Tools to deal with complexity, chaos, and entropy

Complexity, chaos, and entropy have one thing in common. They all thrive on interactions, impacts, and flow between elements of any system. Having 500 individuals with no interactions between them doesn’t create any complexity. Having five people with interactions and all three elements above kick into action. 

Focusing on interactions, impacts, and flows focuses on the underlying system that organizations are running based on. This focus on the “system” differs from the regular focus on parts of the system. Obviously different focus required different tools. In this post, I will share all the tools and methods I’m aware of. 

System Thinking

The most comprehensive tool is System Thinking. This is actually a visual language, method, and philosophy. System thinking is supported by several modeling and simulation platforms. Several are free and the other commercial. 

System thinking sees any interaction between two elements in the system as bi-directional. This is a shift in thinking from the default human behavior that sees the other as responsible for any situation. To get a better understanding of the bi-directional relations, system thinking defined several visual methods.

The first method is depicting causality between parts of a group or organization. Those parts can be people or teams. Causal diagrams show how parts of the system impact each other. Causal diagrams also show if the impacts creating balance (status quo) in the system or reinforcing loops (that can be positive or negative). 
Causal diagrams have definitions of Archetypes. Those are known patterns in causal loops that create known flaws in the system. Archetypes also contain best practices to resolve them. There are several tools that enable you to model causal diagrams for free. I’m using InsightMaker (

The second diagram is a more in-depth understanding of causality by defining stocks and flows. Stocks are like sinks that can contain or accumulate anything. Flows are like pipes that connect two sinks. Once something moves in the pipe, it impacts both connected sinks. This model required more detailed thinking. 

“Stocks and flows” diagrams are augmented with more data on the flow and system behavior. Capturing of Behavior Over Time (BOT) of elements in the system. depicts impacts between elements using graphical function diagrams. Structure behavior pair, which depicts the behavior of a part of the system.

All the tools that support modeling “stocks and flows diagrams” also enable running a simulation. Simulation enforces you to get a more in-depth understanding of the system. Simulation is also a great way to validate your understanding of the system.

Agent-based modeling

An agent-based model (ABM) is a class of computational models for simulating the actions and interactions of autonomous agents. This diagram enables model agents in a system, internal states, and rules that can change states. Based on modeling platforms such as InsightMaker or Net Logo can run a simulation and see you how many agents following your rules will behave over time. 

ABM is a valuable tool to understand the current dynamics in organizations and to get a general idea of how changes in structure or policies will change the behavior and if the change will be the same as you expect from the change. I would recommend starting with a model of how different personalities impact groups.

Cellular Automata

This is a simplified model of Agent-base modeling. In this model, there are very simple rules (ABM can support AI type of rules) and agents just impact the surrounding cells (ABM enable agents to impact any agent). This simplicity can help a lot if you want to model simple scenarios. The simplicity saves time and effort, but not work for any need.

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