Why do I believe strongly even when I’ll likely end up wrong

A case for “strong belief, weakly held”

Disclaimer: As stated at end of my first post, I’m by no means qualified to give startup advice. However, I’m going to write as if I’m an expert because it’s easier to write that way. This post itself is an example of believing strongly even though it might be wrong. :)

Prediction, luck, and timing

Successful companies seem to have their breakthrough moments by doing the right thing at the right place at the time. Microsoft was started right before the beginning of the PC revolution. Youtube was launched just when broadband was taking-off. It seems that one can create successful companies by predicting technological trends. This may be how some VCs operate, but I’m going to argue that it is futile to predict and exploit technology trend as a startup founder and give my two cents on more reliable strategies than having to predict the future.

Microsoft founders Bill Gates(13) and Paul Allen(15) connect to a PDP-10 computer at the University of Washington, through a teletype terminal at their Lakeside School in Seattle in 1968 — Source

Learning and discovery: the ultimate startup advantage

An early-stage startup is optimized for learning and experimentation by default. Its small and tightly-connected team is quick in processing new information and nimble in reacting to it. The team is well-connected both to the problem on the ground and the technology driving the solution. Learning and experimentation are some of the fundamental reasons why small startups with almost nothing can beat large resourceful incumbent companies time after time.

Therefore, it is a tremendous waste of opportunity if an early-stage startup stop learning. However, successful companies always look like they got it all sorted out; their predictions are correct and they are way ahead in exploiting it. Learning, experimenting and being proven wrong in the process seems like the opposite of success. It is easier and tempting to approximate the appearance of success than to go through the process of becoming successful.

Strong belief maximise learning opportunities, weakly held ensures learning

Strong belief, weakly held is a powerful concept in dealing with uncertainty when there is not enough information to make prediction. In the context of early-stage startup, it is essential because of the learning that result from adopting this perspective.

The best way to avoid being wrong is to be vague and not have a strong belief. Using blockchain as example, a founder might say that he is super optimistic on blockchain. But when pressed what value proposition blockchain brings and who are the customers, he might reply, “the banks, maybe the government, oh, really it’s anyone who needs a distributed consensus system, and maybe everyone will store file on a blockchain some day.” The founder has strong belief on blockchain but weak belief or no opinion on who are the customers, how customers will use it, and what is the value proposition. When it’s time to pick something to do, the founder may end up picking the easiest thing to do. In the case of blockchain, he might choose to do an ICO for file storage coins. Without a strong belief in a specific value proposition, it hard to stay committed to a particular choice to make it work, because there are ten other things that he thinks are equally likely to work. Conversely, if one is to strongly believe in a specific value proposition of the blockchain, he will actively prove it. The stronger the belief, the harder he will work to prove it, and the clearer the feedback he gets.

The “weakly held” part is what separates a stubborn and delusional person from an actively learning one. For best result, one needs to go beyond interpreting incoming information objectively to actively looking for information that does not fit. This seems to contradict the work of actively proving the belief, but it is all part of being truly honest with the work. The magic happens when evidence contradicts the strong belief but in the process a new belief starts to emerge.

Coincidentally, my PhD thesis on decision-making under uncertainty advocates for planning according to the most likely outcome because learning that a prediction is wrong gives the most valuable information and is the better thing to do for long term reward.

I strongly believe in specific processes of starting a company, which is why I’m writing these down even though I’m likely to embarrass myself more than anything else. Hopefully, someday I will evolve from this embarrassing belief to something more useful.

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