What Bayes and a Great Product Person Have in Common
A great product person thinks like Bayes. It is about the mindset of looking at the world skeptical like Bayes did centuries ago.
Bayes didn’t think his famous theorem, known as Bayes’ theorem, was worthy of publication when he first came up with it. He’d abandoned it for more than a decade, and only after he died, his theorem was formulated and published by Laplace in 1812. Since it was formulated, it has been so influential and become one of the fundamental rules in probability and statistical studies, and found itself many applications from medical science to artificial intelligence, from DNA de-coding to homeland security. If you used your email today and not being spammed it is also thanks to Bayes’ theorem.
However, Bayes has another meaning to me as a product person and it is not about how his theorem has been so fundamental to several disciplines for over two centuries. It is about how Bayes looked at the world which eventually led him originate his great formula. I believe his way of looking at the world coincides with the mindset of great product people building software products now, three centuries later.
How Bayes Looked at the World
Bayes didn’t think of the world as a place we could understand perfectly. But although he accepted that we couldn’t understand it, he thought that experimenting was an essential tool to understand it better if it is not the only way.
What Bayes was suggesting in this case that all we could hope to do was to update our beliefs about the world when there was a new evidence and data that came to light and new information gained. He looked at the world in a way that as we learnt new things we could update our understanding with this new evidence, data and information and better model a reality around it. And this is exactly the belief that eventually led Bayes to his well-known theorem.
What Bayes’ Theorem Teaches Us
Software wasn’t a thing when Bayes lived but his thinking is exactly how great product people look at the world and build successful software products today. They know that the connection between what they build and what people will do with it is almost always unpredictable for them until they experiment it. Thinking in this way, a great product person makes it a second nature to get their ideas and hypotheses out into the public and all they hope to do is to experiment them quickly to get better understanding whether the market will be accepting them or not, or if they are building the right thing or not. That’s why great product people believe, like Bayes, experimenting is one of the most essential tools to improve their results and this understanding by running more and more experiments and gathering more and more data until their hypotheses fail or pass their bar for success to make the right product decisions.
What Bayes’ theorem also shows us is that if anyone stops being skeptical and hold things with with 0% certainty or 100% certainty, there is basically nothing you can do to change or affect things. If the “prior” in his formula — which is a person’s prior knowledge about the conditions related to the event that is being tested — is 0% or 100%, the formula simply cancels itself out and it fails to work in those cases. This simply shows that there will be absolutely no data or information that could change the results you get from the formula, thus anyone’s mind if they hold things with 0% or 100% certainty. When a great product person run experiments, they know that the results of their experiments will never bring them a 0% or 100% certainty on their hypotheses. They know they always have to be skeptical about their prior knowledge and the results of their experiments. This implies that our actions play a role in determining the outcome and how true things actually are.
What might define a good product person is their experience, qualities and skills. But being a great product person is about the mindset. It is the mindset of having constant curiosity and looking at the world skeptical like Bayes did centuries ago. It is about the mindset that we can not understand the world perfectly until we experiment things and updating our beliefs and understanding through experimenting and iterations in order to get more and more evidence and information in search for answers and solutions to our problems and eventually build great products.
The mindset of questioning nearly everything, being skeptical and experimenting ideas and hypotheses were essential to Bayes’ thinking as much as they are to people building great products today.