Marxism, system theory and enterprise architecture

Copyright 2017 Graham Berrisford. One of about 300 papers at Last updated 13/08/2017 10:16


This paper looks at examples of systems thinking in the 13th and 19th centuries.
One aim is to illuminate and challenge presumptions of Marxism about system in general and social systems in particular.

And indicate where the basis of Marxism in analogy may lead to confusion or error.

Another aim is to exposes ambiguities in the concept of system change.


Preface. 1

Core ideas and laws of Marxism.. 2

Core ideas and principles of system theory. 3

Marxism’s first law: the interpenetration of opposites. 5

Marxism’s second law: the transformation of quantity into quality (and vice versa) 6

Marxism’s third law: the negation of the negation. 7

Inexorable progress?. 8

Generational system change: an early example of enterprise architecture. 9

Inexorable progression in systems thinking approaches?. 11

Conclusions and remarks. 12



Heraclitus of Ephesus was a Greek philosopher known for his doctrine of change being central to the universe.

Plato quoted him as saying “Everything changes and nothing stands still.

Many systems thinkers have addressed system change by borrowing or adapting the biological ideas of homeostasis and evolution.

Given the importance of these two ideas, it is strongly recommended you start by reading this short preface The origins of systems thinking.


People have long looked at systems and considered making transformational or generational changes to them.

Think of the barons who drew up the Magna Carta in the 13th century (more on this later).

Amongst the earliest sociological systems thinkers were Karl Marx and Frederick Engels.

Core ideas and laws of Marxism

Karl Marx (1818 to 1893) studied political economy and Hegelian philosophy; he was a philosopher, economist, political theorist, sociologist, journalist, and revolutionary socialist.

Friedrich Engels (1820 to 1895) was a German philosopher, social scientist, journalist, and businessman.

Together, Engels and Marx founded Marxist theory.

At the heart of Marxism is an ideology - a logic of ideas called “dialectic materialism”.

The logic of dialectic materialism is based on two ideas and three laws about system change.


The two ideas that underpin dialectic materialism

The two ideas are materialism and continual change/development.



Marx said: “the idea is nothing else than the material world reflected in the human mind.”

This triangle captures the notion.



<form>                        <idealise>

Humans     <observe and envisage>   Material world


Some may use the word realism rather than materialism.

Contrarily - for reasons explained elsewhere – we call this view scientific idealism, and allow that ideas can be formed in brains, writings, pictures or statues.

The label doesn’t matter; the notion does, since it appears also in system theory and in enterprise architecture.


Continual change/development

As the ancient Greek philosopher Heraclitus said: "All things flow, all change."

Engels defined dialectics as: "the science of the motion and development of nature, human society and thought."

System theory might well be defined as “the science of the general laws of motion or change in natural, social and human-conceived systems”.

And enterprise architecture is about applying that science to “the design and planning of changes to business systems”.


The three laws of dialectic materialism

In “Anti-Dühring and The Dialectics of Nature”, Engels defined three fundamental laws of dialectic materialism.

·         Interpenetration of opposites: on state changes: Engels proposed that (at least in a stable system) pluses are balanced by minuses, increases are balanced by decreases.

·         Transformation of quantity into quality: on state changes: Engels proposed inputs incrementally change the qualities of a system’s state.

·         Negation of the negation: on development: Engels proposed ideas and things can change or develop (by contradiction) in a direction that is ever onward and upward.


For more on dialectic materialism, read

Note however: throwing scientific ideas into a pot and drawing analogies doesn’t amount to science.

Scientific hypotheses may be informed or prompted by analogies, but theories are tested by experiment rather than proven by analogy.


Read on for how these ideas and laws appear in system theory, and may be challenged in some ways, but first, some ideas of system theory.

Core ideas and principles of system theory

This section is a minimal reminder of system theory ideas expressed by W Ross Ashby.

Read Ashby’s ideas for more.


W. Ross Ashby (1903-1972) was a psychologist and systems theorist.

“Despite being widely influential within cybernetics, systems theory… Ashby is not as well known as many of the notable scientists his work influenced.

W Ross Ashby was one of the original members of the Ratio Club, who met to discuss issues from 1949 to 1958.” Wikpedia in 2017

Unless otherwise stated, quotes below are from Ashby’s Introduction to Cybernetics (1956).



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

“Cybernetics depends in no essential way on the laws of physics.”

System theory

System descriptions

<form>                        <idealise>

Systems thinkers <observe and envisage> Real world entities


“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.”


A system is a view of a reality; or a role you can observe or envisage real world actors as playing.

To apply system theory is to form an abstract system description that hides the infinite complexity of real-world entities you observe or envisage.

You describe the state of a real-world system in terms of variables whose values can be measured (e.g. the positions of the planets).

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

You describe a process in a way that enables real world behaviors to be tested as matching your description.


System change

“The word "change" if applied to such a machine can refer to two very different things.

·         change from state to state, which is the machine's behaviour, and which occurs under its own internal drive, and

·         change from transformation to transformation, which is a change of its way of behaving, and occurs at the whim of the experimenter or some other outside factor.

The distinction is fundamental and must on no account be slighted.”


In other words, one should on no account confuse:

·         changing a system’s state (performing behaviors that changes its variable values): e.g. scoring a point in a tennis match

·         changing a system’s generation (changing its behavior or variable types). e.g. changing the laws of tennis.


Ashby (and other early system theorists) focused heavily on homeostatic systems.

In early discussions, the term adaptation meant system state change.

So, we need another term for system generation change – and evolution is a natural fit.


Cybernetics: control systems and target systems

Just as we abstract a system description from a reality, so, a mechanical control system models some variable(s) detectable in a target system.

Control system

Model of target system variables


Target system

Target system variables and behavior

Heating system on/off


Ashby furthered the ideas of general system theory through discussion of control systems.

“Ashby popularised the usage of the term 'cybernetics' to refer to self-regulating systems

The book dealt primarily with homeostatic processes within living organisms, rather than in an engineering or electronic context.” Wikipedia 2017

In “Design for a Brain” (1952) Ashby viewed the human body as self-regulating system.

The graphic below separates a control system (the brain) from its target system (the remainder of the body).

Control system

Target system

“Design for a brain”

<wrote>                  <realised in>

Ashby                 <envisaged>               Brains



<monitor> Body state variables

<control>  Muscles and organs


Note that information flows are central to cybernetics.

Ashby saw the brain as a regulator that maintains a body’s state variables in the ranges suited to life

He presented the brain-body relationship as an information feedback loop.

A brain holds (or has access to) an abstract model of the body’s current state.

The brain receives information from sensors, and sends instructions to motors and organs.

The aim is homeostasis – to maintain the state of the body - and so help it achieve other desired outcomes.


Read Ashby’s ideas for more of Ashby’s ideas.

Read Beer’s ideas for how Beer used Ashby’s ideas.

Read Introducing General System Theory for an explanation of more system theory terms and concepts in the context of early sources.

Marxism’s first law: the interpenetration of opposites

On state changes: Engels proposed that (at least in a stable system) pluses are balanced by minuses, increases are balanced by decreases.


“The principal heuristic innovation of the systems approach is what may be called ‘reduction to dynamics’ as contrasted with ‘reduction to components’ ” Laszlo and Krippner.

For example, in the context of Forrester’s “System Dynamics”, Meadows defined a system as follows.

“A set of elements or parts that is coherently organized and interconnected in a pattern or structure that produces a characteristic set of behaviors." Meadows


The state of one very narrow ecology can be described in terms of two variables: the quantity of sheep and the quantity of wolves.

Forrester’s System Dynamics helps to explain how these stocks interact.

It employs the idea of causal loop between what Engels might call opposites.

A growth in the stock of


will increase the stock of


A growth in the stock of


will deplete the stock of



The state of the wider world’s ecology can be described in terms of three variables: the mass of plants, the mass of animals and the mass of oxygen in the atmosphere.

We all depend on the fact that plants and animals balance the stock of oxygen.

Forrester’s System Dynamics helps to explain how these stocks interact so as to reach a balance.

A growth in the stock of


will increase the stock of


A growth in the stock of


will deplete the stock of



Note however: not all processes and feedback loops act to keep a system stable.

A system may deplete a stock to zero, or increase a stock continually; and this kind of instability may be desirable.

A system may exhaust a resource it needs: E.g. A moon rocket exhausts its fuel in a few minutes.

A system can continually expand or grow in some way: E.g. A business increases its revenue every year.

Marxism’s second law: the transformation of quantity into quality (and vice versa)

On state changes: Engels proposed successive inputs incrementally change the qualities of system’s state.

And sometimes, the increments build up to a point where they trigger a dramatic change.


To quote from this glossary:

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

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

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

·         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 stimulus by acting in a predictable way.

In the 1950s, Ashby wrote that the notion of a deterministic system was already more than century old.

Sociologists, biologists, psychologists and engineers all describe deterministic systems.

So general system theory is much about the general principles of such deterministic systems.

And individual changes of the kind that Engels called “interpenetrations between opposites” may be deterministic.


Note however: the build up of small incremental changes can lead to a swift and dramatic increase or decrease in quantitative system state variable values.

Small differences in the initial values of a system’s state variables may lead over time to dramatically large differences in the values of those variables.

Such wide variations in the outcomes of a system are called “chaotic”.

E.g. A system with just two element types (wolves and sheep) and simple rules can behave unpredictably or chaotically.

The behavior of an individual actor (wolf or sheep) in response to an event may be deterministic, predictable from its current state.

Yet at a macro level, the volumes of populations (wolf packs and sheep flocks) may fluctuate in what seems a random or chaotic manner.

Multiple actions and interactions between individual actors at a micro-level may lead to unpredictable outcomes at the macro level.

Populations may remain stable for a while, then boom or bust unexpectedly.

For more, read Modelling a continuously varying system using System Dynamics.


Note also: In the progress of human thought, the transformation is from quality to quantity.

You can’t quantify (count the instances of a type) until you know and can recognise a quality (a type).

You can’t count how many apples you have until you know and can recognise the qualities of an “apple”.

You can’t count how many dollars you have until you know what qualifies as a “dollar”.

You can’t give a value to a variable instance (e.g. 44 degrees) until you know the variable type (e.g. the temperature in Celsius).

For one way to abstract quantities from qualities read Converting a discrete model into continuous model.

Marxism’s third law: the negation of the negation

On development: Engels proposed ideas and things can change or develop (by contradiction) in a direction that is ever onward and upward.


“Dialectics envisages the fundamental processes at work in the universe, in society and in the history of ideas,

not as a closed circle, where the same processes merely repeat themselves in an endless mechanical cycle,

but as a kind of open-ended spiral of development in which nothing is ever repeated exactly in the same way.

This process can be clearly seen in the history of philosophy and science.

The entire history of thought consists of an endless process of development through contradiction”


“Negation of the negation” is a rather obscurely academic way of saying something akin to “trial and error”.

Think of a negation as a contradiction of a hypothesis, proposition or system description.

It triggers, by way of response, a more accurate hypothesis, proposition or system description.

This process continues iteratively and indefinitely.


“Negation of the negation” does not signify a return to the original state of a thing (homeostatic adaptation).

It signifies the regeneration of a thing at a “qualitatively higher level”; this is akin to evolution, but with the addition of inexorable progress.


On “nothing is ever repeated exactly in the same way”.

This is true in the natural or material world.

Note however: system theory is about abstracting system descriptions from concrete systems in operation.

You abstract the essence of some real behaviors to a point where the process you describe is indeed repeatable in exactly the same way.


On “fundamental processes”

Negation of negation is the process by which, Engels proposed, ideas or things evolve from a lower form to a higher form.

The idea is that movement through successive “contradictions” leads to development, from simple to complex, from lower to higher.

Note however: it is unclear to me whether or how clearly Engels distinguished the processes of a system and the processes by which a system evolves.


On “endless process of development”

This may be expressed as eliminating ideas or things that are “contradicted” and rewarding those ideas or things that succeed.

Note however: the evolution of scientific ideas should not be confused with the evolution of things in nature.

Also, many ideas have been contradicted (logically or empirically) yet continue to thrive (cf. Dawkin’s “meme”).

Marxism may be seen as an example, as may some other system thinkers’ ideas.

Inexorable progress?

Theories based only on assertion and analogy are scientistic rather than scientific.


Some leap from discussing the life of an individual, to the evolution of a species.

Or leap from discussing system state change to discussing system generation change.

E.g. the early system theorists were much concerned with homeostasis – how a system maintains its state.

But von Bertalanffy also said that systems “develop towards states of increased order and organization", where the term “states” means something very different.

Restoring system state after a variation from normal (homeostatic adaptation) is one thing.

Changing from one system generation to the next (evolution) is a completely different thing.


Some leap from discussing the evolution of biological forms, to the evolution of human societies and/or sciences.

E.g. Engels defined dialectics as “laws of motion and development of nature, human society and thought."

A common difficulty in discussion of systems is confusing what ought to be distinguished:

·         the state-changing processes of a system (be it a life form or designed procedures)

·         the generation-changing process of evolution between system versions (whether by nature or design)

·         the very particular history of human societies (especially government systems)

·         the very particular history of human thought (as in scientific knowledge).


Bertalanffy stretched his ideas into proposals about human psychology and the meaning of life.

“Life is not comfortable setting down in pre-ordained grooves of being”.

Note however: scientists believe sharks have been comfortable in their groove for 100 million years.

It may be seen as a triumph of evolution that sharks resolutely refuse to evolve towards a higher form.


“At its best, [life] is élan vital, inexorably driven towards higher forms of existence”.

It is possible that when Bertalanffy proposed systems continually evolve into higher forms, he borrowed the idea from Engels.

Note however: evidence suggests 99.9 percent of all species that have existed on Earth are now extinct.

And many biologists believe we are currently in the throes of a sixth mass extinction.


In any case, how to measure one form of existence is higher than another form of existence”?

Nature has no favourite species; the notion of a higher form seems an ego-centric, or human-species-centric, idea.


Did Bertalanffy have in mind that biological evolution increases complexity?

Suppose we could measure the complexity of a living entity, perhaps by counting its possible states, as Ashby proposed.

There is no obvious reason to presume the measurement would show a human is much more complex than a chimpanzee, elephant or mouse.

Also: some changes improve a system by simplifying it, eliminating waste and making a system more economical.

This might apply in biological evolution as well in designed systems.


(By the way, some assume the primary intention or purpose of an organism is to survive.

But decay and death are essential to life on earth.

The death of a sheep is good for the wolf; and may be good for other sheep also (to prevent over grazing).

Moreover, death is essential to evolution; since without it, life forms could not evolve to fit changing environments.

So, you might argue a purpose of the individual is to die - after passing on its genes.

And that survival is, rather, the primary purpose or intention of genes.)

Generational system change: an early example of enterprise architecture

Many have appropriated "enterprise architecture" to mean whatever they want it to mean.

The fact is, EA emerged in the 1980s out of business system planning rather than business planning, to which it has always been subordinate.

EA is about making generational system changes – from baseline business system to target business system.

EA is about designing and planning changes to business systems in which regular business processes create and depend on business data.


Enterprise architecture

Architecture Definitions

<form>                             <idealise>

Architects <observe and envisage> Business systems


The Magna Carta (agreed on 15 June 1215), which proposed a reorganization of England’s government system, can be seen as an early example of EA.

The example might be used to show that generational system change can be "of the people, for the people and by the people".

And at the same time, to show it is about designing and planning deterministic business systems.

The Magna Carta proposed a generational step change in roles and rules to be performed by actors in the English socio-political system.


The baseline system

The barons understood the roles and rules of the current situation, and they didn’t like it.

They had a mental model of the baseline system of interest; did they also have a documented model?

We know that, centuries earlier, the roles and rules of Anglo-Saxon society were well understood.

The roles (abbot, lord, knight, freeholder, villein etc.) were recorded in the Domesday book in 1066.

And we know those roles came with certain rights and obligations, which scribes surely recorded at the time.


The target system

The barons sought to make a “management intervention” by documenting change proposals, discussing and agreeing them.

They agreed their model of the target system, and documented it in the Magna Carta.

The document focused on the rights of free men - especially the barons of course!

For example, it promised limits (rules) on feudal payments (behaviors in which processes move data) to the Crown (a role in the system, played by successive actors).


The meta system

The barons acted as a meta system.

They knew the old system, described the new system they wanted, and pressed for the roles and rules of that target system to be realised.

They also proposed an ongoing meta system - a council of 25 barons to govern adherence of the new system in operation to the system in description.


The Magna Carta might reasonably be seen as an example of critical systems thinking, long before anybody had published a systems thinking approach.

Sure, the barons didn't use any of the words we use now (system, role, rule, behavior etc) but they understood the concepts.

The product represented not only a step change in rules and roles, but also a step forward in the formalisation of roles and rules a documented model.

Imagine it being written by management consultants using some kind of systems thinking approach - would it have been any different?

Inexorable progression in systems thinking approaches?

Social systems are sometimes classified into what is presumed to be an inexorable historical sequence.

E.g. a history that starts with family groups and clans, and progresses through feudal societies to democracies.

Some present this history as an evolution towards a better or optimal state.


Kenneth C. Bausch wrote of “The Emerging Consensus in Social Systems Theory” (2001).

Bausch suggested systems thinkers have a mission to herald a new era of social organization, of advancing participative democracy.

Thus, he presents systems thinking as a political movement.


Some suggest modern social systems thinking derives from, or is an advanced application of, general system theory. E.g.

“Though it grew out of organismic biology, general system theory soon branched into most of the humanities.” Laszlo and Krippner.


You might reasonably view the history of system thinking as running in the opposite direction:

Social systems thinking – in both hard and soft flavours - emerged towards the end of the 19th century.

General systems theory emerged in the 1950s; enterprise architecture emerged in the 1980s.


Social systems thinking tends departs from general system theory in one or more of the ways listed below.

General system theory

Not general system theory



General to all domains of knowledge

Specific to situations in which humans interact

About roles, rules and regular behaviors

About individual actors (purposeful people)

About systems at the base level of interest

About meta systems that define and change roles and rules

Describing testable systems

Solving any problem in any consensual way


Promoting a “participative democracy”


These differences are further explored in related papers at

Conclusions and remarks

This paper has indicated ways in which Marx and Engels may have been naïve about systems in general, and system change in particular.

The effort needed to define, build, test and deploy complex state-dependent systems, and to change them, may be greater than they envisaged.
The section on the Magna Carta shows that designing and planning changes to deterministic systems can be "of the people, for the people and by the people".


A suggestion is that both social systems thinkers and enterprise architects can benefit from gaining a deeper understanding of general system theory, and respecting it more than they do.

System theory is good to know, good for the soul, and practically useful in all kinds of thinking about systems.



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