When you invite four friends to your house for a dinner, there should be an optimal seating arrangement. It’ll likely be obvious, easy, and you won’t have to think twice about who sits where.
If you bump the number of invitees to 10, seating gets a bit more tricky, but still: Should be easy enough to find the perfect spot for everyone, right? Everyone will sit next to or across from someone they like, someone they know, or someone they should know. Possibly all three.
Now, imagine you’re planning you’re wedding. As soon as my partner and I were staring at a giant seating chart, we knew: It will be impossible to make everyone happy. We mapped out an initial version, then let it ripen.
A few weeks later, we’d had some cancellations and shifts. We sat down to finalize the plan for 75 guests in total. Initially, we got pulled into optimization mode. Then, we caught ourselves. “Stop. There is no perfect solution. Let’s just get this done.” In the end, we mostly stuck with our initial choices. We filled the gaps, made sure both sides of the table were roughly even, and called it a day.
It’s not like our choices were entirely random. We did put some thought behind them. But not more than necessary. As long as families sit together and everyone has one good match to talk to, each guest will be fine. As soon as dessert is done, folks start moving around as they like anyway.
Overthinking rarely helps with anything. Small choices don’t warrant the time. Big decisions become an endless circle. But especially when you go in knowing there won’t be a perfect solution, overthinking is nothing but hours and energy you won’t get back.
Run your optimization algorithms where they can actually lead to above-average results, and 80/20 the rest. Even if that means your friends might have to swap seats, everyone can still have a great time.
