history of complexity theory leadership insights harvard business rev

An overview of the complexity leadership literature is provided. This includes a history of complexity theory leadership insights harvard business review pdf its core concepts, the central propositions of complexity leadership, a review of six prominent frameworks, and a summary of practitioner guidelines.

The article also discusses two key limitations to complexity theory: the need to supplement it with other epistemologies and leadership approaches, and the importance of recognizing that its sustained execution likely requires a developmentally mature meaning-making system. The conclusion is that complexity leadership offers a fresh and important way of perceiving and engaging in the management of complex organizational behavior, one which may help leaders to address the most pressing and complex social, economic, and environmental challenges faced globally today. It is based upon the application of complexity theory to the study of organizational behavior and the practice of leadership. In the 1990s, researchers drew from complexity theory studies in physics, chemistry, biology, and computer science to cultivate novel insights about their fields. This article offers an overview of the complexity leadership literature.

To understand complexity leadership requires knowledge of the fundamentals of complexity theory. The first section of this article briefly describes the history and lineage of complexity theory and defines some of the important concepts from it that are applied in the field of complexity leadership. This if followed by a summary of the core concepts of complexity leadership and a review of six complexity leadership frameworks. The article continues with an overview of guidelines for putting complexity leadership theory into practice, and concludes with a discussion of two key limitations to its application. While the entire theory is more complex than this, this definition is useful as it encompasses three fundamental characteristics of complex systems: they involve interacting units, are dynamic, and are adaptive.

Complexity theory developed out of myriad sources, many of which arose during World War II. However, nine main, interrelated research strands form the lineage of its contemporary expression. Each of these traditions offers core constructs that are essential to the overall theory. A full review of complexity theory is beyond the scope of this article, but the following key concepts are explained below, as they are instrumental for understanding complexity leadership: complex vs. For example, computers or jumbo jets are complicated systems. A system is complex if its relationships cannot be explained fully by merely analyzing its components because they are dynamic and changing.

Complexity generates novel features, often called emergent properties. Complex systems incorporate myriad interacting elements. The interactions between these elements are nonlinear and minor changes can cascade into large-scale consequences. Such systems are dynamic, with a whole greater than the sum of its parts. The elements of complex systems evolve with one another, integrating their past with the present, and their evolution is irreversible. Due to the constant fluctuations and changes of external conditions and connected systems, complex systems are not predictable, although they may seem ordered and predictable in retrospect. As such, no forecasting or prediction of their behavior can be made.

This is due to the fact that individual elements and the system itself constrain one another over time. Such mutually constraining behavior is different than in ordered systems in which the system constrains the elements, or in chaotic systems which have no constraints. The structures, dynamic behaviors, and patterns that arise from these complex interactions become unrecognizable when perceived as linear combinations of the initial actors. These interactive behaviors and outcomes ultimately create feedback loops with each other, leading to effects becoming causes and influence arising from extensive chains of effect. Complexity does not refer to static events. While there is global stability and resilience within complex systems and complex behavior, they are fundamentally defined by change.

Adaptation refers to a complex system’s ability to strategically change or adjust in response to individual or systemic pressures. Adaptation arises at two levels, the individual and the aggregate. Individual adaptation concerns local stimuli and individual preferences. Individual adaptations amongst agents in a system can interact with each other, resulting in compromises that simultaneously serve the individual and the collective, thus forming aggregate adaptation. There are certain, universal mechanisms that drive complex dynamics.