Dynamical Systems Theory in Practice

Addressing intractable conflict through the lens of the dynamical systems theory is embraced in the practice model, Dynamical Systems Theory of Practice (Coleman, Redding and Fisher, in press).  The model can be applied in a variety of contexts and levels of reality– from familial, community, and organizational to intergroup and international.

We invite you to read more about the model, and cases presented below.

DST in Practice

The four-element model is iterative and dynamic as individual skills and competencies develop in preparation for the work of comprehending a particular system through expanding understanding in order to explore underlying dynamics and identify opportunities for engagement. Recognizing that one can never fully understand nor predict the behavior of a complex system, the engagement strategy embraces experimentation to test understanding and system behavior through an assessment and learning process that leads to adaptation.

To explore each element of the DSToP model more fully, please click on the embedded links in the paragraph above or scroll down for a brief description, tools and other resources related to each of the four major elements of the model.

*Coleman, P. T., Redding, N. & Fisher, J. (in press). Understanding intractable conflicts & Influencing intractable conflicts (two chapters). In A.K. Schneider & C. Honeyman (Eds.) The Negotiator’s Fieldbook: The Desk Reference for the Experienced Negotiator (2nd Edition). Washington, DC: American Bar Association.

Systemic Preparation

Engaging with intractable conflict and complex social systems call for both an understanding of complex systems paradigms and possessing competencies that contribute to constructively engaging with conflict.

What are the implications of systems thinking and complexity science to how I think about things?

Thinking from a complex systems perspective incorporates a different set of mental models than traditional cause and effect – “if this then that” – way of understanding how things work. Complex social systems and intractable conflict are influenced by a networked set of factors, interacting, evolving, and adapting over time in complex ways.

  • In a World of Systems (Video 9:22).  This is an introductory video by the Donella Meadows institutes highlights that we live and interact with systems continuously – from our families, to our homes, to our neighborhoods to our world – they are all around us in our social, technological and ecological world.  For students of all ages, the video not only gives examples but the implications for how we think about and act with the world around us differently if we’re thinking in systems .
  • Complexity Science: 1 Introduction  (Video 5:08).  This five-minute video by Complexity Academy traces the development of reductionist thinking that explores individual parts to understand the whole and the more recent conceptualization of complexity theory.   Complex systems are characterized by highly interconnected and interacting elements resulting in patterns of behavior not seen in the individual elements. These local interactions help to explain systems, such as ecological, economic and social, which evolve and change.

What is a complex system and what are some of its characteristics?

  • Complex Adaptive Systems: 2 Complex Systems (Video 10:49).  While there isn’t full agreement on what a complex system is, this video by Complexity Academy shares the elements that a variety of perspectives hold in common: many parts operating on different scales (time, hierarchy, and so forth); non-linearity, feedback and deep interdependence among elements; and autonomy of elements enabling self-organization, adaptation and emergence.

What competencies contribute to successfully engaging with intractable conflict?

Three behavioral competencies that research suggest contribute to successfully engaging with complex conflicts (Coleman and Ferguson, 2014) include

1) Exercising adaptivity, the ability to apply differing strategies as the situation evolves or different circumstances demand;,

2) Seeking optimality, the ability to combine differing approaches to resolving conflict in order to reach an optimal solution; and

3) Fostering systemic agency, the ability to consider the conflict as an interdependent set of intertwined factors and sufficiently understand the system to identify points of opportunity where the action can be taken to change the dynamics of the system.

Systemic Comprehension

The understanding of an intractable conflict often collapses to an overly simplified “us versus them” situation where parties believe there may be a single “simple” answer to resolving the conflict. The only problem is that for every party, there is a different “simple” answer. This element of the model seeks to complexify the mental model of the conflict – gain a nuanced understanding from a variety of perspectives – and re-contextualize your own and stakeholder’s understanding of the intertwined network of forces holding the conflict in place.

What tools help to build systemic comprehension and complexify understanding?
Techniques and tools to explore our own and other’s understanding of complex environments are indispensable.  Visualization techniques including the Attractor Software Platform, concept mapping and causal loop diagramming have proven useful in exploring our own and other’s understanding, particularly in facilitated sessions that provide safe space to share and understandings and perspectives and negotiate new meaning that offers innovative opportunities to engage.

Attractor Software Platform:  This tool was developed by Andrzej Nowak and Wieslaw Bartkowski (copyright 2007) to demonstrate the complex dynamical properties of conflict systems in an easy and accessible way. The Attractor Software® creates a platform where a multitude of issues can be processed simultaneously, visually illustrating short-term, nonlinear transitions, and long-term unpredicted systemic effects. The platform is useful for policy decision makers, negotiators, and educators, as a tool to provide assistance in visualizing and evaluating complex conflicts. Click on the following links to explore the tool.

Introduction to the Attractor Software Platform
• Attractor Software®

Concept Maps: When entering a messy environment and stakeholders are beginning to explore their understanding of an environment, concept maps offer a format to brainstorm and start exploring ideas, factors, and relationships without the added structure of causal loop diagrams. Click here to download a pdf of guidelines to create a concept map.

Causal Loop Diagramming: While there is some variation in techniques to build causal loop diagrams, the following resources may be helpful:

• Two short videos by Gene Bellinger offer an introduction:
Causal Loop Diagrams/Intro (1 of 2)  (4:54)
Causal Loop Diagrams/Loops (2 of 2)  (4:06)

Click here to download a pdf of step-by-step introduction to exploring understanding of a system through causal loop diagrams.

Other visualization techniques include actor mapping, conflict mapping, stock and flow diagrams and rich pictures.

There are many internet based visualization software products including the free platforms from Kumu and Insight Maker along with many others that support causal loop mapping, network mapping, and other forms of visualization.

Systemic Engagement

Unlike linear systems where results of actions can be anticipated, complex systems with an array of relationships and feedback loops is inherently unpredictable. Non-linear change, importance of initial conditions, and the probability of unintended consequences, point to a strategy of initiating change mindfully through, identifying high impact levers for change, and conducting experiments to test our systemic understanding.

What is a ‘lever’ for change?
A lever for change is a relatively small action that has a large impact that ripples through the system. Donella Meadows has identified 12 levers  or places to intervene in a system – from low to high impact – to induce change. She cautions however, don’t push it the wrong way! Intuition is often wrong in a complex system.

Where can we look for levers in an intractable situation?
Coleman, Redding an Fisher (in press), suggest opening up the system to complexity, movement and adaptation; work upstream and away from the conflict; search for soft power in the form of third parties; look for what is working in the system and build positive attractors; take apart or reverse engineer those attractors that are holding the conflict in place.

What else can levers look like?
In his book, Making Peace Last (2012), Rob Ricigliano proposes looking for opportunities for change in system structures, attitudes and transactions with transactions being the easiest place to start. Rob reflects in the evolution of his model in a short (7:03 minute) video.

Is there a way to test understanding and leverage points without actually intervening?
For very high impact situations or very large systems, change experiments may be impractical or too costly. Building computer simulations, such as agent based models may be a cost effective means to test hypotheses and assumptions. Two cost free and relatively easy platforms to learn to build simulations include Insight Maker and Net-Logo.

Learning and Adaptation

As change is introduced to the system, monitoring the impact of the change efforts is needed in order to learn and adapt systemic understanding and future behavior. Evaluation in a non-linear system, however, requires in addition to more traditional and recognized linear assessments (“Were the 10 schools built that we planned for?”), non-linear change should also be assessed, even if it cannot be tied directly in time and space to interventions (“Has the standard of living of the community improved?”).

Beyond ‘systems thinking’, is there a way of thinking or behaviors that support more effective engagement with a complex system?
In addition to engaging others to get multiple perspectives, Dorner (1996), in The Logic of Failure, notes the following tend to be more effective methods of decision making and problem solving in complex systems:

• Make more decisions
• Demonstrate complexity of action
• Focus on real problems first
• Test hypotheses more
• Asked ‘why’ more
• Stayed focused on the long term goal
• Did not get fixated on one solution

How can non-linear assessments be conducted?
Assessment and evaluation in complex, non-linear systems is a growing area of research and practice. The USAID Evaluation Toolkit is one practical resource for exploring impact of actions in a complex, non-linear environment.


While the DSToP model addresses a process for understanding, action and learning, practitioners will often engage in the process incrementally with mental models of specific systems evolving over time as individual perspectives are iteratively shared, evolve and are synthesized.

ColombiaReportMemory and Reconciliation in Colombia

Read the Report

As Colombia emerges from over 50 years of civil war, AC4 partnered with the Fragility, Conflict and Violence Unit of The World Bank to aid in the exploration the role of memory and reconciliation to sustainable peace.   AC4 facilitated a three-day workshop in Bogota, Colombia with governmental and civil society organizations working on memory and reconciliation, to explore the dynamics across levels – local, regional and national – that affect their ability to impact local communities and identify opportunities to leverage their collective impact. The workshop utilized the Dynamical Systems Theory of Practice model as a basis for workshop design, alternating instruction and facilitated activities that incrementally developed the participants’ understanding of the larger system dynamics and situated their individual work in this broader context. Concurrently with building understanding, the network of actors was strengthened and ability to work across divisions strengthened.

Read more on the project.

Fisher, J., Mazzaro, K, Redding, N., & Straw, C. (2015). Contribution of Reconciliation and Victim Memory to Sustainable Peace in Colombia: A Dynamical Systems Analysis Pilot Workshop, May 20 – 24, 2015, Bogotá, Colombia. New York. The Advanced Consortium on Cooperation, Conflict and Complexity.

Accord case study

Pride, conflict and complexity: Applying dynamical systems theory to understand local conflict in South Sudan

This case study uses a systemic approach to conflict assessment to capture the multiple sources and complex temporal dynamics of a local conflict activated after termination of the war of nationhood in South Sudan. This approach helped to identify patterns that were central to the conflict but unrecognized through other means. It was found that typical explanations for post civil war violence – resource and political competition and insecurity – were oversimplifications and better understood as elements of a dynamical system where the probability of violence is strongly influenced by an emotional component – the clans’ competing desire to maximize group pride.

Go to the paper.

Roos, J., & Gray, S. (2012). Pride, Conflict and Complexity: Applying Dynamical Systems Theory to Understand Local Violence in South Sudan. The African Centre for the Constructive Resolution of Disputes, (4), 1-14.

Cat Ba Biosphere Reserve and Leverage Points

Cat Ba Fixes that Fail

(Nguyen & Bosch, 2013, p. 111) Copyright © 2012 John Wiley & Sons, Ltd.

This study by Nguyen and Bosch (2013) incorporates a complexity perspective to explore and understand the complex sustainability issues in the Cat Ba Biosphere Reserve in Vietnam, a UNESCO designated biosphere reserve. The authors considered a range of key variables including the environment, tourism, GDP, population an poverty rates to build qualitative causal loop diagrams to provide insights into system behavior and identify leverage points for systemic intervention strategies.

Go to the research paper.

Nguyen, N. C., & Bosch, O. J. (2013). A systems thinking approach to identify leverage points for sustainability: a case study in the Cat Ba Biosphere Reserve, Vietnam. Systems Research and Behavioral Science, 30(2), 104-115.