The (Not So Subtle) Art of Not Giving A Fuck About Data
F*ck best practices, data quality, data/ML teams, adversity, BI & Analytics, Data as Product, data & what to do instead.
1957 was the year that Ford launched a ten-year project backed by solid market research, expected to sell 2 million units in its first year: The Ford Edsel.
The result? A $250m loss, backed by lots of data.
One version of what happened is the “moving target” theory, the idea that while Ford did great at gathering data and acting on it, they failed to update their data once they hit production. Tastes simply changed, and Ford didn’t see it coming because they had worked so extensively with data.
Often, it is better to just don’t give a fuck about data.
Over a decade, I’ve cared deeply about data projects, decision-makers, and machine-learning algorithms. Sometimes, I’ve decided to say fuck it; I didn’t give a fuck about best practices, projects, or people. These decisions made all the difference.
I’ve now spent over a decade in data, cofounded a business intelligence startup (and failed miserably), worked as an analyst, worked inside a hot data startup, led a data team as data PM, and through my writing, have been fortunate to…
