Almost every metric can be abused by increasing the frequency, resolution and dimensions in which it is measured.

In terms of some real world examples:

Labour force statistics are almost always reported on an instance level by commentators/media, but its trend that's recommended/meaningful.

Net promoter scores and breakdowns are consistently done and reported too frequently on too small a base to establish a trend, and they're usually cross tabulated and spoke on far too many dimensions.

Customer opinions and employee ratings/surveys.

Generally it's just fundamental statistics: don't reason too much about the general from the specific. And as you get greater resolution and move towards real time events, your specific becomes smaller and smaller, which means that extrapolations onto the general result in greater and greater errors...

Interesting. Thanks for sharing. Do you know of any good writing on the web or print that talks more about such abuses in the analytics and corporate world? Interested to learn how to spot when kooky tactics are at play in a tech/corporate setting, specially when its willful.

"Proofiness" : https://www.amazon.com/Proofiness-Youre-Being-Fooled-Numbers...

It is also a common tread in books by Tufte : https://en.wikipedia.org/wiki/Edward_Tufte

I like "Visual Explanations: Images and Quantities, Evidence and Narrative" : https://www.amazon.com/Visual-Explanations-Quantities-Eviden...