Systems Thinking Intro: A Powerful Approach for Design & Analysis

notion productivity systems thinking

Systems Thinking will magnify your ability to create, solve problems, and contribute more to any effort. It enables you to do just about any complex work better. And it will empower you to build a life operating system for yourself (more on that in the next article).

Most crucially, Systems Thinking enables you to see causal relationships that others are missing. You will bring new ideas and powerful insights to any discussion.

This article is an introduction to Systems Thinking, intended to provide a working understanding. In the next article, I’ll apply it more specifically to designing a productivity system for personal and small business use. Notion is the best software platform I’ve ever seen for non-coders to build personal life enhancement systems and to streamline business operations. But using Notion without a strong sense of Systems Thinking will limit how far you can take the platform.

What Is Systems Thinking?

Systems thinking is a holistic approach to looking at the world, one that’s in direct contrast to the standard way our society tends to look at issues. It’s not the approach we are taught in school or at work. It’s an unconventional thought process.

Systems Thinking starts with the recognition that all systems are part of larger systems, and every system is defined by its function in the larger system. A car is not defined by its components (engine, tires, doors, seats), but by what it does within the larger transportation system (gets you from point A to point to B with a certain speed, effort level, comfort, carrying capacity, etc….). It’s compared with other systems (buses, subways, airplanes) by how they each fit into the overall transportation system.

A system divided into component parts cannot function. Its worthwhile properties (i.e., its functions) derive from the interactions of its parts, not its parts taken separately. “Analytical thinking”, in contrast to “systems thinking”, is the more common approach in our society. In analytical thinking, you study the various component parts. Once you know each, you integrate them into an understanding of how the whole works. But if you apply analytics (i.e., study the individual parts) to a system, the system loses its essential properties. And so do its parts. It loses its function and how it fits into the larger system. Broken into parts, the thing of interest in your system does not exist. The only way to understand a thing of any complexity is to look at it in its entirety and see how it functions within greater systems.

So, Systems Thinking is looking at the world as a series of interconnected ecosystems orbiting and interacting with each other over time. With this approach, you’re looking for patterns rather than identifying individual elements. When you see the world this way, endless new insights reveal themselves — and you can better design the ways in which you interact with the world.

Furthermore, you will find similar repeating patterns at various detail levels within a system, both micro and macro — and across disciplines. They’re essentially fractal patterns.

Traditional Types of Thinking

To clarify how rare systems thinking is in modern society, let’s take a look at the standard approaches. The more common methods go by terms such as linear thinking, analytical thinking, scientific thinking, or mechanical thinking. The unifying element among them is applying a set of simplifying assumptions to make the issue more manageable. It’s an understandable impulse given the complexity of the modern world.

These reductionist approaches break everything down. They study parts, then extrapolate to an understanding of the whole — presuming that the functionality is the sum of the parts. They make simplifying assumptions that often poorly model the world. This typical approach leaves us with the same old obvious explanations. Starting with limited frameworks, we end up with limited solutions.

Emergence

The value of Systems Thinking is that it reveals properties and causal relationships in systems that do not exist in their components. We’re looking at the qualities of the fully-functioning system beyond the sum of its parts. This phenomenon of new qualities forming beyond the core properties when they work together is called “emergence”.

Emergence occurs when an entity is observed to have properties its parts do not have on their own. These properties or behaviors emerge only when the parts interact in a wider whole. — Wikipedia

Consciousnesses and life itself are examples of emergence, but it happens at all levels big and small, profound and mundane. Water is made up of hydrogen and oxygen atoms, but neither of these two component parts has the quality of wetness. Wetness emerges only when the two parts interact as a whole.

The ability to recognize Emergence is a cornerstone element of Systems Thinking. Ultimately, the ability to design for Emergence in systems is a superpower that we’ll explore in future parts of this series. But merely recognizing it provides powerful insight and a starting place to better understand essential causal relationships. This is how Systems Thinking helps us see what others are missing and enables us to contribute important ideas to any conversation.

How to Do Systems Thinking

Step 1: Define the inputs, outputs, and movements.

Determine what is moving around in the system. What’s entering from outside of it, then ultimately exiting from it? Where are the entry and exit points? What path do they take? How quickly do they move, is that pace steady or inconsistent? Are there bottlenecks? What happens to the buildup at the bottlenecks?

Step 2: Distinguish Linear from Circular.

Evaluate what functions in the system are linear, and what parts of the process are circular. You’ll find the fundamental parts of systems tend to be circular, not linear. This step helps you weed out a lot of linear elements that are not essential, and zero in on the critical parts of the system, which tend to be circular. This will help you identify patterns which takes us to…

Step 3: Look for Patterns.

Patterns exist all throughout systems and they are central to its function. Systems perpetuate and facilitate patterns of activity and behavior. Define the patterns, describe them, visualize them. Write them down. Map them out. Flow charts are great for this. I love flow charts, they reveal the ghost in the machine (i.e., in the system). My favorite flow chart tools are Whimsical and Miro. Put them to work.

With practice, you will see the patterns emerge.

Once you see a pattern in one area of a system, look for echoes of it elsewhere in other aspects of this and related systems. Look for it in small clusters and in large clusters of participating elements. Zoom out for a wider perspective and zoom in tighter, looking for the same pattern to repeat itself at varying levels. These self-similar patterns at all levels of the system are fractals again. Get used to this, fractal patterns are everywhere.

Step 4: Find the Feedback Loops.

Can you see Feedback Loops in the system’s patterns? A pattern is a repeating design of some sort (could be over space, or over time, or both). A feedback loop is a self-magnifying or self-diminishing pattern over time. With each iteration, it increases or decreases in magnitude — perpetually and systematically. The results of the previous cycle pour greater resources and momentum into the beginning of the next cycle, over and over again. Amazon’s famous Flywheel business model is a feedback loop. Anything with exponential growth has a feedback loop at work. It can work in reverse too, decreasing rather than increasing.

Once you see the feedback loops, you will see causality. Everything is cause and effect, and these are typically buried inside patterns and feedback loops.

Step 5: Understand the Balancing Processes.

Feedback loops are powerful and perpetual magnifying forces. But any system that sustains over a long duration will have balancing properties to prevent it from going off the rails as feedback loops and anomalies in the process pressure its boundaries. Balancing properties will help to maintain equilibrium. Ask what guardrails, constraints, or counter-forces serve to keep things on track, and how surprises are dealt with. Without Balancing elements in a system, it will likely be short-lived. Look for these countermeasures in the system to evaluate its sustainability.

Step 6: Study your system’s Interaction with other systems.

As we’ve discussed, all systems are part of larger systems — and every system is defined by its function in the larger system.

So ask:

What larger systems is this system a part of?
Define the inputs, outputs, and movements of that larger system.
Look for Patterns in the bigger system. I’ll bet you find the same patterns you saw in the initial system. Yep, fractals.
Find the Feedback Loops in the bigger system.
Understand the Balancing Processes.
Study its interaction with Other Systems. What system is that larger system a part of… then apply these questions to that larger system… Rinse. Repeat.

Which puts us in an infinite loop here, and that is exactly how systems operate within systems… endlessly.

We could do an entire PhD program on this stuff, but I wanted to lay a foundation as this will be fundamental to ideas I hope to explore together in future articles.

In the next article, we’ll look specifically at how to apply this to a personal or professional productivity system.