Ways data driven decision can be worse than careful thinking:
A repeatable and precise measurement of a system may not be the measurement that matters most.
Tendency to measure what is easy to measure. And ignore what is hard to measure.
A false assumption about the data, methodology mistake, or bug in the code, can invalidate a conclusion.
Who’s double checking?
“You can’t improve what you don’t measure”. But also, it might become the only thing you improve, as the cost of the main prize.
Data, tables, charts, graphs... are great to fool people with. Don’t fool yourself.
I remember a study giving a bunch of experts the same data, and they all ended up with different conclusions.
Intuition has access to more varied data.
Think first, then do data.