Flywheels (17/30)

I'm writing 30 posts in 30 days. This is number 17.

I like flywheels. I have 3 favorite flywheels : 2 concrete and 1 abstract. The two concrete ones are from Disney and Amazon. I will cover all three in today’s post.

Disney

Figure 1: Disney Flywheel

The Disney flywheel has probably more granular details than most flywheel diagrams you see elsewhere. Another astounding fact about this particular flywheel was how it was first formulated decades ago and how much of it has been realized today.

Amazon

Figure 2: Amazon flywheel

This flywheel was said to be drawn by Amazon founder, Jeff Bezos himself on a napkin. Definitely, it cannot be too complex like the Disney flywheel. Personally, there are two ways I interpret this flywheel.

1. I see this as a one-and-half flywheel. The main Growth node are equivalent to other nodes such as Sellers, Selection, etc. So it’s not part of any closed loop. How can it be part of a flywheel? There is one closed loop (Selection -> Customer Experience -> Traffic -> Sellers) hence one and a half flywheel.

2. The closed loop (Selection -> Customer Experience -> Traffic -> Sellers) that wraps the Growth node will naturally lead to Growth node getting bigger.

I lean towards the 2nd interpretation now, but my first instinct was the first interpretation. The more I look at the flywheel through the 2nd intepretation, the more I like this flywheel. It turns usually an abstract business outcome (Growth) and makes it a causal factor in the flywheel (Growth -> Lower Cost Structure). Yet, it acknowledges that Growth is not something that can be directly affected, only indirectly. Which is why no arrows lead to Growth directly.

Double-Loop Learning

This is taken from the wikipedia piece on double-loop learning. In fact it’s best appreciated when you contrast it against the single-loop learning flywheel.

Figure 3: Single-loop learning

There’s a simple flywheel in the middle of the diagram with (Real world -> Information feedback -> Decision). The entire diagram looks like a flipped 9 or 6. Now, contrast this with double-loop learning diagram.

Figure 4: Double-loop learning

This is a more complicated and a richer flywheel than the single-loop learning. By adding two arrows, you have added two additional closed loops:

1. Information feedback -> Mental model

2. Real world -> Information feedback -> Mental model -> decision-making rules -> Decision

And this abstract flywheel for me is like the secret cheat code to learn and do well in life. It’s like the flywheel that produces all other flywheels. Imagine you design a concrete flywheel to produce outcomes in your life. Based on feedback from implementing the design, you either adjust the flywheel’s design or the implementation. That way, your flywheel will get better over time.

At least that’s the plan.

What about you? Do you have a particular flywheel that you’re fond of?