System Dynamics: Simplifying Complexity and Uncovering How the World Works

We make sense of the world by making models in our brains, often without even noticing it. This is how we deal with the complexity of life; we pick the aspects that are the most relevant to us, and we immediately start trying to figure out how these elements behave together. These models can have many forms, one of the most common being proverbs such as “Action speaks louder than words”; this is a phrase that came to be by society noticing the connection, and the disparity between saying something and actually doing it. When done through a conscious and scientific approach, this process is called System Dynamics.

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System Dynamics is the art and science of understanding why things happen/behave as they do. It encompasses a wide range of fields, including engineering, economics, ecology, public policy, and social sciences. As a quick introduction, try to ask yourself the following questions:

1. Why does releasing wolves in a park result in rivers changing their course?
2. Why does introducing driving restrictions result in increased pollution?
3. Why does working more result in lower productivity?
4. Why do actions speak louder than words?

There is a straightforward explanation for all of these questions (mentioned later in the article), but truly understanding why these things happen requires taking a high-level view of all the elements that are involved (the system) and a detail-level view of how they affect each other over time (the dynamics). So, in short, System Dynamics seeks to identify causal relationships and study how these interactions create changes over time.

The beauty of System Dynamics is that it aligns with our need to make simplified models of reality in order to reach our objectives in the most efficient way. Just as we naturally make simplified connections to allow us to react quickly to different situations (most people will, purely on instinct, not get close to a snake because we naturally associate snakes with danger), System Dynamics helps us simplify more obscure connections such as wolf population to river course to allow us to react quickly to systemic problems. To do this, System Dynamics relies on two simple concepts:

1. Feedback loops. One of the most popular phrases is that “Every action results in a reaction”, System Dynamics often “closes the loop” by adding that “Every reaction influences a new action”. An easy example of this is that if I invest money I will earn money, which in turn will allow me to invest more money, or I will lose money which will make me stop investing; the reaction (winning or losing money) will have an effect on the initial action (invest or not invest).
2. Delays. Even though we are extremely familiar with delays, it is a concept that often escapes our analyses of the world. However, for System Dynamics, this is key because a small action today can result in a big reaction in ten years (learning Python 10 years ago results in making you one of the most sought-after developers in 2023).

By combining both concepts, System Dynamics becomes a powerful tool for decision-making and policy design. Moreover, System Dynamics fosters a holistic mindset, encouraging people to see beyond isolated events and embrace the interconnected nature of the world. It promotes critical thinking, as it challenges everyone to identify the hidden causes behind complex problems, avoiding superficial solutions that fail to address the root issues. As promised, here are examples of how to go over complex problems for the previously mentioned questions:

1. Lack of predators often leads to the overpopulation of non-predatory animals such as deer. Overpopulation of herbivores in turn restricts the growth of flora in the environment which in turn leads to less materials for beavers to build natural damns. By reintroducing wolves, the deer population is diminished and forced to be on the move, therefore, allowing flora to grow and beavers to build dams and therefore change the course of rivers.
2. By introducing restrictions on the number of days that people could use their cars, the government in Mexico City created a positive effect of having less emissions of CO2 into the environment. However, because people still had to go to work, this action resulted in most families buying a second car as a secondary reaction. After a couple of years, emissions grew, not only because of the increased number of vehicles, but because the increased traffic led to even more fuel consumption.
3. The basic mental model tells us that more work equals more production. However, when we account for the long-term effects of overworking, we see that too much work leads to a lack of motivation, diminished creativity, and increased mistakes. This results in countries that favor extended working hours having lower productivity per work hour. In other words, the direct effect of more work is more productivity, but the delayed effect of more work is tiredness which directly leads to less productivity.
4. The phrase “Actions speak louder than words” can have many connotations, in this case, I am explaining why people believe in direct actions more than they believe in passive actions such as words. This goes to one of the most fundamental models that is ingrained in our brains: thought ➡️ actions ➡️ reactions ➡️ thoughts. Additionally, we know that more direct actions lead to stronger reactions and therefore carry more risk and that the amount of actions one person can take is limited, so passive actions carry less weight as we can do more of them. Because this model is ingrained in all of us, we automatically trust and/or learn more from people carrying out actions than from people saying things.

As you can see from all the examples, there are many ways to use System Dynamics to model and simplify reality so that we can understand it better and make decisions that are good in the short and long term.