Musings - System thinking - Notes on Donella Meadow's Book

Donella H. Meadows
Notes and musings
James Cracknell
SFEDI Accredited Business Adviser
March 2017
Thinking in Systems

System Structures and
Behaviours

Is it a system?
Can you identify
specific elements?
No
Yes
Not a system
Are the parts
interconnected
and dependent on
each other?
No Not a system
Yes
When the parts
work together is
the effect different
from each part on
its own?
No Not a system
Yes
Is the effect
persistent over
time despite the
environment?
Yes
No Not a system
It’s a system

A system consists of:
• Elements
• Interconnections
• Common
Purpose
System

The competitive exclusion principle
Two species that compete for
the exact same resources
cannot stably coexist.

The Blind Men
and the Matter
of the Elephant
“The behaviour of the system cannot be known by
just knowing the elements of which the system is
made” - DHM

Systems – more than the sum of its parts
Behaviours can and may include:
• Adaptive
• Dynamic
• Goal-seeking
• Evolutionary

Flow of Information
drives
interconnections
Information holds
systems together

What can determine a system’s behaviour?
• Purpose & Function working n
harmony
• Interconnections married to purpose

And discourse?
Changing relationships normally
changes a systems behavior
“To ask whether elements,
interconnections, or purpose are the
most important in a system is to ask
an unsystemic question” - DHM

Information
The flow of which often
holds the system
together so when
combined with
knowledge and know-
how they operate as a
collective force.

Functions and
Purpose
Functions are often
ascribed to machines whilst
purpose is associated with
human elements. In truth a
system has both because
elements are often
intertwined
A system will behave as the
function or purpose
determine

Stock
Elements you can
see, feel, count or
measure
The memory and history of the
changing flows within the
system
“Changes in stocks set the pace
of the dynamics of systems” P22
There rate of change tends to be
slow – so they act as a buffer or
shock absorbers to a system

Feedback loops
Attributes
• Closed chain of causal connections
• Runs from a stock and is impacted by
a set of rules
• Often dependent upon stock levels
• Circular and iterative
Type –
Balancing Feedback Loops
• Stabilizing – stock equilibrium maintained
• Goal relevant
• Sources of resistance to change
Type
Reinforcing Feedback
• Ability to reproduce itself
• Self-enhancing – exponential
leanings
• Non linear

Reinforcing
Loop – Doubling
Time
Or
Td = 70 / R
Where R is the rate of growth
Ln(2) Ln(1+R/100)
Years to
double
R = 5.00
Ln(2)/Ln(1+R
/100)
0.693147 0.04879016 14.20669908
Approx
70 R = 5.00 14

Delays
Causality and delay
The delays in information mean
that feedback can only effect
future behaviour.
Even non-physical feedback is not
fast enough to correct behaviour
it can only impact the future
behaviour

Room temperature
Heat from furnace Heat to outside
Discrepancy between
desired and actual room
temperature
Discrepancy between
outside and inside
temperatures

A heating system is a
stock maintaining
balancing feedback loop
with natural heat loss or
gain. To establish
equilibrium the goal
must be set high or low
of target to avoid over or
undershoot. Flow does
not respond to flow – it
responds to a change in
the level off the stock

Shifting dominance
• Dominance – when one
feedback loop (reinforcing or
balancing) has hold of a system.
This relationship can be dynamic
and has a profound impact upon
system behaviour.
• When neither feedback loop
dominates the system is said to
be in ‘dynamic equilibrium’

Be wary of acceptance – not all models are good
• Are the driving factors of the
model realistic?
• Do you believe the model is a
fair representation of
behaviour?
• What are driving the driving
factors?
System dynamics – What if?

Systems for population and economic growth
Systems with
similar feedback
structures
produce similar
dynamic
behaviour

Stock control
• Perception delay – is the change
in demand for real?
• Response delay – is there a need
to make partial adjustments?
• Deliver delay – If demand is rising
what delays are wholesalers
experiencing of their own?

Delays – a system would
never be without them
• They are pervasive
• They have repercussions
• Systems can modify their
behaviours on the back off
them
• They lead to oscillations

Limits
• In any exponentially growing system with physical aspects
there must be a reinforcing feedback loop driving growth and
a balancing loop acting against this.
• No physical system can grow forever

Resilience
The ability of a system to
bounce back after a large
perturbations
“There are always limits to
resilience” – DHM p76
Dynamic systems need to be
resilient – this resilience needs to be
managed

Koch snowflake
Systems often have the
ability to self-organise,
to learn, diversify and
become increasingly
complex
Fractal geometry – elaborate
shapes created by relatively
simple rules

Hierarchy
“An arrangement of systems
and sub-systems is called a
hierarchy.” DHM p82
In hierarchical systems relationships within each
sub-system are denser and stronger than relationships
between sub-systems

Hora and Tempus were
both fine watchmakers
but Tempus was losing
money whilst Hora
was very successful.
Why?
Hierarchy

Each watch was
made of 1000
pieces. Tempus
constructed his
watch one piece at
a time. When the
end of day came
and the watch was
not complete he
would lay the
pieces down and
the watch fell
apart.

Hora on the other
hand built his watch
in 100 units of 10
pieces that held
together. So at the
end of the day, if the
watch wasn’t
finished the most
work he lost was just
the one unit.

Traits of
Hierarchical
Systems
• Self-organising systems modify
hierarchies
• Hierarchies evolve from the
lowest level – up
• The goals of a subsystem can
subsume the overall goal –
resulting in suboptimisation
• Autonomy and control need to
be in balance
• The purpose of the ‘upper levels’
is to serve the purpose of the
lower ones

Evolution
started with a
single cell
Systems start from the bottom
• A cell to an organ
• An organ to organism
• Individual to team
• Production to management of
production

“Everything we think
we know about the
world is a model”
(DHM p87)
Models have a strong correlation
with the reality but fall far short of
‘being reality’
Systems are our longer term
perspectives – avoiding short term
distractions and focusing on the
bigger picture

Systems are not represented by sequential events -
events are the outputs that occur from the black box of a system

Examples of system
behaviours
Event analysis does not predict the future; has no
ability to change behaviours or achieve stability in the
stock market
Behaviour based models emphasise the ‘system
flows’ and play down the ‘system stock’ since flows
move quickly and stocks respond slowly.
Feedback between flow and stock is ignored placing
the focus on changing the flows.
FLUX

Looking for the linear – and not recognising it!

Nonlinear –
more often
than not

Spruce
Budworms,
Firs and
Pesticides

Tree Rings
tell a system’s
story of a
battle of
nonlinear
proportions

The story of
400 years of
budworm
carnage
• Spruce supply only became an issue when the ‘white
pine’ ran out
• Spraying only increased the population and now the
expense of the practice exceeds the value (Cost benefit)
• Predators – wasps, birds, spiders and disease primary
means of population control (unintended harm)
• 6 to 10 year cycle of outbreaks related to rise of balsam
fir crowding out spruce and birch (limiting factors)
• Nonlinear relationship between fir population and
budworm outbreak – reproduction dependent upon
weather conditions as well (Multiple goals)
• Predator numbers grow (reinforcing relationship) but
capped (nonlinear)
• Eventual death of food supply sees population crash
(nonlinear) – resurgence of spruce and birch – cycle
begins again
• Spraying creates an imbalance that will likely lead to a
failure in the future (unbounded consequence)

Nonlinear
relationships
• As stock shifts strength of
flows change
disproportionally
• Nonlinearities in feedback
produce shifting
dominance in loops
• Behaviours are complex

Boundaries – where are they?
Beware the clouds –
• Main source of system surprises
• Mark the beginning an end of flows
• Clouds = Stocks, sources and sinks
• Mark the ‘boundary of a system model’
• Greatest complexities at the point of the
boundary
• Can be the greatest sources of creativity and
diversity
• Boundaries drawn around systems are
dependent upon the purpose of the
discussion

Musings - System thinking - Notes on Donella Meadow's Book

Layers of
Limits
“At any given time, the input
that is most important to a
system is the one that is most
limiting.”

Limits
Growth itself depletes or enhances limits
There always will be limits to growth.
Any physical entity with multiple
inputs and outputs is surrounded by
layers of limits.
Limits to growth – self-imposed or
system imposed

Delays
When there are long
delays in a feedback
loop – foresight is
essential

Bounded Rationality
“To make reasonable
decisions based upon
the information they
have”

“The bounded
rationality of
each actor in a
system may not
lead to decisions
that further the
welfare of the
system as a
whole”
– DHM p110

Systems
Traps….. and
Opportunities

Problematic
behaviour
• Delays
• Non-linear properties
• No firm boundaries
How they mimic the real world
– information is subject to
delay; life outcomes are non-
linear and all boundaries
depend upon the problem
itself.

Archetypes
Those systems that ‘produce truly
problematic behaviours such as:
• Addiction
• Drift to low performance
• Escalation
We call these ‘Archetypes’ -system
structures that need changing because
they are destructive.
Our response – tinkering at the edges
which will never change the systemic
risk
TRAPS

The Trap: Policy
resistance
• Various actors pull the stock toward
various goals. New policy actions, if
they are effective, just pull the stock
further from other actors goals
adding to the resistance.
• No one likes the direction and
everyone fights against it. Energy that
is expended and has no value.
The Way Out
Let go! Seek out ways that satisfaction
can be achieved through compromise and
negotiation.
See the bigger issue – unite the direction
through this

Policy Resistance –
Fixes that Fail
Examples of fixes that fail
• Farming cycles that create gluts
• War on drugs – no change despite billions
spent
• Banking regulation to stop excessive risk
taking
Policy resistance comes from the ‘bounded
rationality’ of the actors – multiple goals and
multiple directions
Resistance happens when goals of
subsystems are incongruent and misaligned.

The Trap: The Tragedy
of the Commons
“Ruin is the destination toward which
all…rush, each pursuing his own best
interest”
A commonly shared resource that
benefits all from its direct use. Weak
feedback (delays) from the condition of
the resource allows for ‘overuse’ leading
to erosion and eventual collapse.
The Way Out
Give & restore feedback through
education to the users of the common
resource. Privatise the resource so that
all users feel the impact of its declining
availability and quality. Regulate access
which further emphasises the
vulnerability.

The Trap: Drift to low
performance
“The actor tends to believe bad news
more than good news so that the
desired state of the system is
influenced by the perceived state”
If past performance has disappointed
we use this to reset the goals creating
a feedback loop that erodes goals and
the system drifts to ever lower
performance
The Way Out
Maintain standards and keep them absolute.
Set the goals in a state of betterment not
discouragement. Reverse the cycle and set up
a positive reinforcement loop

The Trap: Escalation
Competition between two stocks
seeking to out-do each other. This
creates a reinforcing feedback loop
that creates the exponential
escalation and eventual collapse of
one party.
Examples of this include – The Arms
Race, tit-for-tat killings between
factions.
‘Escalation’ can be in a good direction
– but again not always of benefit
since they lead to the wrong goals
Goals are not absolute since they are
dependent upon the state of the
other actor.
The Way Out
Best way out – avoid it in the first place. If
you’re in – then unilaterally disarm and leave.
Manage the system with balancing loops that
control escalation

The Trap: Success to
the Successful
Those who win are rewarded by the
means of winning again. A person
who owns land, rents the land and
uses the rent to buy more land.
It is pervasive and creates inequality
because it is biased towards the
successful.
Winner takes all – losers are
eliminated
The Way Out
Diversification – get out of this game and start a
new one. Limit the pie – company law and
antitrust laws. Progressive taxation systems that
aim to rebalance the system. Start a fresh at each
round – inheritance tax to remove the ‘leg-up’
children get.

The Trap: Shifting the
Burden to the Intervenor
The shifting of the burden to an
intervenor is when the enacted
solution to a systemic problem does
nothing to actually eradicate the
underlying problem – it simply
disguises or covers up the symptoms.
Atrophy can then set in as the self-
maintaining functions of the system
are weakened. The system becomes
even more dependent on the drug.
Examples – a businesses need for
perpetual funding; health and our
reliance on drugs to fight disease
weakening our immune systems;
children’s ability to do mental
arithmetic – replaced by a calculator
The Way Out
Avoid getting in – but of you are in, be aware
of all the signs and symptoms of masking.
Move the goals of the system from short
term to longer term.

The Trap: Rule Beating
Rule beating stems from the
desire to pervert the system in
some shape or form. It is
following the ‘letter of the law’
but not the ‘spirit in which the
law was created’. In a hierarchy –
rule beating stems from lower
order rebellion against rules
from above.
The Way Out
Let creativity redesign the rules so that the energy
is redirected into achieving the goals of the system
not the defeat of the rules.
Reacquaint the actors with the higher purpose and
a set of principles

The Trap: Seeking the
Wrong Goal
If the goal of a system is poorly
defined, cannot be measured
effectively then the system will not
function in the way it is designed to.
If you set the goal of society to be
measured by GNP – it will aim for this.
If we seek to measure well-being then
this will be the desired target.
What we aim for – the system will
obediently work to produce it
The Way Out
Understand the most desirable system
behaviours and be specific. Take care not to
create a system of effort but not results –
since you will end up with effort and no
results

Creating Change – in
Systems and in Our
Philosophy

Changing the structure of
systems through ‘leverage
points’

Intuition
- Can lead to
“pushing with
all your might
in the wrong
direction”
Systems are
often
‘counterintuitive’

Complexity
Finding some leverage
points in a hierarchy of
stocks and flows

12 Point List of ‘leverage
points’

12. Numbers –
Constants and
parameters such
as subsidies,
taxes, standards
Parameters become leverage
points when the act as the
catalyst to some more powerful
leverage point. System goals
are parameters that can really
change the system.

11. Buffer –
The sizes of
stabilizing
stocks relative
to their flows
Big stocks relative to their
flows are more stable –
these are known as ‘buffers’.
Stores hold inventory; banks
hold our life savings; certain
soils are more stable
because there is a large
stock of nutrients.
Big buffers can lead to
inflexibility, slow reaction or
response times and the
prospect of large systemic
errors leading to failures

10. Stock-and-
Flow structures
– Physical
systems and
their nodes of
intersection
The only way to fix a
poorly designed system –
rebuild it! This leverage
point is hard to change,
can create bottle necks
and have unintentional
consequences. The real
leverage point is to design
it well at the beginning.

9. Delay – The
length of time
relative to the
rates if system
changes
Delays in the feedback loop
determine the way the system will
behave. Rates of change in a stock,
impacted through delays in
feedback, can make the difference
between success or failure. Delays
though are not easy to change – it
is easier to change the ‘rate-of-
change’ itself.

8. Balancing
Feedback Loops –
The strength of
feedbacks relative
to the impacts
they are trying to
correct
Whistleblowers – given protection to call time on
bad practice.
Balancing Feedback Loops are self-correcting
Ubiquitous in systems – either
occurring naturally or through human
intervention they are essential to the
long term health of the system. The
purpose is to keep the stock at or near
its goal but this depends upon all the
parameters, the ability to monitor and
respond appropriately. Price is often
used by the market to keep supply and
demand in check.

7. Reinforcing
Feedback Loops
– The strength
of the gain of
driving loops.
The more soil erodes, the less vegetation it can support,
the greater the run-off, the more soil erodes
Self-reinforcing loop that
eventually will explosion,
erosion or collapse of a system.
It is normal for a balancing loop
to kick in at some point.
Slowing the growth is a
powerful point of leverage.

6. Information
Flows – The
structure of who
does and who
does not have
access to
information
Missing information the most common
cause of system malfunction. Adding
this is a powerful point of leverage. Fish
stocks are low – price rises – more
people fish – price is not a great piece
of information – fish stocks would be.
There is a tendency for humans to avoid
accountability – a reason for missing
feedback loops.

5. Rules –
Incentives,
punishments,
constraints
Rules – define scope and boundaries of a
system, Rule of gravity – but laws,
punishments, incentives and social
agreements are weaker forms of rules.
Leverage comes from restructuring the rules
and understand the power of them

4. Self-
Organisation –
The power to
add, change or
evolve system
structure
Rules for self-organisation – complexity is
evolved from simplicity – grown by a set of
rules. DNA – governing evolution; technical
advancement through innovation. Leverage
comes from encouraging experimentation –
but pushing the lever in the wrong direction
and we could wipe out eco-systems

3. Goals – The
purpose or
function of
the system
The goal sets the direction of all other
leverage points. If the goal of the system is
to bring about radical social change then all
levers must push in that direction. Systems
can have multiple goals under which the
whole system goal sits. The goal of keeping a
market competitive trumps the goal
organisational monopoly.

2. Paradigms – The
mind-set out of
which the system –
its goals, structure,
rules, delays,
parameters – arises
Our social model has one embedded
assumption – money is the measure of a
person’s worth, if you do not have money
you are simply worth less. This is our
understanding of fairness and why we repel
the notions of redistribution. Paradigm's like
this are the source of the system, they are
hard to change because they are ingrained.
A powerful leverage for change.
Changing a paradigm: - Point at anomalies of the existing
system, failures that standout and that you can identify as
reasons for change. Act with braveness, be bold in those
actions and promote those who have already made the
shift. Work with active change agents – open minded
advocates for change. Build a model of life inside the new

1.
Transcending
Paradigms
Realising that ‘no paradigm is true’ and
getting comfortable with this. Let go of ‘not
knowing’ and reach the point of tranquillity
or enlightenment. Mastery over paradigms –
relieves of the burden of dependency of
inclusion and the basis for radical
empowerment.

General notes on the ‘list of leverage points’
 The higher the leverage point the
harder the change will be resisted.
 The order is by no means set in
stone
 The direction that the point of
leverage will take you is not always
intuitive correct.
 Be humble – not knowing is the first
step towards mastery of knowing
 Dance with the system – observation
and engagement with the outcomes
creates clarity

“Life is not an illogicality; yet it is a
trap for logicians. It looks just a
little more mathematical and
regular than it is.” – G.K.
Chesterton

Prediction
and Control
It is one thing to
understand how to fix
the system but it is
entirely different to
actually fix it.

Questions
lead to
questions System thinkers cannot reduce the complex to a set of rules from
which to control or predict an uncertain future. The ability to
utilise the tools of system thinking opens up a whole world of
possibility of design. It allows us to envision a different future, to
design and then redesign in a more purposeful way. To profit
from uncertainty as surprise and chance events reshape the
future design or what we strive to build.
• Remain awake
• Listen to the system – what it is telling us beneath the surface
• Learn to ‘dance with them’
“A system insight … can
raise more questions!” –
DHM p167

Get the Beat of the System
• Do Not Disturb – spend time listening
to and watching the behaviours of a
system
• Learn its culture, history and map its
outputs over time
• Focus on facts
• Recognise your assumptions and
misconceptions
• Look at the data
• Remain observant, objective and
emotionally detached
• Question – dynamic analysis not just
static observation
• Clear articulation of a problem
• Listen in at meetings
• Watch people leap to solutions
• What is the system doing and why is it
doing it?

Expose mental models to the light of day
• Be aware of all your assumptions and
articulate them
• Mental models are slippery – you resort to
a model to fit a purpose – be aware of this
• Diagrams help
• Clarity of thinking aids speed and accuracy
• Practice mental flexibility – redraw
boundaries; be observant to paradigm
shifts
• It’s all only a model – get it challenged by
others with evidence
• Be diverse in your thinking – don’t hang
your hat on one model
• Rigorous models – mean scientific models

Honour, Respect and Distribute information
• Information is the glue of the
system
• Delays, inaccuracies and
missing information leads to
broken outcomes
• Decision makers need timely,
accurate, complete
information
• Information is power
• Information is regulated,
policed and filtered by those
who have a short term interest
to do so

Use Language with Care and
Enrich it with Systems
Concepts
• Information is transmitted primarily
through language
• Mental models can be verbalised
• Avoid language pollution
• Expand our language to be able to
communicate about complexity
• A society that talks about
‘productivity’ but rarely mentions
‘resilience’ – will become productive
but not resilient
• We are what we communicate
• Go for concrete, meaningful and
truthful
• Enlarge language to match our
enlarged understanding of systems
• Learn the language of systems

Pay Attention to What Is Important, Not Just
What Is Quantifiable
• What we can measure is no more
important than what we can’t
• We make quantity more important
than quality
• Put emotive and emotional labels
into systems things like – self-
esteem, quality of life, prejudice
• Make up quantitative scales to
measure qualitative experience
• If it’s hard to quantify but essential
to understanding include it

Make Feedback Policies for Feedback Systems
• Set the feedback policy to change
dependent upon the stocks and
flows of the system
• Policies that include the ability for
the system to learn by establishing
dynamic feedback loops
• Example – to protect the ozone layer
the Montreal Protocol was signed. It
set chemical manufacturing targets
based on scientific feedback. If there
was an accelerated expansion in the
ozone hole – the list of damaging
chemicals to be controlled increased.
This is a feedback policy designed for
learning

Go for the Good of the Whole
• Don’t focus on the one sub-system
within hierarchy while ignoring the
whole
• Hierarchies exist to serve the
bottom layers not the top
• Focusing on relationships without
spending time on health is a short
term fix

Listen to the Wisdom
of the System
• Before contemplating changing a
system focus on the value of what is
already within
• Don’t destroy the areas of system
that are designed to self-serve it
• Example – the difference between
the micro finance initiative in rural
India vs. a macro government
response was the micro finance
worked directly with the people. It
took what was good and worked to
make it better. The macro response
was to bring in big business and
build what was not wanted

Locate Responsibility in the System
• Intrinsic responsibility – creating
systems where the feedback is
directed to the decision maker and
is compelling, direct and quick.
• A pilot sits at the front o the plane
because the actions they take have
a direct impact on them
• Focus on what can be controlled
from within – do not seek to
apportion blame to activities,
inputs and resources beyond the
scope of the system

Stay Humble – Stay a Learner
• Listen to your gut, go with your
intuition
• Keep building mental models
• Don’t bluff – don’t freeze –
experiment & learn
• To learn – take small steps,
constantly monitor outcomes,
embrace change if the direction is
not correct
• Make mistakes and admit them
• Error embracing – seeking, using &
sharing information about goals and
why they have not be achieved
• Be the kind of person who truly
accepts their responsibilities

Celebrate complexity
• The world is messy – non-linear,
turbulent and dynamic
• The world is – self-organizing and
evolving; it creates diversity and
uniformity
• The world is beautiful
• As humans we embrace linear,
structured and whole but we must
learn to embrace chaos, the
incomplete and the unknown

Expand Time Horizons
• We focus only on the first
generations – we need to look
longer
• In systems there is no long or short
term distinction
• Actions today have immediate but
also long-term ripple effects
• Embedded within systems – nested
• Kondratieff Wave – economic
patterns set at 50 year intervals
• You are a fool just to look at the
path directly ahead of you without
looking at the long term
destination.
• Whole systems require an
appreciation of short and long term

Defy the Disciplines
• The system’s journey is not the
specialist one
• Be able to step from each discipline
with a learning hat on
• Systems cross borders and
boundaries
• Systems require a focus on the
desired future state and the ability
to communicate this across
disciplinary boundaries
• Systems require learning

Expand the Boundary of Caring
• Embrace the morality and ethical
codes
• All systems are interconnected and
interdependent
• If the rich succeed at the expense of
the poor then that is not success
• If our lungs fail our heart cannot
succeed
• If the human race is to survive the
eco-system we inhabit must also
survive

Don’t Erode the Goal of Goodness
• System architype - “Drift to low
performance” – the modern
industrial culture has eaten away at
our morality
• Cynicism is everywhere – distrust of
authority and an inability to talk of
love and compassion but an easiness
to talk about hate
• Expectations are lowered, the goal of
the system no longer uplift
• Don’t way the bad news MORE
heavily than the good
• Set your standards in absolute terms

Donella H. Meadows
Edited by Diana Wright
Sustainability Institute
Chelsea Green Publishing
2008
ISBN 978-1-60358-055-7

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