By George P. Richardson and David F. Andersen
What can you do if you are in a group that is trying to deal with problems that are developing over time, where:
- root causes of the dynamics aren’t clear;
- different stakeholders have different perceptions;
- past solutions haven’t worked;
- solutions must take into account how the system will respond; and,
- implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?
The fields of systems thinking and system dynamics modelling bring four important patterns of thought to such a group decision and negotiation:
- thinking dynamically;
- thinking in stocks and flows;
- thinking in feedback loops; and,
- thinking endogenously.
This refers to thinking about problems as they have developed over time and will play out in the future. The principal tool to facilitate dynamic thinking is graphs over time. Sketching graphs over time helps groups move from a focus on separate dramatic events to a focus on the persistent, often almost continuous, pressures giving rise to the discrete events we see.
Thinking in stocks and flows
Stocks are accumulations and flows are their rates of change. Therefore, thinking in stocks and flows focuses on populations, physical stocks, inventories, backlogs, and other accumulating characteristics central to the problem, and on the production capacities, resources, and distinctive competencies available to deal with the problem.
Stocks change gradually over the time frame of interest, growing or declining as inflows compete with outflows. System capacities result not from quick changes, but from sustained investment. System policies must work through flows to change key stocks over time.
Thinking in feedback loops
This focuses on circular causality, the likely extended ramifying effects of actions taken by actors in the system. Feedback loops are a source of policy resistance. Exposing reinforcing and balancing feedback loops, active or latent in system structure, gives planners the opportunity to avoid the natural tendencies of complex systems to compensate for or counteract well-intentioned policy initiatives.
This is the most powerful aspect of systems thinking. Thinking endogenously refers to the effort to see the ‘system as cause’, to extend the boundary we naturally place around our thinking about a problem to the point that root causes are seen not as independent forces from outside but linked in circular causal loops with internal forces over which we might have some control. ‘Systems thinking’ drives many apparently diverse schools of thought, but at the core of them all is the mental effort to uncover endogenous sources of system behaviour.
Combining these patterns of thought
These patterns of thought underpin a group model building process using system mapping and modelling that integrates data, other empirical insights, and mental models into strategy and policy processes.
Strategic policy making begins with the pre-existing mental models and policy stories brought into the room by stakeholders affected by the problem and by stakeholders charged with dealing with the problem.
Strategic policy consensus and direction emerge from a process that combines social facilitation with technical modelling and analysis. The method blends dialogue with data. It begins with an emergent discussion and ends with an analytic framework that moves from ‘what is’ baseline knowledge to informed ‘what if’ insights about future policy directions.
The modelling processes themselves are not described here, but can be found in Richardson and Andersen (2010).
There are a number of process features related to building these models that contribute to their appeal for stakeholders:
- Engagement. Stakeholders are in the room as the model is evolving, and their own expertise and insights drive all aspect of the analysis.
- Mental models. The model building process uses the language and concepts that stakeholders bring to the room with them, making explicit the assumptions and causal mental models stakeholders use to make decisions.
- Complexity. The resulting nonlinear simulation models lead to insights about how system structure influences system behaviour, revealing understandable but initially counterintuitive tendencies like policy resistance or ‘worse before better’ behaviour.
- Alignment. The modelling process benefits from diverse, sometimes competing points of view as stakeholders have a chance to wrestle with causal assumptions in a group context. Often these discussions realign thinking and are among the most valuable portions of the overall group modelling effort.
- Refutability. The resulting formal model yields testable propositions, enabling stakeholders to see how well their implicit theories match available data about overall system performance.
- Empowerment. Using the model, stakeholders can see how actions under their control can change the future of the system.
Group modelling merges stakeholders’ causal and structural thinking with the available data, drawing upon expert judgment to fill in the gaps concerning possible futures. The resulting simulation models provide powerful tools for strategy and policy development.
Do you have experience to share with group model building using system mapping and modelling? Do the features outlined above resonate with your experience? Do you have other tips to share?
To find out more:
Richardson, G. P. and Andersen, D. F. (2010). Systems thinking, mapping, and modeling for group decision and negotiation. In, C. Eden and D. N. Kilgour (eds.), The handbook for group decision and negotiation. Springer: Dordrecht, The Netherlands: 313-324.
Biography: George P. Richardson PhD is Emeritus Professor of Public Administration and Policy in the Rockefeller College of Public Affairs and Policy at the University at Albany, State University of New York, USA and affiliated Professor of Informatics in the College of Computing and Information. He is the author of ‘Introduction to System Dynamics Modeling with DYNAMO’ (1981) and ‘Feedback Thought in Social Science and Systems Theory’ (1991, 1999), both of which were honored with the System Dynamics Society’s Jay W. Forrester Award. He founded the System Dynamics Review and later served for seven years as its Executive Editor. He has been honored with awards for Excellence in Teaching (2003) and Excellence in Academic Service (2010). In 2011, the System Dynamics Society recognized him with its award for Outstanding Service for his contributions to the Society and the field.
Biography: David F. Andersen PhD is the O’Leary Distinguished Service Professor, Emeritus, of Public Administration, Public Policy, and Information Science at the Rockefeller College, University at Albany, State University of New York, USA. His work centres on applying system dynamics, systems thinking, and information technology approaches to problems in the public, not-for-profit, and private sectors. He has served as a technical consultant to organizations at the federal, state, and local levels. He is co-author of ‘Introduction to Computer Simulation: The System Dynamics Modeling Approach’ (winner of the Forrester Award in 1983) and ‘Government Information Management’.