Introducing system terminology

Copyright 2016 Graham Berrisford. One of about 300 papers at Last updated 04/03/2018 16:46


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.


The systems movement 1

System boundary. 2

Interactions between system actors. 2

Deterministic systems. 3

Abstract and concrete systems. 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

The idealism triangle. 9

Conclusions and remarks related to systems. 10


The systems movement

Bertalanffy’s ideas were picked by others including William Ross Ashby, Anatol Rapoport and others.

In the 1950s, they looked for patterns and principles common to systems across all sciences.

 “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.

There are forms and functions - structures and behaviors - within a system.

There are descriptions and realisations - abstract and concrete systems.

There are accidental and purposive - natural and designed - systems.

These and many other system terms and concepts are explained below.

System boundary

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


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

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


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 

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

The actors in a system can interact by forces, matter, energy or information, the last of which is the main interest here.


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 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

Deterministic systems

 “Cybernetics deals with all forms of behaviour 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.

Abstract and concrete systems

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

This triangle represents the idea more graphically.


System theory

System descriptions

<form>                        <idealise>

Systems thinkers <observe and envisage> Real world entities


We can describe 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 test that he real planets behave according to the description.


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.


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

Normally, a collection of active structures that interact in regular behaviours that maintain system state and/or consume/deliver inputs/outputs from/to the wider environment.

Sometimes it means the abstract (theoretical) system description.

Sometimes it means the concrete (empirical) realisation of a description.


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.

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 actually observed as matching the description.


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.)


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.


Note also that Ashby, Checkland, and Ackoff all recognised that one discrete entity can be conceptualised as many different systems.

So, to agree an entity is "a system", we must share (in our minds or documentation) a description of its behaviors.

System structure and behavior

The structure/behaviour dichotomy: the distinction between structures addressable space and behaviors that happen over time.

This table draws the distinction in reasonably natural language.


Structure: passive structures and actors in space

Behavior: atomic actions and processes over time

Structures -  shaped or directed by behaviors.

Entities -  created, changed and destroyed by Events.

Stocks -  incremented and decremented by Flows.

Components - perform Processes and deliver Services.

Behaviors - performed by active structures.

Events - create, change and destroy Entities.

Flows -  increment and decrement Stocks.

Processes performed and Services delivered by Components.


This table draws the same distinction as in the Unified Modelling Language (UML) standard.


Structure - along the lines defined in UML

Behavior - along the lines defined in UML

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.


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.

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.

System stability and change

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.

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 of a systems 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; its outcomes might be regarded 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: a system that runs before it is described by man.

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

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


Observation of a natural system in operation precedes its description

First, the natural system runs in reality as phenomena instances.

·         The Krebs cycle was a system in operation before it was described.

·         The solar system was in operation before it was described.


The solar system can be called a discrete entity – meaning it is separable from the rest of the universe.

Telling you that the orbiting planets form a solar system conveys an additional meaning.

It tells you that the system’s behavior can – conceivably - be tested against a description.

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.


The solar system is composed of a few planets that display regular behaviors.

If/when those regular behaviors cease, that entity will stop being the system we understood it to be.


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, or the world cup.

Designed systems are often described in terms of aims (motivations), behaviors (activities) and structures (actors and obiects).


The description of a designed system precedes its operation in reality.

First, the designed system is described as a set of phenomena types.

·         Microsoft Word had to be described in coded types before it could be used to write a document.

·         A professional tennis match was described in laws before any matches of that type were played.


A tennis match can be called a discrete entity – meaning it is separable from the rest of the universe.

Telling you that it is a system conveys an additional meaning.

It tells you that the system’s behavior can – conceivably - be tested against a description.

The correspondence of 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 related to systems

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


Systems are islands of orderly behaviour, describable in terms of roles and rules.

Roles are performed by system actors - persistent entities – active structures – locatable in space.

Rules govern system activities – behaviors over time – which follow some logic or law.


And realised by concrete actors and 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.


A 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.


An empirical system is an entity in which actors play roles in performing described activities.

This entity is only an empirical system when, verified by observation, it matches 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.




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