![]() ![]() Systems that at first glance seem vastly different-ant colonies, human brains, cities, immune systems-all turn out to follow the rules of emergence. It's a bottom-up model rather than being engineered by a general or a master planner, emergence begins at the ground level. (2001) say, “Emergence refers to a process by which a system of interacting subunits acquires qualitatively new properties that cannot be understood as the simple addition of their individual contributions.” Johnson (1999) says, “Emergence is what happens when an interconnected system of relatively simple elements self-organizes to form more intelligent, more adaptive higher-level behavior. Similarly, fish schooling would not be predicted form the swimming characteristics of a single fish. It is only when several geese fly together that the V-pattern emerges. The V-formation of geese, for example, could not be predicted from the flying characteristics of a single goose. These emergent properties develop as result of the relationships among the system elements or between the system elements and the environment. Emergence Natural patterns are usually emergent-that is, they are properties of the system that cannot be predicted from the properties of the system’s components. Combination physical-temporal patterns include traffic jams, birds flocking, and fish schooling. Temporal patterns are exemplified by predator-prey populations over time, Newton’s cradle, my boss being grouchy every Thursday, and the spawning runs of salmon every autumn. Examples of physical patterns include stripes on zebras, crystals, sand dunes ripples, compound fly eyes, and termite cathedrals. Patterns may be physical, temporal, behavioral, psychological, or some combination. Patterns defines a pattern as a consistent and recurring characteristic or trait that helps in the identification of a phenomenon or problem, and serves as an indicator or model for predicting its future behavior. ![]() Each of these concepts is explained in greater detail in the following sections. Good systems thinkers try to first recognize and then explain patterns by attempting to understand the underlying structures and forces that yield the patterns. To reiterate, natural patterns (often emergent) are caused by self-organized structures (feedback loops, hierarchies) and their underlying forces. There may be unintended consequences of the structures, as well: an unsavory employee may attempt to take credit for work that she did not do in order to increase her own compensation. In a corporation, the underlying mental model that “money motivates employees” results in an incentive compensation structure which, in turn, results in a pattern of excellent performance in some employees. The Iceberg Model for Natural Systems (after Monat and Gannon, 2015a)įor example, the underlying forces of gravity and centrifugal force result in the structure of the solar system, which in turn results in patterns of day and night on planets, the patterns of planetary orbits around the sun, and the patterns of seasons on earth. The Iceberg Model conveniently shows the relationships among events, patterns, structures, and underlying forces (Figure 1).įigure 1. Structures develop because of natural underlying forces in natural systems or because of mental models in human-designed systems. The underlying structures represent the interactions or relationships among system components: the system’s stocks, flows, and feedback loops. The patterns are often emergent, meaning that they cannot be predicted from knowledge of the system components only when those components interact do the patterns emerge. Systems Thinking posits that repeated events or objects represent patterns and that those patterns are caused by systemic structure, which is (in turn) caused by underlying forces. The explanation begins with the Iceberg Model. In this paper, we describe how Systems Thinking can explain a great many natural patterns in the world: why zebras have stripes, why geese fly in a V-formation, why fish school, why the universe looks as it does, and how life began on earth. In those previous works, Monat and Gannon have shown how Systems Thinking can explain and address political and socio-economic issues. It focuses on relationships among system components (as opposed to the components themselves), it is holistic instead of analytic, it recognizes that systems are dynamic and usually include multiple feedback loops, and it acknowledges that systems often exhibit emergent and self-organizing behaviors. Introduction: Systems Thinking According to Monat and Gannon (2015a and b, 2017) Systems Thinking is a perspective, a language, and a set of tools.
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