If you’ve spent any time around an organization using data, you can probably close your eyes and hear the words “the data” ringing in your head. “The data isn’t right”, “the data isn’t easy to find”, “the data doesn’t make sense”. This triggers a feeling that “the data” needs to be fixed, or easier to use, or more reliable. So data product managers (and the organizations that support them) try to tackle “the data” in aggregate. But here’s what I’ve learned: you cannot win all at once. (View Highlight)
Note: So much clear pain
Depth enables you to tell candidates (both internal and external) exactly what they’ll be doing and what they’ll be responsible for. It is really hard to hire good data product managers, not just because the skillset is hard to find, but because good candidates are hesitant to walk into something entirely ambiguous (though some ambiguity is a natural part of this type of role). Imagine how powerful it is to say “you’d own this dataset, this monitoring process, with these KPIs” compared to “you’ll have to figure out how to make an entire platform operate well”. (View Highlight)
Note: I need to be more specific with my candidates
Depth enables you to speak to your wins and impact in a way owning an entire platform often does not. There will always be issues with “the data” or with “the platform”. No data or platform is perfect or works in the right way for everyone. But by defining goals and outcomes that are specific, it is much more likely a data product manager can show success and impact in a space. The conversation moves from “why didn’t they address this other stuff?” to “they hit the change targets we had in this area”. (View Highlight)
