I used to joke that Data Scientists exist not to uncover insights or provide analysis, but merely to provide factoids that confirm senior management's prior beliefs.
I did several experiments, and noticed that whenever I produced analysis that was in line with what management expected - my analysis was praised and widely disseminated. Nobody would even question data completeness, quality, whatever. They would pick some flashy metric like a percentage and run around with it.
Whenever my analysis contradicted - there was so much scrutiny in numbers, data quality, etc, and even after answering all questions and concerns - analysis would be tossed away as non-actionable/useless/etc.
if you want to succeed as a Data Scientist and be praised by management - you got to provide data analysis that supports managements ideas (however wrong or ineffective they might be).
Data Scientist's job is to launder management's intuition using quantitative methods :)
I did several experiments, and noticed that whenever I produced analysis that was in line with what management expected - my analysis was praised and widely disseminated. Nobody would even question data completeness, quality, whatever. They would pick some flashy metric like a percentage and run around with it.
Whenever my analysis contradicted - there was so much scrutiny in numbers, data quality, etc, and even after answering all questions and concerns - analysis would be tossed away as non-actionable/useless/etc.
if you want to succeed as a Data Scientist and be praised by management - you got to provide data analysis that supports managements ideas (however wrong or ineffective they might be).
Data Scientist's job is to launder management's intuition using quantitative methods :)