The 37% Rule
The 37% Rule

The 37% Rule

Have you encountered the renowned Secretary Problem? If you hold a decision-making role, it’s crucial to familiarize yourself with this problem and understand how to consistently make optimal choices.

In essence, the Secretary Problem illustrates that the optimal decision is typically made when you select the 1/3rd option or the 37th percentile among the available choices.

For example, suppose you’re hiring for a job opening with 5 applicants. The rule dictates that once you choose a candidate, the others must exit. If, after interviewing the first candidate, you are satisfied, you face a dilemma. Should you let the other 4 leave and select the first one, or should you let the first one go and take your chances with the remaining candidates?

This decision is challenging, and there’s no definitive right or wrong answer. However, a mathematical approach exists for such situations:

  • Let n be the number of options for making one selection (refer to the Odds Algorithm).
  • e represents the natural logarithm, where the base e is the mathematical constant approximately equal to 2.718.

Applying the Look-Then-Leap rule to our problem, you designate a predetermined time for “looking” without making any choices. After this set time, you take a “leap of faith” and choose the option that feels the best.

With two candidates, it’s a 50-50 chance of selecting the best candidate. However, as the number of candidates increases, the dynamics change. For 4 candidates, start leaping after the second candidate; for 5, start leaping at the third. As the number of applicants grows, the looking and leaping statistically remains around 37%, hence the 37% rule.

Apply this principle to your ideas and potential solutions. With two solutions, it’s a 50-50 chance; with three, consider the second one. As the number of solutions increases, the likelihood of finding the right solution converges toward the 37% mark.

Before applying this rule, ensure all relevant data is collected for designing the solution. Without data and subsequent analysis, this method proves ineffective.

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