Having reached the 12th week of the process to hire a new employee, I recalled videos I had seen on how to know when to stop (see below). The examples are a bit simplified compared to hiring a real person, after all, the candidate must also decide when to stop looking for a job. Since either party can decline the relationship, the term "optimal" may not apply. Nevertheless, the optimal stopping theory does provide a good principle for how to establish a baseline of acceptability among the candidates. The theory works best with a known number of candidates or a limited amount of time to make the decision.
Optimal Stopping
Brian Christian, coauthor, with Tom Griffiths, of
Algorithms to Live By. He writes, codes & lives in San Francisco. In an
article on medium.com, he wrote:
If you want the best odds, spend 37% of
your hunt noncommittally exploring options. You’re just calibrating. But after that point, be prepared to
immediately commit to the very first candidate you see
that beats whatever you’ve already seen. This is not merely an
intuitively satisfying compromise between looking and leaping. It is the
provably optimal solution.
37% = 1/e
YouTube Videos
Optimal Stopping. The Secretary Problem Explained.
Taken from a chapter of the book "Algorithms to Live By - The Computer
Science of Human Decisions" by Brian Christian and Tom Griffiths
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