I like to think a lot, and as a result of thinking a lot I come up with a lot of theories and mental models. When I was younger I was one of those “Why don’t you believe me!?” types, but as I’ve gotten older I’ve noticed that I had been wrong so many times, that just because a theory I came up with made sense to me, it could very likely be false.
But if I immediately dump my theories, then I think I could be dumping a lot of value. Because all high level work — anything conceptual or longterm lives in the realm of theory.
So how does one make sure they're not stuck in theory, and that they're actually getting results that apply to the real world?
In my opinion, the easy answer, and the answer you hear most often is: "take action”. While this is accurate advice, I think it’s one of those simplistic pieces of advice that doesn’t really get you anywhere.
I want this post to be helpful to you, but in order to do that, I need to quickly explain what I think theory is.
Theory is what the scientific method says it is. It's a guess. That sounds quite obvious, but I think I missed this understanding for two reasons:
The scientific method is a universally agreed upon method, and while learning about the scientific method in high school I remembered the instructions were to develop a hypothesis and to come up with an unbiased way of testing them.
Again, I’d like to reemphasize that similar to people who like to smoke weed and develop theories on life, scientists like to develop ideas too — they just happen to use the scientific method to make sure that they’re ideas are accurate.
Unlike scientists, however, I’m not necessarily concerned with proving mental models on how the universe works, I just want my ideas to be accurate enough that I can make long term decisions and get results.
Below are things I’ve found helpful in guiding me to accurate thinking.
In order for a theory to exist, assumptions have made. For example in Wing Chun, a martial art popularized by the movie Ip Man, there’s the assumption that because the shortest distance between two objects is a straight line, the most effective punch is the straight punch from your chest area to your opponents chest area.
This assumption makes sense in itself, but If you examine this assumption, you could be opposed to this assumption and argue that a longer armed person throwing a hook will have the advantage over your straight punch.
Back a couple years when I was really into martial arts I would spar my friends and try to practice wing chun; I could deal with their jabs well, but would always get punched in the face when I moved in for an attack and was a beat too slow — I would get punched in the face by their hook.
This is why its important to test the assumptions and the results of the theory put in practice. Knowing that the assumption you’re making is missing clarity, you can go back and rework your theory: If an opponent’s curved line of attack is longer than your straight line, then you need to find a straight line attack that’s even longer. The straight line theory still works, but the best way to deal with hooks isn’t necessarily to develop a faster step, its to utilize the straight kick.
I saw this playing out while watching Lyoto Machida fight. He forced his opponents to be wary of distance with the straight kick, and only when his opponents got frustrated and over reached did he close in quickly with punches. Although his fighting style was Karate and not Wing Chun, because I thought about the assumption I was making, I was able to relate it back to the martial art I was practicing. Slightly unrelated, I found this youtube video that breaks down Machida’s technique to be really interesting.
I talked about testing assumptions first because it transitions well from talking about the scientific method. But the main to getting results is to be able to see results, i.e. setting metrics. This is often talked about so I won’t really go into depth, but the most obvious example is that if you have a theory about how the market will play out in the next couple years, you set revenue metrics so that you know you’re actually making money on the bets that you’re making.
Again, not really going to talk about this much since its talked about a lot, but I do have to say that I have a lot of friends that are into poker, they all differ in opinion on poker theory, and many of them don’t know how much they’re up (or down) from playing poker. Just sayin.
Both quantitive and qualitative:
Setting metrics is easy for business related results or things that are easily quantifiable, but what about things that aren’t so easily measured? Ideally, it would be to estimate your ability in a certain area and record those estimates overtime — Sebastian Marshall writes about this in the “Unit of Account” issue of The Strategic Review:
My friend Nick Winter, who wrote the terrific book The Motivation Hacker, tracks his experiential happiness every day on this scale –
“Here is my happiness tracking scale:
1: Suicidally depressed.
2: Majorly depressed or in tons of pain.
3: Frustrated or annoyed or sad or hurting or generally unhappy.
4: A little down.
5: Okay, I guess.
7: Happy to the point of smiling or rocking out.
8: Excitedly happy; awesome.
9: Everything is just perfect.
10: Contender for best moment of my life.
I like to think of it as a logarithmic scale, or rather two logarithmic scales, where each point above five doubles my happiness and each point below five doubles my unhappiness.
You can make your own scale with the bright lines that most clearly delineate different moods for you. The most useful one for me is that a 7 requires me to be smiling or rocking out or something like this--if I'm not physically reflecting the happiness, it's a 6 at best. My scale is nothing special, but having some sort of scale helps prevent drift.”
– entry from the Beeminder blog
Nick is a wonderful guy who has done a lot of terrific things in his life – and I think a big part of that is that he actually has a good unit of account for his happiness-over-time is.
Seriously, think of that! Winter developed a scale that works for him to account for precisely how happy he is!
It’s realistic, too – his “highly ambitious goal” during a summer project was to “…try to raise my average happiness from 6.3 to 7.3 out of 10.”
I think this is a wonderful approach, but in the beginning, its easy to be inaccurate with your own estimates. Also, trying to think about what areas to record can cause overwhelm. In situations where the area that you’re developing a theory for is a new area for you, I’ve found that a qualitative approach works well, and by qualitative I mean journaling. Journaling let’s you look back on your progress and see improvement or notice patterns, which is the whole point of setting metrics.
Eventually I think you’ll be able to estimate your own stats. Like its a sports video game where all characters have stats on speed, agility, defense etc. And you can see these improvements go upward.
Work on developing short term, low level theories first. Once you’re comfortable testing assumptions, setting metrics, and proving to yourself that your estimations are unbiased, you can move up to mastering higher level concepts.
Come back down too; once the higher level concept clicks, come back down and tweak / adjust the lower level stuff to reinforce your understanding.
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