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In this case, the number was accurate. The company was in a tailspin with people actively trying to abandon it.

We had to re-earn their business.




What meaning are you putting into the word "accurate" here? Are you sure you don't mean "precise"?


How would you differentiate in this case?


Neither really makes sense from a statistical perspective: your number is effectively the true value, and there is no repeatable measurement process you’re evaluating.

Your use of the non-statistical meaning of “accurate” as “free from error” is spot on.


No, the number is given in a causal statement, it is not simply the reporting of a measurement as you claim. So the distinction between "accurate" and "precise" is definitely relevant.


No one really doubts that the revenue increased. The question is whether the claim that it was by aligning the blah-de-blahs with the foobars is an accurate one and, related, what the individual contribution/leadership was. (Could another peer make the exact same claim with similar credibility?)


That’s fair.

In this situation I was actively evaluating support issues, customer reported problems and new feature requests to triage what was worked and when. I’m comfortable suggesting that if somebody else was making those decisions at the time, the entire company would have folded. It’s hard to expand further on that without going into a lot more detail though.




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