More you should know - part three

Copyright 2017 Graham Berrisford. A chapter in “the book” at https://bit.ly/2yXGImr. Last updated 05/05/2021 10:58

 

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This chapter divides systems thinking into two broad schools, both of which are needed. And outlines ideas to be explored in later chapters

Contents

Activity system thinking. 1

Social entity thinking. 3

Change. 5

Remarks and relevance to EA.. 5

 

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.)

 

SEE “ACTIVITY SYSTEM THINKING” CHAPTER

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.

Systems thinking is not a movement for social change

Karl Marx referred to Darwinian evolution as though it provided a rationale for political revolution. Some now speak of systems thinking as though it is a movement that will solve problems they see in education, government or the biosphere. Some see systems thinking as a kind of philosophy or socio-cultural mission statement of the kind “everything is connected, and we've all got to work together” or “decentralization is preferable to centralization”. This kind of thinker tends to promote the ideas to the left of this table over the ones the right.

 

Do we value these?

Over these?

Holism

Reductionism

Individuals and interactions

Following processes

Network structures

Hierarchies

Bottom up

Top down

Distribution

Centralization

Collaboration

Client-server relationships

Self-determination of actions

Direction and coordination of action

 

This book does not favor either side of the table. As Clemson said in his 1984 book on “management cybernetics” a systems thinker looks to find the optimal balance between centralization and decentralization. System design is a process that involves making trade-offs between alternative design patterns. The designer’s role is to understand the trade-offs and fit the pattern to the situation. And to prioritise what is achievable over what some might promote as an ideal.

 

Our ability to solve the world's problems by promoting "holistic thinking" and "self-organization" is limited. Moreover, to solve some problems (like climate change) we may need central authorities to agree a set of goals, rules and measures for all.

 

SEE “SOCIAL ENTITY THINKING” CHAPTER

Change

Systems thinkers commonly refer to the adaptation of a system or business. What does adaptation mean? Ashby wrote that the word is commonly used in two senses which refer to different processes. He urged us to distinguish system state change from system mutation.

 

In fact, system change can be classified in three ways: continuous or discrete, state change or mutation, natural/accidental or designed/planned. Representing change as a three-dimensional phenomenon helps us to think about what it means to model change and design for it.

 

 

Continuous

Discrete

State change

Natural

the growth of a crystal in liquid

Natural

asleep to awake, or day to night

Designed

analogue light dimmer switch

Designed

light on to light off

Mutation

Natural

maturation of child into adult

Natural

parent to child

Designed

X

Designed

version 1 to version 2

 

X? Continuous mutation may occur in nature. A designed activity system cannot mutate “continually”, but it can change in discrete steps. Continuous mutation can be simulated by dividing changes into discrete steps frequent and small enough to appear continuous.

 

SEE “SYSTEM CHANGE” CHAPTER

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.