I might title this: how to prioritize work in a modern data team. It is a super super interesting topic, and the post goes much deeper than the prior art in this space. This process—"What does the data team work on?"—is so central to the operations of the team and yet is often such a black box.
I won't try to summarize it further here, the post itself isn't so long. I do want to highlight the passage below, though, as I think it's so incredibly critical:
...don’t accept new work without requirements. If a stakeholder is not able or not willing to answer the hard questions about why they want something done, then the work is either not clear enough or not important enough for a data team to work on.
One of the things I feel strongly about re: org dynamics of the modern data team is that it needs to have real organizational power—it needs to be able to say "no" and mean it. If your data team doesn't truly have the power to say no to stakeholders, it will get sent on all kinds of wild goose chases, be unproductive, experience employee churn, etc. This is one of the reasons why data should report directly to the CEO.Read more...