My essay in the previous issue dove into the core premise of Systems Thinking. It’s a framework for viewing many aspects of the world, and counter to the mainstream paradigm. Systems Thinking is much needed to complement the more traditional analytic, reductionist, scientific, component thinking that dominates our society.
It’s also a powerful tool for us as individuals to bring new perspectives and unconventional insights to any conversation or team effort. This is Part II of what I started in the previous issue’s essay.
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 something emerging beyond the core properties when they work together is 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 have the quality of wetness. Wetness emerges only when the two parts interact as a whole.
Emergence is not the same as synergy, but they’re related. Emergence is a process in which component parts interact to form synergies, which in turn introduce new qualities into the system. These new qualities further impact the system resulting in more growth, evolution and more emergence. So emergence is a process, synergy is an element of the process. Emergence is the holistic sum of all the parts and all of their synergistic interactions.
There is nothing in a caterpillar that tells you it will be a butterfly — R. Buckminster Fuller
The ability to recognize Emergence is a cornerstone element of Systems Thinking. Ultimately, the ability to design for Emergence in systems is a super power that we’ll explore in future issues. 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.
If this isn’t clear or you want to explore from other angles, hit reply to this email and let’s chat. Seriously.
How to Do Systems Thinking
Step 1: Define the the inputs, outputs and movements. Determine what is moving around in the system. What’s entering from outside of it, then ultimately exiting 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
Miro and
Whimsical. Put them to work.
With practice you will see the patterns emerge. It’s a beautiful thing, you will feel a little bit taller with these discoveries.
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 wider perspective and zoom in tighter, looking for the same pattern to repeat itself at varying levels.
Fractals again, get used to this. They’re 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.
Armed with this info, you’ll be the smartest person in the room. (Though when you’re the smartest person in the room, you’re in the wrong room. Get into a better room.)
Step 5: Understand the Balancing Processes. Feedback loops are reinforcing and magnifying/minimizing forces. But any system that sustains for a long duration will have balancing properties to prevent it from going off the rails as feedback loops and anomalies in the process push 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 Its Interaction with Other Systems. As we discussed last time, 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.
Uh oh, seems we’re caught in an infinite loop here. Reboot.
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 issues.
And I want you guys to kill in meetings and at cocktail parties, so go blow them away!
Next up System Design and Design Thinking.
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