How to know you need a metric tree

Someone listening in the audience who's like, I feel we might be in the same situation as you do. We have too much data. Like, can you think of a kind of a like, a a litmus test of, like, how you would they would know they're in that state? Like, what would you if you look back and think about what I was doing then or what we were doing as an organization then, which really was a was a was a warning sign to us that there's something wrong, like, can you think about what that might be? Yeah. From my perspective, it really is a feeling. And I think sometimes, you know, being data people, our instinct is sort of like, let's ignore that feeling unless it's a numbers. But I think in this particular case, we really do need to just lean into the feeling and be like, if this spiel is not great, then it's probably not great. There's something wrong. You know? And I think it's hard because exactly as I said, in in the startup space, not as in the crypto space, but in startups in general, that is sort of par for course. Right? You're still, like, every day is a little bit chaotic because that's the nature of being a start up. I mean, if we wanted to work someplace that was super structured and and clean and and is a nine to five, we wouldn't be here. And so it comes, you know, part and parcel of the job. However, I think there's a a sort of like a like a tipping point in which you're sort of like, you know what? This is not sustainable. So I think Matt can also speak to this as well, but exactly as he said, the problem with not having that structure and we're not giving ourselves that structure. And for myself, this is is exactly right as leader as well as, I know that Matt had this experience on the ground, right, that you you're just feeling so overloaded, which is very typical of most data teams, especially at the very beginning. And, that was essentially sort of the place where I'm just like, this is not sustainable. We're gonna go burnout. There's a massive risk there, and that is not the intention. Right? As a leader, I don't want my people to burn out, one. Two, I don't want myself to burn out. And three, it was also one of those things where, exactly the sick we we keep harping on on, basically, is that it just didn't have that much focus. And so I was sort of like, okay. How can I give myself focus? How can I give my team focus? And how can we therefore also give the business focus? Yeah. And I think there's also something to be said here about also claiming that ownership is super important as a data team. Think, again, in typical, in typical startups or actually most companies, actually, because data especially at bigger companies, in fact, this is even more of a problem or more of a more of a how do I say it? Like yeah. It it harder to uncover, let's say. It's because data has typically been a sort of sub team or support team that people go to, and then their expectation is that they the data team just answers. Yeah. And that is extremely problematic because, actually, all the knowledge sits on the data team. And so you're asking the data team to simply be servants in some sense, which is I mean, maybe service isn't the best word, but, like, that's essentially what it felt like to some extent. I remember early in my career that was exactly what it felt like. Yeah. I mean, that's not the best use. And it's also very yeah. It's a bit of a waste, to be honest, of the skill sets that are available and the capacities that are available on the team. And so, essentially, what we want to do is make sure that, that feeling, again, right, is is sort of alleviated, and and there's a way to do that where, exactly as we've, you know, been talking about today that you can just say, you know what? I'm gonna claim I'm gonna reclaim my ownership. I'm gonna reclaim my place. You know? If I wanna sit at the table, I wanna influence. I wanna I wanna maximize my impact. I wanna maximize my team's impact. That's all on me. I need to make sure that I take control of that, and that is essentially where we ended up.