Complexity Science for Management

Complexity Science for Management
 

Complicated contexts, unlike simple ones, may contain multiple right answers, and though there is a clear relationship between cause and effect, not everyone can see it. This is the realm of “known unknowns.” While leaders in a simple context must sense, categorize, and respond to a situation, those in a complicated context must sense, analyze, and respond.

Understanding Complexity

Complexity is more a way of thinking about the world as advanced by complexity science, as combined with knowledge from the cognitive sciences.  They are transforming the field once again. Complexity is poised to help current and future leaders make sense of advanced technology, globalization, intricate markets, cultural change, and much more. In short, the science of complexity can help all of us address the challenges and opportunities w face in a new epoch of human history.

A complex system has the following characteristics:

It involves large numbers of interacting elements.

The interactions are nonlinear, and minor changes can produce disproportionately major consequences.

The system is dynamic, the whole is greater than the sum of its parts, and solutions can’t be imposed; rather, they arise from the circumstances. This is frequently referred to as emergence

The system has a history, and the past is integrated with the present; the elements evolve with one another and with the environment; and evolution is irreversible. Though a complex system may, in retrospect, appear to be ordered and predictable, hindsight does not lead to foresight because the external conditions and systems constantly change. Unlike in ordered systems (where the system constrains the agents), or chaotic systems (where there are no constraints), in a complex system the agents and the system constrain one another, especially over time. This means that we cannot forecast or predict what will happen.

One of the early theories of complexity is that complex phenomena arise from simplerules. Consider the rules for the flocking behavior of birds: Fly to the center of the flock, match speed, and avoid collision. This simple-rule theory was applied to industrial modeling and production early on, and it promised much; but it did not deliver in isolation. More recently, some thinkers and practitioners have started to argue that human complex systems are very different from those in nature and cannot be modelled in the same ways because of human unpredictability and intellect. Consider the following ways in which humans are distinct from other animals:

They have multiple identities and can fluidly switch between them without conscious thought. (For example, a person can be a respected member of the community as well as a terrorist. They make decisions based on past patterns of success and failure, rather than on logical, definable rules.

They can, in certain circumstances, purposefully change the systems in which they operate to equilibrium states (think of a Six Sigma project) in order to create predictable outcomes. Leaders who want to apply the principles of complexity science to their organizations will need to think and act differently than they have in the past. This may not be easy, but it is essential in complex contexts

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