I once worked at a firm that ended up spending > 10 MM dollars because a very senior person did not understand statistical noise. There was a metric composed of ~600 human created data points with an error rate of 2%. Every week if the errors doubled very expensive ICs/managers would need to investigate. So the firm started spending more on trying to stabilize the metric - multiple applied scientists were hired to develop new statistical models. Engineering teams were funded to improve data collection. At its peak, there were probably 15+ engineers and scientists working on making sure that 12 errors out of 600 didn't become 24 errors out of 600 a couple weeks out of the year. This problem was compounded by trying to measure ~30 different segments with 600 measures per segment per week.

To this day I'm shocked at how much time that ate up. Expecting leaders to understand statistics was unlikely to work, and we shouldn't be surprised that 5 statisticians paid handsomely to solve the problem came up with ways to occupy their time.