Someone I was mentoring asked me a good question today.
When making an important decision, how do you know when to trust the data and when to trust your intuition?
I think there are three useful questions.
First, will more information actually change the decision?
If you are choosing between two vendors, another reference call or a closer look at the commercials may genuinely change your view. Get the data.
But if you are launching a new product, you can research the market endlessly and still not know whether customers will actually buy. At some point, more analysis stops reducing uncertainty.
Second, is this a problem we have seen before?
If you are opening another office, hiring for a familiar role, or entering a market where a proven playbook exists, use what has already worked.
But if you are creating a new AI solution for a customer, there may be no playbook. Historical data can tell you what happened before. It cannot tell you exactly what should happen next.
And finally, has your intuition earned the right to be trusted?
An experienced salesperson may walk out of a customer meeting feeling that the deal will not close, even though every formal signal looks positive. Perhaps the real decision maker was disengaged. Perhaps the questions lacked urgency.
That instinct may simply be years of pattern recognition showing up.
But put the same person into an unfamiliar domain, and that instinct deserves less weight.
Good intuition is not magic. It comes from years of seeing patterns, making mistakes, and noticing what worked and what did not. Experience gets compressed into instinct.
So I do not see data and intuition as opposites.
Use data while it is improving the decision. Then know when to stop analysing and trust the judgment your experience has built.