Here's an interesting puzzle hiding inside a routine spreadsheet question: how many ways can a simple age calculation go wrong? Earlier today, someone posted a formula for figuring out a person's age in whole years, and it returned an incorrect result. The post was deleted, but a community member collected the eleven formulas that commenters suggested, tested each one against 100,000 randomly generated date pairs, and found that only three of them, 27 percent, are accurate in every case. That is a sobering figure for anyone who has ever assumed a spreadsheet is doing what they asked.
The practical takeaway is not that spreadsheets are unreliable, but that even straightforward date logic demands precision. The three formulas that passed every test are Method 1 (the original poster's, despite its one known failure), Method 2, and Method 3. Methods 4 through 7 fail only on edge cases, typically when the day and month of the date of birth match the "as at" date. That kind of boundary error matters if you are calculating ages for benefits, eligibility, or legal compliance. A one-year swing on someone's birthday is not a rounding issue; it is a real consequence.
What stands out is the gap between what people recommend and what actually works. The deprecated DATEDIF function, used with the "Y" option, is not known to be buggy, yet many users avoid it because it is unsupported. YEARFRAC, often promoted as a modern replacement, fails in those same edge cases regardless of which "Basis" parameter you choose. The European 30/360 basis comes closest, two or three errors per 100,000, but "close" is not the same as correct. The lesson is clear: when accuracy matters, trust a formula that has been tested at scale, not one that simply sounds current.
For anyone managing dates in a spreadsheet, the path forward is straightforward. Use one of the three verified methods. Test your own edge cases, birthdays, leap years, end-of-month boundaries, before relying on the output. The community's analysis proves that even a small formula can hide a surprising number of failure modes, and a 73 percent error rate among suggested solutions is a reminder that expertise is not the same as popularity. The smart move is to adopt what is proven, not what is promoted.