Meadows’ generalizations

Copyright 2020 Graham Berrisford. A chapter in “the book” at Last updated 31/05/2021 11:37


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This chapter discusses Meadows’ generalization of two different systems thinking schools

·       Activity systems thinking as in system dynamics

·       Social entity thinking as in management science




Meadows’ terms and concepts. 1


On abstraction. 5

On change. 7

Remarks. 7


Meadows’ terms and concepts

Donella Meadows (1941 –2001) was an environmental scientist, teacher, and writer. She was much concerned with resource use, environmental conservation and sustainability. She is surely best known as lead author of the popular and influential book “Thinking in Systems: a Primer”.


In the 1970s. Meadows had, famously, used system dynamics to model the effect on the world of exhausting its available resources. The first half of this later book explains and exemplifies Forrester’s system dynamics in a conventional fashion. For example, Meadows defines stocks and flows.


“Stocks are the elements of the system that you can see, feel, count, or measure at any given time. A system stock is just what it sounds like: a store, a quantity, an accumulation of material or information that has built up over time. It may be the water in a bathtub, a population, the books in a bookstore, the wood in a tree, the money in a bank, your own self-confidence. A stock does not have to be physical. Your reserve of good will toward others or your supply of hope that the world can be better are both stocks. (Meadows)


“Flows are filling and draining: births and deaths, purchases and sales, growth and decay, deposits and withdrawals, successes and failures. A stock, then, is the present memory of the history of changing flows within the system.” (Meadows)


However, in the introduction and the second half of her later book, Meadows generalised from the strictly mathematical concepts of stocks and flows in order to discuss social and business systems. Chapter one starts thus:


“A system isn’t just any old collection of things. A system is an interconnected set of elements that is coherently organized in a way that achieves something. If you look at that definition closely for a minute, you can see that a system must consist of three kinds of things: elements, interconnections, and a function or purpose.” (Meadows)


Readers may presume that elements correspond to stocks, and interconnections correspond to flows, but it isn’t that simple. Meadows spoke of social systems for which no model has actually been built, and system dynamics ideas and principles more informally. Also, she added purposes into the picture. Meadows’ concept of function and/or purpose was not entirely consistent.


“The elements of a system are often the easiest parts to notice, because many of them are visible, tangible things.”


Meadows wrote of elements as structures. Mostly, she spoke of material structures, both active structures (actors) and passive structures.


 “the elements of your digestive system include teeth, enzymes, stomach, and intestines.”

“A football team is a system with elements such as players, coach, field, and ball”

“The elements that make up a tree are roots, trunk, branches, and leaves.”


Sometimes Meadows wrote of intangible elements such as quantities of a variable quality possessed by a structure. For example:


“school pride and academic prowess”


So, elements may be read as physical material structures (human actors, hardware or other resource items), or logical data structures (quantities of a population, resource or quality). Was she meaning to embrace the modelling of individual entities as in event-driven dynamics, and the modelling of stocks, populations or resources as the continuous dynamics of system dynamics?


Individual actors do not appear in a System Dynamics model, except as units in a quantity. But the roles they play – the activities they perform and the effects they have – do appear in the model. Meadows characterised a system by its activities, allowing that the actors may come and go.


Interconnections seem to be anything that carries a cause-effect relationship between elements. An interconnection can be a physical material flow, a batch of events or actions, a logical data flow (signal or message), or even, perhaps, a social/authority relationship.


“Some interconnections in systems are actual physical flows, such as the water in the tree’s trunk or the students progressing through a university. Many interconnections are flows of information—signals that go to decision points or action points within a system.”


In speaking of interconnections, was she meaning to embrace the modelling of individual events (signals) as in event-driven dynamics, and the modelling of continuous flows as in system dynamics?

Functions and purposes?

“The word function may be used for system with non-human actors; the word purpose for a human one. But the distinction is blurred, and many systems have both human and non-human actors.”


Meadows blurred the distinction between functions and purposes. And perhaps also the distinction between aims and outcomes. Aims are motivations, goals or intentions (individual or communal). Outcomes are state changes over time or lines of behavior


In the first half of the book:

“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”


Here, Meadows discusses activity systems (networks of activities), in which the function or purpose of a system is its outcome, how it changes over time, its lines of behavior, how it increases, maintains or exhausts resources or populations. And in this regard, she follows the lead of Stafford Beer who coined the phrase the Purpose Of a System Is What it Does (POSIWID).


So here, what Meadows calls purposes are not purposes as you think of them. They are not the goals declared by owners or managers of a system, or even the aims of the system’s actors. They are instead the long-term outcomes that emerge from the system’s repeated behaviors.


Meadow’s system is defined by the roles of actors and the rules by which they interact. The system repeats its behaviors, performing the same operations on the same variables. It continues doing this, unless the system exhausts some necessary resource, at which point it stops.


Meadows proposed any intervention in the business should attend first to its outcomes rather than any published goals. (In chapter 5, she notes that manager-set goals can lead to unintended consequences and counter-productive results.)


Suppose you observe a system produces unwanted results (say financial losses, or global warming). You may change the system by design to a new system. To change the outcomes, you need to change the interconnections, which means changing the roles of actors and the rules by which they interact. The new system may be regarded as the next generation of the system, or a different system altogether.


"Change the rules from those of football to those of basketball, and you’ve got, as they say, a whole new ball game.” Meadows


Still, suppose you notice the NHS acts to cure the sick, employ doctors and nurses, fund drug companies, and cover up its mistakes. Surely, to call all those the purposes of the NHS is contrary to our normal use of the term?


In the second half of the book:

"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".


Here, Meadows discusses social entities (networks of actors), and seems to use the term purposes to mean motivations, goals or intentions - communal rather than individual.


In management science (and agile software development methods) rhetorically setting goals is a valid technique. An idea is not to fix the roles of actors and the rules by which they interact. Instead, the process is to declare some high-level goals and then motivate actors to meet them.


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


Is the something achieved an aim rather than an outcome?


What does “coherently organized” mean? Does it mean the actors are organized? There is management structure in which actors are told what to do? Might there be an anarchical structure in which autonomous agents determine their own activities? Can that be called “coherently organized”?


Or does it mean the activities are organized? There are processes in which actors are triggered by flows of some kind to perform activities? If so, what kind of flow?



Might be read as

Or else


Causal flows that connect two populations or actors; one triggers the other to change or do something, so the

Denotic causal flows by which managers give workers general duties and obligations, or even tell them to define their own activities, so the

Coherently organized?

actors cooperate according to defined rules so as to

actors are directed by managers to

Achieve something?

producing an outcome, a line of behavior (POSIWID)

perform activities to meet aims (given or agreed)


Surely, Meadow was primarily interested in systems modellable in a causal loop diagram (CLD). Note that different observers may observe different casual loop networks in a business,. Each is only one of the many, possibly conflicting, perspectives. Note also it is possible that denotic causal flows (telling actors what to do) may have effects contrary to those defined in rule-bound causal flows.


In defining elements, interconnections, functions, purposes, Meadows made canny generalisations, allowing readers to interpret each in different ways. Did Meadows intend these several interpretations to be made or allowed?


It seems to me Meadows slipped from discussing the outcomes of activity systems in the first half, to discussing the aims of managers and human social entities in the second half.


This table below maps Meadows’ terms to general activity system thinking terms.


Meadows’ system dynamics

General activity system theory

Purpose or function




Pattern of behavior over time.

Aim or outcome?




Line of behavior (state change trajectory)


This table quotes from Meadows’ answers to questions about system dynamics.



Meadows’ answers

What characterizes an activity system?

“A system is a set of things [elements] people, cells, molecules, or whatever interconnected in such a way that they produce their own pattern of behavior over time.”

“The system may be buffeted, constricted, triggered, or driven by outside forces. But the system’s response to these forces is characteristic of itself. The behavior of a system cannot be known just by knowing the elements of which the system is made.”

What are the aims or purposes of a system?

“The word function is generally used for a nonhuman system, the word purpose for a human one, but the distinction is not absolute, since so many systems have both human and nonhuman elements.”

“If information-based relationships are hard to see, functions or purposes are even harder. 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.”

Is every composite entity an activity system?

“A system isn’t just any old collection of things. A system is an interconnected set of elements that is coherently organized in a way that achieves something.”

Is there anything that is not an activity system?

“Yes—a conglomeration [of elements] without any particular interconnections or function.”

How to know you are looking at a system? And not just some stuff that exists or happens?

“How to know whether you are looking at a system or just a bunch of stuff:

a)      Can you identify parts? . . . and

b)     Do the parts affect each other? . . . and

c)      Do the parts together produce an effect that is different from the effect of each part on its own? and perhaps

d)     Does the effect, the behavior over time, persist in a variety of circumstances?”

Which of actors, activities and aims are most important?

“To ask whether elements, interconnections, or purposes are most important is to ask an unsystemic question. All are essential. All interact. All have their roles. But the least obvious part of the system, its function or purpose, is often the most crucial determinant of the system’s behavior. Interconnections are also critically important.”

What does it mean to change a system?

See below


Meadows took a side-swipe against event-driven models. In system dynamics however, a causal flow often represents a stream of events happening the real world. E.g. a flow may represent a batch of predation events in which wolves kill sheep.

On abstraction


-1- Everything we think we know about the world is a model. Every word and every language is a model. All maps and statistics, books and databases, equations and computer programs are models. So are the ways I picture the world in my head—my mental models. None of these is or ever will be the real world.


Conformance of concrete systems to abstract systems

2. Our models usually have a strong congruence with the world. That is why we are such a successful species in the biosphere. Especially complex and sophisticated are the mental models we develop from direct, intimate experience of nature, people, and organizations immediately around us.


Selective abstraction

3. However, and conversely, our models fall far short of representing the world fully. That is why we make mistakes and why we are regularly surprised. In our heads, we can keep track of only a few variables at one time. We often draw illogical conclusions from accurate assumptions, or logical conclusions from inaccurate assumptions. Most of us, for instance, are surprised by the amount of growth an exponential process can generate. Few of us can intuit how to damp oscillations in a complex system.


Did Meadows abstract activity systems from entities?

Meadows’ primer in systems thinking offer the following entities as examples of systems.

"A school, a city, a factory, a corporation, a national economy, an animal, a tree, the earth, the solar system, a galaxy."


Many activity systems can be abstracted from observation of one such entity. It is important in activity system thinking to realize that a system is only one perspective of an entity. Each system may be useful for some purpose, yet two systems be unrelatable or incompatible.


Did Meadows abstract activity systems from social entities?

The first half of the book is clearly about system dynamics as Forrester might define it. In the second half, there is some scope creep where human institutions are discussed. Meadows sometimes refers to a human organization as though it is a system, and says things contrary to system dynamics and/or conventional business management practices.


“[A system’s] purposes are deduced from its behavior over time, not from rhetoric or stated goals.”

This view of purpose as outcome differs from the view of purpose as aim or goal– which is the usual one in management science.


“Hierarchical systems evolve from the bottom up.”

This may be true of biological organisms, but the normal practice in business is to shape the organization structure from the top down.


“The purpose of the upper layers of the hierarchy is to serve the purposes of the lower layers.”

This view of the “servant leader” (discussed in chapter 2) has some merit, but again, is contrary to the normal business practice of top-down goal definition.


In business, the term organization usually refers to a management structure. Meadows doesn't clearly distinguish this social entity from her core idea of looking at a real-world entity as a causal loop network. A result is some statements that casual readers may read as they like, but studious readers may find difficult to interpret.


The importance of verifying a model

In chapter 7, Meadows discusses the importance of verifying system models against real world phenomena.

“Expose Your Mental Models to the Light of Day... making them as rigorous as possible, testing them against the evidence, and being willing to scuttle them if they are no longer supported is nothing more than practicing the scientific method —something that is done too seldom even in science, and is done hardly at all in social science or management or government or everyday life."

On change

“Changing relationships usually changes system behavior. The elements, the parts of systems we are most likely to notice, are often (not always) least important in defining the unique characteristics of the system.” Introduction


“Changing elements usually has the least effect on the system. If you change all the players on a football team, it is still recognizably a football team. A system generally goes on being itself, changing only slowly if at all, even with complete substitutions of its elements —as long as its interconnections and purposes remain intact. If the interconnections change, the system may be greatly altered. It may even become unrecognizable. Changes in function or purpose also can be drastic.” Chapter 1


[Which is to say that changing the purpose of a system is to change the system itself.]


Like Ackoff, Meadows starts from a place rooted in classical cybernetics and mathematics. The discussion is of a system that has fixed set of state variables and regular behaviors, which can be modelled in a causal loop diagram. The model can be run to show (given an initial state) the outcome – the lines of behavior.


Then, also like Ackoff, Meadows slips from there into speaking of a human organisation as a system. Meadows says many wise things about human organisations, diagnosing problems and resolving them. It is not always evident how far these things derive from or depend on system dynamics.


A difficulty with applying system dynamics to the real world is that a socio-technical entity (like IBM) realises countless different systems. At the same time, its employees also, necessarily, act in ad hoc or impromptu ways. Also, unforeseeable external changes (government regulations, competition, technology innovations) can undermine any attempt to predict IBM’s line of behavior over time.