Systems as people discuss them

Copyright 2016 Graham Berrisford. One of about 300 papers at Last updated 17/02/2019 18:30


The universe is an ever-unfolding processes in which we perceive discrete entities.

If every one of those discrete entities is a system, the term has no useful meaning.

Systems architects should understand the properties that characterise a system.

Because if it can't be described as having the properties of a system, then it ain't a system, and it can’t be designed as a system.


Encapsulation. 1

Inside a system.. 1

The primacy of behavior or dynamics. 2

Abstract and concrete systems. 3

Inputs and outputs. 4

Granularity, circularity and recursion. 4

More definitions and features of a system.. 5

A system classification. 7

System change. 7



A system is a way of looking at the world, or rather, a part of the world.

The system describer encapsulates it, separates it from its wider environment.

The describer decides where to draw the boundary; and may expand or contract it.

The boundary can be physical (as is a solid structure in a liquid) or logical.


A system can be closed or open, meaning that inputs and outputs cross its boundary.

Having identified external structures or behaviors that interact with a system, the boundary can be expanded to include them.

Thus, the ecology of the first system is definable as a wider system.

Inside a system

Inside a system you may see:

·         actors and activities,

·         entities and events,

·         roles and rules, or

·         stocks and flows.


Each pairs of terms expresses the structure-behavior dichotomy that runs through all general system theory.


Inside the systems of interest to us, there are usually:

·         active structures or actor(s) that perform

·         behaviors or activities that modify

·         passive structures that form the state (material and/or information) of the system.


The actors and activities are orderly in the sense that they conform to some roles and rules.

The roles and rules can be described, and the conformance of a system’s behavior to the rules can be assessed.


Here are a few simple examples to get us started.


A solar system

Actors: planets.

Activities: orbits.

State: the current condition and position of the planets.


A termite nest

Actors: termites (individuals come and go, their roles and rules remain).

Activities: deposits of materials, dispersions of the pheromone.

State: the structure of the nest.

The nest grows as termites deposit material at peaks in the pheromone gradient and disperse the pheromone.


A prey-predator system

Actors: wolves and sheep (individuals come and go, their roles and rules remain).

Activities: births and deaths of wolves and sheep.

Material state: the condition of the wolves and sheep at a moment in time.

Information state: wolf and sheep population numbers.

The populations grow and shrink in response to each other, and may settle in a stable cyclical pattern.


A tennis match

Actors: tennis players (ignoring their internal organs).

Activities: the motions of the ball and the players.

Material state: the condition of the court, the balls and the players at a moment in time.

Information state: the game, set and match scores.

The match score is a structural side effect of players acting according to laws of the game.


A circle calculator

Actors: an atomic software component (ignoring the operating system and computer it depends on).

Activities: calculate perimeter, calculate area.

Information state: an invariant, the value of pi.


In each example above, the essence of the system is its dynamics.

The primacy of behavior or dynamics

Typically, a system may be discussed in terms of actors, activities and state.

The actors perform some actions which modify some material and/or information state.


The first decision  is what to treat as the basic elements of the social system.

The sociological tradition suggests two alternatives: either persons or actions.” Seidl 2001.

Is a system a set of actors performing actions?

Or a set of actions performed by actors?


Most system theorists have focused on the actions, the behaviors or dynamics.

In the domain of cybernetics, Ashby said the question is not so much "what is this system?" as ''what does it do?"

In the domain of soft systems, Churchman said “a thing is what it does”.

In the domain of System Dynamics, Forrester and Meadows, the dynamics are the rules that incrementally change the system state.


In other words, systems are characterised by exhibiting behaviors that are regular or repeatable, orderly or rule-bound.

The system’s dynamics are the roles and rules that constrain the actors and their activities.

This kind of system remains the one most system theorists are interested in.

Abstract and concrete systems

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

Our first impulse is to point at [a concrete entity] and to say "the system is that thing there".

This method, however, has a fundamental disadvantage: every [concrete entity] has 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.” Ashby 1956


Ashby, Ackoff and other thinkers distinguished an abstract system from its realisation by one or more concrete systems.

An abstract system contains the roles and rules that actors and their activities are supposed to adhere to. E.g. The stickleback mating ritual.

A concrete system contains actors playing the roles and following the rules, and their actions on objects or variables. E.g. Countless pairs of sticklebacks.


Abstraction to hide complexity

The granularity of the atomic actors, activities and state variables in a system is whatever we choose it to be.

In discussion and observation of the stickleback mating ritual, the particulars of any one stickleback are ignored.

We necessarily ignore their internal structures and behaviors, give no thought to the complexity therein.


Note that the widespread use of the term “complex systems” is questionable.

Some discussion is of disorderly situations rather than systems, but surely the absence of order is simple rather than complex?

Some discussion is of unpredictable systems, but we know simple systems can be unpredictable - as per chaos theory.

Inputs and outputs

A system can be closed or open, meaning that inputs and outputs can cross its boundary.

The table below adds inputs and outputs to the actors, activities and state we started with.

And shows the similarities between systems as they are defined in five different sources.


Generic structure

Principia Cybernetica

Boulding’s social system

Checkland’s Soft System

Maturana’s biological entity

Wikipedia’s “system” entry (2016)


Interrelated parts

Individuals perform roles in

Components interact coherently in

Interacting components are transformed and destroyed

Related components perform


interact in processes to meet goals by

repeatable processes according to

activities to meet a purpose by

by a network of processes that form

processes that transform


maintaining system state and

remembered mental images, and

maintaining their integrity and

a machine, a concrete unity


I/O boundary

sending/receiving information

exchange messages

sending/receiving inputs and outputs


inputs into outputs (material, energy or data)


to/from each other and external actors


to/from each other and external actors

in space


Granularity, circularity and recursion



In “General Systems Thinking”, Gerald Weinberg suggests “medium size” aggregates are the “blind spot” for classical modeling approaches.

I believe this is misleading.

There is no blind spot for modelling - between fine and coarse-grained systems.

At every level, we hide the internals of what we choose to regard as atomic.


In modelling the cardio-vascular system, we ignore the internal biochemistry of the cells.

In modelling a tennis match, we ignore the cardio-vascular systems of the players.

In modelling the Lawn Tennis Association, we ignore the game and set structure of a tennis match.

In modelling a nation’s economy, we ignore the internal operations of businesses that pay dividends to investors.


There is a different blind spot – which does appear around the middle level of granularity.

That is human creativity, invention and flexibility.

We cannot model, in a system description, the infinite choices that humans may make, and all that they may do.

We cannot model the dynamics of a system in which humans continually modify the actions they take.

That is simply beyond the scope of system theory.



Much systems thinking (homeostasis, cybernetics and System Dynamics) is about circularity.

It features causal or feedback loops that may act to dampen or stabilise system state change.

As for example in a solar system, a weather system, or an organism.

The system may move from one stable state to another.



The roles and rules of one system may be shaped by a higher process or meta system.

·         Planets don’t define the roles and rules of a solar system – the laws of physics do that.

·         Termites don’t define the roles and rules of termite nest – via a process of reproduction, their DNA does.

·         Tennis players don’t define the laws of tennis – the Lawn Tennis Association do that.


Think of systems layered on top of each other, at different levels of abstraction.

There can be a hierarchy of process control: a control system at level N throws an exception up to a control system at level N+1, and awaits direction.

There can be a hierarchy of system definition: the rules of a system at level N are state variables that can be manipulated by a meta system at level N+1.

More definitions and features of a system


Natural language (five sources)

This table shows system features found in three dictionaries (A, B and C) and two popular internet sources.









Wholeness (or holism)






parts cooperate in processes to act as a whole (rather than act in isolation).

Inter-related components






all parts are related directly or indirectly

Orderly or rule-bound behaviour






system processes are constrained, bound by the rules of physics, chemistry or man.

System boundary (or encapsulation) 






things inside the system are separable from things outside the system.

Input/output exchange across boundary






the system is open to and interacts with its environment


The table suggests this general definition.

·         A system is a whole composed of inter-related components that exhibit orderly or rule-bound behaviours.

·         It may be encapsulated by a boundary, across which inputs and outputs may be exchanged with entities in  the wider environment.


Classical cybernetics (Weiner, Ashby, Turing)

The properties of systems were generalised by system theorists before and without consideration of business or software systems .

“The same concepts and principles of organization underlie the different disciplines (physics, biology, technology, sociology, etc.), providing a basis for their unification.” Principia Cybernetica


Principia Cybernetica says this of a system:

real systems are open to, and interact with, their environments….”

“Systems theory focuses on the arrangement of and relations between the parts which connect them into a whole.”

“Systems concepts include: system-environment boundary, input, output, process, state, hierarchy, goal-directedness, and information.” Principia Cybernetica (Web)


Soft systems (Churchman, Checkland, Ackoff)

Churchman was concerned with business systems in particular.

He said "a thing is what it does" and outlined these considerations for a system.

·         the total system objectives and performance measures;

·         the system’s environment: the fixed constraints;

·         the resources of the system;

·         the components of the system,

·         their activities, goals and measures of performance; and,

·         the management of the system.


General system theory (Bertalanffy, Boulding, Rappaport)

To generalise from the analysis above, the general elements of a system might be expressed as

·         parts/actors (active structure) interact by

·         playing roles in processes (behaviors) to meet goals by

·         maintaining system state and

·         sending/receiving information to/from each other and

·         to/from the external environment (across the I/O boundary)

·         using resources.


Use the links below to find discussion of further properties discussed in the general system theory literature:

·         Encapsulation of structure and behaviour

·         Information feedback loops

·         The primacy of behaviour

·         Determinism and hysteresis

·         Change: adaptation and evolution  

·         Holism and emergent properties

·         Complexity

·         Goal-directedness

·         Chaos and non-linear behaviour

·         Unpredictability


A system classification

This table below maps some system properties above to a classification of system types.

Our main interest is dynamic systems; however passive data structures also feature in what follows.

Like all such classification, this one is questionable.


Discrete entity


disorganised, unstable


organised, stable

Passive structure

does not act

Dynamic system

acts in an orderly or rule-bound way

Natural system


Designed system

described (e.g. symphony or software system)


e.g. solar system


e.g. tree, cat


e.g. bee hive, hunting party

Closed system

e.g. System Dynamics model

Open system

I/O across a boundary

System change

Later papers explore four varieties of system change with reference to Ashby’s ideas.


System change

System state change

System mutation

Discrete system state change

Continuous system state change

Discrete system mutation

Continuous system mutation?



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