EA and social systems thinking

Copyright 2017 Graham Berrisford. One of about 300 papers at http://avancier.website. Last updated 11/05/2019 13:01


A system contains or employs actors that play roles in regular processes.

E.g. consider the system that is an orchestra’s performance of a symphony.

The symphony score defines the roles and rules of the system, which is instantiated in reality by every performance of the score.

A social network is a group of actors who can chose their own behaviors and interact to reach agreed aims.

E.g. consider the group of actors hired to play in an orchestra.


If management is about hiring and motivating the actors in the orchestra (the social network).

Then EA is about the roles and rules of the symphony (the social system).

The paper EA as an application of general system theory introduces 20 system theory ideas that are used in EA.


There is far less evidence of social systems thinking in EA history, EA job adverts and what enterprise architects today are employed to do.

However, this paper collects some thoughts about EA in relation to social systems thinking.


On human organisation thinking. 1

Social systems, social networks and social cells. 3

Social systems and enterprise architecture. 4

EA and “action learning”. 6

EA and other social network thinking. 6

Complex adaptive systems. 7

Four kinds of system change. 7

Micro and macro levels of system modelling. 8

Business organisation. 9

Seven principles of EA.. 9


On human organisation thinking

General system theory is about general, cross-science, principles.

However, much social systems thinking is specific to human situations and sociology.


What do all managed human organisations have in common?

They feature actors performing regular activities that change or maintain the state of the system.

They depend on actors playing roles and following rules - well enough.


Here, a social system is the realisation by some social actors of some regular behaviors.

The actors play describable roles and communicate information using describable data types.

Think of the bees in a beehive, or the hunters in an early human hunting party.

Humans have evolved ever more complex legal, religious and political systems.

Often, a system has a “domain-specific” language for communicating information.


Systems contribute much to the success of human organisations.

The paper EA as an application of general system theory introduces 20 system theory ideas that are used in EA.

General system theory and cybernetic helps to explain what enterprise architecture can do, and cannot do.


However, system theory is not enough; other kinds of analysis are necessary.

Human organisations contain and involve much that cannot be described as a system.

People are not well-called the “parts” of any system they play roles in, since they also act outside of their roles.


Here, a social network is a group of actors who exchange information.

The information can include descriptions, directions and decisions - and requests for them.

The actors may well act according to information in messages received and memories retained.

But not necessarily in a way that is regular or predictable.


Much of what human actors in a business do is ad hoc – not defined in roles or rules.

Not everything that happens in a human organisation can be captured in a system description.

So to label all analyses of human organisations as “systems thinking” is unhelpful.


Socio-cultural human organisation thinking can be equally or more important than systems thinking

E.g. Suppose a human organisation’s sponsor publishes goals – some target outcomes.

But it turns out the organisation’s actors go on to achieve different outcomes.

A management consultant might analyse the discrepancy by asking whether:

·         the goals were unrealistic

·         the sponsor didn’t really care about the goals

·         the sponsor hid their real goals

·         the sponsor changed their mind about their goals

·         the actors were inept

·         the actors were not aware and reminded of the goals

·         the actors were not motivated or rewarded for meeting the goals

·         the actors were encouraged (perhaps financially rewarded) to do something else

·         the actors were not discouraged by managers from doing something else

·         external forces (political, economic, social, technical, legal, etc) steered the organisation differently.

Social systems, social networks 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 network: 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.


The orchestra’s actors both play roles in a system and belong to a social network.

The actors cannot perform other symphonies in parallel, because the dynamics of a symphony are continuous.

But other social networks can play roles in different (discrete event-driven) systems - in parallel.

A business can be seen as a social network in which actors play roles in many systems

Those business systems may be consistent or inconsistent, coordinated or unrelated, or even in competition with each other.


Social cell: a social system whose roles reward the actors of a social network 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 network.

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 system (like Dawkin’s “meme”) may be so appealing that actors replicate it


Note: this definition of social cell has no negative connotation.

It allows that social cells can be of mutual benefit to all actors in it.

Indeed, the general idea of the social cell may be regarded as a model for the survival of a business.


Daniel Dennet introduced the notion of social cells (in this essay) as insidious, even as parasites on society.

His essay started with a somewhat strained analogy between biological cells and social cells.


A biological cell has

A social cell

captures materials and energy (metabolism)

preserves itself in a social environment

reproduces (using genes or the like)

finds the nutrients its needs

has a membrane that lets in only what needs to come in.

fends off the causes of its dissolution.


Denneit’s examples were: Japanese tea ceremonies, debutante parties, Ponzi schemes and some Christian churches.

He described his examples as sharing some common features.

They are “insidiously effective” social mechanisms.

They “thrive on human innocence and are threatened with extinction by the rising tide of accessibility to information.”

He proposed that the full system description is hidden by a “membrane” from innocent initiates.

And when those actors see through the membrane they become disillusioned.


Dennet proposed nobody designed the roles and rules of a social cell.

And yet the roles and rules of his examples were designed by somebody.


Dennet described the Japanese tea ceremony thus:

“The Japanese tea ceremony exploits the human desire for status and influence in order to raise the money to capture the energy,

and has evolved an elaborate developmental programme for enlisting and training new hosts

who can eventually reproduce their own schools (with mutations) for training yet another generation of hosts, and so on,

all of this within the kind of protective shell that can readily be constructed and defended in a stratified society.”


Social cells in a wider society

Dennet described the debutante party tradition as “a superannuated cultural parasite”.

He classified Ponzi schemes as parasites on society also.

What does that mean? Is it a political statement?


By definition, a social cell survives because it rewards some if not all cell members.

·         Japanese tea ceremonies can be experienced as a calming, comforting meditative exercise.

·         Debutantes parties fulfil some dreams of their participants and/or their parents.

·         Churches give hope, comfort and support to their members.

·         Ponzi schemes rewards early investors (at the expense of the last ones).


A social cell exists in the wider society its actors are drawn from.

It operates in a market in which actors may regard the social cell as a cost, benefit or threat to them.

These external actors may determine whether the cell thrives or not.

Social systems and enterprise architecture

Mainstream EA is about the optimisation and extension of business roles and processes that create and use business data - and the technologies required.

The paper EA as an application of general system theory introduces 20 system theory ideas that are used in EA.


There is a trend to use “EA” as a label for all manner of business management consulting and socio-cultural systems thinking.

The question arises: when and how does or might EA also employ more social systems thinking ideas.


Systems thinking discussion often confuses actor and activity-oriented viewpoints.

From the actor-oriented viewpoint: a social network is a set of physical actors who inter-communicate and act as they choose

From the activity-oriented viewpoint: a social system (say a tennis club, or choir) is a set of logical roles, which need actors .


One social system can be realised by different social networks – there are many beehives, football teams and choirs.

Moreover, one social network can act as several social systems – its actors can play unrelated roles in (say) a football team and a choir.


Whenever a social network’s actors follow given roles and rules, then that entity acts as a social system.

Honey bees do this when they follow rules (they inherit) to watch another bee’s dance, read the message and find the pollen.

If you could persuade the same bees to follow different rules, the same social network would act as a different social system.


EA prioritises the role/activity-centric view over the actor-centric view.

EA is about social systems rather than social networks.

It is about formalised social systems, or business capabilities, that are under change control.


EA addresses a directed business; it starts from the executive-level business drivers, goals, principles.

Its strives to ensure business functions or capabilities cooperate to meet the goals of the executive body.

It assumes the business deploys actors to play roles, perform activities and meet goals such as satisfying customers.


EA deliberately distances itself from organisation’s current management structure – the social network.

EA models the business as a using a logical business capability hierarchy or function decomposition structure.


Sometimes, changes planned by EAs have significant impacts on the actors who play employee roles.

Then, the EA team often works in concert with business managers and some kind of "business change" team, who may draw on more sociological ideas.

It may be argued that social systems thinking is more relevant to “business change” than “enterprise architecture”.


Read “Socio-cultural EA” for discussion of a paper that radically deconstructed EA.


Having said all that, can EA be seen as applying the ideas of systems thinking?

EA and “action learning”

Most EA teams work in traditional organisations that separates the meat system from the system.

The EA team is composed of actors who sit aside from the employees in business operations.

Business system: actors in business operations monitor and direct the activities of actors that the business wants to monitor and direct (customers, suppliers, employees and machines).

Meta system: actors in EA team monitor and direct the fitness for purpose of roles played by actors in business operations.

EA plans generational changes that replace a baseline business system by a new (target) business system.


Action research merges the business system and the meta system.

Business operations are iteratively refined by people involved in the processes.

In our terms, this means people switching from the operational business system to the meta system and back again.


Suppose the EA team is composed instead of the employees?

Suppose employees and business units, by annually re-negotiating SLAs with each other, make generational changes to business operations?

Read “Hierarchies and networks in business management” for a case study along these lines.


EA and other social network thinking

An EA framework (like TOGAF) could reasonably recommend some systems thinking tools.

E.g. Checkland’s “Soft Systems” and Beer’s “Viable System Model” might be useful.

Such tools can prove useful in stakeholder management, in requirements definition and in business architecture definition.


EA cannot be all things to all people; it cannot embrace all social sciences.

An EA team focuses on designing and planning changes to orderly business systems

It is not expected to plan changes in human abilities: intelligence, intuition, creativity or social skills.

Or to supervise how teams use agile development practices.


Some say EA should put people first, but it is not always clear what they mean by that.

Do enterprise architects identify stakeholders and their concerns, and try to address them? Yes

Do enterprise architects focus on customer/consumer requirements? Yes, by taking a service-oriented view of business systems.


Do enterprise architects give control of business systems to the actors employed in them? Hmm…

Suppose employees can change the organisation structure, change the rules, flout the rules, or even change the aims of a business system.

Suppose the structure and behaviour of a business system are volatile and cannot be described with any certainty.

Then there is no describable business system or enterprise architecture.

Complex adaptive systems

In system theory, terms may be used thus:

·         Complex means the system's describable activities and rules are complex (staggeringly complex in most digitised systems).

·         Adaptive means the system is self-sustaining; it maintains its own state via input/output feedback loops with entities and events in its environment.

·         System means a describable collection of actors playing roles in processes to maintain system state and/or transform inputs into outputs.


In social systems thinking, terms may be used thus:.

·         Complex means the actors are complex, but the activities and rules only lightly prescribed (so there is little describable system in the EA sense).

·         Adaptive means the actors are self-directing and make up the rules as they see fit, with some overarching goals in mind.

·         The system is a vaguely-scoped and ever-evolving entity with few describable activities or rules, and perhaps not even an identifiable group of actors.


EA takes for granted that business people will make decisions and act according to their own judgement, or the judgement of their peers.

Much business is conducted informally, in social networks in which people talk, negotiate and make decisions.

This surrounds and envelops the business systems described and deployed as a result of EA.

Four kinds of system change

Change can be divided into two kinds

·         Discrete state change: as in analogue signals or data, which vary continuously, as in the hands on a clock face.

·         Continuous state change: as in digital signals chunked into discrete units, as in a clock that displays discrete numbers. 


There is another way that change can be divided into two kinds.

·         System state change - within one system generation; does not change the nature or identity of the system.

·         System mutation – makes a new system generation; changes he nature of a system, to its roles, rules or DNA.



EA plans changes that move a system from one generation to the next.

This table presents EA as being about discrete change rather than continuous change.


Four kinds of change

Discrete change

Continuous change

System state change


System Dynamics

System mutation


No describable system


EA presumes a system is under change control, which implies an old system is replaced, in a discrete step, by a new system.

By contrast, if actors continually change their roles and rules, then the notion of a describable system/capability crumbles.


Of course, all businesses and human social networks are in continual flux.

Change control does not prevent the actors in a business or the activities they perform from changing.

But it does prevent change to those systems of roles and rules that are under the governance of EA.


Human actors have personal goals or purposes outside of a entity they belong to. (These conflicts of interest may prove a hindrance to the entity.)

A social network may have few rules and/or its members may act outside of roles given to them. (This flexibility may prove helpful to the entity.)

Wherever the interacting roles of actors can be described, there is a system that can be placed under change control and governed.

Beyond that, where behaviour cannot be described, there is no system that can be placed under change control or governed.

Micro and macro levels of system modelling

Sociology is about how micro-level actors (each of which can be seen as system in its own right) interact in macro-level entities.

While the behaviour of individuals may be deterministic, the behaviour of the population may appear not to be.

Multiple interactions between individuals, some of them simultaneous, may lead to unpredictable system states, results or outcomes.

Agent-based modeling or system dynamics might be used to model such a system.


This table presents a classification that positions different system modelling approaches. (Agent-based modelling might be used for heterogenous populations also.)


Modelling approaches

Heterogeneous population

Homogeneous population

Micro-level modelling

System Dynamics

Agent-Based Modelling

Macro-level modelling

Enterprise Architecture (EA)



Fans of agent-based and system dynamics models are interested in the idea that complexity “emerges” at the macro level from simplicity at the micro level.

Individual actors, following simple behavioral rules at a micro level, can generate “complex” or “chaotic” behavior at a macro level.

The words “emergent”, “complex” and “chaotic” may be interpreted in various ways (as discussed in other papers).

In this context, they usually mean that macro level outcomes are unpredictable and unexpected by observers of the system.


EA prioritises taking a macro-level role/activity centric view over a micro-level actor-centric view.

Why do actor-centric approaches to modelling social networks not feature in EA frameworks?

Because the directors who employ EA teams want enterprise systems that behave, as whole, in an orderly, repetitive way.

Directors want micro-level actors (workers) to cooperate in macro-level activities (work) to meet macro-level goals.

EA is concerned with how an enterprise behaves at the highest and widest level of business system description.

It looks first to the results required from multiple interacting actors, before it defines roles and assigns actors to them.

Business organisation

EA focuses on the behaviour required of business systems.

EA usually maps actors and activities to an abstract business function structure (aka capability map).

Why? Because an organisation’s management structure is volatile, and organisation design is somebody else’s job.


Of course, to change business processes or systems usually requires paying attention to human factors.

It is important to address concerns to do with changes to human roles, the motivation and management of people.

But organisation design and cultural change require knowledge and skills usually found outside the EA team.

Others (line managers, HR, business change consultants, whoever) normally address these matters.


EA is not centred on social organisation design in the way that some management consultants are.

That is a good thing, since it leaves a space for those people to work in parallel with an EA team.

To regard EA as a framework for all social network thinking would surely exaggerate the widespread confusions out there about what EA means.

Surely, it is better to leave a space for business management consultants and others to contribute to business planning in parallel with enterprise architects?

This paper suggests EA frameworks should continue to base themselves on system theory principles.

Seven principles of EA

EA is alive, has a place in the development of business systems.

It is also overhyped, misunderstood and more challenging than some like to admit.

And sometimes gets lost in the space between two questionable schools of thought, one defining technology road maps; another about socio-cultural factors.

So, seven principles are proposed below.

(1) Business systems descriptions abstract from operational systems

A named individual playing a role in a system or capability is a physical “actor”.

An actor is an infinitely complex and ultimately unknowable entity.

Much happens inside an actor - above, below and beyond any description of it.

EA does sometimes name individual actors, but it is not interested in the actor per se

EA is primarily concerned to describe the roles that actors in play in the system of interest.


A named system or capability that behaves according to a description is an “operational system”.

In operation, it is an infinitely complex and ultimately unknowable entity.

Much happens inside it - above, below and beyond any description of it.

EA-level descriptions are the most abstract descriptions of operational systems or capabilities.

(2) Calling an enterprise a system doesn’t make it a system

No social network, though casually called a system, is a system per se.

It only becomes a system when it exhibits system properties you have in mind or have written down.

A business, however orderly it appears, cannot be called a system without reference to a system description.

Moreover, if IBM (say) behaves according to several system descriptions, then it is several different systems at once.

(3) EA as a process is different from EA as a product

EA is a meta system; it intervenes in operational systems, and plans changes to them.

Architects employ social skills and informal methods like stakeholder management.

But the end products are formal operational systems in which actors follow defined rules.

Your personal enthusiasm for following rules may be limited.

Nevertheless, EA is about helping executives to formalise business roles and rules.

(4) Informal "complex adaptive systems” have their place in an enterprise

A manager may give some actors some goals and general principles.

Then direct them to do whatever is necessary – reorganising themselves as need be.

But that is barely a system at all, and largely beyond the reach of EA.

EA describes systems under change control, not changed spontaneously by actors in them.

(5) Silo systems have their place in an enterprise

Silo systems are not standardised, not integrated, and don't share common services.

They can be good, provide a proving ground for innovations, be easy to change in an agile way.

EA teams, looking to standardise and integrate systems, give waivers to silo systems.

(6) EA is political: obtaining and maintaining sponsorship is challenging

EA regards an enterprise as a large and coherent system of business systems.

If asked, executives may say they want to optimise – standardise and integrate - systems.

They would like to reduce cost and quality issues caused by silo systems.

They want to improve data quality and better exploit data collected from processes.

But they don’t necessarily prioritise these things, or realise how challenging they are.

And if sponsorship for EA is limited, then you’d do better to rename your EA team.

Because deploying EA team members as solution or technical architects ends up obscuring what EA is.

“Which exactly describes so many cases.

EA falls back to engaging in decision support (such as projects heat mapping) and project technical design work.

So EA doesn't happen… and what does happen becomes the norm for EA.” Ron Segal

(7) Beware rebranding of business management consulting as EA

Consultants make “interventions” in business systems; some use socio-cultural techniques.

Architects also use such techniques – in stakeholder management for example.

However, EA applies system theory more than sociology.

The key differentiator is that EA presumes business systems are formalised and placed under change control.



All free-to-read materials on the Avancier web site are paid for out of income from Avancier’s training courses and methods licences.

If you find them helpful, please spread the word and link to the site in whichever social media you use.