System theory terms and concepts

Copyright 2017 Graham Berrisford. One of about 300 papers at Last updated 27/11/2017 18:00


Systems thinkers use the terms of system theory with a variety of meanings, and it isn’t always clear what they mean.

This paper offers a coherent and consistent set of definitions – to help you understand and explain system theory concepts.

This glossary is “a controlled vocabulary” or “domain-specific language” rather than a general-purpose dictionary.

It labels system theory concepts using words found in systems thinking discussions; in other contexts, the same words may have different meanings.

If you adopt any definitions from this glossary, please link to this web page.


Read Introducing General System Theory for a deeper exploration of what follows in the context of system theory history.


Descriptions. 1

Systems. 2

System boundary and information. 4

System structure and behaviour 5

System change. 6

Social systems, social entities and social cells. 7

Footnote 1: on easily-confused terms. 7

Footnote 2: on the structure/behaviour dichotomy. 8

Footnote 3: on the description/reality dichotomy. 9



Description: a memory, message, model or view that captures/encodes knowledge of a thing’s properties.

It enables that knowledge to remembered and/or communicated.

It enables some questions about the described thing to be answered.


Name: an identifier or label for a thing whose properties can be described.

To those familiar with a description, a name serves as a short-hand for that description.


Reductionist view: identifying the parts of a whole, naming or describing parts without considering how the parts are related in the whole.

E.g. listing the organs and limbs of the body without relating them. Or analysing and describing the heart without reference to the lungs.


Holistic view: a description of how parts relate, interact or cooperate in a whole.

E.g. a description of how the muscles of the human heart interact.


Organicism: the idea that systems are describable at multiple hierarchical levels (as named by von Bertalanffy).

E.g. Consider the decomposition of a human body through organ, cell, organelle and molecule to atom.

Or the decomposition of software application through component, class and operation to executable instruction.


Emergent property: a behaviour or structure of a whole that depends on interactions between its parts.

E.g. the forward motion of a cyclist on a bicycle, or the V shape of a flight of geese.

Typically, the property is not found in any one part, or predictable by studying a part in isolation from others.

The exception is systems with homogenous populations, where a subset of the whole may have the same properties as the whole.

(Note that emergent properties are the very purpose of system design.)


Atomic element: an element that is not further divided in a description.

E.g. An organ is an atomic actor in a description of the human body.

A human is an atomic actor in a description of a society.

A note is an atomic activity in a musical score.

“Enter start and end stations” may be an atomic activity in a description of booking a train seat.


Note that atomic system actors (living or non-living) may be complex entities in their own right, and may play roles in other systems.

This system

has atomic actors

that perform behaviors

The solar system

sun and planets


An email system


executable instructions in source code

A human activity system


steps in work procedures

A beehive


deliver pollen, perform and observe wiggle dances

A predator-prey system

wolves and sheep

eat sheep, eat grass

The global ecology

animals and plants

transform oxygen into carbon dioxide, and vice-versa


“At this point we must be clear about how a "system" is to be defined.

Our first impulse is to point at [an object repeating a behavior] and to say "the system is that thing there".

This method, however, has a fundamental disadvantage: every material object contains no less than an infinity of variables and therefore of possible systems.

Any suggestion that we should study "all" the facts is unrealistic, and actually the attempt is never made.

What is necessary is that we should pick out and study the facts that are relevant to some main interest that is already given.” (Introduction to Cybernetics (1956) W. Ross Ashby)

In other words, the system is not the reality; it is a role we can describe the reality as playing.


System: an overloaded term; a catch-all term used to label passive structures and activity systems.

Also abstract (theoretical) system descriptions and concrete (empirical) systems.

Commonly used to mean a concrete activity system.


Passive structure: an element or group of related elements that may be acted on, but do not act.

E.g. a table, a data item, a data structure, the Dewey decimal system, an abstract system description.

Activity system (aka System): a structure whose elements interact (directly or indirectly) in regular behaviors.

A thing whose regular or repeatable activities act to maintain the state of the thing and/or reach other goals.

E.g. the solar system, an organism, a software system, a choir, a tennis match.


Abstract system description: a description or model of a concrete system.

E.g. a physical model, a narrative, a context diagram, a network diagram, a causal loop diagram, or a combination of such artifacts.

Concrete system (aka System): a system that runs in reality.

A realization in physical matter and/or energy of an abstract system description.

A real world entity that can be tested as meeting an abstract system description – well enough.

(Note that one real world entity can realise many different abstract systems.)


This table illustrates how a concrete entity realises (or instantiates) an abstract system description (or type).

Abstract system description

“Solar system”

Laws of tennis

The score of a symphony

The roles in a radio play

Concrete system realisation

Planets in orbits

A tennis match

A performance of that symphony

Actors playing those roles


Natural system: a system that runs before it is described by man.

Its repeated behaviors evolve without externally-defined drivers or goals.

E.g. a solar system, weather system or biological organism.

Designed system: a system described by man before it runs.

Its reproducible behaviors are defined in response to externally-defined drivers or goals.

E.g, a cuckoo clock, a motor car, an accounting system, a choir, a tennis match.

System boundary and information

System environment: the world outside the system of interest.

The environment of one system may be a wider system.

The environment of a business system is sometimes called its market.


System boundary: a line (physical or logical) that separates a system from is environment

It encapsulates the system’s internal structures and behaviors.


System interface: a description of inputs and outputs that cross the system boundary.

An interface defines the system as it is seen by external observers.

An interface may be defined in a contract defining services provided or required.

In social and software systems, the primary inputs and outputs are information flows.


Information: a meaning created or found by an actor in any physical form that acts as a signal.

Any description or direction that has been encoded in a signal or decoded from it by an actor.


Signal: any structure of matter or energy flow in which an actor creates or finds information.

In human communications, the physical forms include brain waves and sound waves.

In digital information systems, the physical form is a data structure in a binary code – in matter or energy.


Information flow (aka message): physically, a signal passed from sender to receiver, logically, a communication.

Information state (aka memory): see “state”.

Information quality: an attribute of information flow or state, such as accuracy, speed, throughput, availability, security, monetary value.


Information feedback loop: the circular fashion in which input flows influence future output flows and vice-versa.

Brains and businesses can both be seen as information systems.

Both maintain a monitor-direct feedback loop with their environment.

·         They detect events and changes in their environment - via input information flows.

·         They remember the entities and events they monitor - in an internal model or information state.

·         They send messages to direct those entities and events.

If the system does not monitor and direct entities and events in its environment – well enough - then it expires or is changed.

System structure and behaviour

The structure/behaviour dichotomy:.structures exist in space; behaviors happen over time.

Structure: passive structures and actors in space

Behavior: atomic actions and processes over time

Structures that are shaped or directed by behaviors.

Entities that are created, changed and destroyed by Events.

Stocks that are incremented and decremented by Flows.

Components that perform Processes and deliver Services.

Behaviors that are performed by structures.

Events that create, change and destroy Entities.

Flows that increment and decrement Stocks.

Processes performed and Services delivered by Components.


Footnote 2 extends the table above with definitions adapted from the Unified Modelling Language (UML) standard.

And adds further discussion of the structure/behaviour dichotomy.


State: the current structure of a thing, as described in values of its variable properties.

An entity’s concrete state is directly observable in the values of its physical position, energy and material variables.

E.g. the location, temperature, colour, and matter state (solid/liquid/gas) of a thing you see in front of you.

Information state is found in the values of descriptive variables held in a memory or database of some kind.


Event: a discrete input that triggers a process that changes a system’s state, depending on the current state.

(Note: this is the basis of modelling a system using discrete event dynamics and system dynamics.)

(Note: information systems also consume enquiry events that report current state.)


Process: one or more state changes over time, or the logic that determines which state changes lead to which other state changes.

A process may be directly observed in changes to the state of the world.

E.g. an apple falls from a tree; a cash payment is handed by one actor to another.

In the abstract, a process is a description or specification of discrete or continuous state change.

E.g. a flow chart showing the control logic governing event-triggered activities that result in discrete state changes.

E.g. mathematics describing the continuous change to the position of a planet in its orbit.


Hysteresis: the process by which a system’s information state can be derived by replaying all events that have so far crossed the system boundary.


Deterministic: the quality of a system that means its next state is predictable from its current state and input event.

Stochastic: the quality of a system that means its next or future state is not predictable, and appears random.

(Note that what is describable as a deterministic system can appear stochastic over the long term.)


Linear change: progress or change over time that is represented in a graph as a straight line (or else a regular shape).

Non-linear change: progress or change over time that is represented in a graph as a curve (or else an irregular shape).

(Note what you model as deterministic can behave in a non-linear way over the long term.)


Complex: a term that implies complicated in some way, but for which there is no agreed measure.

The only way to measure the complexity of a system is by reference to a description of it structures and behaviors.

But scores of complexity measures have been proposed.

The term complex is sometimes used to mean a non-linear or stochastic system.

But simple deterministic systems can behave in non-linear or stochastic ways.

System change

This complex topic is explored elsewhere; this section is only a brief distillation of key terms and concepts.

System adaptation: a change to the state of a system, which changes the value of at least one variable.

System transformation: a change to the nature of a system, which changes the type of at least one variable or behavior.

“The distinction is fundamental and must on no account be slighted.” Ashby (1956)


Meta system: a system that defines a system or transforms it from one generation to the next.

Meta systems include biological evolution, which depends on the process of sexual reproduction and DNA to define and change an organic system.

And those human actors who perform processes (as in an analysis and design methodology) to define and change a designed system.


These two triangles may help to explain the relationship of a meta system to a system.

Meta system


System architect role

<define>               <idealises>

Methodologists  <observe and envisage> Architects

System roles

<define>                        <idealise>

Architects  <observe and envisage>  System actors


Read Stability and change in entities and systems for a longer discussion of system change and more system change varieties.

Social systems, social entities and social cells

Social system: a system in which animate actors play roles in regular, repeatable processes.

E.g. bees collecting pollen for a beehive; an orchestra’s performance of a symphony.

The symphony score is a system description; every performance of that symphony instantiates that system description in reality.


Social entity: a group of actors who may chose their own behaviors, and may interact to reach agreed aims.

E.g. the group of actors hired to play in an orchestra, who may agree to hold a party after the performance.

Since the roles and rules of a social entity are adhoc and in flux, it cannot be described and tested as matching that description.


System theory is primarily about the roles in the symphony (the system).

Some systems thinking is more about the social entity - the actors in the orchestra, and their motivations.

A social entity may succeed in meeting goals, of its actors or sponsors, despite the roles and rules of a system in which the actors work.

But the ideal business is a social entity in which actors work happily in the roles of whatever system those actors are hired to work in.


Social cell: a social system whose roles reward the actors of a social entity sufficiently well to ensure the actors voluntarily perpetuate the system.

In other words, there is a symbiotic relationship between the roles of the social system and the actors of the social entity.

E.g. regular choir rehearsal meetings, a tennis club, and Japanese tea ceremonies.

Reward examples include hope, comfort, endorphins and money.

The very idea of a particular social cell may be so appealing that other actors, who hear of it, may replicate it (cf. Dawkin’s “meme”).


Read Social cells for discussion of a social cell as mutually beneficial, or insidious, or even as a parasite on society.


A few social/business-specific terms.

Enterprise: has several meanings; usually implies a business led by executive managers/directors or a segment thereof.

Organization: generally, a structure in which elements are related; often, a structure in which human roles of enterprise are related; it usually implies lines of command and control.

Management system: generally, a system that monitors and directs an entity; often, one that monitors and directs the operational systems of an enterprise.

Team: generally, a group of actors who interact; sometimes a node in an organisation structure; sometimes a group dedicated to the completion of a behaviour (a project or task).

Capability: a notoriously ill-defined and variously-defined term, perhaps most easily distilled as: “business function + goals + resources”.


Footnote 1: on easily-confused terms

In systems thinking discussions, the following pairs of terms are often confused; but strictly, each pair represents two distinct concepts.


Holistic versus Systemic

Holistic: considering how the parts of a whole are related; taking a view that addresses how parts cooperate to the benefit of the whole.

See also:

Systemic: relating to the whole rather than a part; reaching throughout the whole, pervasive throughout a system.

(E.g. A systemic drug or disease that reaches and has an effect on the whole of a body.)

See also:

To be holistic isn’t the same as being pervasive throughout a system.


Reductionism versus Analysis

Reductionist view: identifying the parts of a whole, naming or describing parts, without considering how the parts are related in the whole.

Analysis: dividing a whole into parts, which can at the same time reveal how the parts are related in the whole.


Analytic(al) versus Systematic

Analytic (aka analytical): using or skilled in using analysis; separating a whole (description or reality) into parts or basic principles.

See also:

Systematic: methodical, acting according to a fixed process or system.

See also:

You may be analytical in a systematic way; but you may be systematic without analysing anything.

Footnote 2: on the structure/behaviour dichotomy

The structure/behaviour dichotomy:.structures exist in space; behaviors happen over time.

The table below has a natural language section, followed by a section adapted from the Unified Modelling Language (UML) standard.

Structure: passive structures and actors in space

Behavior: atomic actions and processes over time

Structures that are shaped or directed by behaviors.

Entities that are created, changed and destroyed by Events.

Stocks that are incremented and decremented by Flows.

Components that perform Processes and deliver Services.

Behaviors that are performed by active structures.

Events that create, change and destroy Entities.

Flows that increment and decrement Stocks.

Processes performed and Services delivered by Components.

Structure - along the lines defined in UML

Behavior - along the lines defined in UML

A structural entity may be an active actor (with a thread of control) or a passive object.

Actors respond to messages generated by actors performing communication actions.

All behavior is triggered by and composed of actions performed by actors.

An actor instantiates an entity type/role by performing the behaviors of that type/role.

An action is the atomic unit in the specification of behaviour.

An action converts a set of inputs and into a set of outputs.

Repeatable behaviors are often modelled as discrete event-driven processes.

The time between events can small enough to simulate continuous behaviors.


The universe may be viewed as ever-unfolding processes.

And the structures within it viewed as results of those processes.

E.g. Stars and planets can be seen as side effects of gravitational forces.


A biological entity maintains itself cyclically by what is called autopoiesis.

The processes are performed by structural elements.

The structural elements are manufactured and maintained by processes.


A designed activity system may be viewed as a set of designed processes.

And some structures within it may be manufactured by those processes.

However, we must hire or build active structures (actors/components) to perform designed processes.

E.g. hire musicians to perform the parts in a symphony.


(It is wrong to think of people (hired to play roles) as parts of a designed system.

The parts are performances of system roles by people.

The people live outside of any system they play a role in, and are much more than any role they play.)


Natural systems and analogue designed systems are continuous; time is not divided into units.

Most business systems are discrete event-driven, meaning that every process is triggered by an event.

The event may carry some input data, or may be only a trigger; it can be a time unit event.


In practical systems analysis and design it is normal to distinguish processes from systems.

A system has persistent structure (describable in a network or data flow diagram) in which actors perform processes in parallel.

A process is an event-triggered behaviour (describable in simple flow chart) that runs from start to end over time.

Footnote 3: on the description/reality dichotomy

Systems thinking discussions use terms like “holistic”, “linear” and “complex” with a variety of meanings.

It isn’t always clear whether they are discussing a description or a reality.


Abstract system description and concrete system

“Perfect” is a descriptive attribute known only to humans.

We don’t require that a performance of a Beethoven symphony matches his musical score perfectly.

It need only be good enough to satisfy us, and if the conductor sneezes, we don’t regard that as part of the symphony.

We don’t require that all the data in an enterprise database matches the reality it describes perfectly.

It need only be accurate enough for a business to monitor and direct real-world entities well enough.

We don’t require that every concrete activity system matches an abstract system description perfectly.

It need only pass system testing well enough.

Description and reality

Abstraction system descriptions

<create and use>                       <idealise>

System thinkers <observe & envisage> Concrete activity systems


However, software systems are perfect in the sense that, at run time, they can do only what is described in their code.


Linear description or linear reality?

Some interpret linear differently from above; they to mean nothing more than “sequential”.

What we say or write must be presented sequentially; the reality we describe may or may not be sequential.

We might teach, sequentially, the sequential process for making a hamburger.

We might teach, sequentially, the multi-level and multi-faceted whole that is the US constitution.

US government system

US constitution

<amends>                    <idealises>

Constitutional convention <observes & envisages> US governments


The US constitution is a linear document; the reality it describes is complex network of government bodies.


Complex description or complex reality?

Every hamburger, every real-world US government, is infinitely complex.

But the recipe for a hamburger, and the US constitution are relatively simple abstract system descriptions.

(Probably much simpler than the code of software applications you use.)

Where and in so far as it realises the US constitution, a US government can be called a system.

But most of the time, government actors are choosing and performing activities in ad hoc ways not explicitly described in the constitution.

As a social entity, the US government is infinitely complex; as a system it is relatively simple.



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