> One of the things I don't like about statements like this said in a Data Science context, is that they are true outside of Data Science as well. Executives make big decisions, managers make smaller decisions, nobody can evaluate how good/bad they really were for months or years. Engineers build something amazing, or build a house of cards, nobody cares as long as the money people are happy, even if the business use case turns out to be wrong in the long run.
This is purely anecdata, but I have found that this is more pronounced in a data science context. Managers and executives are (in my experience) more willing to admit they don't understand engineering work product and seek input from technical advisors, and executives and managers deal with decision making on a daily basis and understand that it can be nuanced. But since almost everyone reads financial reports or has to make a chart in Excel every now and then, they know enough to read someone else's analysis but not enough to recognize their knowledge gaps (particularly wrt advanced statistics).
This is purely anecdata, but I have found that this is more pronounced in a data science context. Managers and executives are (in my experience) more willing to admit they don't understand engineering work product and seek input from technical advisors, and executives and managers deal with decision making on a daily basis and understand that it can be nuanced. But since almost everyone reads financial reports or has to make a chart in Excel every now and then, they know enough to read someone else's analysis but not enough to recognize their knowledge gaps (particularly wrt advanced statistics).