Dynamic Complexity 50th Annual Meeting of the International Society for the Systems Sciences George P.

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Transcript Dynamic Complexity 50th Annual Meeting of the International Society for the Systems Sciences George P.

Dynamic Complexity
50th Annual Meeting of the
International Society for the Systems Sciences
George P. Richardson
Rockefeller College of Public Affairs and Policy
University at Albany, SUNY
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
1
Learning in and about
Complex Systems
Sterman (1994)
Real World
Unknown structure
Dynamic complexity
Time Delays
Impossible experiments
Virtual World
Implementation
Game playing Decisions
Inconsistency
Short term
Known structure
Variable Complexity
Controlled Experiments
Selected
Missing
Information Delayed
Feedback
Biased
Ambiguous
Strategy, Structure, Inability to infer
dynamics from
Decision Rules
mental models
Rockefeller College of Public Affairs and Policy
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Misperceptions
Mental Unscientific
Biases
Models
Defensiveness
G. P. Richardson
July 2006
2
Dynamic Complexity arises because systems are…
•
•
•
•
Changing over time
Tightly coupled
Governed by feedback
Nonlinear: changing
dominant structure
• History-dependent
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•
•
•
•
•
Self-organizing
Adaptive
Counterintuitive
Policy resistant
Characterized by
tradeoffs
G. P. Richardson
July 2006
3
System Dynamics Contributions
• Thinking dynamically
• Move from events and decisions to
patterns of continuous behavior
over time and policy structure
• Thinking in circular causal /
feedback patterns
• Self-reinforcing and self-balancing
processes
• Compensating feedback structures
and policy resistance
• Communicating complex nonlinear
system structure
Rockefeller College of Public Affairs and Policy
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• Thinking in stocks and flows
• Accumulations are the resources
and the pressures on policy
• Policies influence flows
• Modeling and simulation
• Accumulating (and remembering)
complexity
• Rigorous (daunting) model
evaluation processes
• Controlled experiments
• Reflection
G. P. Richardson
July 2006
4
The system dynamics modeling process
Perceptions of
System Structure
Comparison and
Reconcilation
System
Conceptualization
Representation of
Model Structure
Model
Formulation
Empirical and
Inferred Time
Series
Comparison and
Reconciliation.
Deduction Of
Model Behavior
Adapted from Saeed 1992
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
5
Processes focusing on system structure
Mental Models,
Experience,
Literature
Empirical
Evidence
Perceptions of
System Structure
Comparison and
Reconcilation
System
Conceptualization
Representation of
Model Structure
Model
Formulation
Diagramming and
Description Tools
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
6
Processes focusing on system behavior
Empirical
Evidence
System
Conceptualization
Model
Formulation
Rockefeller College of Public Affairs and Policy
University at Albany
Literature,
Experience
Empirical and
Inferred Time
Series
Comparison and
Reconciliation.
Deduction Of
Model Behavior
Computing
Aids
G. P. Richardson
July 2006
7
Two kinds of validating processes
Mental Models,
Experience,
Literature
Literature,
Experience
Empirical
Evidence
Perceptions of
System Structure
System
Conceptualization
Comparison and
Structure
Reconcilation Validating
Processes
Representation of
Model Structure
Diagramming and
Description Tools
Rockefeller College of Public Affairs and Policy
University at Albany
Model
Formulation
Empirical and
Inferred Time
Series
Behavior
Validating
Processes
Comparison and
Reconciliation.
Deduction Of
Model Behavior
Computing
Aids
G. P. Richardson
July 2006
8
Six Traditions
Contributing to the
Evolution of
Feedback Thought
•Biology: math models
•Econometrics
•Engineering
•Social Sciences
•Biology: homeostasis
•Logic
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Two Threads of
Feedback Thought
•System dynamics arises in
the servomechanisms thread
(the first four in this list)
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
9
Forrester’s Hierarchy of System Structure
• Closed boundary around the system
• Feedback loops as the basic structural elements within the
boundary
• Level [stock] variables representing accumulations within the
feedback loops
• Rate [flow] variables representing activity within the feedback
loops
•
•
•
•
Goal
Observed condition
Detection of discrepancy
Action based on discrepancy
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
10
The Endogenous Point of View
• The closed causal boundary takes top billing
• Dynamics arise from interactions within that boundary
• Systems thinking is the mental effort to uncover
endogenous sources of system behavior.
Rockefeller College of Public Affairs and Policy
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July 2006
11
Dynamics
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12
New York City Population, 1900-2000
Bronx
Brooklyn
Manhattan
Queens
Staten Island
9000000
8000000
7000000
6000000
5000000
4000000
3000000
2000000
1000000
0
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
13
Global Atmospheric Methane (1860-1994)
Global Atmospheric Methane
400
350
Teragrams
300
250
200
150
100
50
1980
1950
1920
1890
1860
0
Year
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G. P. Richardson
July 2006
14
Global Average Temperature
(Reconstruction 1400-1980; Data 1902-1998)
Quic kTime™ and a
TIFF ( LZW) dec ompres s or
are needed to s ee this pic ture.
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
15
Stocks and Flows
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G. P. Richardson
July 2006
16
Stocks and flows help to explain
self-reported drug use data
Have
ever
used
Potential
users
Frequent
users
Occasional
users
Past users
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
17
‘Challenging the clouds’ in a study of leasing in the
automobile industry
?
New vehicle
inventory
Production
Purchase
or lease
“We’re not in the used car business!”
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
18
Stocks and flows in new car purchase and leasing
Relative
attractiveness
of leased cars
Used
inventory
Trade cycle
Purchase
used
Vehicles
being driven
New vehicle
inventory
Production
Sell or
trade in
Purchase
or lease
Rockefeller College of Public Affairs and Policy
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Scrapping
G. P. Richardson
July 2006
19
Intuitive view of effect of leasing on auto sales:
Leased car pipeline
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
20
Stocks and Flows in Global Warming
Thought
experiment:
Capital
stock
capital
investment
CO2 annual
production
Atmospheric
CO2
Breakdown of
atmopheric CO2
Economic
activity
incoming solar
heat energy
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Global heat
energy
outgoing global
heat energy
G. P. Richardson
July 2006
21
Life of aerosols in atm
Life of GH gases in atm
Aer osols i n atm
Aer osol br eakdown
Aer osol pr oduction
But although the
stock-and-flow
insight holds, global
climate is of course
much more complex
than that.
GH g ases in atm
GH g as pr oducti on
GH g as br eakdown
Aer osol al bedo efct
Aer osol concentr ati on
Atm volume
Atm volume
~
GH g as concentr ation
~
Ice and cloud cover
Total albedo
~
Ear th Ocean and Atm heat
Cloud cover
GH g as reten efct
Ear th ar ea
Solar heat reachi ng ear th
Ear th heat radi ati on
Ear th ar ea
~
Ice cover
Cloud reten efct
Ice thi ckness
~
Solar heat incoming
Water vap reten efct
Sur face temp
Ice ar ea
Cloud thickness
Cloud ar ea
CO2 r eten efct
Atm temp
~
Ice density
Atm volume
Net thawing factor
Evap factor
Ice volume
Ear th ice
Ear th water
Net thawing
And still much more
complex than this
simple global climate
model, as well!
Cloud volume
Water vap conc
Water vapor in atm
Cloud density
Water in clouds
Evaporation
Condensation
Water density
Precipitati on
Ear th water vol ume
Atm volume
CO2 atm conc
CO2 water conc
Ear th photosynthesi s
Ocean photosynthesis
CO2 i n atm
CO2 i n oceans
Car bon in ocean biomass
Ocean CO2 br eakdown
CO2 ocean r el ease
Atm CO2 breakdown
Ear th biomass decay
Ocean biomass decay
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Car bon in earth biomass
Ocean CO2 pr oduction
CO2 ocean uptake
G. P. Richardson
July 2006
Atm CO2 production
22
Feedback Thinking
“For one good deed leads to another good
deed, and one transgression leads to
another transgression.” (Pirke Avot)
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
23
The Classic Cybernetic Balancing Loop
Goal
Perceived
gap
Perceived
state
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Actual state of
the system
Changes in
the State of
the system
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Intended
actions
G. P. Richardson
July 2006
24
The Cybernetic Loop with Complications
Goal
Perceived
gap
Perceived
state
Autonomous
changes in the state
of the system
Actual state of
the system
Changes in
the State of
the system
Rockefeller College of Public Affairs and Policy
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Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Intended
actions
G. P. Richardson
July 2006
25
The Cybernetic Loop with Complications
Goal
Perceived
gap
Perceived
state
Autonomous
changes in the state
of the system
Actual state of
the system
Changes in
the State of
the system
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Intended
actions
Unintended
actions
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
26
The Cybernetic Loop with Complications
Goal
Perceived
gap
Perceived
state
Autonomous
changes in the state
of the system
Actual state of
the system
Changes in
the State of
the system
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Intended
actions
Unintended
actions
Ramifying
effects
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University at Albany
G. P. Richardson
July 2006
27
A Classic Reinforcing Loop
(Myrdal 1944, Merton 1948)
Prejudice against the
minority group
Majority’s perception
of the inferiority of
the minority
(R)
Economic and educational
discrimination against the
minority
Achievements of the
minority group
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
28
Structure and Dynamics of Terrorist Cells
(R)
Peripheral
support for
terrorists
Terrorist
funding
(R)
Interfering with
terrorist funding
Terrorist
actions
Efforts to
suppress
terrorists
(B)
(R)
Terrorist
zeal
(B)
Recruiting
(R)
terrorists
(R)
Terrorist
group
Terrorist martyrs to
the cause
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(B)
(B)
Losing
terrorists
(R)
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July 2006
29
Insights about building teamwork in a public school
Teamwork and Communication are self-reinforcing
Quality of
communication
+
Trust
+
(+)
Risk
taking
+
Quality of
communication
within teams
+
Teamwork
+ Resistance to
teamwork
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G. P. Richardson
July 2006
30
Isolation of teams and punishing risk-taking inhibit the growth of trust
+
Quality of
communication
+
+
Positive
responses to
experiments
?
Trust
+
(+/-)
Individual
experiments
(+)
Risk
taking
Quality of
communication
between teams
+
(-)
Quality of
communication
within teams
+
Teamwork
+ -
+
Resistance to
teamwork
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
31
But longterm experience with teamwork can build communication
Quality of
+
communication +
between teams
+
Quality of
(-)
communication
Quality of
+
(+)
communication +
+
within teams
Trust
(+)
+
Cumulative
Positive
+
Risk
experience with
responses to
Teamwork
taking
teamwork
(+/-)
experiments
+ +
?
+
Individual
Resistance to
+
+
experiments
Team
teamwork
effectiveness
-
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
32
Risk taking can enhance effectiveness, which can build trust
Quality of
+
communication +
between teams
+
Quality of
(-)
communication
Quality of
+
(+)
communication +
+
within teams
Trust
(+)
+
Cumulative
Positive
+
Risk
experience with
responses to
Teamwork
taking
teamwork
(+/-)
experiments
+ +
?
+
Individual
Resistance to
+
+
experiments
Team
teamwork
effectiveness
+
+
Personal learning
Average personal
effectiveness
+
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
33
A team-player culture is self-reinforcing: an opportunity or a trap
Quality of
+
communication +
between teams
+
Quality of
(-)
communication
Attractiveness
Quality of
+
(+)
of the org to
communication +
+
within teams
+ team players
Trust
(+)
+
Cumulative
Positive
+
Risk
experience with
responses to
Teamwork
+
taking
teamwork
(+/-)
experiments
+ Fraction of
staff
who are
+
?
team players
+
Individual
Resistance to
+
+
experiments
Team
teamwork
+
effectiveness
+
+
Personal learning
Average personal
effectiveness
+
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
34
Likely leverage points
+
Extent of
Learning
Organization
characteristics
present
Quality of
communication
+
+
Trust
(+)
+
+
Positive
responses to
experiments
?
+
(+/-)
Teamwork
+ -
+
Resistance to
teamwork
+
Team
effectiveness
-
+
Personal learning
+
Average personal
effectiveness
Rockefeller College of Public Affairs and Policy
University at Albany
Dialogue
training
Attractiveness
of the org to
+ team players
Cumulative
experience with
teamwork
+
Individual
experiments
Adm
teaching
role
Risk
taking
+
Quality of
communication +
+ between teams
+
(-)
Quality of
(+)
communication +
within teams
+
+
+
+
Fraction of
staff who are
team players
+
+
Understanding
stages of
community
building
G. P. Richardson
July 2006
35
The Problem: 1996 U.S. welfare reform
• Since 1930, a guarantee of lifetime Federal support
• 1996 legislation ended that:
• Temporary Assistance for Needy Families - TANF
• At most five years of Federal support in one’s lifetime
• The clock started for everyone on TANF in 1997
• People began timing out in 2002
• Financial burden will begin shifting to the states and
counties
• A series of facilitated group modeling efforts in three New
York State counties tried to help counties cope. Where are
the leverage points?
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University at Albany
G. P. Richardson
July 2006
36
Rockefeller College of Public Affairs and Policy
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G. P. Richardson
July 2006
37
Rockefeller College of Public Affairs and Policy
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July 2006
38
Three Policy Mixes
• Base run (for comparison)
• Flat unemployment rate
• Historical client behaviors
• Investments in the “Middle”
• Additional services to TANF families
• Increased TANF assessment & monitoring
• Safety net assessment & job services
• Investments on the “Edges”
• Prevention
• Child support enforcement
• Self-sufficiency promotion
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University at Albany
G. P. Richardson
July 2006
39
Investing in the “Middle”
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40
Investing on the “Edges”
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July 2006
41
Base, “Edges,” and “Middle” Compared:
Populations on the Welfare Rolls
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G. P. Richardson
“Edges” looks better.
July 2006
42
Total Job-Finding Flows from TANF
Rockefeller College of Public Affairs and Policy
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“Middle” looks better.
G. P. Richardson
July 2006
43
Program Expenditures
G. P. Richardson
“Edges” looks worse, then better.
July 2006
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University at Albany
44
Populations in the Welfare System
Rockefeller College of Public Affairs and Policy
G. P. Richardson
“Middle”
looks worse than “Base”! “Edges” looks much
better.
University at Albany
July 2006
45
Total Recidivism Flows
(back to TANF)
The hint for understanding the puzzling dynamics: recidivism.
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
46
A Stock-and-Flow Archetype
at Work Here
+
(R)
Probability of
recidivism
Recidivism
Families on
TANF
Enter TANF
Job finding
rate
Post TANF
employed
To mainstream
employment
(R)
Load on TANF
support capacity
+
(R)
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
Load on employment
support capacity
G. P. Richardson
July 2006
47
Behavior of the Archetype in response
to increased TANF support capacity
6,000
Total families at risk
4,500
Families on TANF
3,000
1,500
Post-TANF employed
0
0
6
12
18
Fam ilies on T ANF : archet ype base
P ost T ANF employed : archet ype base
T otal families at risk : archet ype base
24
Rockefeller College of Public Affairs and Policy
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30
36
T im e (M ont h)
42
48
54
60
families
families
families
G. P. Richardson
July 2006
48
The Behavior of the Archetype
• Families on TANF initially declines, as more support
hastens job finding.
• Post-TANF families employed initially increases, just as
policy makers would predict.
• Eventually (it takes a year and a half to begin to see it), …
• Families on TANF rises higher to a new high,
• Post-TANF Employed declines to a new low,
• And Total Families at Risk rises!
• …All because of increased TANF support capacity!
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
49
Why?
• Increasing TANF support
• Speeds job finding,
• Swamping downstream
Post-TANF jobs and support
Time in post
TANF employ
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
+
-
Job finding
rate
Time to find
first job
TANF support
capacity
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
50
Misattribution?
• Desirable rise in Post-TANF employed continues for
almost a year and half after the intervention
• Families on TANF falls below initial for over a year after
increasing TANF support capacity
• Very hard (impossible?) to see that the rise in Total
Families at Risk is attributable solely to the improvement
in TANF support capacity
• Dynamics almost certainly to be blamed on a weakening
economy, a rise in client pathologies, or other exogenous
factors
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
51
A Loop View of the Archetype in Detail
Time in post
TANF employ
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
+
-
Job finding
rate
Time to find
first job
TANF support
capacity
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
Suppose TANF support capacity increases…
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
52
4,000
White bar (left) is the
time slice of interest
3,000
B: Employed load
controls recidivism
2,000
Red arrows (below) are
the dominant influences
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
53
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
54
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
55
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
56
4,000
White bar (left) is the
time slice of interest
3,000
B: Employed load
controls recidivism
2,000
Red arrows (below) are
the dominant influences
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
57
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
58
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
59
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
60
4,000
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
61
4,000
Dynamic
complexity even in
a structure this
aggregate and tiny!
3,000
B: Employed load
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
Load on TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
Rockefeller College of Public Affairs and Policy
University at Albany
+
Post TANF
employed
- To mainstream
employment
Load on employment
support capacity
Probability of
recidivism
Post TANF employment
support capacity
G. P. Richardson
July 2006
62
System Dynamics and Dynamic Complexity
• Thinking dynamically moves us beyond separate events
and decisions, toward understanding.
• Feedback thinking extends traditional causal thinking.
• It improves (makes more realistic) how we think about
the world and how we think about changing it.
• The endogenous point of view is empowering.
Rockefeller College of Public Affairs and Policy
University at Albany
G. P. Richardson
July 2006
63