37% Rule - Balancing Analysis with Action
Arosh Jayamanna
Director - Enterprise Applications & APJ Operation @ Loop1 | Doctoral Student
Last week at work, I had the opportunity to have an interesting conversation with two of my colleagues. The problem at hand was quite straightforward. We had one opening for a technical position to fill and were to kick off our recruitment campaign as usual. But just like any other recruiter would expect, we wanted the best candidate for the position.
The challenge, however, was that the number of CVs we would receive and the time it would take to get enough CVs were variables beyond our control. On top of that, my two friends who were in that discussion had several thought-provoking questions. What if we commit to a candidate too early? What if someone better applies later? What if we miss our best candidate just because we kept on shopping? How long should we keep looking before making the decision?
By the end of the conversation we made the decision that we must just find the "right balance", hit that sweet spot based on our "judgement" and just make the call. But on my way home the same evening I couldn’t shake the feeling that there had to be a methodology to address these kinds of problems. And there is: the 37% rule.
The 37% Rule
In its simplest form, the 37% rule recommends that we spend the initial 37% of our time exploring our options without committing to anything. And beyond that point, pick the next best thing that comes your way which is better than everything you have seen before. Now, as you can understand, this rule can be applied to many similar problems that we encounter in life. Recruitment, apartment hunting, shopping and even in dating. The math behind this is pretty complicated, and it relates to the mathematical branch of optimal stopping .
Application of the "Rule"
Applying this "rule" to real-life situations can vary depending on the problem at hand. I realised that applying the 37% rule to a time duration can be common for many similar problem categories. Imagine the scenario below to grasp the concept thoroughly.
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However, an important point to note is that this is purely a probability-based mathematical recommendation. This is not going to guarantee the best outcome but provide guidance to achaive highest probability in that endeavour.
In real life, there can be obvious scenarios where you might find the best thing you have been looking for in that particular context on your first attempt itself, and you might feel very confident about it. In such absolutely confident scenarios, the adaption of the rule is totally up to you, and the math should not govern such situations. But in a generalized situation, spending almost 1/3 of the time exploring and making a decision based on such a framework will help many other situations, preventing us from analysis paralysis.
Further Reading
I found the following articles interesting and to be doing a good job in explaining the concept with better examples: