Complexity Thinking

© Jurgen Appelo  version 2  management30.com
Complexity Thinking
or Systems Thinking ++ ?
“The search for simple –if not simpleminded–
solutions to complex problems is a consequence of
the inability to deal effectively with complexity.”
– Russell L. Ackoff

Jurgen Appelo
writer, speaker,
trainer, entrepreneur...
www.jurgenappelo.com

What happens when
you go to a bar full of
systems thinkers and
complexity researchers

Russell L. Ackoff
Ralph Stacey Dave Snowden
Donella H. Meadows
W. Edwards Deming
Peter M. Senge
Peter F. Drucker
Peter Checkland Gerald M. Weinberg
John H. Holland
Michael C. Jackson
John Seddon Max Boisot

“What exactly is
the bar?”

“Are the people
here part of the
bar?”

“Is the beer part
of the bar?”

“If we drink the beer, is
it still part of the bar?”

“What if my beer and
I go outside?”

“What is the
purpose of the
bar?”

Reductionism
Holism
Complexity Theory
Models
Complexity Thinking
Example
Final words

We converse about abstractions
Abstractions are imperfect and incomplete.

It is a form of interaction
The activity of abstracting is basically a form
of interaction between people in which they
simplify the complexity of their own ordinary,
everyday interactions […] in an effort to make
meaning of what they are doing […].
– Ralph Stacey
Complexity and Organizational Reality

To make sense of the world
Sense-making is the way that humans
choose between multiple possible explanations
of sensory input.
– Dave Snowden
http://kwork.org/Stars/Snowden/snowden3.html#Simplicity

reductionism
re·duc·tion·ism noun ri-ˈdək-shə-ˌni-zəm
– explanation of complex life-science processes and
phenomena in terms of the laws of physics and
chemistry
– a procedure or theory that reduces complex data
and phenomena to simple terms
http://www.merriam-webster.com/dictionary/reductionism

The bar is... the building,
inventory, employees,
guests, some interaction,
etc...
reductionism

A problem is that people have become addicted
to the successes of reductionism.
http://en.wikipedia.org/wiki/Reductionism

“Left-brain” thinking
All system theories were created by engineers
and scientists (“left-brainers”).

Analysis in management
This systems movement […] has come to
form the foundation of today’s dominant
management discourse, so importing the
engineer’s notion of control into understanding
human activity.
– Ralph Stacey

Problem: Dehumanization
Cold numbers in spreadsheets

Problem: Objectivation
“Designing” human interaction

Problem: Alienation
Instructions from ivory towers

Problem: Prediction
“Controlling” the future

Problem: Attribution
Blaming people for problems

• Problem: Dehumanization
• Problem: Objectivization
• Problem: Alienation
• Problem: Prediction
• Problem: Attribution
This list of five problems is my abstraction,
and my attempt at sense-making!

Revenge for “right-brainers”
Some people have suggested more holistic
approaches.

See the whole system
Living systems have integrity. Their
character depends on the whole. The same is
true for organizations.
– Peter M. Senge
The Fifth Discipline

Greater than the sum of the parts
The enterprise must be a genuine whole:
greater than the sum of its parts, with its output
larger than the sum of all inputs.
– Peter F. Drucker
Management

Synthesis, not analysis
Analysis is only one way of thinking;
synthesis is another. [...] In analysis, something
that we want to understand is first taken apart.
In synthesis, that which we want to understand
is first identified as part of one or more larger
systems.
Recreating the Corporation

Problem: Impossible
If everything is connected to everything,
what is the “whole”?

Problem: Unscientific
new age fluffy bunnies
– Dave Snowden
http://km4meu.wordpress.com/2011/09/14/radical-ideals-and-fluffy-bunnies/

An unquestioned assumption
By formulating a research aim to uncover
the fundamental characteristics of systems of
various kinds, we were making the
unquestioned assumption that the world
contained such systems.
– Peter Checkland
Systems Thinking, Systems Practice

Actually, there are no systems
Where to draw a boundary around a
system depends on the questions we want to
ask.
– Donella H. Meadows
Thinking in Systems

There are perspectives
A system is a way of looking at the world.
– Gerald M. Weinberg
Introduction to General Systems Thinking

Systems depend on context
The boundaries of systems keep shifting,
using reductionism and holism.
How much to abstract or extend depends on
what you want to understand.

No radical holism/reductionism
Complexity theory does not embrace the
radical holism of systems theory, the notion that
everything matters and everything has to be
taken into account.
– Steve Phelan
The Interaction of Complexity and Management

Brains, bacteria, immune systems, the Internet,
countries, gardens, cities, beehives…
They’re all complex adaptive systems.

A team is a complex adaptive system (CAS), because it
consists of parts (people) that form a system (team),
and the system shows complex behavior while it keeps
adapting to a changing environment.

One perspective
The properties of complex adaptive systems are:
• Aggregation
• Nonlinearity
• Flows
• Diversity
– John H. Holland
Hidden Order

Another perspective
There are six notions in complexity theory:
• Sensitivity to initial conditions (butterfly effect)
• Strange attractors (unpredictability)
• Self-similarity (fractals)
• Self-organization (distributed control)
• The edge of chaos (emergence)
• Fitness landscapes (continuous improvement)
– Michael C. Jackson
Systems Thinking: Creative Holism for Managers

And it evolved like this...
– Jeffrey Goldstein
Complexity and the Nexus of Leadership

Or like this...
http://en.wikipedia.org/wiki/File:Complex_systems_organizational_map.jpg

Or like this...
http://www.flickr.com/photos/jurgenappelo/4948963883/

Of course, these are all just abstractions...

Complexity theory itself is complex
Papers are being posted on the Web long
before publication and there is rapid movement
of what could be called precodified or
protocodified knowledge. […] I am not saying
whether this is good or bad; I am merely
suggesting that this is one of the characteristics
affecting the evolution of complexity sciences.
– Max Boisot

Complexity theory is about change
Complexity theory is not a cohesive theory.
It is not one equation. It is really a collection of
ideas about the concept of change in
complex adaptive systems […]. It talks about the
dynamics of change in a system.
– Irene Sanders

People and relationships
We found that this new science leads to a
new theory of business that places people and
relationships […] into dramatic relief.
– Roger Lewin, Birute Regine

And about hype
I think the next century will be the century
of complexity.
– Stephen Hawking
San Jose Mercury News, 23 January 2000

And about unification
We can justifiably think of Complexity as a
sort of umbrella science – or even the Science of
all Sciences.
– Neil Johnson
Simply Complexity

But who wants unification?
Scholars […] have been understandably
reluctant to see their pet subject as simply one
more example of some broader 'general
system'!
– Peter Checkland

No consensus, no unification
Perhaps because the field has attracted
researchers from a wide diversity of home
disciplines, there is no consensus as to how
to define, measure, describe, or interpret
"complexity."
– Steve Maguire

Complexity theory explains why complex
problems need multiple perspectives.
It is successful in explaining its own failure at
being one theory!

But complexity is growing
Accelerating economic and social change in
the global economy, the consequent imperative
for ever faster innovation, the emergence of
global networks of partners, […] the
multiplication of media channels, and
burgeoning diversity in both the workplace and
marketplace.
– Steve Denning
Radical Management

And complicated is not complex
Analysis works in complicated cases (plic in
complicated means "fold"), but the
interweavings (plex) of the complex do not yield
to reductionist analysis or to a concentration on
details.
– Michael L. Lissack

You can try to simplify a system to make it understandable
But you cannot linearize the system to make it predictable

Complicated vs. Complex is itself is reductionism
(and a false dichotomy)!
Some systems can be seen as both complicated
and complex.

This is all great, but
how do we use all
these ideas about
complexity

The Scientific Method
The traditional approach...
1. Observations
2. Hypotheses
3. Predictions
4. Experiments
http://en.wikipedia.org/wiki/Scientific_method

Houston, we have a problem
This makes the standard method of
accumulating evidence highly problematic,
because it is based on the assumption of
repetitive events. Evidence is accumulated by
observing repetitions in traditional science but
rather different notions of evidence need to be
developed for the complexity sciences.
– Ralph Stacey

Complexity invalidates prediction!
The crucial problem which science faces is
its ability to cope with complexity.
– Peter Checkland

Complexity theory predicts that we cannot rely
on predictions.

That doesn’t seem
very helpful.
Is there anything
else we can do

http://www.flickr.com/photos/hey__paul/6223650676/
What’s
this?

model
mod·el noun ˈmä-dəl
– a usually miniature representation of something
– a description or analogy used to help visualize
something (as an atom) that cannot be directly
observed
– a system of postulates, data, and inferences
presented as a mathematical description of an
entity or state of affairs
http://www.merriam-webster.com/dictionary/model

We use models for two reasons
Confirmatory models: prediction & control
Exploratory models: insight & understanding
– Steve Phelan

We’ll focus on exploratory models
Confirmatory models are impossible to make in
complexity theory. But we can use exploratory
models to aid in sense-making.

Making sense of improvement
http://en.wikipedia.org/wiki/PDCA
http://gumption.typepad.com/blog/entrepreneuria/

Making sense of learning
Shu
Ha
Ri
Beginner
Advanced Beginner
Competent
Proficient
Expert
http://en.wikipedia.org/wiki/Shuhari
http://en.wikipedia.org/wiki/Dreyfus_model_of_skill_acquisition

Making sense of complexity
Ralph Stacey Dave Snowden

There’s only 1 criterion for models
Does the model help people to make sense of
the world (insight and understanding)?

Of course, it requires a balance
How detailed (complicated) will you make the
model to make it useful?
The usefulness of a model depends on the
complexity of the mind and of the environment.

A simple model of London
http://3.bp.blogspot.com/_FHHhq9JdAXg/TIUalCWz_zI/AAAAAAAAAUg/C0CTOtV6iiw/s1600/cowshed-spasmap-aw8-low+res.jpg

A complicated model of London
http://www.bestcitymaps.com/citymaps/images/london.jpg

http://effectiveagiledev.com/AgileTraining/ScrumImplementationWorkshop/tabid/74/Default.aspx
A simple model for projects

http://wyzsadvies.blogspot.com/2010/08/project-beheer-en-de-papierwinkel.html
A complicated model for projects

A simple model for managers
– Jurgen Appelo
Management 3.0

A complicated model for managers
– Dan Levinthal

Models are never perfect
All models wrong, some are useful.
– George Box
Usefulness is context-dependent. It depends
on the people and their environment.

http://www.flickr.com/photos/miguelpdl/4356975474/
What’s
this?

metaphor
met·a·phor noun ˈme-tə-ˌfȯr also -fər
– a figure of speech in which a word or phrase
literally denoting one kind of object or idea is used
in place of another to suggest a likeness
or analogy between them
http://www.merriam-webster.com/dictionary/metaphor

Metaphors in science
• Butterfy Effect
• Edge of Chaos
• Survival of the Fittest
Metaphors are fuzzy but effective models.

Metaphors in management
organizations as machines;•
organizations as organisms;•
organizations as brains;•
organizations as flux and transformation;•
organizations as cultures;•
organizations as political systems;•
organizations as psychic prisons;•
organizations as instruments of domination;•
organizations as carnivals• .

Organizations as machines
Machine images pervade management
jargon. We have managers who “run” a
company, much the way you would run a
machine. We have the “owners” of the
company, which is perfectly appropriate
terminology for a machine but somewhat
problematic when applied to a human
community. And of course there are leaders
who “drive change.”
– Peter M. Senge

Danger of metaphors
Reminiscence syndrome
Jumping to conclusions because things look “the same”
– Jack Cowan

Example: inventory as waste
The metaphor of inventory applied to
knowledge work can be useful, but it fails fast.
It leads people to draw conclusions about
“waste” that make no sense (to me).

Useful question: when do they fail?
Metaphors are the weakest of all models.
They fail fast.
Science likes mathematical models.
They fail much later.

A key point of complexity theory
Multiple weak models can make just as much
sense as one strong model. (And it’s certainly
better than no models.)
In the end all models fail.

This point makes it clear you also need other
people’s views on complexity thinking.
A single perspective is not enough!

What’s this?
http://www.flickr.com/photos/adactio/2634586376/

mathematics
math·e·mat·ics noun ˌmath-ˈma-tiks, ˌma-thə-
– the science of numbers and their operations,
interrelations, combinations, generalizations, and
abstractions and of space configurations and their
structure, measurement, transformations, and
generalizations
http://www.merriam-webster.com/dictionary/mathematics

Scientific management (Taylorism)
The earliest attempt at applying mathematics to
management of organizations.
• Improving efficiency
• Reducing variation
• Increasing output
http://en.wikipedia.org/wiki/Scientific_management

What’s
this?
http://www.flickr.com/photos/inacentaurdump/2604198505/

simulation
sim·u·la·tion noun ˌsim-yə-ˈlā-shən
– the imitative representation of the functioning of
one system or process by means of the functioning
of another
– examination of a problem often not subject to
direct experimentation by means of a simulating
device
http://www.merriam-webster.com/dictionary/simulation

The heart of complexity theory
At the heart of complexity theory are these
formal models that utilize new techniques in
artificial intelligence to motivate artificial
agents. Behind them are some heavy-duty
mathematics and computer science.
– Steve Phelan

Problem: prediction & control
For systems dynamics thinkers, the aim is to
identify leverage points for interventions that
will enable them to identify where, when and
how to initiate change and so stay in control.
However, the ability to do this in a system that is
sensitive to tiny changes is called into question.
That obviously has serious implications for the
human ability to stay ‘in control’.
– Ralph Stacey

What’s
this?
http://www.flickr.com/photos/mikebaird/3464803900/

pattern
pat·tern noun ˈpa-tərn
– a form or model proposed for imitation
– a reliable sample of traits, acts, tendencies, or other
observable characteristics of a person, group, or
institution
– a discernible coherent system based on the
intended interrelationship of component parts
http://www.merriam-webster.com/dictionary/pattern

Causal Loop Diagrams
Seeking
patterns

Archetype: Shifting the burden
Shifting the burden, dependence, and
addiction arise when a solution to a systemic
problem reduces (or disguises) the symptoms,
but does nothing to solve the underlying
problem.
Thinking in Systems

Archetype: Shifting problems
Solutions that merely shift problems from
one part of a system to another often go
undetected because, unlike the rug merchant,
those who “solved” the first problem are
different from those who inherit the new
problem.
– Peter M. Senge

Archetype: The easy way out
We all find comfort applying familiar
solutions to problems, sticking to what we know
best.
– Peter M. Senge

Problem : objectivation
Consider how this systems thinking
compares with the earlier framework of
scientific management. The manager continues
to be equated with the natural scientist, the
objective observer, and just as the scientist is
concerned with a natural phenomenon, so the
manager is concerned with an organization.
– Ralph Stacey

Problem : objectivation
Hard systems thinking is unable to deal
satisfactorily with multiple perceptions of
reality. […] Different stakeholders will have
diverse opinions about the nature of the system
they are involved with and about its proper
purposes.

So, how should
we use those
models in a
social system

“Soft Systems Thinking”

“Soft Complexity”
Systems theory ->
Hard systems thinking
Soft systems thinking
Complexity theory ->
Hard complexity
Soft complexity
– Steve Maguire

“Social Complexity”
– Dave Snowden
http://emergentpublications.com/ECO/ECO_other/Issue_6_1-2_19_FM.pdf

Complexity Thinking
(as I see it)

1) Address complexity with complexity
The complexity of a system must be
adequate to the complexity of the environment
that it finds itself in.
– Max Boisot
The human mind is more complex than tools
Use stories, metaphors, pictures…

Law of Requisite Variety
If a system is to be stable the number of
states of its control mechanism must be greater
than or equal to the number of states in the
system being controlled.
– William Ross Ashby

Law of Requisite Variety
Ashby's law of requisite variety is as
important to managers as Einstein's law of
relativity to physicists.
– Anthony Stafford Beer
Designing Freedom

The Kanban board is complicated, not complex.
http://www.xqa.com.ar/visualmanagement/tag/kanban/

Narratives useful for sense-making
[Complexity thinkers] argue that complex
thinking is best accomplished in a narrative
mode of thinking rather than the propositional
thinking of the traditional scientific method. […]
Both involve recursiveness, nonlinearity,
sensitive dependency on initial conditions,
indeterminacy, unpredictability and emergence.
– Ralph Stacey

https://picasaweb.google.com/114043888000663006020/ALENetworkWorldCafeAtXP2011Results
Consider stories, metaphors, pictures or video

Reduction vs. Absorption
Complexity reduction entails getting to
understand the complexity and acting on it
directly, including attempting environmental
enactment. Complexity absorption entails
creating options and risk-hedging strategies.
– Max Boisot

From reduction to absorption
Top-down rules reduce an organization’s
ability to deal with variety.
– John Seddon
Freedom from Command & Control

Insofar as the business environment is
becoming more complex, firms will need to shift
from the complexity-reducing strategies that
secured their success from the end of the
nineteenth until the end of the twentieth
century and place more stress on complexity-
absorbing ones-a shift away from bureaucracies
and toward fiefs, markets, and clans.
– Max Boisot
Reduction vs. Absorption

2) Use a diversity of models
Complexity itself is anti-methodology. It is
against "one size fits all."
– Tom Petzinger
Multiple weak models can make just as much
sense as one strong model.

Each systems approach is useful for certain
purposes and in particular types of problem
situation. A diversity of approaches, therefore,
heralds not a crisis but increased competence in
a variety of problem contexts.
Multiple approaches

Different people and tools•
Different metaphors and analogies•
Different patterns and simulations•
Different methods and practices•
Multiple approaches

3) Assume dependence on context
Best practice is past practice.
– Dave Snowden

Retrospective coherence
Any evidence provided will depend on the
period selected and the place in which the
events are occurring as well as other aspects of
context. It follows that any relationship anyone
identifies between a management action and an
outcome could have far more to do with a
particular time and place where the sample is
selected than anything else.
– Ralph Stacey

4) Assume subjectivity and coevolution
The observer influences the system, and the
system influences the observer.
The people form the culture, and the culture
forms the people.

Feedback changes
the whole system.

5) Anticipate, adapt, explore
Anticipation
Looking forward, proactive, imagining improvement
Adaptation
Looking backward, reactive, responding to change
Exploration
Trying things out, safe-to-fail experiments

6) Develop models in collaboration
Does the model help people to make sense of
the world (insight and understanding)?

1. Address complexity with complexity
2. Use a diversity of models
3. Assume dependence on context
4. Assume subjectivity and coevolution
5. Anticipate, adapt, and explore
6. Develop models in collaboration

Address1. complexity with complexity
Use2. a diversity of models
Assume3. dependence on context
Assume4. subjectivity and coevolution
Anticipate, adapt, and explore5.
Develop6. models in collaboration
Does Scrum Match ComplexityThinking?
Yes
No
Yes
Yes
No
Yes

Example
What is the purpose of an organization?

It’s about the shareholder
Our aim is to be the biggest or second
biggest market player, and to return maximum
value to stockholders.
– Jack Welch (General Electric)
http://en.wikipedia.org/wiki/Shareholder_value

It’s about the customer
There is only one valid definition of business
business purpose: to create a customer.
– Peter F. Drucker
Management

It’s about the employee
When we talk to our People, we proudly
draw a pyramid on the chalkboard and tell
them: You are at the top of the pyramid. You are
the most important person to us. You are our
most important Customer in terms of priority.
– Colleen Barrett (Southwest Airlines)
http://leaderchat.org/2011/01/10/customers-employees-and-shareholders%E2%80%94who-comes-first-in-your-organization/

It’s about the organization
The fundamental mission of an organization
is to survive.
– W. Warner Burke
Organization Change

It’s about the environment
The function of firms is to produce and
distribute wealth.
Recreating the Organization

It’s about all of them
Organizations must be viewed as social
systems serving three sets of purposes: their
own, those of their parts and those of the wider
systems of which they are part.

It’s about none of them
A system has no purpose. Purpose is a
relation, not a thing to have.
Introduction to General Systems Thinking

Well, it depends...
Purposes are deduced from behavior, not
from rhetoric or stated goals.
Thinking in Systems

My view (with complexity thinking hat)
They all have a good point.
Sometimes we need a simple model.
Sometimes we need a complicated model.

The Shu-Ha-Ri of purpose
Shu Delight customers
Ha Delight all stakeholders
Ri Delight yourself

All models can be useful.
Some fail faster than others.
– Jurgen Appelo

There is nothing as practical as good theory.
– Kurt Lewin

We should not take our models too
seriously.
Introduction to Systems Thinking

Is it Complexity Thinking
or Systems Thinking ++

The magpie
Finds what’s valuable and uses it in its nest
The only bird capable of self-reflection

Address1. complexity with complexity
Use2. a diversity of models
Assume3. dependence on context
Assume4. subjectivity and coevolution
Anticipate, adapt, and explore5.
Develop6. models in collaboration
Copy and change7.

The peacock
Showing off a complicated but totally useless idea
Not capable of self-reflection

Don't take speakers too seriously.
Listen (critically) to the magpies
Be wary of the peacocks.

@jurgenappelo
slideshare.net/jurgenappelo
noop.nl
linkedin.com/in/jurgenappelo
jurgen@noop.nl

http://creativecommons.org/licenses/by-nd/3.0/
This presentation was inspired by the works of many people, and
I cannot possibly list them all. Though I did my very best to attribute
all authors of texts and images, and to recognize any copyrights, if
you think that anything in this presentation should be changed,
added or removed, please contact me at jurgen@noop.nl.

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