Adriel Frederick

The hardest part of it is they say getting in somebody else's shoes. The hardest part is taking my own shoes off. Basically going, Yo, okay, I came into this, there's something I wanted, I wanted to get rid of that. Now just talk to this person and try to understand what's going on with them, what they care about for their life goals and motivations, what they're scared of, what they're excited by, how you might be able to help them.

For me, it's a person who is just on the cusp of taking the action you want to take... I would try to find a country where we had a lot of growth, but for some reason our conversion rates were terrible. So we had a lot of traffic, but conversion rates were terrible. And I was like, okay, that's the marginal user. This is the person who is just on the cusp of coming in, wants to come in as you can see by the traffic, but we can't get them in.

When you have that kind of a melting pot of ethnicities, religions, media consumption and kind of socioeconomic status in one place, you learn a lot of them because in school you're mixing up with everyone... we work on mobile devices, people make an assumption that one phone number plus one device tied to one person. And growing up in Trinidad, I just knew that wasn't true.

What I thought was brilliant about that was not the metric, it was the designing it to be understood and communicated... When you create a discreet number and a discreet time and there is a concrete goal to chase and there's a number and a graph that everybody can look at and see, we are going to go make that thing go up, the organizational effect of that is galvanizing.

There are probably, I call them techno utopians who would say, feed all data to the algorithm, give it an objective, and it will do the right thing. And I was like yeah, the reason that falls down is the algorithms don't understand long term effects often, nor do they understand how people might respond to it, nor do they understand your intent for the product, and I think it's really important for product managers to play that role. That is our job. When you are working on algorithmic heavy products, your job is figuring out what the algorithm should be responsible for, what people are responsible for, and the framework for making decisions.

I think as a product manager and especially product managers working on systems that are heavy on machine learning or operations research and optimization, to think about where you want a person to make a decision and where you want the machine to be off to the races and to think about that as a product design problem because there actually is actually a computer interface that you have to think about there.

I'd say probably 60% successful, 40% you should turn off. But within that 60%, I think there's a hidden cost to the experiment, which is that you're futzing around with something small. You could have used your time on something bigger and more meaningful... There's a laziness that can creep in where you're just finding a lot of little things because they're easier to come up with and they're easier to design and think about.

Organization design and empathy... I recognize the job's different. It's more about building a great team, creating the right incentives for the team on blocking them, guiding them, and helping them work efficiently. Those mattered way more than anything else.

When you recognize that you get business value from it, then it all of a sudden becomes something that you look out for and you take care of. That's it... when it goes from frankly something people feel they need to do to be PC or for cultural reasons or because they're getting social pressure to do it to something that you really recognize concretely, no, I get value from this and you are willing to take the other steps to have a culture at your company that utilizes it, then it becomes easy because when you bring folks in from diverse backgrounds, they retain.