Social entity thinking – and its application to EA

Copyright 2020 Graham Berrisford. Now a chapter in “the book” at https://bit.ly/2yXGImr. Last updated 24/01/2021 20:19

 

For a preface outlining the motivations for this work, click here.

 

Contents

PREFACE. 1

MANY VIEWS OF SOCIETY.. 2

AIMS. 8

ORGANIZATION STRUCTURES. 11

SOCIAL ENTITY EVOLUTION.. 15

CONCLUSIONS AND REMARKS. 17

 

 

 

 

PREFACE

 

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

 

In 1956, Kenneth Boulding wrote on what was becoming known as management science. In his article, he presented general system theory as the skeleton of science. He asked what are the elements of a social system? Are they actors, or the roles actors play in activities?

 

This question has hung over social system discussions since the nineteenth century. "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." Seidl 2001

 

We may put people at the centre of our thinking: e.g. study the people in a card school. Or put actions at the centre of our thinking: e.g.  study the game of poker. The example features three systems thinking concepts.

 

Abstract activity system

the rules of poker

Physical activity system

a poker game in progress

Social entity

a card school

 

A system's actors may be only part-time, and perform activities in other systems. E.g.  most card school members both play poker and pay taxes.

 

It has been said that enterprise architecture (EA) regards an enterprise as a "system of systems". Better, say EA sees a business as a social entity. That social entity may realize any number of (possibly conflicting) activity systems. EA strives to extend, improve and coordinate those activity systems.

 

EA as activity system thinking

EA is primarily concerned with activity systems employed or deployed by a business. A business activity system may reasonably be defined as orderly and dynamic. It is characterized by regular activities, performed over time.

 

Activities are performed by actors (people, computers, other machines) that occupy space. Actors and the resources they need are organized and interconnected. Activities advance the state of things (people, processes, materials and machines of interest).. The state can be remembered in the values of state variables and communicated in messages.

 

EA looks for which activities are better systematized and which are better left to local or even individual human judgement. However, EA does need some social entity thinking as well.


EA as social entity thinking

Thinking of an ant colony sits at an extreme end of social entity thinking. The actors (ants) perform only regular activities in recognizable systems (nest building. By contrast, in a human society, the actors are free to invent aims and activities. They can make ad hoc decisions that lead them down novel paths. Suppose innovation is taken to an extreme; and the actors continually innovate. So, there is no pattern of behavior, no observable regularity or repetition. Then, there is no recognizable activity system in the social entity.

 

The advice in short is:

 

Is your interest what actors do to

Then use

meet aims however they choose?

Social entity thinking

 

do both above and below?

Social entity thinking

Activity systems thinking

play roles in regular processes?

 

Activity systems thinking

                                                                                                 

This chapter looks at social entity thinking with regard to EA. The next chapter looks at activity systems thinking with regard to EA.

 

MANY VIEWS OF SOCIETY

 

This section reviews several of many ways of looking at human society.

Society as organism

Many ideas discussed by systems thinkers today emerged more than a century ago. The first sociological thinkers include Herbert Spencer, Emile Durkheim, Gabriel Tarde, Max Weber, Kurt Lewin and Lawrence Joseph Henderson. Some drew some terms and concepts from biology. Notably, homeostasis, hierarchy, roles and rules. And the emergence of effects or results from interactions between autonomous actors.

 

Then and today, some liken a human organization to a biological organism.  Like many metaphors, this can be more misleading than helpful.

 

·       In biology, the response of a cell to an input falls within the range of activities allowed by the biochemistry of the organism. By contrast, in sociology, the response of a human actor in an organization to an input may be not only unpredictable, but also purposefully innovative.

 

·       Organisms cycle around processes that maintain their state. By contrast, organizations progressively advance their state.

 

·       In an organism, a cell has its role and cannot be repurposed. By contrast, in an organization, a human actor can play several roles, and choose which to play.

 

·       An organism does not choose or change its inherited mechanisms. By contrast, an organization does choose and change the mechanisms it employs and deploys.

 

·       Organisms evolve by whole-scale replication (the young replace the old) with tiny mutations. By contrast, organizations evolve well-nigh continually, now and then adding a part discarding a part, or replacing a part by a new and different one.

 

The purpose of EA is to optimize the activity systems of a business, to standardize and integrate them. And to plan changes that increase the efficiency and effective of the business. It is rarely to transform the whole business all at once.

Society as tribe

The societies from which we emerged (and still prevail over much of the world) were dominated by clans and tribes, in which loyalty to kin overrides any other consideration. What seems a virtue in a family can be a corrupting influence in business.

 

Some anthropologists concluded 25 people is the magic number for a tribal community. That number includes children, elders and only 7-8 productive foragers. "The Foraging Spectrum: Diversity in Hunter-Gatherer Lifeways." (Robert J. Kelly ,2007).

 

Add a dash of biology to the story.

In many animal communities, from chickens to primates, there is a dominance hierarchy. "Social hierarchy is a key element in the organization of many human and nonhuman groups that undertake collective and cooperative activities. Dominant group members standing at the top [have] benefits including priority access to limited resources (food, mates, space). To maintain their position, dominant individuals exercise behavioral tactics that rely on subtle interplay between cooperation, affiliation, and aggression directed toward subordinates. In contrast, submission, though it limits the access to resources, allows weaker and less skillful individuals to minimize consequences of aggressive encounters [they don't get beaten up]." Quoted from this paper.

 

Neuro-scientific studies conducted during the last decade have pointed to the role of the serotoninergic system in establishing social hierarchies in primates and humans.

"In macaques, alpha males have twice the level of serotonin in the brain as subordinate males and females. Dominance status and CSF serotonin levels appear to be positively correlated." Quoted from Wikipedia on seratonin.

 

In business, a decision is often made by the socially dominant members of a team, though a matrix comparing options may be used to rationalize the decision. Sometimes that is OK, because the dominance hierarchy reflects a competence hierarchy, but not always.

 

In the modern "information age", tribes are nested, overlapping and fluid. Social entities are volatile, they merge and divide. Moreover, one actor can belong to different groups with different aims. Questions for the social entity thinker include: How does an actor join or leave a group? Who determines membership? Are there degrees of membership? Is it full time or part time? Can or should actors align their individual aims with the declared aims of all (potentially conflicting) groups they belong to?

 

EA may reasonably view a business organization as a tribe in which loyalty to the aims of the directors is a strong influence on employee behavior. And conformance to the rules of specific activity systems can reasonably be expected - though allowances should be made for exceptions.

Society as homeostat

The idea? The biologist Claude Bernard introduced the idea that a homeostatic organism, maintains its state in equilibrium.

 

Several early sociologists compared human societies to organisms. Spencer declared three principles for a social system:

 

A common idea in sociology is that a society (or its members) has an equilibrium. It resists changes and strives to maintain its roles and rules. The idea appears today in the idea of the "social cell".

 

How homeostasis is maintained by feedback loops between control and target systems is the domain of cybernetics. Ashby’s "Design for a Brain" and "Introduction to Cybernetics" provide a foundation for much modern activity system thinking. For ten cybernetic principles applied in EA, read this chapter.

 

Stafford Beer treated a business as homeostatic. Beer applied cybernetic principles to the supply chain of state-run businesses in Chile. Later, in "The Brain of the Firm", he used the structure of the central nervous system as a metaphor for the structure of a business organization.  Systems thinkers often use metaphors to discuss the structures of social entities. For my discussion of how Beer applied cybernetic ideas to management science, and the metaphor he used, read this chapter.

 

EA is much concerned with the information a business needs and uses to monitor and direct actors in its environment. Today, much social systems thinking discussion is less about homeostatic stability and more about system evolution or innovation. And of course, EA is about the design and planning of changes to business systems.

Society as knowledge builder

The idea? Knowledge comes from social interaction. The sociologist Herbert George Blumer (1900 to 1987) wrote of “symbolic interactionism”, which rests on premises about human activities. The table below compares his thinking with activity systems thinking.

 

Activity system thinking

Blumer’s social entity thinking

Bias

Regular activities are performed by actors

Actors interact in activities

Activities effects

Change the state of objects and communicate information.

Same.

Information

Encoded in the symbols or data structures of messages and memories.

Same.

Actors create and find information in

Symbols, using a language.

Social interactions

Communication

Successful communication requires actors to share a language - to share the meanings of symbols

Actors handle and modify meanings through an interpretive process (they interpret a message as they see fit)

Generation system change

Between discrete generations of a system, its language may be changed.

There is no concept of generational change to a system or language.

 

Blumer's thinking is variety of social constructivism, which sees human development and knowledge as constructed through interaction with others. Clearly, animals acquired knowledge of the world eons before they communicated more than mating intentions to each other. And humans acquire knowledge in other ways, not the least being a process of trial and error.

 

So, social constructivism can be only a partial explanation of knowledge acquisition. And social verification is a weak way of verifying knowledge. For a wider psycho-biological perspective of knowledge acquisition and verification read the second half of this book.

 

EA is much concerned with how a business, through interactions, acquires knowledge about entities and events of interest.

Society as autopoietic (self-sustaining)

The idea? Maturana proposed autopoiesis to be the unique and defining feature of a life form. It is the self-sustaining process by which a biological organism manufactures its own structures from primitive chemicals. And those same structures perform those same self-sustaining processes.

 

Stealing the term rather than the concept, by way of an analogy or metaphor with biology, Nicklas Luhmann defined a theory of "autopoietic social systems".  It is based on the idea that for every particular topic or theme, there is a self-sustaining system of communication events.  Hmm.. Who defines the themes?

 

Note that Luhmann and many other sociologists hold to the (hermeneutic?) idea that the meaning of a message is determined only by its receiver(s). So, not only may different receivers may associate one message with different themes, but what the sender meant to say doesn’t matter.

 

Luhmann's system is purely conceptual. There is no way to capture or record his communication events about a theme. So, his theory is abstract to the point of being metaphysical, it is not testable in the real world.

 

For my analysis of Luhmann's theory, read this article.

 

EA is much concerned with messages and memories. With communication events that monitor or direct business entities and events of interest. As in general, meaning is not in a message alone; there is a meaning in both the intent of the sender on encoding a message and the interpretation of a receiver on decoding that message. Those two meanings may match or differ. EA usually presumes they match, because senders and receivers share a language. There is a domain-specific language that defines the meanings of business terms such as "order", "invoice" and "payment".

Society as network structure

The idea? A society is a structure that connects people in communication and/or dominance relationships.

 

For sure, actors do interact in networks, hierarchies, chains and other definable structures.  And many sociologists have discussed societies in terms of such structures. Some turn to terms and concepts from harder sciences.

 

Graph theory is a field of mathematics (well introduced by Robin Wilson). It is concerned with how things connect in network structures. There is considerable interest in applying graph theory to social entities. In my view, its relevance is debatable.

 

Over a given period of time, you might monitor electronic communications between the actors in a given network. You may well find actors group themselves into more or less cohesive clusters. (Actors interact frequently within a group, and less frequently with other actors in other groups.) You may also find clusters are nested, at several levels of hierarchical composition.

 

No great surprise there. What to conclude from such analysis? Observing over a different period of time, you may find different clusters. And on its own, applying graph theory to human society is naive. Having said that, anthropologists have studies societies in the real world.

 

"Although humans are capable of living in structurally diverse societies, our communities, even in the digital world, have a distinctive layered structure, with successive cumulative layer sizes of 15, 50, 150, 500 and 1500." https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5756541/

 

EA makes extensive use of hierarchical structures to make sense of and manage complex networks, as discussed later in this chapter.

Society as an ecology of interacting organizations

The idea? Human health and welfare are advanced more by an ecology of trading relationships between autonomous tribes or organizations than by warfare or central planning.

Free trade and fair competition between autonomous agents is not only a complex system in itself, but has produced amazingly complex systems.

Did you know that a toaster may have 400 interacting components, a Boeing 747 has six million components, and Google has two billion lines of code?

 

"It’s easy to forget how systems of free exchange miraculously assemble complex systems. The minute division of skills required for the manufacture of each component, the role of prices in signaling scarcity, the supply chains linking sub-providers - all this happens spontaneously and rather beautifully. In a system of free exchange, individuals succeed not by favoring kin over strangers, but by cultivating a reputation for impartial fairness and co-operation, because these qualities will help them attract the most customers and the best business partners. People in market societies tend to score higher on trustworthiness. Other societies lie at significantly higher rates" Matthew Syed in “Join me in a toast to capitalism

 

EA is much concerned with how a business, in a particular market, interacts with its customers and suppliers - in the regular and repeated operations of the business - by way of exchanges of information, sometimes associated with materials.

Society as an organization within a market

The idea? A business organizes how actors cooperate to meet the aims of the business. Max Weber spoke of a bureaucratic model, with a hierarchy, roles and rules.

 

In EA, the social entity of interest is usually business organization or a subset thereof. The internal actors are readily identifiable (perhaps by having employee numbers). They are employed to play roles and expected to follow rules. And EA is about those regular roles and processes that create and use business data.

Society as an organization to be “developed”

I don’t know much about “organization development”; follow that link to learn more. But the definition below suggests it is a social entity thinking approach that may involve some activity systems thinking.

 

“Organisation Development (OD) enables people to transform systems. OD is the application of behavioural science to organisational and system issues to align strategy and capability. It enhances the effectiveness of systems through interventions that enhance people’s collective capability to achieve shared goals.”

 

Let us move on to discuss goals, after a few remarks on enterprise architecture

Relevance to EA?

EA is about the modelling, planning and designing business activity systems A large proportion of what enterprise architects do is underpinned by activity system thinking. However, holism not = wholeism; EA cannot define the whole of a business as one activity system. Rather, it identifies where selected parts of a busines act holistically in regular or repeated ways. Architects may identify many activity systems (nested, overlapping, competing) in one social entity. And look to optimize how those systems are best coordinated to the benefit of the whole.

 

Moreover, EA requires at least some measure of social entity thinking. At the very least, logical functions and roles must be mapped to physical organization units and actors.

AIMS

 

In her primer on systems thinking, Meadows defined a system in terms of not only actors and activities, but also purposes or aims. “A set of actors and resources that is coherently organized and interconnected so as to perform a characteristic set of activities, to achieve some aims". Similarly, a social entity thinker may characterize a system as a network of actors that communicate with each other to meet some shared aim(s).

Ackoff’s view of aims

Russell Ackoff was a brilliant observer of humans, their institutions and their failings. 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".

 

Ackoff's interest was in systems that are open and dynamic. They consume inputs from, and produce outputs that change the state of, their environment. In an effort to build a unifying system theory that bridges the schism between machines and social entities, Ackoff built elaborate hierarchies of aims, activities and four system types. The graphic is my attempt to stitch his system ideas together in a coherent whole.

 

Ackoff’s system classes

Actors (parts)

Activities (parts)

Aims (purposes)

State maintaining system

Play roles in an activity system

No optional activities

Fixed aims

Goal-seeking system

ditto

No optional activities

Fixed aims

Purposive system

Are members of a social entity

Define their own activities

Fixed aims

Purposeful system

ditto

Define their own activities

Define their own aims

 

The first two kinds of system are activity systems with a fixed range of possible activities. Ackoff surely realized they could be deterministic. I don't know if he recognized they could instead be probablistic or possibilistic.

 

Ackoff's primary interest was in social entities of the third and fourth kinds. He assumed actors can define their own activities, or even aims. He characterized these social entities as being "purposive" or "purposeful". The aims of a purposive social entity lie in the desire of external actors. They want the entity to produce particular state changes in the state of its environment. The internal actors may be seen as slaves to that end. The aims of a purposeful social entity are found in the desire of its internal actors. They want to produce internal and/or external state changes that benefit themselves.

 

Must a social entity be one or the other? It can be both, It may be called purposive where it is shaped by the aims of external actors. Those actors may include sponsors, stakeholders, managers, designers and others. It may be called purposeful where it is shaped by the aims of actors who play roles in the system. In a purposeful social entity, actors may change not only their activities but also their aims, in ad hoc ways.

 

OK, but if there is no regularity or repetition, then what is systematic or systemic about it? Ackoff's purposeful system "can change its goals in constant environmental conditions; it selects goals as well as the means by which to pursue them. It displays will.” However, it does have one stable feature - an "ideal" - which Ackoff said is unobtainable. Who defines it? Who knows what it is? Why can it not be changed?

 

Ackoff did a great job of highlighting the failings of organized social entities. Especially "public" ones such as government agencies and universities. However, he is partly responsible for spreading the confusion in "systems thinking" between social entities and activity systems. For managing the former, we need some wisdom. For designing the latter we need some science.

 

For more on Ackoff's ideas read the chapter on activity systems thinking.

Two kinds of purpose (intent and outcome)

Purposes can be motivations - aims we have - reasons to do things. Or else, purposes can be uses we find for things, and outcomes of systems we observe.

Purpose as intent

This concept implies envisaging a future, having aims, then acting with intent to reach them. Many animals retain memories, and use them to compare new sensations with old ones. Some animals (not only humans) display consciousness of their environment. Consciousness give them the ability think about the past and envisage the future. And so to have intentions, to set aims and act to achieve them.

Purpose as outcome (POSIWID)

Some system theorists regard the emergent outcomes/effects of a system as its aims. Stafford Beer and others have said: "the purpose of a system is what it does" (POSIWID).

 

POSIWID is teleological. Teleology is the explanation of phenomena in terms of the purposes they serve, rather than of the causes by which they arise. In Thailand, generations of macaque monkeys have used stones to open oysters and nuts. Is the existence of the stones explained by the uses monkeys make of them?

 

“Biologists do speak of the purposes of the heart, or the liver, or a kneecap. But that is just a way of speaking. The teleological metaphor was just a metaphor: underneath it lay quite simple mechanical explanations. Today’s scientists are pretty certain that the problem of teleology at the individual organism level has been licked. Darwin really was right." https://aeon.co/essays/what-s-a-stegosaur-for-why-life-is-design-like

What is a system’s purpose? Outcome or intent?

Meadows' Primer in Systems Thinking appears to use the terms function, purpose and goal both interchangeably, and with different meanings. The authors slip from one context to another. The first half of the book discusses activity systems (networks of activities), in which purposes outcomes (POSIWID).

 

“A system’s function or purpose is not necessarily spoken, written, or expressed explicitly, except through the operation of the system. The best way to deduce the system’s purpose is to watch for a while to see how the system behaves. Purposes are deduced from behavior, not from rhetoric or stated goals”

 

Obviously, everything we say, do or create can have effects that are mix of intended and unintended consequences. To speak of unintended consequences as being designed or purposeful seems perverse, however clever-sounding the resulting POSIWID aphorism.

 

The second half of the book discusses social entities (networks of actors), in which purposes are intentions.

"one of the most powerful ways to influence the behavior of a system is through its purpose or goal" "a change in purpose changes a system, even if every element and interconnection remains the same".

 

We can't have it both ways. Either purposes are inexorable outcomes of systems, or they are what we intentionally direct or shape a system to do. Better, we say one of the most powerful ways to influence the behavior of a social entity is through its purpose or goal, By changing its purpose(s) you can change the activity system(s) that a social entity realizes, and the outcomes it produces.”

Team and personal aims

Peter Senge recommends building a shared vision from personal visions through interaction, give and take. Inevitably, some people may be obliged to suppress a personal aim or vision that others in the same social entity don't share or don't accept.

 

Aside: You don't belong to one social entity; you belong to many, with potentially conflicting aims and visions. Today, the internet helps you do the reverse of what Senge suggests, which is to discover groups that already share your personal vision. The applications you use on the internet direct you toward groups that share your interests. Not always a good thing.

Directors aims

Obviously, EA starts from analysis of the mission and vision of a business, drivers acting on it, and the goals declared by business directors. Sometimes the goals are defined in a hierarchy of aims, or a "balanced score card". Sometimes that hierarchy is mapped to the organization structure.

ORGANIZATION STRUCTURES

 

The actors in one social entity may cooperate in any number of activity systems. Conversely, one activity system can be realized by several social entities. How does the concept of an "organization" relate to those two ideas?

 

Hmm... do the words society, organization and system represent one, two or three concepts? How do they relate? Can one change without changing another? Can actors act in several (perhaps conflicting) organizations or systems? Can actors act within your organization, yet outside any system it employs?

 

Generally speaking, the term organization can refer to any order in a structure or behavior. Sociologists use the term organization with two different meanings. A pattern of behavior, a repeated pattern of inter-actor communication in a group or network of actors from which properties emerge (an activity system). Or else: the management structure of a social entity under which human actors are arranged to perform the required activities. This second is the meaning used here, and in EA.

Trade offs

Generally, a social entity is a network of actors that perform a network of activities. But for management purposes it is normal to impose some structure(s) on the network. An organization's management structure is usually a compromise between many possible structures - each having its own pros and cons.

 

A history of civilization might be told in terms of these scales.

·       centralization and standardization <> decentralization and local variation

 

Human organizations strive to find the sweet spot on each scale above.

 

Aside: Today, a tendency to centralize bottom-up from the eagerness of individuals to make themselves customers of global businesses (for whatever price or quality reasons). And accept their activities being monitored by those companies.

How about a decentralized collective network organization?

Some, perhaps applying a political philosophy, oppose hierarchical organization. They recommend flattening hierarchies and cutting out middle managers.

 

Some go further, as suggested by Pia Macini in this video https://bit.ly/3hQdSKO. Pia seeks an organization model in which no individual has to make decisions or take responsibility. She envisages a collective as a distributed network with no legal entity or bank account. However, she proposes no other way to gather, hold and distribute money. She makes a huge a jump from discussing a collective with a shared mission, doing what they love, to a city, which is not a cohesive network or community.

 

For a collective to succeed, people do need to make decisions and coordinate actions. They must take responsibilities and be rewarded for them. Google tried eliminating all middle managers, and had to reintroduce some. Open-source software organizations distribute work with minimal top-level control. But some are very autocratic, and many contributors are unpaid.

 

There are good reasons why businesses usually organize actors hierarchically. Hierarchical organization structures do not necessarily imply top-down command and control.

Logical hierarchies

When people are faced with a complex network they often impose a hierarchy on it. They do this first of all to understand and manage it.

 

How to understand and manage the actors, activities or aims of a system? Business architects use hierarchies to help them do this. They may use:

 

 

In the EA framework called TOGAF, the "enterprise continuum" can be seen as a matrix. It features four columns (degrees of generalization) and four rows (degrees of idealization).

 

Business architects probably make more use of composition and delegation hierarchies. They may draw:

 

·       An aim hierarchy – which decomposes grand aims or goals into finer-grained objectives. It records SMART outcomes managers declare can and should be achieved.

·       An activity/ability hierarchy - a functional decomposition or capability map. This decomposes broad-ranging activities or abilities into finer-grained one. It gives architects and other stakeholders a logical and stable picture of what a business does or should be able to do.

·       An actor hierarchy - a composition/delegation/reporting structure. This decomposes large actor assemblies into finer-grained ones. It is usually defined by business managers. Typically. some actors direct other actors to act and/or report the progress of activities. Sometimes one hierarchy corresponds closely to another. Sometimes the hierarchies differ.

How is an organization's composition structure defined?

EA practices draw a logical function or capability hierarchy (over the top of regular business activities). They do it to make sense of what a business does, or should do.

 

Aside: the theory is simple, the practice is not so simple. Different stakeholders may have different ideas of which activities belong together. They value clustering activities using different "cohesion criteria". So, there is no one function/capability hierarchy all are happy with. There are as many hierarchies as there are different, valued, cohesion criteria.

 

I recall (c20 years ago) the CIO of a government agency describing their practice. He said the different interests of 9 board members were represented in 9 different hierarchies. They settled on one primary hierarchy for most purposes, but still, the forest of trees had to be considered.

 

EA maps the chosen logical hierarchy to the real-world or physical organization structure that is or will be imposed over the human actors. They may do this either perfectly (one to one) or in a matrix structure. When the mapping is one function to one organization unit this creates a so-called" functional organization structure".

 

Often, business directors and managers divide the real-world organization structure in other ways, for more or less good reasons. They may divide by location, product type, customer type, or a combination of such cohesion criteria.

 

On the use of organization, function and capability hierarches in EA, read this slide show.

 

The top level of a function/capability hierarchy may be shown in a value chain diagram. This imposes a structure on the activities of a business. It gives the impression of the business as a single coherent activity system. But it is such a superficial view that it likely masks disco-ordinations between activity systems (e.g. billing and customer service) at a lower level.

 

EA is much concerned with the cross-organizational standardization and integration of business activities that are, or should be, digitized. The rest of section discusses how actors may be composed into social structures, from small to large.

Grouping actors into productive teams

Wherever actors must communicate and cooperate to do something, it seems the size of a productive team has not changed. It is still around the 6 to 8 foragers who can support a moderately-sized tribe of people. A basketball team needs 5, baseball 9, and soccer 11. The optimal size for a board of directors, a software development team, or a meeting of any kind, is often said to be 6 to 9 people.

 

 "According to Wittenberg, while the research on optimal team numbers is “not conclusive, it does tend to fall into the 5 to 12 range, though some say 5 to 9 is best.” This source.

 

In business, how productive teams form and reform is discussed in this source.

 

"Dynamic Reteaming is team change. Teams evolve and change structurally according to 5 base patterns: one by one, grow and split, isolation, merging and switching. These changes happen at different levels: individual, team, team of teams, department, company, industry and beyond." This source.

 

How about scaling up from a team to a wider community or organization?

Grouping actors into hierarchical organization structures

Many deprecate hierarchical command and control. They promote distribution of authority and anarchical communication networks. But hierarchical organization structures do not necessarily imply top-down command and control.

 

Perhaps the earliest large human organizations were armies. Most armies are organized hierarchically. But even army commanders delegate some authority, down to the platoon level. https://en.wikipedia.org/wiki/Platoon

 

And most are trained to adapt to feedback from below. As most famously advised by Helmuth von Moltke (1800-1891).

 

The traditional management hierarchy widens exponentially from the top down. Say 1 > 7 > 49 > 343 > 2401 > 16,807. As a reporting structure this reduces the information load on each manager. But distances higher level managers from bottom-level operations. Hence the advice for business directors to “walk the shop floor”.

 

What else influences the design of organization's management structure? It ought to take into account its role in four kinds of relationship.

 

·       In a dominance hierarchy, the higher ups impose their will

·       In a delegation hierarchy, the higher ups divide work between teams, which may be paired in customer-supplier relationships.

·       In a competence hierarchy, the higher ups direct and assist those below them.

·       In a reporting hierarchy, information about the state of things is reported upwards, often in a summary form, to higher ups.

 

The trick is to get the benefits of the last three aspects, without the de-motivating effects of a dominance hierarchy.

 

Aside: the structure of an organization does not dictate how autonomous the actors are. Whatever the structure (network or hierarchy) actors may be either largely autonomous agents or else largely incapable of acting without direction or cooperation.

Mapping actors to roles

In a business, the recruitment, motivation and management of human actors to play roles is primarily the concern of business managers, rather than EA.

 

Aside: wrt diversity.

If we presume men and women differ, then we can expect them to choose different roles. If we presume they are the same, then we can reasonably expect a role be divided between the sexes. On the other hand, we cannot reasonably propose (as some do) that one sex should learn from the other. That would be patronizing or matronizing, and sexist.

 

Aside: wrt overlapping social entities

You no longer belong only to one family and small tribe. In the modern "information age", your memberships of social networks are fluid. You can identify with any group you like. You can celebrate you belong to infinite nameable groups. Best not to let yourself be defined by any of them, and not to get sucked into "identity politics". At the extreme, this leads to treating people labelled differently as enemies, and blames descendants for what their ancestors did.

On dysfunctional organizations

A popular idea is that organization or project managers should be "servant leaders". The idea of a confident leader setting goals and accepting inputs from below is an old one. Again, try Helmuth von Moltke (1800-1891).

 

The idea is good, it can work well, but in practice is often difficult to apply. It is easy and natural to be a servant leader when a) those you lead know as well or better than you and b) you are confident in your position as leader.

 

Very often, one of those conditions is not fulfilled, and the result can be a dysfunctional organization.

 

As I see it, the root causes of dysfunctionality lie at the personal and interpersonal level. And in the natural desire of people to maintain or advance their own role in an organization. The more trusting "culture" that we'd all like to work in has to address problems that individuals create by one or more of:

 

1.      Unclear, ambiguous, communication

2.      Fear of exposing ignorance

3.      Fear of sharing knowledge

4.      Not appreciating, praising, thanking, rewarding

5.      Acting to keeping others apart, prevent communication

6.      Refusing to hear or accept criticism or alternative views

7.      Blaming and blame passing

8.      Absenteeism - physical or virtual

9.      Incompetence

10.   Animosity, unfriendliness, unkindness.

 

Minimizing issues arising is a task for everybody, and managers in particular.

 

SOCIAL ENTITY EVOLUTION

 

System change can be classified in three ways:

·       continuous or discrete

·       state change or mutation

·       natural/accidental or designed/planned.

 

So, change can be represented as a three-dimensional phenomenon. This helps us to think about what it means to model change and design for it.

 

 

Continuous

Discrete

State change

Natural

Natural

Designed

Designed

Mutation

Natural

Natural

Designed

Designed

 

Of eight potential varieties of change, four are continuous.

1.     Continuous natural state change (e.g. the growth of a crystal in liquid)

2.     Continuous designed state change (e.g. analogue light dimmer switch)

3.     Continuous natural mutation (e.g. maturation of child into adult)

4.     Continuous designed mutation (impossible)

 

A social entity continuously and naturally mutates. Its members change, and it responds to environmental changes that were not predicted or anticipated. It is impossible to design a system that continually changes its nature; that would be a contradiction in terms. However, continuous change can be simulated by dividing changes into steps frequent and small enough to appear continuous.

 

There are four kinds of discrete change.

5.     Discrete natural state change (e.g. asleep to awake, or day to night)

6.     Discrete designed state change (e.g. light on to light off)

7.     Discrete natural mutation (e.g. generational change, parent to child)

8.     Discrete designed mutation (e.g. system version 1 to version 2)

 

Primarily, EA is about the design of activity systems that change state in discrete steps (6), and are changed under change control (8).

 

Read the chapter on activity systems thinking for discussion of discrete step mutation and design for change. This chapter adds only a few notes on social entity change.

Transformational or incremental change?

Remember Pia Macini’ video https://bit.ly/3hQdSKO. The conclusion – that to push boundaries we must cast aside old models - is misleading. Many whole-scale revolutions have led to disaster or the opposite of what was intended. And it has been reported that 70% of business transformations fail. By contrast, biological evolution has pushed boundaries in amazing ways. It produces sustainable solutions, without ever making a radical change. Mature businesses and governments have evolved over millennia. Legislation is changed incrementally in response to issues and change requests. Agile software development works on the same principles.

 

Read the chapter on activity systems thinking for discussion of the choice between transformational and incremental change.

Change through human innovation

Some social systems thinkers promote "organizational learning". They deprecate what they call command and control in favor of the idea that employees should be autonomous, innovative, agents.

 

At one extreme, the actors in a social entity do nothing but act in regular activity systems (think, an ant colony). At the other extreme there is continual innovation, and a social entity with no regular or repeated activities. (The only recognizable activity system is the meta system in which employees are commanded to be innovative.) Real-world businesses sit somewhere between those extremes, and do give their employees some degree of freedom.

 

Most of human society is not a designed activity system; it evolves with or without government. Leaders pass laws - people adapt their behavior - leading to unintended consequences. These consequences create the need for new laws, sometime reversing the original ones. Also, the strength of a democracy lies less in the ability to elect a government who promises to do certain things. And more in the ability to unseat that government in the light of what it does. The incoming government is chosen precisely because it promises to do something different.

 

It might be argued that economic and social progress is a process of trial and error. It depends on leaders changing their minds and electors changing their leaders. Supported by the trial-and-error process of science that tries to crystallize stable knowledge for future use.

CONCLUSIONS AND REMARKS

 

This chapter has discussed several views of society. Including society as homeostat, as autopoietic, as a network structure, and as a social organization. We have contrasted two kinds of systems thinking. EA sees a business as a social entity. That social entity may realize any number of (possibly conflicting) activity systems. EA strives to extend, improve and coordinate those activity systems.

 

Activity systems thinking is about a network of regular activities, performed by actors. E.g. a poker game. The response of an actor in an activity system to an input falls within the range of allowed activities. Clearly, humans are not limited to performing regular activities. And what we call an "organization" is not an organism or a machine. As Ackoff suggested, a business is more a mess of aims and activities than a single coherent activity system.

 

Social entity thinking is about a network of actors, who perform activities. E,g. a card school. The response of a human in a social entity to an input may be not only unpredictable, but also purposefully innovative. Social entity thinking is important to the success of business operations, and changes to them. However, the field is too diffuse and diverse field to be described easily. One ends up listing the names of countless gurus, who propose countless models and techniques. To list gurus, models tools beyond the scope of this chapter.

 

Suffice to say, you may find some useful models for social entity management. For structuring, steering, motivating and leading a group of people to achieve some desired aims. And note that many software development gurus put more emphasis on the sociology of actors in the development process. E.g. stand up meetings, JAD workshops and the importance of "psychological safety". These concluding remarks go on to raise some general issues with social entity thinking.

What is a system?

Ackoff's writings on "social systems" are widely respected. But when applying cybernetic terms and concepts to human society, he contradicted himself. To begin with he said: “Different observers of the same phenomena [e.g. human organization] may conceptualize them into different systems”. Later, he expressed the opposing view that regardless of different observers "Every human organization is a system."

 

Better, we say a human organization is one purposeful social entity. Its actors may play roles in any number of activity systems, and may change those systems from time to time.

Questionable metaphors and analogies

Some thinkers flip between discussing activity systems and discussing social entities. The use the same terms in both contexts, but with somewhat different meanings.

 

Misunderstandings arise when social entity thinkers speak metaphorically (use words figuratively). So, beware that words may not mean what you think. Some take words from hard sciences and use them in social entity thinking with different meanings. This is not generalization; it is diversification that overloads a word with multiple meanings, and leads to cross-domain misunderstandings.

 

E.g. the term fractal is used by some systems thinkers. A Mandelbrot fractal is an infinitely detailed two-dimensional image (set of points). As you zoom into its border areas, you see the same pattern emerges, recursively, at lower levels of decomposition. It looks complex. But the formula to generate or calculate this output is based on a simple formula: z(n+1) = z(n)^2 + C. The process can be coded in less than 20 lines of code. Is that well-called a complex system?

 

One systems thinker defines the term fractal very differently. "A fractal system is a complex, non-linear, interactive system which has the ability to adapt to a changing environment." Surely that describes every social entity you know of?

 

No human organization is fractal. An organization's reporting hierarchy is not fractal. Zoom in, you divide one element into different elements. Zoom out, you group different elements into one.

 

Some thinkers draw conclusions from the observation that one thing is isomorphic with another thing (has, or seems to have, the same structure). Beware that having the same structure does not mean two things behave in the same way, or should be treated in the same way.

Post-modern relativism

Some say there is no objective meaning in a message, and it doesn’t matter what the sender meant. It only matters how each receiver interpret the message (which can incriminate the innocent sender). Many sociologists are, to some extent, infected by "perspectivism" or "relativism". This leads them to say two things about any proposed model or classification scheme.

 

Some say: “Any interpretation you make of my model is a valid interpretation.” This undermines the idea that the model meant something in the first place.

 

Some say:"Super-positioning of the types in my classification scheme allows you define things as belonging to several, possibly contrasted, types.” This undermines the value classifying things into distinct, contrasted, types.

 

Ian Glossop expresses the issue thus:

"The fundamental problem with (epistemic) relativism (characteristic of postmodernism) is this. If all views are equally valid then no view is valid. None is too extreme, incorrect or wrong and notions of truth and analysis and objectivity and reason and science become worthless. All that matters is the highly subjective "what-it-means-to-me". Anyone can believe anything they like and say so - and nobody can say there is a better way of looking at anything. Nobody need analyse and understand and try to justify their views they can just spout their own prejudices and biases as 'fact'. And in this fertile ground prejudices and conspiracy theories and, frankly, bullshit flourish. See Harry Frankfurt's book."

What does coherently organized mean?

“A system is an interconnected set of elements that is coherently organized in a way that achieves something.”

 

This opening sentence of chapter one in Meadow’s primer on systems thinking is often quoted. The troubles is that the sentence is generalized to the point it is variously interpretable. Consider two different ways actors may interact in a given structure.

 

Causal flows of the kind in a causal loop diagram (CLD).

A CLD organize two or more populations of actors and resources by connecting them in causal relationships.

In this case, coherently organized may be read as saying actors and resources are inter-related as shown in a CLD.

And to achieve something may be read as POSIWID. As producing "a pattern of behavior over time" rather than as meeting given or agreed aims.

 

Denotic causal flows between actors in a management structure.

In a denotic relationship, a manager gives goals, duties and obligations to an employee. Whereas causal flows trigger actors to perform defined activities, denotic causal flows can define the activities to be performed. Or even tell actors define their own activities. In this case, coherently organized may be read as saying actors are directed by managers. And to achieve something may be read as performing given activities to meet given or agreed aims.

 

For a discussion of other ambiguities of Meadows' Primer on Systems Thinking, read the later chapter on ambiguities. You can find some more notes on social systems thinking on this page.