Introducing system terminology

Copyright 2016 Graham Berrisford. One of about 300 papers at Last updated 12/03/2018 11:02


The role of enterprise architects is to observe baseline systems, envisage target systems, and describe both.

So, you might assume their profession uses a controlled vocabulary of system concepts; but not so.

This paper defines terms introduced in Introducing system ideas and adds some more.


Preface. 1

Systems. 3

System boundary. 4

Interactions between system actors. 4

System structure and behavior 5

System stability and change. 6

Natural systems and designed systems. 7

Social systems, social entities and social cells. 8

Conclusions and remarks. 9

Footnote on behaviors. 10



The general systems movement was started by Ludwig von Bertalanffy and others including William Ross Ashby and Anatol Rapoport.

“The systems movement took hold in post-war America with the convergence of ideas drawn from biology, systems engineering, cybernetics and sociology.

Biology, with its evolutionary emphasis, contributed the ideas of emergence and hierarchy among and within living systems.

Systems engineering contributed the “hard systems” approach to problem solving that grew out of… trying to develop weapons and logistical systems during WWII.

Cybernetics introduced the idea of control through information (feedback) in operational systems.” Bausch (2001)


Understanding systems involves drawing three distinctions.


Structures and behaviors within a system

Structures (actors, components, animals or machines) perform behaviors.
Understanding the structural roles played by actors is part of understanding a system.

The individual actors may come and go; and understanding individual animals or machines is different from understanding a system they play a role in.


This table distinguishes structures and behaviors.


Structures in space

Behaviors over time

Actors (active structures) who perform activities.

Passive 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 respond to service requests and perform processes.

Activities in processes performed by actors

Behaviors that are performed by active structures.

Events that create, change and destroy entities.

Flows that increment and decrement stocks.

Services delivered and processes performed by components.

Along the lines defined in UML

Along the lines defined in UML

A passive object, or an active actor with a thread of control.

Actors respond to messages generated by actors that perform 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.

Actions, and sequences of actions in longer behaviors.

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


Natural and designed systems

A natural system has evolved without any intent, though some may speak of its accidental outcomes as its aims.

A designed system was created by intent; so, it can be tested by comparing its outcomes with its aims.

If it ain’t described before it exists, then ain’t designed.


Abstract and concrete systems

Ashby was keen we separate abstract system descriptions from physical entities that realise them.

This triangle represents the idea more graphically.


System theory

Abstract systems

<form>                        <idealise>

Systems thinkers <observe and envisage> Concrete systems


We can model the state of the solar system in terms of variables whose values can be measured (e.g. the positions of the planets).

And model whatever regular processes can change the values of those variables (e.g. the orbits of the planets).

And then test that the real planets behave according to the description in our model.


Every real tennis match is unique in the immensely rich and complex detail of individual player’s actions.

Every tennis match is the same in so far as it conforms to the abstract description of a tennis match’s qualities in the laws of tennis.

Suppose a tennis player scratches his nose; that is an act in reality but not in the tennis match system.

The action is irrelevant to the target system controlled by the umpire.

The player’s breathing and biochemistry (though essential in reality) are also outside the described system.


Note that the actors playing roles in one concrete system can play roles in other systems at the same time.

For example, orchestra members are more than the parts they play in a symphony performance; they simultaneously play roles in other systems.

They are tax payers in a tax system - sons or daughters in a family – guests in a hotel system.

These disparate systems do not meaningfully add up to one system, unless and until the systems are related in one holistic system description.


The term system is overloaded with different meanings.

It can refer to a passive structure of connected things and/or an abstract system description.

Here, it usually means a concrete activity system, composed of actors interacting in the activities that characterise the system.


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

E.g. the Dewey decimal system, the Linnaean classification system, a telephone directory, or a data structure.


Activity system: an island of orderly behavior.

A structure of elements that interact (directly or indirectly) in regular or repeatable behaviors.

The behaviors may maintain or advance the state of the system, consume inputs or deliver outputs.

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


Abstract system: 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.

Abstract descriptions do take concrete forms (they are found in mental and documented models).

At the same time, they describe (model, conceptualise, idealise) a physical reality that can be envisaged or observed as matching the description.


Concrete system: a system that runs in reality.

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

The realisation by a real world entity of an abstract system – near enough to satisfy the observer.

One concrete entity can realise many different abstract systems.

So, to say an entity is "a system” implies a particular description of the behaviors that characterise it.

System boundary

“Every living organism is essentially an open system. It maintains itself in a continuous inflow and outflow…” Bertalanffy


System environment: the world outside the system of interest.

Most system design methods separate a system from its wider environment

The environment of one system may be a wider system.


Closed system: a system that does not interact with anything in the wider environment.

All events of interest are internal to the system.

E.g. A System Dynamics model is a closed system of stocks and flows.


Open system: a system that interacts with entities and events in a wider environment.

Inputs can change the state of the system; outputs can change the state of entities in the environment.

Many system design methods scope a system by its inputs and outputs


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

It encapsulates the system’s internal structures and behaviors.

It defines the system’s input-process-output boundary.

Inputs and outputs can be flows of material, energy or information.


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.


Read System boundary for more.

Interactions between system actors 

“connected with system theory is… communication. The general notion in communication theory is that of information.” Bertalanffy


Interaction: an exchange of forces, materials or energy or information.

It is usually presumed that all actors in an activity system interact (directly or indirectly) else there would be two or more separate systems.


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.


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 speed, throughput, availability, security, monetary value.


“A second central concept of the theory of communication and control is that of feedback.” Bertalanffy


Information feedback loop: the circular fashion in which system inputs influence future outputs 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.


Read Communication theory and Information feedback loops for more..


Somewhat related concepts include the following.

Entropy: disorder; across the universe, the total entropy increases with time.

Chaos: unpredictable disorder in how things relate to each other or change over time.

Autopoesis: the process by which organisms build and maintain their bodies from primitive chemicals consumed.

System structure and behavior

“Systems concepts include: system-environment boundary, input, output, process, state….”   Principia Cybernetica


State: the current structure of a thing, as described in the current 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.

In the abstract, description or specification of how state changes over time, either in discrete steps or continuously.

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.

A concrete 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.


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.

System stability and change

“Cybernetics deals with all forms of behavior in so far as they are regular, or determinate, or reproducible.” Ashby 1956

In Ashby’s view (as many dictionary definitions suggest) a system is orderly rather than disorderly.

He wrote that the notion of a deterministic system was already more than century old.


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

A deterministic system, in a given state, will respond to a specific stimulus or eventby acting in a predictable way.

Paradoxically, as a result of processing a series of events, a system may change in an unpredictable, chaotic or non-linear fashion.

Read Determinism and hysteresis for more.


Again, a system is an entity whose behavior is organised, regular or repeatable.

Like every other discrete entity, such an activity system has a discrete life time, which can be long or short.



Life span



In our solar system

for eons

the planets

orbit around the sun, as determined by the law of gravity.

In a human body

for years

the organs

process chemicals, as determined by instructions encoded in DNA.

In a clock

for days

the pendulum

sways back and forth, converting a coiled spring's energy into clock hand movements.

In a tennis match

for hours

the players

behave in an orderly way, as determined by the laws of tennis.

In a symphony performance

for minutes

the orchestra members

make sounds, as scripted in a musical score.


Ashby was keen we differentiate inter-generational system mutation from system state change within the life span of a system.

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


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


Discrete (or digital) state change: a system’s state advances incrementally in response to discrete events.

Continuous (or analogue) state change: a system’s state advances continually in response to continuous forces or inputs


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).


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


The following three notions are central to modelling activity systems.

1) The state of an activity system may change.

2) The roles and rules of a system are fixed for a system generation.

3) Changing the roles or rules makes a new system version, or a different system.


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


Read System stability and change for more.

Natural systems and designed systems

A natural system has evolved without any intent, though some may speak of its accidental outcomes as its aims.

A designed system was created by intent; so, it can be tested by comparing its outcomes with its aims.

If it ain’t described before it exists, then ain’t designed.


Generic concept

Natural systems

Designed systems






Planets are


Humans and machines



bodies in space that

play roles in

play roles in

instantiate classes so as to


complete orbits and

performing processes and

performing processes and

transform and remember data and


exchange forces that

exchanging materials that

exchanging information to

exchange information to


maintain the solar system.

sustain an organism.

meet business goals

monitor and direct external entities


Natural system: an entity that behaves as a system before it is perceived to be a system.

Its repeated behaviors are the outcome of evolution rather than the ideas of a living entity.

E.g. The solar system behaved as a system before it was described.

Other examples: a weather system, biological organism, the Krebs cycle.


The correspondence of the real solar system to its description need not be perfect.

It only needs to be near enough to help people predict its behavior – well enough.


Designed system: an entity that behaves as a system only after it has been conceived by a living entity.

Its reproducible behaviors are a response to the interests or aims of one or more living entities.

E.g. A professional tennis match is conceived and described in the laws of tennis.

Other examples: a cuckoo clock, a motor car, an accounting system, a choir, a tennis match, the world cup.


The correspondence of the phenomena in a real tennis match to its description need not be perfect.

It only needs to be near enough to help people predict and direct its behavior – well enough.

Social systems, social entities and social cells

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.


Social system: a social entity 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.


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.

Conclusions and remarks

This paper has attempted to restore order to the concept of a system - along the lines defined by Ashby.


Systems are islands of orderly behavior, describable in terms of roles for actors and rules for activities.

Actors are structures or components that exist in space and perform activities expected of their roles.

Activities are behaviors that happen over time, and change the state of the system or something in its environment.


An abstract or theoretical system is a description of roles played by actors, and rules governing their activities.

The scope of the system is determined by its describers.

Give some aims or interests, describers focus on some activities performed by some actors

They describe instances of actors and activities as general types - the roles and rules of the system.


A concrete or empirical system is an entity in which actors play roles in performing described activities.

An entity is only an empirical system when, verified by observation, its behavior matches that of a theoretical system.


Ashby's idea of a system gives us insights into a wide variety of disciplines.

Together with Darwin's theory of evolution, it leads us towards theories of information and communication.

It leads us towards answers to philosophical questions about description and reality.

And helps us to make sense of what enterprise architecture is about.


For more, read the papers under GENERAL SYSTEM THEORY on the "System Theory" page at

Footnote on behaviors

A concrete 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.


An abstract 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.


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.


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.



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