But again - isn't the antithesis of this that the company never does the work to look into any of this and, in doing so, misses a huge but non-obvious problem that these tools might reveal? So you need to build it to do the work and check, and then you need to maintain it (because you already built it and the possibility still exists, etc, etc)....
Like, absolutely, there's some impossible to define line below which the org does not care about the data. But also there's probably a point where they would care! Being data driven is not about spending all of your energy optimizing for exactly the scenario you have data to optimize for (see: the post-covid logistic crisis).
To me - it seems like you need to "waste" a certain amount of money tracking down problems that don't happen to exist - but you can't know for sure they didn't exist before you tracked them down.
I guess like...do you have the impression the data should drive people in a direction they are not going? Like...if the systems you work on are saying things are ok aren't they ok?
Author here once again. I have the worst possible answer for this - most data teams that I've seen (and my network is large enough through my own socialising + my blog to be reasonably confident on this) are working on dashboards that could not conceivably be acted upon. As in, the nature of the thing they are reporting on is not susceptible to top-down intervention.
You are however totally correct that some places will have actually valid use cases for this kind of reporting. The article is very much not for those people, as they don't have these kinds of concerns for the most part. This is for people that are watching their organization talk about behaving one way, then acting in a totally different way.
This. It's like arguing that we are wasting time with application logs because 99% of devs aren't reading them. They aren't there for your pleasure, they are there because, the one time you actually need them, you'll be sorry they aren't there.
I think this highlights the big difference between being Data Driven versus Data Reactive. If a dashboard surfaces a strategy problem; you're reacting to data. If you're forming strategy based on a dashboard; you're being driven by data.
That’s true from a top-down corporate perspective, but this blog post is addressing the perspective of an individual on the team, who is repeatedly told that the company really cares about data, and then can’t seem to understand why serious problems with the data are just ignored.
I don't think that's actually what it says though! The blog post talks about how no one looks at the data (implying that the data is not used) and it separately talks about the inconsistent and disconnected ways that companies allocate funds. It does not, that I could tell, actually say the metrics work has revealed data the company is ignoring. Obviously if they are that's different from what I said!
> It does not, that I could tell, actually say the metrics work has revealed data the company is ignoring.
I guess I wasn’t clear: The metrics work isn’t _revealing_ anything new, the data requested is what is produced. The fact that the data is _ignored_ means that it can have serious errors, but then nobody seems worried about correcting it except for our frustrated conscientious developer because producing the reports is a performative act. Nobody really uses the data for anything.
Like, absolutely, there's some impossible to define line below which the org does not care about the data. But also there's probably a point where they would care! Being data driven is not about spending all of your energy optimizing for exactly the scenario you have data to optimize for (see: the post-covid logistic crisis).
To me - it seems like you need to "waste" a certain amount of money tracking down problems that don't happen to exist - but you can't know for sure they didn't exist before you tracked them down.
I guess like...do you have the impression the data should drive people in a direction they are not going? Like...if the systems you work on are saying things are ok aren't they ok?