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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Yes, data analysis is about convincing someone (perhaps yourself) that something is or isn't true, but it takes a special kind of talent to do it consistently. It's easier to remember your analyses that changed someone's mind because it's easier to remember unusual events
That's definitely been the case for me, at least. I've done a lot of analysis over the course of my career, and I can only think of a handful that meaningfully changed the conversation around a subject
I've been mulling over what I think the alternative to Insights™ should be and while I have yet to come up with a satisfying conclusion, I do think one of the biggest flaws of the DS-As-Insights-Generators model is that it's a narrow strategy
If your job is to ensure data is a part of the decision making process at your company, you probably won't achieve it with artisanal Insights handcrafted by a data scientist. Maybe if you work for a magical company where the DS-stakeholder ratio is 1-to-1, and if you do--hey hmu
One of our unique strengths as DSes is getting data into a shape where the signal is differentiable from the noise, so maybe we should direct our energy towards creating environments where data is widely accessible and hard to use wrong
That's the promise of self-serve analytics, I suppose. But IMO such initiatives focus too much on making it possible for everyone to be a data scientist, when in actuality they should make data scientists unnecessary in as many situations as possible
And don't get me wrong, data scientists still have tremendous influence in a world like that. You make what you measure, so designing the datasets, metrics, procedures, dashboards, etc. that other teams use gives a DS tremendous influence over where the company puts its focus
Stepping up as owner of these things, really taking responsibility for their quality, reliability and improvement over time--it gives you way more leverage than a dropping few Insights every quarter, even if the Insights are Actionable®
Put another way, in aiming for insights (a lofty hard to reach goal) don't we necessarily fill many other needs along the way?
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