Being an analyst in an unclear organization

We got to a stage where we, as data scientists, were never able to spend any time on on the real, like, juicier problems, and we were spending all our time kind of debugging, trying to find issues with with certain launches, what's been going wrong in in different places of the business. And all of these took ages, and it was just one of those where I would get to the end of the week, and my manager, Emily, would be like, what did you do? And we would list out we've, you know, we were in this incident. We're looking to this x y zed, but we'll never actually get into the things that we really wanted to get to and the things that, as data scientists, I think, excite us. Right? Like, we don't want to be debugging and looking at dashboards every day. We wanna be, you know, focusing on how we can drive the business forward. So we we're in the state where it was very difficult to to look into issues or, you know, as I said, we had too many dashboards. We had too much going on. We had different stakeholders sharing different things from different sources, and even matching those up made our lives difficult. So So when the metric tree idea came around, it was kind of one of these things. Okay. Cool. Like, we can very easily show to the rest of the organization this is this is what's gone wrong where, and then we can either enable them to go dig into further or very quickly allow us as data scientists to dig into further and and hopefully resolve any problems as quickly as possible.