This is less an argument against quantifying performance in general and more just an example of the importance of choosing the right metrics and interpreting them intelligently.

I have no doubt that more than a few moronic managers will try to make large decisions based on a trivial surface-level metrics like time per customer (which, at the very least, needs to be normalized against the complexity of the order), but still, I think the thing to be criticized is poor data analysis rather than the very concept itself. A smart manager would use this data to learn more about how their operations are going and have discussions with employees about what’s going on and how various differences might be explained, while a stupid one would just fire the apparently slowest barista every few months, completely missing the fact that said barista has developed personal relationships with tons of customers and only performs slowly during off-peak hours when it makes no material difference at all.

That’s a good point, although I presume the same technology could be used to monitor customers and collect statistics about whether the identity of the server affects the probability that a customer will return.

Metrics can be dangerous because if people are rewarded according to a metric, they’ll work to maximize their score, which might not be what the actual purpose of their job is. However, I don’t think that’s a reason to assume that metrics are worse than no metrics.