Choosing the best option from many possibilities is a common challenge in hiring, entrepreneurship, and everyday life. When candidates appear one at a time and rejected options cannot be revisited, deciding when to stop searching and commit becomes difficult. The 37% Rule, based on the mathematical concept known as the optimal stopping problem, offers a structured way to make better decisions.
The Problem: When Should You Stop Searching?
Imagine you need to hire the best candidate from a group of applicants. Each candidate is interviewed one after another, and once you reject someone, you cannot go back and hire them later. The challenge is deciding when to stop evaluating candidates and make an offer.
If you hire too early, you might miss a stronger candidate later. But if you wait too long, the best candidate may have already passed by. This dilemma is known as the “Secretary Problem”, a famous decision-making problem studied in mathematics, statistics, and economics.
Researchers discovered that the most effective strategy follows a surprisingly simple rule.
What Is the 37% Rule?
The rule suggests dividing your decision process into two phases:
1. Observation Phase (First 37%)
Spend the first 37% of your search simply observing options. During this stage, you should not commit to any candidate. Instead, use this time to understand the overall quality of the pool and establish a benchmark.
2. Decision Phase (Remaining 63%)
After the observation phase, choose the first candidate who is better than everyone you saw earlier.
This strategy gives you the highest probability of selecting the best candidate available, with about a 37% chance of choosing the absolute best option.
While a 37% success rate may seem low, it is actually the best mathematically proven strategy for situations where options appear sequentially and cannot be revisited.
Why the Rule Works
The effectiveness of the 37% rule comes from probability theory. The optimal stopping point occurs at approximately 1 divided by Euler’s number (e ≈ 2.718), which equals about 36.8%, commonly rounded to 37%.
This percentage represents the ideal balance between two competing needs:
- Exploration: gathering enough information to understand the range of options
- Commitment: acting before the best opportunity passes
By using the first portion of the process as a learning phase, decision-makers gain a realistic benchmark. Then, during the second phase, they can confidently recognize a candidate who exceeds that standard.
Example in Hiring
Imagine a company plans to interview 100 candidates.
Using the 37% rule:
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Interview the first 37 candidates without hiring anyone.
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Identify the best candidate among those first interviews.
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Continue interviewing.
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Hire the first candidate who is better than all previous ones.
This method maximizes the chances of selecting the top candidate from the entire pool.
Real-World Applications
Although originally developed to model hiring decisions, the 37% rule applies to many real-life choices where options appear sequentially and decisions must be made immediately.
Examples include:
- hiring employees
- choosing a job offer
- selecting a business partner
- finding a house or apartment
- choosing suppliers or vendors
In each case, the challenge is the same: you must decide when to stop searching and commit.
Limitations of the Rule
While the 37% rule offers a powerful framework, real-world decisions rarely follow the strict assumptions of the mathematical model. In reality:
- candidates may drop out
- offers can sometimes be reconsidered
- decision criteria may change
- external benchmarks may exist
Because of these factors, the rule should be viewed as a guideline rather than a rigid formula.
For example, if candidates may reject offers or withdraw from the process, decision-makers might need to move earlier in the process. Conversely, if previously rejected candidates can be reconsidered, the strategy may change.
Key Insight: Learn Before You Decide
The most valuable takeaway from the 37% rule is not the exact number itself, but the decision strategy behind it.
Successful decision-making requires two stages:
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Exploration – gather enough information to understand the landscape
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Commitment – act decisively when a clearly superior option appears
Without exploration, decisions are rushed and uninformed. Without commitment, opportunities are lost while waiting for perfection.
The 37% rule provides a structured way to balance these two forces.
Final Thoughts
The 37% rule demonstrates how mathematics can guide complex decisions in uncertain environments. By dedicating the early part of a search to learning and using that knowledge to evaluate later options, decision-makers can significantly improve their chances of success.
Although it cannot guarantee the perfect outcome, the rule helps prevent two common mistakes: choosing too early or searching endlessly.
In hiring and beyond, the real lesson is simple: observe first, set a benchmark, and then act when something truly better appears.
