Simplicity on the Other Side of Complexity

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Simplicity on the Other Side of Complexity

• An Introduction to Complexity
• Science, Management Health Care

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Complexity Lens Reflection

• We are finely tuned complex adaptive systems,
  especially when we are working at our highest
  intelligence purpose.
• Describe a time or experience when a
  collaborative effort created or encouraged
  something surprising. It should be something you
  are proud to have been a part of a difference
  that made a difference. It can be a very small,
  subtle thing. It could be from your current
  workplace or a past effort of any kind.
• See the Workbook Handout

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Heart Rate Dynamics
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Blood Cell Dynamics
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EEG Dynamics
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Looking For Success In The Wrong Places

• Substantial gains in performance - 40 - have
  been documented in productivity, quality, value.
• What matters is managers point of view.
• confronting how we think about work,
  organizations, and the people in them.
• Pfeffer, The Human Equation

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Tom Petzinger Wall Street Journal

• Even as it was toppled from unassailability in
  science, Newtonian mechanics remained firmly
  lodged as the mental model of management, from
  the first stirrings of the industrial revolution
  right through the advent of modern-day M.B.A.
  studies.
• As biologists and other pioneers began to
  realize, it could not explain the self renewing
  processes of life.

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Scientific Origins
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Before Complexity

• Scientists believed the future was knowable given
  enough data points
• Dissecting discrete parts would reveal how
  everything -- the whole system -- works
• Phenomena can be reduced to simple cause effect
  relationships
• The role of scientists, technology, leaders was
  to predict and control the future
• Increasing levels of control over nature would
  improve our quality of life

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Newton the Machine Metaphor

• In science
• the search for the basic building blocks
• In management
• The whole is no more or no less than the sum of
  parts, so focus on the parts (e.g. functions,
  disciplines)
• Organizations and people are implicitly viewed as
  machines (or machine parts)

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Roots Of Complexity

• Santa Fe Institute
• Physics-chaos theory
• Math-fractal geometry
• Meteorology-butterfly effect
• Biology-complex adaptive systems

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• From Physics Envy To Biology Envy

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Surprising Convergence of Disciplines
Chemistry
Computer Science
Biology
Mathematics
Psychology
Sociology
Physics
Economics
Meteorology
Ecology
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Surprising Convergence We Stand on the
Shoulders of Giants
Chemistry Ilya Prigogine, Order Out of Chaos
Sociology Robert Alexrod, Complexity of
Cooperation
Physiology Ary Goldberger, Cardiac Research
Complex Adaptive Systems ((( Murray Gell-Mann
))) The Quark the Jaguar ((( Stuart Kaufmann
))) At Home in the Universe ((( John Holland
))) Emergence ((( Brian Arthur ))) Increasing
Returns
Physics-Ecology Fritjof Capra, Web of Life
Physics David Bohm, Wholeness the Implicate
Order
Socio-Biology E.O. Wilson Consilience
Meteorology Edward Lorenz, The Butterfly Effect
Computer Science Christopher Langton
Philosophy Ken Wilbur, Integral Science Religion
Genetics R.C. Lewontin, Biology as Ideology
Ecology James Lovelock, Gaia Hypothesis
Mathematics Mandlebrot, Fractals
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More Giants

• Complexity applied to organizations

Strategy/Leadership Ralph Stacey
Market Strategy Kevin Kelly
Leadership Gareth Morgan
Complex Adaptive Systems
Management Brenda Zimmerman
Leadership Meg Wheatley
Strategy S. Brown K. Eisenhardt
Innovation Everett Rogers
Sustainability Paul Hawken/James Moore
Planning Henry Mintzberg
Learning Etienne Wegner
Management Jeffery Goldstein
Mass Customizing Martha Rogers
Org Development David Cooperrider
Knowledge Ikujiro Nonaka
Org Dynamics Roger Lewin/Birute Regine
People Practices Jeffery Pfeffer
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Inspiration from Complex Adaptive Systems

• Definition A collection of individual agents,
  who have the freedom to act in unpredictable
  ways, and whose actions are interconnected such
  that one agents actions changes the context for
  other agents.
• Examples termite colonies, stock markets, the
  Internet, gardens, human beings, groups of people

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DefiningComplex Responsive Systems

• Alternative CAS definition by Ralph Stacey
• CASs consist of a network of agents that
  interact with each other according to a set of
  rules that require them to examine and respond to
  each others behavior to improve their behavior
  and thus the behavior of the system they
  comprise.

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Interdependent Attributes
Adaptable Elements
Natural Emergence Creativity
Simple Rules
Order w/o Central Control
Embedded Systems
Co-Evolution
Not Predicable in Detail
Non-Linearity
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Attributes of Complex Adaptive Systems

• Elements of the system change themselves (they
  adapt)
• Complex behaviors can emerge from a few simple
  rules that are applied locally
• Emergence of novelty creativity is a natural
  state
• Order emerges without central control
• Non-linearity small changes can have BIG effects
• Systems are embedded in systems their
  interdependency matters
• Not predictable in detail forecasting is an
  inexact, yet boundable, art
• Co-evolution of life proceeds through constant
  tension balance

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Living Systems Are Non-Linear

• Not predictable in long-term
• Future not just unknown but unknowable
• Small events may trigger huge effects
• Huge efforts may have negligible effects

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Examples Of Non-Linearity

• Rosa Parks refusal to yield her seat
• Weather, hurricanes
• A statement or word used by Alan Greenspan

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Stacey DiagramKnow When Your Challenges Are In
the Zone of Complexity
Far from
Chaotic Seek Patterns
Agreement
Zone of Complexity
Simple Plan, control
Close to
Far from
Certainty
Close to
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When Complexity Practices Are Useful

• When you are frustrated with current and past
  approaches
• When challenges are wicked and messy
• When you want to start something new
• When there is little agreement or certainty about
  how to respond
• See the Zone of Complexity in Ralph Staceys
  diagram

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Nine Interdependent Principles
Good Enough Vision
Clockware/ Swarmware
Complexity Lens

Chunking
Tune To The Edge
Competition/ Cooperation
Seek Paradox
Shadow System
Multiple Actions
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Seeing Through A Complexity Lens
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Simple Rules in Practice

• Living systems follow simple rules
• Craig Reynolds Boids simulation uses minimum
  rules of interaction
• Gareth Morgans min specs
• Simple rules include Must dos or Never dos

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Example Reynolds Steering Rules

• Maintain a minimum distance from other boids and
  objects
• Match speed of neighboring boids
• Move toward the center of mass of flock-mates in
  your area
• Complex flocking emerges!

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The 15 Principle

• W. Edwards Deming suggested that everyone -- from
  the CEO to the front line worker -- has influence
  over 15 of their system. The other 85 is
  beyond their discretionary control.
• Recognize that you have 15 discretionary
  influence it may sound small but you can use it
  to make a difference that makes a difference.
• Marry 15 principle with Multiple Actions At The
  Fringes Let Direction Emerge

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Tune Your Place To The Edge
Far from
Chaotic
Info Flow Diversity Anxiety
Agreement
Simple
Close to
Far from
Certainty
Close to
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• Farmers dont grow crops. They create the
  conditions for crops to grow.
• Gareth Morgan