Jessica Lachs: belief

Transcript context

…Oh, there's so many. Okay, so the first thing is a consistent and high talent bar. I think this is something I saw when we would have some pockets of analytics folks embedded is having a consistent bar for talent in terms of what we're looking for, what are the technical skills, what are the soft skills? And being able to evaluate candidates with that same bar, using our same rubric. You just get more consistent and higher talent in my opinion. I think that's number one. Number two is actually growth opportunities. So if you're siloed, you may be the most senior data person within... I keep picking on marketing. But you might be the most senior data scientist within marketing. Where do you go from there? I think when you have the central org, you're able to see if there are growth opportunities in other areas within the company. And so that really helps folks to stay engaged because they can look at new problems if the problems they've been working on for several years are getting maybe boring and they want something new, there's an opportunity, move from marketing over to merchant analytics. And then I think similarly, if there isn't a promotion or room to grow, if you want to be a people manager and there just isn't a people management role within your functional area, well, you've got 10 other ones to look at and maybe there is that opportunity. So I think it helps with the growth opportunities for the team, which helps to retain talent. So that's a second thing. The third thing is just consistency of methodologies and metrics. So you don't have sales that was as defined by one team and sales as defined by another team. You just have sales and everybody is using the same metrics, the same methodologies, and you're able to improve your methodologies with input from more people. And rather than recreating the wheel, building the same churn prediction model on six different teams. You can instead build one and have the input of six different teams. I think that's definitely another benefit. Also helps you just scale because you start to see the same problems across teams and so you're like, "Ooh, this is an issue that we need to get ahead of. This is something we need to automate," or, "This is something that we need to improve upon," or, "a problem that is going to grow as our business, as our teams scales." So I think it helps you see around corners a little bit more. And then just lastly, there's a team culture brand. I think that's really important, not just externally for recruiting top talent, but the team is really proud to be members of the analytics team. We have a unique culture of learning, of sharing. You have someone you can go to talk about your challenges. You have someone who can peer review your work. I think just having that team culture that we have is really important. learning, of sharing. You have someone you can go to talk about your challenges. You have someone who can peer review your work. I think just having that team culture that we have is really important. And it's a lot harder to get when you have the individual silos, particularly in an earlier stage when it's a smaller team, you just don't have as many people around. Everybody wants to have friends at work and we're creating an environment where they can find like-minded data nerds. It makes me think about Airbnb's first data team. I don't know if you know Riley Newman well, but he built Airbnb's first data team and it was actually an analytics team. They called themselves the 'A-Team' on the point of culture, and that always felt a lot of fun and they loved being part of that team.…

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