Glossary

It refers to the organizational pattern of non-living systems or machines. An allopoietic system is defined by the fact that its operational network produces something that is not the system itself. For example, a factory is an allopoietic system because it produces cars, which are products external to the factory’s own structure. Allopoietic systems are maintained and defined by external agents, unlike living systems.

The strategy of increasing the number of responses or capabilities available to the control system (making the manager more complex).

The active process by which a system, especially a living one, takes in energy and information to organize itself and resist its own natural decay into disorder.

Archetype dynamics refer to the behavior that a system’s structure creates over time. It is the story of the archetype, and you can see it on a graph that shows how different parts of the system change. While the structure is the “why” of the problem, the dynamics are the “what” you see happening in the real world.

The archetype structure is the specific arrangement of reinforcing and balancing loops that form the blueprint of a systems archetype. It is the reason a system behaves the way it does. You can visualize a structure with a causal loop diagram, which shows how all the variables in the system are connected and influence one another.

The strategy of reducing the number of challenges or complexities coming from the system being controlled (making the system simpler).

Its, meaning “self-creation,” defines the organizational pattern of all living systems. An autopoietic system is one whose components constantly interact in a network to produce and replace the very components that constitute the system itself. This process creates a structural and organizational closure, where the system’s entire purpose is dedicated to maintaining its own identity and continuation, distinguishing it fundamentally from non-living machines.

A balancing loop is a self-correcting cycle that works to bring a system back to a stable state or a specific goal. It is a force that resists change and tries to keep things in check. Think of a car’s cruise control system; when the car goes a little too fast, the system automatically slows it down to get it back to the set speed.

A Behavior Over Time (BOT) graph is a graph that shows how a problem or a variable in a system changes over time. These graphs are a useful tool for understanding archetype dynamics. They can help you see if a problem is getting worse or better, and if it is getting worse quickly or slowly.

A common economic phenomenon where small changes in customer demand at the retail end are amplified into massive, disruptive swings in orders up the supply chain due to accumulating time delays.

A causal loop diagram is a tool used in Systems Thinking to visualize a system’s structure. It uses arrows to show how different elements in a system affect each other. A “Causal Loop Diagram” is a graphical representation of the system.

A system characterized by a large number of interconnected variables, nonlinear relationships, and significant time delays, making its behavior difficult to predict and control. Examples include an ecosystem, a large city, or a global economy.

The field of study concerned with the principles of control and communication based on feedback loops, in both living systems and machines. The name comes from the Greek word for “steersman.”
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A paradoxical communication pattern where a person is trapped between two conflicting demands from a powerful figure and cannot comment on the conflict or escape the relationship.

A specific communication paradox identified by Gregory Bateson, consisting of two contradictory messages (one verbal, one non-verbal) delivered by an authority figure that cannot be escaped or commented upon. This structure creates systemic paralysis in the receiver because any response to one command automatically violates the other command, making correction impossible.
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This is the principle that a complex system exhibits properties or behaviors that cannot be explained or predicted by analyzing the system’s individual parts alone. These properties are not present in the individual components but arise entirely from the interactions, connections, and relationships among those components. A classic example is consciousness, which is an emergent property of a network of simple, non-conscious brain cells.
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This refers to the specific, complex characteristic that arises from the collective interaction of simple parts. It is a feature of the system as a whole. For instance, the intricate navigation patterns of an ant colony or the ability of a neural network to recognize images are emergent properties. They represent the complexity created by the relationships rather than the inherent complexity of the single elements.

The universal tendency for all physical systems to move toward disorder, randomness, and breakdown. It is a measure of the disorder within a system.
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The mechanism by which a system monitors its output and adjusts its input to achieve a goal. It is the central concept of Cybernetics.

The lack of a clear, fixed edge of a system. Complex systems often have fuzzy boundaries because they are constantly interacting with their environment, making it difficult to separate internal causes from external influences.

The self-regulating process by which a complex system maintains stability while adjusting to constantly changing external conditions.

Ashby’s fundamental theorem stating that for a controller to manage a system effectively, it must have at least as much variety (complexity, number of responses) as the system it is trying to control.

In the context of Systems Thinking, the act of identifying and changing a fundamental mental model is considered the highest point of leverage, leading to the most profound and lasting change in the system’s behavior.

A place in the system where a small action can lead to a large, lasting change. Due to complexity, these points are often not obvious and are usually far away from the symptom of the problem.

The leverage point is the single most important place in a system where a small change can have a big, positive effect on the whole system. When a problem keeps coming back, it means that the easy solutions are not working. A true, lasting solution requires you to find and change the leverage point.

A deeply held set of assumptions, beliefs, and images that shape how an individual or group understands the world and takes action. They are the ‘maps’ in our minds that guide our decisions.

A system, either biological (the brain) or artificial (AI software), composed of many interconnected, simple processing units (neurons or nodes) that work collectively. As shown by McCulloch, complex functions like thinking and learning are emergent properties that arise from the network’s structure and the flow of signals through its vast web of simple connections.

In Systems Thinking, a paradox is a statement or situation that is self-contradictory but seems true or reasonable. A communication paradox like the Double Bind occurs when the rules of communication force a system into an unstable state by presenting a logical contradiction that cannot be resolved within the existing structure.

A reinforcing loop is a powerful cycle that makes a change happen faster in the same direction. It is a self-growing process that can lead to either rapid growth or a rapid collapse. Think of it as a snowball rolling downhill — the more it rolls, the bigger it gets, which makes it roll even faster.

An anthropological concept for a self-intensifying process (a positive feedback loop) in which the actions of one group cause the continued, escalating opposition of another group, leading to social division.

Systems Archetypes are classic “stories” or common patterns that repeat themselves in many different situations, from a company’s struggles to a person’s personal habits. They are one of the most powerful tools in Systems Thinking because they act as a kind of shorthand. Instead of trying to figure out a new problem from scratch, you can look at its behavior and match it to a known archetype.

The Systems Hierarchy is a framework developed by Kenneth Boulding that organizes all known systems into a series of nine levels of increasing complexity. These levels range from static frameworks (like a map) up to transcendental systems (dealing with the unknown).

Systems Thinking is a way of looking at the world that focuses on recognizing the connections between different parts of a system. Instead of viewing problems as isolated events, you see them as part of a larger, interconnected web. This approach helps you understand how actions in one part of a system can cause unexpected consequences in another, and it moves the focus from blaming individuals to understanding the underlying patterns and structures.

Transcendental Systems represent the ninth and most complex level in the hierarchy. This level deals with the areas of knowledge that are currently unexplained or reserved for ultimate, absolute truths.

The ability of a system to maintain its desired state or survive a severe shock by radically changing its own internal structure and connections.

A mental model that operates automatically without the person being fully aware of it. These beliefs are often the strongest drivers of system-level failure because they are never questioned.