1 / 63

Dynamic Complexity

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. Learning in and about Complex Systems Sterman (1994). Unknown structure Dynamic complexity

oshin
Download Presentation

Dynamic Complexity

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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. Learning in and about Complex Systems Sterman (1994) Unknown structure Dynamic complexity Time Delays Impossible experiments Real World Virtual World Known structure Variable Complexity Controlled Experiments Selected Missing Delayed Biased Ambiguous Implementation Game playing Inconsistency Short term Information Feedback Decisions Misperceptions Unscientific Biases Defensiveness Strategy, Structure, Decision Rules Mental Models Inability to infer dynamics from mental models

  3. Changing over time Tightly coupled Governed by feedback Nonlinear: changing dominant structure History-dependent Self-organizing Adaptive Counterintuitive Policy resistant Characterized by tradeoffs Dynamic Complexity arises because systems are…

  4. 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 System Dynamics Contributions

  5. The system dynamics modeling process Adapted from Saeed 1992

  6. Processes focusing on system structure

  7. Processes focusing on system behavior

  8. Two kinds of validating processes

  9. 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 theservomechanisms thread • (the first four in this list)

  10. 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

  11. 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. Dynamics

  13. New York City Population, 1900-2000

  14. Global Atmospheric Methane (1860-1994)

  15. Global Average Temperature(Reconstruction 1400-1980; Data 1902-1998)

  16. Stocks and Flows

  17. Stocks and flows help to explain self-reported drug use data

  18. ? ‘Challenging the clouds’ in a study of leasing in the automobile industry “We’re not in the used car business!”

  19. Stocks and flows in new car purchase and leasing

  20. Intuitive view of effect of leasing on auto sales: Leased car pipeline

  21. Stocks and Flows in Global Warming Thought experiment:

  22. 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. Feedback Thinking “For one good deed leads to another good deed, and one transgression leads to another transgression.” (Pirke Avot)

  24. The Classic Cybernetic Balancing Loop

  25. The Cybernetic Loop with Complications

  26. The Cybernetic Loop with Complications

  27. The Cybernetic Loop with Complications

  28. A Classic Reinforcing Loop(Myrdal 1944, Merton 1948) Prejudice against the minority group Majority’s perception of the inferiority of the minority Economic and educational discrimination against the minority (R) Achievements of the minority group

  29. Structure and Dynamics of Terrorist Cells (R) Interfering with terrorist funding Terrorist funding Peripheral support for terrorists (B) Efforts to suppress terrorists (R) Terrorist actions (B) (B) (R) Recruiting terrorists Terrorist group Losing terrorists (R) (B) Terrorist zeal (R) (R) Terrorist martyrs to the cause

  30. Insights about building teamwork in a public school Teamwork and Communication are self-reinforcing

  31. Isolation of teams and punishing risk-taking inhibit the growth of trust

  32. But longterm experience with teamwork can build communication

  33. Risk taking can enhance effectiveness, which can build trust

  34. A team-player culture is self-reinforcing: an opportunity or a trap

  35. Likely leverage points

  36. 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?

  37. 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

  38. Investing in the “Middle”

  39. Investing on the “Edges”

  40. Base, “Edges,” and “Middle” Compared:Populations on the Welfare Rolls “Edges” looks better.

  41. Total Job-Finding Flows from TANF “Middle” looks better.

  42. Program Expenditures “Edges” looks worse, then better.

  43. Populations in the Welfare System “Middle” looks worse than “Base”! “Edges” looks much better.

  44. Total Recidivism Flows (back to TANF) The hint for understanding the puzzling dynamics: recidivism.

  45. A Stock-and-Flow Archetype at Work Here

  46. Behavior of the Archetype in response to increased TANF support capacity Total families at risk Families on TANF Post-TANF employed

  47. 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!

  48. Why? • Increasing TANF support • Speeds job finding, • Swamping downstream Post-TANF jobs and support

More Related