Wrong but useful. Working @Twitter, tweeting about data science and people management.
"Wait, it's all her views?" 
"Always has been"
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Hot take: a reason many data science projects are unsuccessful is that they're not planned in a user-centric way, which results in them not being valuable to the stakeholder they're created forhttps://shopify.engineering/make-dashboards-using-product-thinking-approach …
Sure, stakeholders don't always make clear requests, but end users rarely do and it's not their job to in the first place. Instead, put your analytic skills to the test and think through what problem they're really trying to solve before prescribing solutions
They may not appreciate the subtleties of well-executed data science work work, but they'll scramble to get their hands on it if it's useful and they'll absolutely remember it if it made life easier for them
Relatedly, your future self is likely to be a customer of the work you're doing today. Even when you're designing for someone else, it's worth keeping yourself in mind as an end user in your user-centric data science process!
I love it. Your observation sounds similar to https://en.m.wikipedia.org/wiki/XY_problem to me. Do you think so too, or are there some notable differences that you'd pull up for attention?
I think you're really on to something with that. Particularly in environments when people are pressured to be data savvy, they may try to ask for something indirectly as a face-saving technique
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