#8: Everything makes sense in the rearview mirror: what systems theory can teach us about human behavior in 2020

In a previous post, All Problems are Relationship Problems, I wrote about lessons from the book, The Courage to be Disliked by Ichiro Kishimi. In this post, I’d like to continue on the thread that all problems are relationship problems, by looking at the adage from the lens of Systems Theory.

Donnella Meadows, the author of the book Thinking in Systems, was a pioneer of Systems Theory, specifically Systems Dynamics, and the world’s foremost systems analyst in the 1970s. She taught Systems Theory for 30+ years and her work was greatly influenced by the work of the MIT Systems Dynamic Group. Interestingly, she also draws on ancient wisdom traditions from the Sufis and Native Americans.

Donella’s purpose in writing the book was to give readers the basic ability to understand complex system’s theory. The book is genius in its simplicity and wisdom. I was fascinated by how her teaching of systems theory echos the main lesson from The Courage to be Disliked: all problems are relationship problems.

Each chapter opens with a quote from someone who Donella was influenced by. Let’s take a look at this quote from Robert Pirsig, author of Zen and the Art of Motorcycle Maintenance.

"If a factory is torn down but the rationality which produced it is left standing, then that rationality will simply produce another factory. If a revolution destroys a government, but the systematic patterns of thought that produced that government are left intact, then those patterns will repeat themselves...There's so much talk about the system. And so little understanding.

The behavior of a system cannot be known simply by knowing the elements that comprise the system. Rather, a system’s behavior is governed by its structure, by the relationships of the elements.

Basics of Systems Theory

Systems are comprised of feedback structures that give rise to behavior. Some of these structures are reinforcing, also known as positive feedback loops. These loops lead to snowball effects, or cycles (some positive, others negative). For example, the more I practice making music, the more pleasure I get from the sound, and the more I want to practice; or, the more prices go up, the more wages have to go up to maintain a standard of living, and the more wages go up, the more prices have to go up to maintain profit. In traditional wisdom, feedback loops go by the adage of, “the rich get richer, and the poor get poorer.”

Some feedback structures are balancing loops. Balancing feedback loops are meant to bring a system back to equilibrium. An example of a balancing feedback loop is the thermostat that regulates a home’s heating and cooling. When the temperature in a room goes above or below the set temperature (and it always does due to a home’s insulation), the thermostat sends a signal to the furnace to turn the heat on or off.

In real world systems, like the industrial economy, there are both reinforcing and balancing loops, because (unlike what economists model!) growth cannot be infinite because the environment is finite. The elements that comprise the system of the industrial economy are finite i.e, natural resources and the human population. This is why some countries have restricted births.

Systems Thinking in 2020

Here’s a quote from Russell Ackoff, an operations theorist:

Managers are not confronted with problems that are independent of each other, but with dynamic situations that consist of complex systems of changing problems that interact with each other. I call such situations messes....Managers do not solve problems, they manage messes

A system’s problems are the result of the system’s structure. The same external event can be applied to two different systems, and both systems will respond differently, but predictably! Thus, a system’s response can be predicted from its structure.

I won’t go into the details in this post, but we’re all familiar with how in 2020, an external event like Covid wrecked havoc because of our systems’ structural problems. This means that we shouldn’t expect policymakers to incite change unless they make policy decisions that change the structure of the system, i.e, policies that contain feedback loops. And not just feedback loops, but also meta-feedback loops - loops that alter, correct, and expand loops, so that learning is built into the cycle.

Lastly, I’d like to leave you with an important lesson from systems theory: don’t overreact. External events, like over-reactions, cause oscillations in a system because systems in the real world are complex and interconnected with many industries, which means that there will inevitably be delays. Patience is a virtue, and the data shows that delays in response time actually prevent swings in a system.

Musica 🎺

Here are some fun tunes for your weekend! Enjoy!