System?

Copyright 2017 Graham Berrisford. A chapter in “the book” at https://bit.ly/2yXGImr. Last updated 31/05/2021 20:19

 

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This chapter divides systems thinking into two broad schools, both of which are needed. It also outlines ideas explored in other chapters.

Four kinds of system

First, a note on the particular and the general. A general type defines properties shared by individual entities of that type. Given a monothetic type, an individual must have all the properties; e.g. a “triangle” is a polygon with three sides, whose internal angles add up to 180 degrees. Given a polythetic type, an individual need not have all the properties; e.g. “mother” may be typified as a female, birth giver, child rearer, partner of a father.

 

Since the term “system” is used so widely, it might be seen as a polythetic type, which different thinkers define in terms of different properties. The list below distils four particular views, the first two from the 1950s, the second two from the 1970s.

 

·       In cybernetics, Ashby's system is a set of state variables, governed by rules that determine how those variables change over time.

·       In management science, Boulding's system is a population of individuals (actors) with their own private memories, who communicate using messages.

·       In system dynamics, Forrester's system is a set of stocks (quantitative variables) that each grow and shrink, and cause related stocks to grow and shrink.

·       In soft systems methodology, Checkland's system is set of interrelated business activities, performed by actors, that transform inputs into outputs of value to customers.

 

However, the value of generalizing one system type from the four views above is questionable. It results in a vacuous definition of the kind “a whole composed of interacting parts or elements”, which is so widely interpretable as to have no practical application, until the terms are defined in more particular (conflicting) ways.

 

Unfortunately, the idea of a general system theory has encouraged people to over-generalize – to use one term for different ideas, or conflate different things into one. Some borrow words from mathematics and physical sciences (such as non-linear, chaotic, fractal, autopoietic) and use them in discussion of human society with different meanings, or no clear meaning.

Two system thinking schools

Boulding (1956) questioned whether, in applying general system theory to management science, the elements of the system should be actors or roles. Similarly, David Seidl (2001) pointed out that "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."

 

These two alternatives appear in management science and enterprise architecture as two schools of thought, as activity-centric and actor-centric systems thinking. 

 

An activity system is a way of behaving, a set of regular interrelated activities, performed by actors. It can be modelled in terms of roles for actors, rules for activities and results (state changes or outputs produced), also, information maintained in memories and exchanged in messages.

 

A social entity is a community, a set of actors who interact by creating and using information of various kinds. It can be modelled in terms of the various structures (power, reporting, competency and communication) in which, for various reasons, actors interact.

 

A pattern of inter-related activities is one thing; a community of communicating actors is another. A system defined one way can be related to many systems defined the other way. For sure, one activity system may be performed or realized by one social entity, as this table indicates.

 

This activity system may be

performed by this social entity

Nest building

A termite colony

A game of poker

A card school

An orchestral performance

An orchestra

Expense claims and payments

A business

 

But to conflate these two concepts is misleading, because they are related many-to-many. One social entity can perform or participate in many different activity systems. One activity system can be performed by many different social entities.

 

This book will show respected systems thinkers have confused activity systems with social entities. Sometimes they talk of a system as a model or perspective, allowing that different observers may abstract different, conflicting, systems from the same institution. Other times they refer to it as being a system, regardless of any model.

 

Look at any business entity, and you will see actors performing activities to meet some aims. The actors and activities are organized to some extent. However, every real-world business is infinitely complex; it is only well-called a system when, where and in so far as it realizes a system model. Strictly, it is meaningless to point to a physical or social entity (be it a steam engine, a tennis club or IBM) and call it a system without reference to a system model.

 

The roles in a business system may be played by human or computer actors. Of course, the human actors may ignore the roles and rules of any described system, and/or determine their own ad hoc response to a stimulus. While that doesn't complicate any describable activity system, it does complicate the management of any social entity that is supposed to realize some activity system(s) or meet some given aims.

 

An aside for seasoned systems thinkers: the distinction drawn here differs from that between hard and soft systems thinking. Activity systems thinking embraces cybernetics, system dynamics, soft systems methodology (and Ackoff's state-maintaining and goal-seeking systems). Whereas social entity thinking embraces so-called “2nd order cybernetics”, the concerns addressed by Jackson and Senge (and Ackoff's purposive and purposeful systems.)

Activity system thinking

This table outlines three schools of activity systems thinking which have a great deal in common.

 

Soft (business) systems

Ackoff and Checkland

Cybernetics

Weiner and Ashby

System dynamics

Forrester and Meadows

Regular activities transform inputs into outputs wanted by customers

Regular activities maintain variables that describe the state of actors (organisms, machines, societies)

Regular flows increase/decrease variable stocks that represent the state of resources or populations of any kind

Feedback loops connect a business to its environment thus:

a) it detects changes in the state of its environment

b) it determines responses

c) it directs entities to perform activities.

Feedback loops connect control systems to target systems or entities

a) a receptor senses changes in the state of the target

b) a control center directs responses, and

c) an effector changes the state of the target.

Feedback loops connect stocks that respond to changes in each other.

The whole model represents a closed system or ecosystem.

Observers may draw a business activity model.

Observers may observe the current state of a system, and draw a graph to show how the system's state changes over time.

Observers may draw a diagram of flows between stocks, and draw a graph of stock level changes over time.

 

The distinction between hard and soft systems is a distraction. All three schools are about systems characterized by regular activities (physical, organic, social, economic or ecological). All presume several activity systems may be abstracted from one social or business entity. All allow that systems may display complex, non-linear, self-organizing or chaotic behavior.

 

Activity systems thinking is applied every day, all over the world, to physical, organic, social, economic and ecological systems. It is useful whenever we seek to:

 

·       understand how some outcome arises from some regular behavior.

·       predict how some outcome will arise from some regular behavior.

·       design a system to behave in a regular way that produces a desired outcome.

·       intervene in a situation to change some regular pattern of behavior.

 

Generally speaking, an activity system is a regular or repeatable pattern of behavior, such as the motion of a rider on bicycle, a game of poker, or a billing and payment system. This table contains more examples of systems in which actors interact in regular activities to advance the state of the system.

 

System

Actors (active structures)

Activities (behaviors)

State variables

A solar system

Star and planets

Orbits

Planet positions

A windmill

Sails, shafts, cogs, millstones

Rotations that transform wind energy and corn into flour

Wind speed, corn and flour quantities

A digestive system

Teeth, intestines, liver, pancreas etc.

Transformation of food into nutrients and waste

Nutrient and waste quantities

A termite nest

Termites

Disperse pheromone. deposit material at pheromone peaks

The structure of the nest

A prey-predator system

Wolves and sheep

Births, deaths and predations

Wolf and sheep populations

A tennis match

Tennis players

Ball and player motions

Game, set and match scores

A church

People

Roles in the church’s organization and services

Various attributes of roles and services

A billing system

Customer and supplier

Order, invoice, payment

Product, unit price, order amount

 

Core concepts:

 

Actor: an active structure of any kind (person, planet, cell, machine etc). It occupies space. It has either evolved, or has been made, bought, hired to perform activities.

 

Activity: a regular behavior or process, performed by actors over time. The term “regular” implies we are able to describe or model the activity, perhaps in a value stream, flow chart or a causal loop diagram. Activities can create, use and change passive structures (material or information) and active structures (actors). They can advance the internal state of a system, and so produce a “line of behavior” over time, and/or produce outputs, which advance the state of the system’s external environment.

 

Aim: a motivation, desired outcome or goal which is ascribed to a system by an observer. (Some express aims as actual outcomes, results or effects, as might be shown in a line of behavior. This ambiguity is addressed in chapter 2.)

Social entity thinking

"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." David Seidl 2001

 

Person-centric social entity thinking is one thing; action-centric activity systems thinking is another. When people speak of a system, they may speak of a social entity or a pattern of activity. Both are useful views, but the system in one is not the system in the other. It is somewhat unfortunate that even highly respected systems thinkers have flipped from one to the other, apparently without realizing it. If systems thinking is to advance, consistently and coherently, the two schools must be distinguished.

 

“More abstract entities are realised by means of more tangible entities.” ArchiMate 3.1

 

This table shows how abstract activity systems are realized by tangible actors who communicate in a physical social entity.

 

How an abstract activity system is realized

Game of poker

Abstract system: a description of roles for actors, rules for processes and variable types

The rules of the game

Physical system: a performance of defined activities, which gives values to variables

A game of poker

Physical entity: one or more physical actors able to perform the activities

A card school

 

In EA? An enterprise is a business entity of some kind, public or private. It could be an army, coal mine, steel maker, bicycle manufacturer, road haulier, logistics company, bank, insurance company, retailer, hospital, government department, or an internet giant like Amazon.

 

A business entity is a social entity that employs some human actors to perform some activities to meet some aims. To paraphrase Meadows, in observing a system, the actors are the most concrete and tangible elements, the activities are harder to see, and the aims are even harder to see. Conversely, in designing an activity system, the natural sequence is aims before activities before actors.

 

In defining aims, the normal practice is to zoom out, encapsulate the system of interest, and consider the effects it should produce. The overarching concern is the desired outcomes of system activity.

 

In defining the activity system needed to meet aims, the focus is on defining processes that produced desired effects, the rules to be followed and roles actors play in activities.

 

In defining the social entity in which actors are employed, the focus is on how actors are directed, motivated and organised to perform required activities; including general principles for actors to follow, specific aims for their activities, and the structure under which actors managed.

 

Whether your focus is on the activity system or the social entity depends on where you are coming from and what you aim to achieve. You may flip from one viewpoint to the other, but they come with different ideas about what it means for a system to be defined, to exist, and to change or evolve.

Causality and choice

Management science addresses human institutions that – in more or less bureaucratic ways - organize most or some of what human actors do. Typically, these social entities employ many discrete activity systems. And when observing actors’ behavior, we can classify their responses to stimuli into four kinds.

 

Causality

In theory, when an event happens, we can predict

Deterministic

exactly which action an actor will perform in response.

Probabilistic

how likely an actor will perform activity type A or activity type B.

Possibilistic

the actor will choose from the range of activity types in our model.

Self-determining

nothing – because actors can invent activities outside any model made.

 

In so far as a social entity realizes a known activity system, its actors always act in the first three ways. We may not be able to predict which action they choose to perform, but we can say they will choose one of the actions available to them in the activity system.

 

In so far as actors act in the fourth way, they act outside any activity system we know of. Even if they are in acting in an activity system we don’t know about, we must to treat them as having free will, and the ability to do what they choose.

Ackoff’s view of systems

Russell L Ackoff (1919-2009) was an American organizational theorist, operations researcher, systems thinker and management scientist. He was concerned with the management of organized social entities – notably, universities and government agencies. He is perhaps best known the following works.

 

·       Towards a system of system concepts(1971)

·       “Re-Creating the Corporation - A Design of Organizations for the 21st Century” (1999

·       “On The Mismatch Between Systems And Their Models”. (2003)

 

Ackoff’s work draws on two traditions. First, a sociological tradition that can be traced back to the 19 century. Second, activity systems thinking of the kind that emerged in the 1950s in form of cybernetics and general system theory, and later embraced system dynamics. Whereas Ackoff strove to combine these two traditions, it is argued below he might have done better to distinguish the actor-centric and activity-centric viewpoints.

Ackoff’s system of system concepts

In “Towards a System of Systems Concepts” (1971) Ackoff started, some distance from human society, with eleven terms and concepts that appear to derive from cybernetics.

1.     System: two or more interrelated objects (parts or elements).

2.     Abstract system: a system in which the elements are concepts. 

3.     Concrete system: a system that has two or more objects.

4.     System state: the values of system properties (state variables) at a particular time. 

5.     System environment: those elements and their properties (outside the system) that can change the state of the system, or be changed by the system. 

6.     System environment state: the values of environment properties at a particular time. 

7.     A closed system: one that has no environment. 

8.     System/environment eventa change to the system's state variable values.

9.     Static (one state) system: a system to which no events occur (it does not change).

10.  Dynamic (multi state) system: a system to which events occur (its state changes).

11.  Homeostatic system: a static system whose elements and environment are dynamic.

 

A concrete business information system (3) realizes an abstract system (2). The system is open (7) dynamic (10) and interacts with its environment (5). It recognizes input events that represent changes to the state of entities (people, processes, materials and machines) in the environment (8). It maintains system state variables (4). It informs, directs or enables consumers or customers to change the system environment state (6) and meet their aims.

 

The communication between a business and the external actors it monitors and serves or directs may be seen as a regulator-to-target feedback loop.

 

Business activity system

Feedback loop

Business environment

Regulator

ßstate information

directionà

Target

Consumes inputs

Produces outputs

Maintains system state

ß Inputs

à Outputs

External actors

Environment state

Ackoff on abstraction

Above, Ackoff’s abstract system is a model of how a concrete entity behaves, or should behave. He wrote that: “Different observers of the same phenomena may conceptualize them into different systems and environments.” This table illustrates the difference between an abstract system and a concrete system instantiated by a concrete entity.

 

Orchestral music

Abstract system: roles, rules and variable types

A musical score

Concrete system: activities giving values to variables

A performance

Concrete entity: two or more objects able to perform the activities

An orchestra

 

Ackoff wrote wisely about the psychology and sociology of people in managed human institutions, but lost the plot when speaking of them as systems. There is much to enjoy in his view of motivating people to learn, the self-serving nature of the leaders of human organizations and other sociological phenomena. And there are things to dispute in his use of the term "system".

 

In cybernetics, system dynamics and soft systems methodology there is

A.     one observable entity or phenomenon

B.      any number of systems abstracted from it.

 

Although Ackoff began by saying “different observers of the same phenomena may conceptualize them into different systems”, later, he used the term system with reference to the observed phenomenon, as in "every human organization is a system." In his writings and speeches, he typically pointed to how:

A.     some institution (government agency or university) is failing

B.      no model of it can address its failings.

 

Ackoff’s 2003 collaboration with Gharajedagh began by asserting that "most contemporary social systems are failing", which is debatable, and concluded "there is a … mismatch between most social systems and the models of them that are in use", which might be seen as the natural way of things.

 

One might equally well say

A.     an institution typically succeeds in part and fails in part, for multiple reasons

B.      no devisable system can eliminate all causes and risks of failure.

 

The joint 2003 paper implies that human creativity and delinquency make any attempt to equate 1 social entity to 1 system not only contrary to system theory, but daft. The trouble for wider systems thinking is that Ackoff’s use of “system” to mean the observed phenomenon, rather than a model of it, increased the confusion in systems thinking discussion between a social entity and any activity system it may realize.

Remarks and relevance to EA

Look at any business and you will see actors, performing activities, to meet agreed aims. To a greater or lesser extent, the actors are organized and the activities are systemized. It has been said that EA regards an enterprise as a "system of systems". More accurately, EA sees a business as a social entity that employs and participates in several activity systems. 

 

Activity systems thinking is about a network of regular activities performed by actors. Regular or repeated activities advance the state of things of interest (people, processes, materials and machines), which is remembered in the values of state variables and communicated in messages.

 

There is no presumption in activity system thinking that information is digitized. But since 1960, business activity systems have increasingly depended on IT. Commonly, when IT operations stop core business operations stop, it is impossible to continue core business operations in some non-IT-using way, and without access to digital data, the business is sunk.

 

Commonly, a business employs a messy patchwork of activity systems supported by IT, which may interact, overlap, and even be in competition. EA strives to extend and improve these systems, and optimize how they are coordinated to the benefit of the whole. And to do that, EA needs architectural descriptions of those systems.

 

Enterprise architecture

Architectural descriptions

<create and use>                 <represent>

System architects <observe and envisage> Business activities

 

Social entity thinking is about a network of actors who perform activities. EA requires a measure of social entity thinking. To begin with, logical functions and roles must be mapped to physical organization units and actors. Moreover, a business is more than the sum of the activity systems it employs. It is also a social entity, in which actors have some freedom to act as they see fit. The advice in short is:

 

Is your interest where actors

Then use

determine their own actions?

Social entity thinking

 

do both above and below?

Social entity thinking

Activity systems thinking

play roles in regular processes?

 

Activity systems thinking

 

This book looks at both social entity thinking and activity systems thinking, and their relevance to EA. It goes on to expose and resolve ambiguities with reference to five new or newly presented ideas.

 

·       Drawing a clear distinction between social entity thinking and activity systems thinking helps us recognize and resolve ambiguities and confusions in modern systems thinking.

·       Classifying causality into four kinds helps us to characterise what makes social entity thinking different.

·       Representing “change” as a three-dimensional phenomenon helps us to think more clearly about what it means to model change and design for it.

·       Separating meta system from system – allowing one actor to play a role in each - helps us to reconcile activity system theory with “self-organization”, and gives us an alternative to second order cybernetics.

·       Using an "epistemological triangle" to distinguish models from what they model, and relate information to the phenomena it corresponds to, gives us a practical and useful alternative to the classic semiotic triangle.