Elizabeth Stone: evaluation

Transcript context

…So kind of along these lines of data, so data itself has always been at the heart of Netflix. My understanding is the way the data team and the insights team is structured has been one of the reasons Netflix has been so successful. And that's the team you led before you moved into this new role. Can you just talk about how these teams are structured and why this structure is so effective? Yeah. I certainly like to think of it as being special. It's unusual. I can explain why. So the scale of company that Netflix now is very often data oriented teams are embedded in other parts of the business. So it could either be they're embedded in a business line like ads or games, or they are organized more functionally separating data engineers from data scientists, from analytics engineers, from consumer researchers. We've resisted that and kept a centralized team that is both functionally diverse. So across all those types of functions that I just described and works on nearly every area of the business from within the team. I sort of understand why a lot of companies move away from this because it really does require basically extraordinary partnership that we would have people working on data problems that don't report into the teams that are relying on them. But the benefit we get is we get to think about our functional expertise. So are we really world's best data engineers, world's best data scientists? And how do we continue to be ever better from a functional and technical perspective? It gives people better career paths because there's more mobility across the teams. It feels like a team that has a functional expertise with a lot of different problems to solve. And so I think it enables more cross-pollination of ideas in a way. It also allows us to be really objective. That is probably the most important thing, that our job is not to tell the story that someone wants to hear with the data or to solve the problem that someone thinks is most important. It's for us to have our own perspective about things. I think that that uplevels the whole organization because it means that we're able to be truth tellers or to be curious in a way that might not fit if we had a different organizational structure. We have to balance, that would be a good partner, deliver on the things we agreed were priorities, be flexible with how we're spending our time, but it gives us agency and responsibility beyond that. And I feel like the team takes that very seriously. So I've seen examples of that in how we bring data to a lot of spaces, including how we partner with engineering on data-related topics or how we partner with content that I'm not sure we would've gotten to if not for having that kernel that's sort of a center of excellence around it. And it's Data and Insights, that was the team that you ran. Insights, is that describing user research or what does that have function actually?…

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