Systems Thinking in Practice

COMP 3530/6353
Systems Thinking in Practice
Barry Newell and Katrina Proust
A
B
Systems Thinking
What is systems thinking?
In this course we take ‘system thinking’ to
mean thinking about the way that the parts of
a system interact to influence each other’s
behaviour.
We are particularly concerned with ‘feedback’
and its effects in complex adaptive systems.
A
B
Systems Thinking
We use the term ‘feedback’ to refer to
cause-effect loops.
In a cause-effect
loop a change in
any one variable
propagates around
to loop to either
amplify or
counteract the
original change.
Dedication of Team to
Hard Work and Good
Communication
Success of Software
Development Efforts
Enthusiasm and
Confidence of Software
Development Team
A
B
Systems Thinking
Why is systems thinking important?
The behaviour of a complex adaptive
system emerges from feedback
interactions between its parts.
Feedback systems can react to policy
interventions in surprising ways. This is
true even when you are dealing with
systems that have simple structures.
A
B
Systems Thinking
Basic Systems Principle
In a complex system all actions
produce a spectrum of outcomes.
The expected outcomes may or may
not occur; the unexpected outcomes
always occur.
A
B
Systems Thinking
Why is systems thinking important?
You cannot understand or anticipate the
behaviour of a complex system without
understanding and thinking about
feedback.
Note that ‘systems thinking’ always
begins with ‘feedback thinking”.
A
Systems Thinking
B
Systems thinking requires an
understanding of feedback:
Physical
Fitness
Ideal Level of
Nutrition
R
Enjoyment
of Exercise
Amount of
Exercise
Gap
Actual Level
of Nutrition
B
Quality and
Quantity of
Food Eaten
There are just two types of feedback – reinforcing
and balancing.
A
Feedback
B
Reinforcing (or positive) feedback amplifies change
Balancing (or negative) feedback counteracts change
When you want
change
When you want stability
Reinforcing
(positive)
Feedback
Helps
Hinders
Balancing
(negative)
Feedback
Hinders
Helps
A
B
The Complexity Dilemma
1.  A feedback system is a set of parts (elements, actors)
that interact to constrain each other’s behaviour. A
software development team is a good example.
2.  The behaviour of such a system emerges from the
interactions between its parts.
3.  Therefore, you can’t optimise the behaviour of the
system by optimising the behaviour of the parts taken in
isolation.
4.  You have to study the system as a whole.
5.  But, when you try to do this, you are overwhelmed by
the complexity of the system.
A
B
Escaping the Complexity Dilemma
One way to escape the complexity dilemma
is to look for shared features or attributes
between things which, at first sight, seem to
be very different.
For example, if a number of apparently
disparate behaviours can be shown to be
just different versions of a single behaviour,
there can be a significant reduction in the
apparent complexity of the observed world.
A
B
Activity 1
What do these policy approaches have in common?
1. Constructing freeways
2. Substance abuse
3. Dependence on refrigerated air conditioning
4. The war on drugs
5. Low-cost housing for urban renewal
6. Constructing flood-control levees
7. Engineering the climate
8. Using miticides to protect bee colonies
9. Spraying ragweed with broad-spectrum herbicides*
10. Using “mould killer” in bathrooms*
11. Introducing shrimp to feed freshwater salmon*
12. Planting wheat on the Great Plains, USA*
A
B
Activity 1
1.  Working in a group of 4 consider the policy
approaches listed in Handout A.
2.  What do these policies have in common?
3.  Discuss this question in your group and be
prepared to present your insights to the whole
workshop.
A
B
Structure à Behaviour
–  The behaviour of a system is driven by its
‘feedback structure’.
–  There are a number of relatively simple feedback
structures that are seen in a wide range of
contexts, that have characteristic behaviours, and
that have the potential to dominate urban-health
outcomes.
–  These structures are called System Archetypes.
A
B
The Ragweed Problem
A
B
The Ragweed Problem
But … leads to more ragweed next year. Why?
A
B
The Ragweed Problem
A
B
The Mould Problem
CHOICE
Magazine
2012
It’s habit forming
A
B
The Mould Problem
A
B
Salmon and Shrimp
Spencer et al. 1991, BioScience, 41, 14-21.
A
B
Salmon and Shrimp
A
B
Wheat on the Great Plains
A
B
Generic
Structure
System Archetype
Fixes That Fail
A
B
System
Archetype
Fixes That Fail
Characteristic Behaviour
A
B
System Archetypes
A system archetype is a simple feedback structure
that has a characteristic pattern of behaviour.
System archetypes
are generic. A single
+
archetype can be
used to explain the
Amount
Extent of Problem
B
of Fix
Symptom
behaviour observed
+
in many contexts.
Popularised by
Peter Senge (1990),
who called them
Nature’s Templates.
R
Extent of
Underlying
Problem
+
+
Strength of
Unintended
Consequences
A
B
System Archetypes
–  A systems-thinking approach that uses system
archetypes does not, of course, yield a full,
predictive model of system behaviour.
–  But it can provide an initial view of feedback
structures that have the potential to dominate
the behaviour of the system.
–  In many contexts system archetypes are
critically important because they focus attention
on the impacts of policy and management
decisions.
A
B
Leverage Points
Problem
Symptom
The problem is not
the Ragweed
infestation but the
lack of perennial
vegetation cover.
Leverage Point
A
B
Fixes That Fail
Leverage Points
A
B
Activity 2
Working in your groups:
1.  Select a policy from those numbered 1 to 8 in
the handout list.
2.  Develop a Fixes that Fail diagram that
explains why your selected policy might fail in
the long term.
3.  Present your diagram and your analysis of
the reasons why policy failure is possible.
4.  Can you identify potential leverage points for
change?