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G. P. Richardson July 2006 1 Rockefeller College of Public Affairs and Policy University at Albany Dynamic Complexity 50th Annual Meeting of the International.

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Presentation on theme: "G. P. Richardson July 2006 1 Rockefeller College of Public Affairs and Policy University at Albany Dynamic Complexity 50th Annual Meeting of the International."— Presentation transcript:

1 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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

2 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Decisions Real World Information Feedback Strategy, Structure, Decision Rules Mental Models Virtual World Selected Missing Delayed Biased Ambiguous Implementation Game playing Inconsistency Short term Unknown structure Dynamic complexity Time Delays Impossible experiments Misperceptions Unscientific Biases Defensiveness Known structure Variable Complexity Controlled Experiments Learning in and about Complex Systems Sterman (1994) Inability to infer dynamics from mental models

3 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Dynamic Complexity arises because systems are… Changing over time Tightly coupled Governed by feedback Nonlinear: changing dominant structure History-dependent Self-organizing Adaptive Counterintuitive Policy resistant Characterized by tradeoffs

4 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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 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

5 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany The system dynamics modeling process Adapted from Saeed 1992

6 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Processes focusing on system structure

7 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Processes focusing on system behavior

8 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Two kinds of validating processes

9 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Six Traditions Contributing to the Evolution of Feedback Thought Biology: math models Econometrics Engineering Social Sciences Biology: homeostasis Logic Two Threads of Feedback Thought System dynamics arises in the servomechanisms thread (the first four in this list)

10 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Forresters 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

11 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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.

12 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Dynamics

13 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany New York City Population,

14 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Global Atmospheric Methane ( )

15 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Global Average Temperature (Reconstruction ; Data )

16 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Stocks and Flows

17 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Stocks and flows help to explain self-reported drug use data

18 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Challenging the clouds in a study of leasing in the automobile industry Were not in the used car business! ?

19 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Stocks and flows in new car purchase and leasing

20 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Intuitive view of effect of leasing on auto sales: Leased car pipeline

21 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Stocks and Flows in Global Warming Thought experiment:

22 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany But although the stock-and-flow insight holds, global climate is of course much more complex than that. And still much more complex than this simple global climate model, as well!

23 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Feedback Thinking For one good deed leads to another good deed, and one transgression leads to another transgression. (Pirke Avot)

24 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany The Classic Cybernetic Balancing Loop

25 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany The Cybernetic Loop with Complications

26 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany The Cybernetic Loop with Complications

27 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany The Cybernetic Loop with Complications

28 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany A Classic Reinforcing Loop (Myrdal 1944, Merton 1948) Prejudice against the minority group Majoritys perception of the inferiority of the minority Economic and educational discrimination against the minority Achievements of the minority group (R)

29 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Structure and Dynamics of Terrorist Cells Recruiting terrorists Terrorist group Losing terrorists Terrorist actions Efforts to suppress terrorists Terrorist zeal Peripheral support for terrorists Terrorist funding Terrorist martyrs to the cause (R) (B) (R) (B) (R) Interfering with terrorist funding (B)

30 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Teamwork and Communication are self-reinforcing Insights about building teamwork in a public school

31 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Isolation of teams and punishing risk-taking inhibit the growth of trust

32 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany But longterm experience with teamwork can build communication

33 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Risk taking can enhance effectiveness, which can build trust

34 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany A team-player culture is self-reinforcing: an opportunity or a trap

35 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Likely leverage points

36 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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 ones 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?

37 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany

38 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany

39 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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

40 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Investing in the Middle

41 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Investing on the Edges

42 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Base, Edges, and Middle Compared: Populations on the Welfare Rolls Edges looks better.

43 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Total Job-Finding Flows from TANF Middle looks better.

44 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Program Expenditures Edges looks worse, then better.

45 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Populations in the Welfare System Middle looks worse than Base! Edges looks much better.

46 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Total Recidivism Flows (back to TANF) The hint for understanding the puzzling dynamics: recidivism.

47 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany A Stock-and-Flow Archetype at Work Here

48 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Behavior of the Archetype in response to increased TANF support capacity Total families at risk Post-TANF employed Families on TANF

49 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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!

50 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany Why? Increasing TANF support Speeds job finding, Swamping downstream Post-TANF jobs and support

51 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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

52 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany A Loop View of the Archetype in Detail Suppose TANF support capacity increases…

53 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month) White bar (left) is the time slice of interest Red arrows (below) are the dominant influences

54 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

55 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

56 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

57 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month) White bar (left) is the time slice of interest Red arrows (below) are the dominant influences

58 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

59 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

60 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

61 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month)

62 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 120 B: Employed load controls recidivism 4,000 3,000 2,000 1, Time (Month) Dynamic complexity even in a structure this aggregate and tiny!

63 G. P. Richardson July Rockefeller College of Public Affairs and Policy University at Albany 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.


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