Systems thinking approaches

And some different ways of thinking about system thinking

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Copyright 2017 Graham Berrisford. One of about 300 papers at http://avancier.website. Last updated 01/01/2019 14:46

 

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Gerald Midgley (2000) presented three classes of systems thinking approach as an evolutionary sequence.

This paper challenges both this classification and the notion of critical systems thinking as a major advance.

It proposes some other ways of thinking about systems thinking.

Contents

Midgely’s classification of approaches. 1

Design thinking. 5

The schism between first and second order cybernetics. 6

Conclusions and remarks. 7

Other ways of thinking about systems thinking. 8

 

Midgely’s classification of approaches

Social systems thinkers like to classify systems: e.g. into organisms, animal societies and machines.

They also like to classify approaches to thinking about systems and solving problems.

Midgley wrote of three phases of inquiry

1.      Hard systems thinking approaches

2.      Soft systems thinking approaches

3.      Critical system thinking approaches

 

He presented each class as an advance on the previous class, bringing a new set of methods.

The classification is misleading, for reasons to be explained.

Class 1: “Hard” systems thinking approaches

Midgely wrote that hard systems thinking focused on solving concrete ‘problems’ where there was perceived “unity of purpose”.

He listed the following approaches under this heading.

1956 General Systems Theory (Bertalanffy)

1956 Classical cybernetics (Ashby)

1957 Operations research (Churchman et al.)

1962 Systems engineering (Hall)

1963 Socio-technical systems (Trist et al.)

1965 RAND-systems analysis (Optner)

1971-72 System Dynamics (Forrester; Meadows et al.)

 

Contrary to Midgely’s supposition, hard system approaches are used where the purposes of the system are not agreed.

Even mechanical engineers are taught identify stakeholders and their different perspectives of what a system is for.

 

Abstraction of description from reality

Ashby defined a system as an abstraction from the infinite complexity of any entity that realises it.

A system may be characterised as a set of roles and rules (e.g. the mating ritual of a pair of sticklebacks).

When those abstract roles and rules are realised by a concrete entity, which behaves as described, we have a concrete system.

 

Abstract system

A set of roles and rules (the logic or laws actors follow)

Concrete system

Actors playing the roles and acting according to the rules

 

There is a many-to-many relationship between abstract systems and concrete entities.

One abstract system may be realised many times.

E.g. the roles and rules of tennis may be realised in many concrete tennis matches.

Conversely, a concrete entity may realise any number of abstract systems.

E.g. a pair of people may realise many tennis matches and many games of chess.

 

Note that a social group in the real world is distinct from any abstract social system it realises.

A social system description hides the infinite complexity of the actors and activities in a social group.

And to be scientific, we must describe a system in a way that enables us to test whether a social group instantiates it or not.

 

Differentiation of system state change from system mutation

Ashby distinguished two kinds of system change:

·         System state change: e.g. maintaining the values of defined state variables

·         System mutation: e.g. re-organizing the system, changing the state variables, or the rules that update them.

 

Meadows, in introducing system dynamics, made the same two points as Ashby, above.

Today, akin to system dynamics, there are agent-based approaches to the analysis of systems.

 

Read Introduction to Cybernetics for more on the cybernetic ideas.

Read Introducing general system theory for more on the ideas of three well-known thinkers.

Read System Dynamics for more on the topic and on the ideas of two well-known system dynamics gurus.

Class 2: “Soft” systems thinking approaches

Midgely wrote that soft systems thinking approaches take wider perspective of people and their perspectives.

He said they focus on problems where the purposes of the system are not agreed.

He listed the following approaches under this heading.

1971 Inquiring systems design (Churchman).

1972 Second order cybernetics (Bateson)

1972 Soft systems methodology (Checkland)

1981 Interactive management (Ackoff)

1981 Strategic assumption surface testing (Mason and Mitroff)

1988 Cognitive mapping for strategic options development and analysis (Eden).

 

People do casually point to an entity (or aggregate of entities) in the world and call it a system.

But soft system thinkers see entities, or at least businesses and other social entities, differently.

 

Abstraction of description from reality

Just as Ackoff wrote that different observers of the same concrete reality may see it as different systems.

So, Checkland wrote that a system is a perspective of a reality or “Weltenshauung”.

 

So, the distinction between hard and soft systems is questionable.

And there are different ideas of what a soft system is.

Moreover, Checkland observed the distinction between hard and soft system approaches is also slippery.

Most of the ideas in his methodology have counterparts in approaches used in designing deterministic human and computer activity systems

The main difficulty here is that much soft systems thinking discussion confuses two concepts: social network and social system.

More on this later.

 

Read Soft Systems for more on that topic.

Class 3: “Critical” systems thinking approaches

The word “critical” implies what some call a dialectic.

That is, a logical investigation or discussion of the truth of propositions.

In the 19th century, this was a feature of Hegel’s philosophy and Marxism (which tends to promote dialectic over evidence).

“Critical theory” emerged from the Frankfurt school of sociology, which came to prominence in the 1930s.

 

Midgley presented critical systems thinking as the latest development in a historical progression

He listed the following approaches under this heading.

1983 Critical system heuristics (Ulrich)

1990 System of systems methodologies (Jackson)

1990 Liberating systems theory (Flood)

1991 Interpretive systemology (Fuenmayor)

1991 Total systems intervention (Flood and Jackson)

2000 Systemic intervention (Midgley).

 

Midgely’s reference dates run suspiciously neatly in sequence from class 1 through class 2 to class 3.

Is it meaningful or useful to regard class 3 as an evolution of class 2, which is an evolution of class 1?

Does critical systems thinking really bring new methods that could not be seen in earlier approaches?

 

A logical investigation?

Ulrich (1983) might have been thinking of critical theory when he added the word “critical” to “systems thinking”.

He defined three heuristics of the approach.

 

·         Making sense of the situation: understanding assumptions and appreciating the bigger picture

·         Unfolding multiple perspectives: promoting mutual understanding.

·         Promoting reflective practice: analysing situations – and changing them.

 

OK, but that could be a description of Checkland’s soft system methodology.

Or a “hard” systems engineering method like TOGAF in which people are expected to

·         Look at the big picture

·         Identify stakeholders, their concerns and viewpoints.

·         Define views and value propositions for each stakeholder group.

·         Analyse the current situation and considering changes.

 

So what is in critical but not hard systems thinking?

 

A system transformation framework?

Midgley presented critical system thinking approaches as a post 1980 development of hard/soft systems thinking approaches.

The terms “total” and “systemic” (in the book titles he listed) imply these approaches lead to a root and branch transformation.

The result, if not a revolution, is a major generational change from a current state of being to a new state of being.

 

OK, but this sounds like Michael Porter’s idea (1985) of radical business process reengineering

Or a “hard systems” approach like TOGAF in which business transformation involves

1.      modelling a current system (N): analysing, discussing and criticising it, envisaging changes.

2.      modelling a target system (N+1): discussing, reviewing and agreeing it.

3.      planning the change from system N to system N+1.

4.      changing system N to system N+1.

 

Of course, every systems thinking approach recommends documenting mental models for discussion and agreement with others.

They recommend the kinds of model you can or should document.

They recommend using techniques such as stakeholder management and risk management.

All these ideas appear in both hard and soft systems thinking approaches.

So what is in critical but not hard systems thinking?

 

System encapsulation?

One reader has suggested encapsulation of systems is a feature of critical systems thinking.

Yet agreeing the boundary of a system (expanding it, contracting it, or shifting it) has always been a feature of general system theory.

So what is in critical but not hard systems thinking?

 

An advanced approach?

Of course gurus like to present their preferred approach as the latest development in a historical progression.

That doesn’t mean their approach evolved from past ones, or applies the core ideas of general system theory.

Read Marxism and System Theory for a challenge to the notion of inexorable progression.

So what is in critical but not hard systems thinking?

 

A unified approach?

It has been proposed that critical systems thinking unifies different systems approaches, and advises managers how best to use them.

But so does any general architecture framework like TOGAF.

And a truly comprehensive unification has to address the deep schism in systems thinking – to follow.

Design thinking

Before we get to the schism in systems thinking, it is worth mentioning another school of thinking.

Design thinking embodies principles described by Herbert Simon in “The Sciences of the Artificial” in 1969.

 

A core idea is that designers spend a lot of time up front deciding the basic, fundamental (root) issue that needs to be addressed.

They don't search for a solution until they have determined the real problem.

They consider a range of potential solutions before settling on one.

 

The Hasso-Plattner Institute of Design at Stanford promotes a design thinking approach with five phases.

But these phases aren't strictly sequential process steps – they can occur in parallel and be repeated (exactly as TOGAF says of its processes).

·         Empathise – with your users

·         Define – your users’ needs, their problem, and your insights

·         Ideate – by challenging assumptions and creating ideas for innovative solutions

·         Prototype – to start creating solutions

·         Test – solutions

 

Design thinking is less a method than a label for a collection of ideas such as.

·         Capture the inspiration, the vision.

·         Take a human-centric view of business roles and processes.

·         Manage stakeholders and value propositions.

·         Treat all design as re-design, as a baseline to target transformation.

·         Make ideas tangible to facilitate communication.

·         Use visual languages, sketch diagrams and technical drawings to show abstract requirements may be met by concrete systems.

·         Double loop learning.

 

All these ideas have long and widely been used in conventional (hard and soft) system design methods.

The last idea is of particular interest here.

 

Remember the distinction made by W Ross Ashby in 1956 between system state change and system mutation?

Single loop learning is the everyday response to some condition.

E.g. A thermostat detects a room temperature less than the selected temperature, turns on the heating, and keeps it on till the room temperature equals the selected temperature.

By contrast, double loop learning analyses why the system exists, and considers ways to change it.

E.g. Why is the room heated at all? What is the best way to heat it? Does it need better insulation?

The schism between first and second order cybernetics

Today, so-called hard systems approaches clearly include ideas found in:

·         soft systems approaches

·         critical systems approaches

·         design thinking approaches.

 

Checkland observed the distinction between hard and soft system approaches is slippery.

The distinction between hard and soft systems is also questionable.

By contrast, the distinction between classical and second-order cybernetics is fundamental.

 

Remember Ashby insisted we should on no account confuse two kinds of change.

 

 

Changes

For example

System state change

the value of at least one state variable

homeostatic regulation of values to stay within a desired range

System mutation

the type of at least one variable or behavior.

re-organization changing the variables or the rules that update their values.

 

Classical cybernetics is about maintaining the values of defined state variables.

Ashby used the term adaptation in the context of homeostatic state change.

Systems thinkers often use the term adaptive in the second – mutation – sense

And moreover, they mean the system is self-organising.

 

Second-order cybernetics was developed around 1970 by Margaret Mead, Heinz von Foerster and others.

It is about self-organising systems; it is the recursive application of cybernetics to itself.

It allows systems actors to be system thinkers, who re-organise themselves.

It allows actors in a system to study the system and change it.

Actors not only play roles in a system, but also observe and change the roles, rules and state variables of that system.

 

What if actors may change a system continually, rather than incrementally, generation by generation?

Read the following papers for how second-order cybernetics and “complexity science” undermined the concept of a system.

Conclusions and remarks

A "situation" or "system" is not a “problem” per se; it is only a problem to an observer.

A problem is a measure of a system’s quality (cost, benefit, speed, etc.) that an observer does not find satisfactory.

 

It is important to distinguish between changing a social system and changing the social network that realises the system.

If there is a problem in the system’s structure and/or behaviors, then the system might be changed.

If there is a problem in the actors’ competencies and/or motivations, then without changing the system, the actors might be retrained, motivated or replaced.

 

There is plenty of advice on how to describe system structures and behaviors, and their qualities.

However, much systems thinking discussion has conflated two or more of the following four ideas.

·         People doing their own thing.

·         People communicating with other people.

·         People playing roles in systems.

·         People playing roles in meta systems that administer and manage those systems.

 

The next paper explores the distinction between:

·         A social group or network in which people communicate

·         A social system in which people realise role and rules.

 

In classical cybernetics, a social network can realise a concrete social system.

But it only does this in so far as its concrete actors follow the roles and rules in an abstract social system.

When actors act in ad hoc, irregular or disorderly ways, they act outside of that system.

And if they follow a different set of roles and rules (either in parallel or at another time) then the same social network realises a different system.

 

By contrast, in second order cybernetics, the actors in a social network can define the system they act in.

The actors may radically change the roles and rules of a system are engaged in - perhaps even change its aims.

For how to resolve confusion created by second order cybernetics, read Social networks versus social systems.

 

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

General system theory remains good to know, good for the soul, and practically useful thinking about what is happening in social networks.

Other ways of thinking about systems thinking

This final section restructures Midgley’s classification of systems thinking approaches

And before that, it proposes several other ways to classifying thinking about systems thinking.

 

·         Stateful systems versus stateless systems

·         Loosely-scripted versus tightly-scripted processes

·         Activity-oriented versus aim-oriented approaches

·         Strong systems versus weak systems

·         System thinking versus situation thinking

 

The actors of a business interact, directly or indirectly.

Sometimes they interact to meet aims of the business, sometimes they act to meet their own aims.

The actors form a social network that can realise many systems – even conflicting ones.

Each of those systems has a current state, which is advanced by processes.

 

Stateful systems versus stateless systems

Stateless systems, which maintain no persistent structure or memory, are of little interest here.

Our interest in systems that do maintain a persistent structure or memory.

 

The actors on a production line collaborate to build the structure that is a motor car.

The state of each motor car is advanced by the processes the actors apply to it.

In a small business, their roles in that collaboration might be loosely scripted.

But most car manufacturers have scripted the roles so tightly that most actors have been automated in the form of robots.

 

Social systems are ones in which actors share and remember information about the world.

Their memory of past events influences how actors respond to future events.

 

A business system can be seen as a formalised social system in which the memory is persisted.

Information is persisted, for future access, in the data structures of messages, documents and databases.

And once persisted, the data structures can be shared, can be accessed by many actors.

 

Loosely-scripted versus tightly-scripted processes

The processes of a business system advance the state of its persistent memory.

Those processes may be more or less tightly scripted.

 

Tightly-scripted (procedural) processes

One or more actors may play defined roles and perform defined activities in end-to-end procedures or workflows. E.g

·         Booking a train seat

·         Applying for a job

 

In the course of an end-to-end procedure, actors may access and update one or more shared data structures.

Often, different roles have different rights to update different parts of the data.

There is usually an end goal, and the procedure ends when it is reached.

 

Loosely-scripted processes

One or more actors may be invited to do what they judge necessary to progress the life history of a data structure. E.g.

·         A document, e.g. a plan for work to be done.

·         A topic on a message board; e.g. a Linkedin discussion thread

 

In a loosely-scripted system, actors may be given considerable freedom of choice over their actions.

To some extent, they may choose which activities they perform (e.g. post message, reply to message, edit message, delete message).

To some extent, they may choose which sequence they perform those activities in.

And they may be given roles that enable them to collaborate in an informal way.

 

Note that even in what appears to be a non-procedural system there are some defined roles and rules.

On a message board, the author role is distinguished from other contributors

The process flow may divide into parallel threads, each with its own constraints: e.g. (post > reply* > delete) and (post > edit* > delete).

If there are no roles for actors and rules for activities, if actors’ activities are wholly unconstrained, then there is no system, only a social network.

 

A loosely-scripted process may have a goal and terminate when the data structure reaches a desired state – e.g. a document is approved.

Or else, there may be no end state - other than deletion of the data structure.

 

Activity-oriented system versus aim-oriented social network

The table below contrasts two management styles which correspond to the schism in systems thinking

 

 

Activity-oriented system

Aim-oriented social network

Processes are

tightly scripted

loosely or not at all scripted

Activities are

tightly constrained by rules

loosely or not at all constrained by rules

People are given

roles and rules follow

targets only

E.g.

call centre operators

door-to-door sales people

 

Classical cybernetics

Second order cybernetics

 

Some approaches focus on defining aims (purposes, goals or targets) and motivating a group of people to meet them.

You may do this with little or no attention to defining roles for actors and rules for activities.

At the extreme, aim-oriented management means simply asking a group of people to meet some goals by doing whatever they choose.

You rely on the individuals’ abilities to interpret your directions and choose behaviors that lead to the given aims

If the nature and nurture-given abilities of the actors are up to it, they may succeed better than you expected.

 

Most people management involves some process-orientation and some target-orientation.

The question here is not which is better or worse, more or less advanced, it is whether it target-oriented management is well-called “systems thinking”.

At the extreme, there is a social entity, a social network, but no social system - as the term is defined here.

Because a system is a set of roles and rules that determine who can do what and when.

 

Strong systems versus weak systems

The table below is one of several system classifications I have toyed with.

I don’t mean to present this as a scale of complexity, or a progression of any kind.

 

System kind

Description to reality relationship

Examples

Strong or

Involuntary

System

 

 

Weak or

Voluntary

System

The script is embedded in the mechanisms of the concrete reality

Designed

Cuckoo Clock

Natural

Solar system

The script (DNA, code) is followed rigidly

Designed

Software system

Natural

Earthworm

The script is followed loosely, as closely as actors choose

Designed

Orchestra, Church

The script is written by the actors, more a social network than a system

Natural

Marriage, Small business

 

System thinking versus situation thinking

Classical cybernetics is scientific in so far as its deals with behaviors that are regular, or deterministic, or reproducible.

Actual (empirical) performances of behaviors are tested for conformance to abstract (theoretical) descriptions of those behaviors.

As, for example, the actual orbits of planets are tested for conformance to astronomers’ descriptions of those orbits.

 

Social system thinking can be seen as a kit bag of ideas and techniques for “situation thinking”.

Some approaches are scientistic, meaning there is little or no evidence to verify or falsify them.

 

It easy to find problems in human organizations.

From the 1970s onwards, systems thinkers have claimed institutions are in crisis, and something must be done.

Surely, institutions will always have problems, and system thinking will never provide a final answer to those problems.

It will always be necessary to intervene now and then.

 

It is more difficult to propose viable changes, and more difficult again to make those changes.

Where an intervention involves describing regular behaviors, realizing them and testing the outcomes, it is an application of classical system theory.

But consultants may make interventions of others kinds – with little or nothing by way of process definition or testing of outcomes.

Even after a change has been made, it can be difficult to prove whether the change was for the better or not.

 

It isn’t always clear that the situation addressed is a “system” beyond being a social network - a named organization or named group of actors.

If every problem or situation or social network is called a “system”, then the word system adds nothing to our understanding.

A problem/situation might be a system, or it might not.

The solution might be the description, testing and implementation of a new of changed system, or it might not.

 

Reshaping Midgely’s classification

Of course, seeing a business as a social network is important; and is a primary responsibility of business managers.

Management consultants continually generate approaches to identifying problems in social networks and solving them.

The question here is whether classifying all these approaches as varieties of "systems thinking” has a useful meaning.

If every problem or situation is a system, if every entity we name or point to is a system, then the term “system” is meaningless.

This table expresses the schism between two kinds of “system thinking”.

 

General system theory

Social network thinking

Classical cybernetics

Second order cybernetics

General to all domains of knowledge

Specific to situations in which humans interact

About roles, rules and regular behaviors

About individual actors who are purposeful people

About describing testable systems

About solving a social or business problem in a consensual way

Apolitical

Promoting a “participative democracy”

 

This table reshapes Midgely’s 3-way classification into a 4-way classification.

 

A 4-way thinking classification

About

Midgely’s classification

General Systems Thinking

A network of actors performing regular behaviors

Class 1 hard systems thinking

Classical cybernetics

Social System Thinking

A network of human actors performing regular behaviors

Class 2 soft systems thinking

Social Network Thinking

A network of human actors who choose their behaviors

Class 2 soft systems thinking

Second order cybernetics

Situation Thinking

Problematic situations

Class 3 Critical system thinking

 

 

 

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