The number of applicants can significantly affect the odds of hiring the best candidate. If an employer interviews a large number of applicants, they can familiarize themselves with the talent pool and identify the best qualities. However, the odds of hiring the best candidate increase with fewer applicants. This is because the employer can spend more time evaluating each candidate's skills and qualifications, leading to a more informed decision.

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Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths

Can computer science teach us the secrets of life? Perhaps not, but they can shed light on how certain everyday processes work and how to exploit them...

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If an employer interviews 100 secretary applicants, that person should allocate the first 37% percent of interviews to familiarize themselves with the talent pool and best qualities. If they hire the very next applicant that appears to be the "best so far," the company has a 37% chance of that person being the best candidate. The odds become greater with fewer applicants.

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The 37% rule, when applied to hiring, suggests that a company should spend the first 37% of the interview process to understand the talent pool and then hire the next best candidate. This could potentially improve the company's overall performance by increasing the chances of hiring the best candidate. However, it's important to note that this rule is based on probability and doesn't guarantee the best outcome every time.

The 37% rule can be used to improve the efficiency of the hiring process by applying it to the interview process. If an employer is interviewing 100 applicants, they should spend the first 37% of interviews familiarizing themselves with the talent pool and identifying the best qualities. After this point, they should hire the next applicant who appears to be the best so far. This approach gives the company a 37% chance of hiring the best candidate. The odds of success increase with fewer applicants.

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