28 terms

Systems Thinking

CUMC Mailman Midterm 2013
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What characterizes a simple system?
Homogeneity, i.e., all agents the same
Random mixing, no structure
No feedback, i.e., no learning or adaptation
Deterministic, predictable cause‐effect relationships
No connection between micro/macro phenomena
System can be reduced to parts and processes
Answers are knowable, with recipes or prescriptions for action and replicated
What is a Complex Adaptive System?
A complex adaptive system is a collection of individual
agents with freedom to act in ways that are
not always totally predictable, and whose actions are
interconnected so that one agent's actions changes the
context for other agents
Hallmarks of a complex adaptive system
Heterogeneity, ie diversity of agents
Dynamic: Nonlinear dynamics
Contact structure, networks, organization
Feedback, adaptation, learning, evolution
Exhibits policy resistance
Emergence
Often no equilibrium
What is Systems Thinking?
It is a way of thinking in approaching problems and in
designing solutions that appreciates the very nature of complex adaptive systems as:
-dynamic, constantly changing,
-governed by historyand by feedback,
-where the role and influence of stakeholders and context is critical, and
-where new policies and actions (of different stakeholders) often generate counterintuitive and unpredictable effects, sometimes long after policies have been implemented
- policy resistance.
Policy resistant problems are almost always systems problems because...
Tight coupling, people interact with one another
Feedback, individuals interact with their environment
Nonlinearity
History dependent
Characterized by tradeoffs
Counterintuitive, cause and effect separated by time an space
Example of a simple system
Following a Recipe
The recipe is essential
• Recipes are tested to
assure replicability of
later efforts
• No particular expertise;
knowing how to cook
increases success
• Recipe notes the quantity
and nature of "parts"
needed
• Recipes produce standard
products
• Certainty of same results
every time
Example of a complicated system
A rocket to the moon
Formulae are critical and
necessary
• Sending one rocket
increases assurance that
next will be ok
• High level of expertise in
many specialized fields +
coordination
• Separate into parts and
then coordinate
• Rockets similar in critical
ways

• High degree of certainty
of outcome
Example of a complex system
Raising a child
Formulae have only a
limited application
• Raising one child gives no
assurance of success with
the next
• Expertise can help but is
not sufficient;
relationships are key
• Can't separate parts from
the whole
• Every child is unique
• Uncertainty of outcome
remains
Why are Health Systems are
Complex Adaptive Systems
Observance of health systems - including
findings from failed interventions - tells us that
the health system is a complex system
BUT
Methods for addressing health problems are
designed as though the health system is merely
complicated
Understanding systems helps to
• Anticipate synergies
• Mitigate negative emergent behaviors
When...
• designing changes in the health system
• evaluating these interventions
How does Systems Thinking inform Public
Health Practice?
-What is happening now? (Events and Behaviors)
-How do patterns play out over time and space?(Patterns)
-What are the drivers and
deep structures? How are
they related? Designing (Structures, Paradigms, Conditions)
The central argument
-Dynamic models point to different possible explanations for observed complex phenomena
-Dynamic models can be used in conjunction with empiric data to narrow down possible explanations and should have a central role in public health analyses
Without Systems Thinking
We are at risk of committing a Type III Error : the Right Answer for the Wrong Question! (In other words we have the perfect solution for a problem that has not been adequately understood!)
We risk doing the wrong things with
greater and greater efficiency rather than
establishing what is the right thing to be
doing.
Obstacles to adopting systems approach
Aversion to failure
Pressure for uniformity
Commitment to command and control structures
Time pressure
Failure to evaluate (turf and secrecy)
Knife of efficiency
Complex system thinking forces us
to think about:
History and context
Interrelations among 'agents'
Discontinuities
Hierarchies
Randomness and chance
Systems Thinking as a World View
Systems and systems problems are more than
the sum of the systems individual components

Systems thinking acknowledges that system
behaviors (and problems) emerge over time as
a result of interactions and relationships
amongst the both internal and external system
components
Systems Thinking as a Process
Systems thinking is an ordered, methodological
approach to understanding problem situations
and identifying solutions to these problems

It takes into account both the "forest and the
trees" - through a process of synthesis, analysis
and inquiry.
Synthesis
putting together, assessing the system as a
whole in its environment/ context e.g. Rich Picture,
Interrelationship Digraph
Analysis
(combined with synthesis) - understanding the
detail and how the components fit together within a
context e.g. Systems Maps (Causal loop diagrams)
Inquiry
developing a range of robust solutions through
critical systemic investigation and thinking e.g. Systems
Dynamic Modeling, Scenario Planning, Critical Systems
Heuristics, Soft Systems Methodologies
Useful Systems Thinking Tools
• Rich Pictures
• Inter-relationship diagraphs
• Systems maps (causal loop diagrams)
• Systems dynamic modeling
• Agent based modeling
• Network analysis
• Scenario development
STEP 1: Rich Pictures
Simply a drawing of the way you see a given situation
- represent all of the elements, relationships, emotions, and interactions relevant to the issue at hand
• Used in the synthesis phase as a mechanism to
gather and capture information about complex
situations
• Ideally built through an iterative process of
engagement and reflection with a group of key
stakeholders
• Attend to relationships and feedback
• Avoid wordiness - use symbols
• Sweep in multiple perspectives
• Remember to consider 'behavior over
time'
Step 2: Identifying Variables
10 - 12 Variables that meet these guidelines:
- Nouns instead of verbs
• Paying user fees vs. User fees
- Measurable and changes over time
• State of mind vs. Staff motivation
- Neutral
• Poor quality of care vs. Quality of Care
- Distinguish between perceived and actual states
• Perceptions of Quality of care vs. Quality of Care
- Include outcome of interest
Definition and Characteristics of a Variable
• Is an element in a situation that may act or be
acted upon.
• Its value can vary up or down over time.
• Is not an event.
• Is something you can discuss as "the level of ..."
• Key test - it's a variable if you can plot its value
over time.
Step Three: Create an Interrelationship Diagraph
...
Step Four: Identify the main drivers and
outcomes
Identify Drivers and Outcomes
For each variable, count the number of arrows
coming in and going out:
• Outcomes: Variables with more arrows coming in
than out
• Key Outcomes or Results: Variables with the most
incoming arrows
• Drivers: Variables with more arrows going out than
in
• Root Causes: Variables with the most outgoing
arrows
The Interrelationship Digraph is a
visual tool that:
• Builds on the rich picture
• Helps make use of team knowledge in the
absence of hard data
• Plots the complexity of causal relationships
• Builds team consensus on priorities.
Purpose of Interrelationship Digraphs
• Force us to consider all possible
interactions amongst the variables
• Challenges our mental models
• Identifies key outcomes and drivers in a
complex system
• Forms the basis from which we can
identify feedback loops and surface a
systems map
Step Five: Surface a Systems Map
Beginning a Systems Map
• Identify your output or outcome of interest
variable
• Identify your key intervention variable
Step Six: Identify feedback loops
Reinforcing loops

• A reinforcing loop is one in which an action
produces a result which influences more of the
same action thus resulting in growth or decline at
an ever-increasing rate
• Where feedback increases the impact of a
change, we call this a Reinforcing Loop.
• Positive reinforcing loops produce virtuous
cycles
• Negative reinforcing loops produce vicious cycles.
Balancing Loops
• Balancing processes generate the forces of
resistance, which eventually limit growth,
maintain stability, and achieve equilibrium

• Balancing loops reduces the impact of a change
and are goal seeking

• Shortcut to determining a balancing loop: Count
the number of minus signs ( - ) in the loop: an
odd number of minus signs = balancing loop
Step Seven: Ongoing revision
How do we use Systems Thinking Tools?

- Explain root problems, their drivers and feedback
mechanisms
- Identify potential leverage points for interventions
- Explore appropriate intermediate and outcome
measures
- Model the potential impact of system
interventions
- Identify potential policy resistance
- Formulate appropriate research questions
- Make explicit our theory of change