There's a better way to think about this problem, and it starts with admitting that the current approach isn't just slow, it's fragile. The user here is doing something completely reasonable: building a reusable sheet where two reports can be dropped in, and a comparison spits out automatically. The goal is clear, the method is logical, and the frustration is earned. But the core issue isn't the data. It's the architecture of the formula. When every timestamp in one list gets compared against every timestamp in another, you're not just asking for a performance hit, you're building a system that will break the moment the data grows even slightly. That's not a spreadsheet problem. That's a design problem.
What this person actually needs is a structural shift, not a formula tweak. They've already identified the right instinct: instead of comparing everything to everything, isolate the work orders into their own columns, then run the comparison only against the matching set. That's not a clever workaround. That's the correct mental model. The reason it feels like a dead end is because the tool they're using, likely a traditional spreadsheet grid, doesn't naturally support variable-width, variable-length pairing without manual intervention. But the logic itself is sound. The fact that they're asking for a way to "spit out the results at the end" without daily adjustments tells us they understand the real requirement: the system should do the heavy lifting, not the user.
This is where the conversation moves from "how do I fix this formula" to "how do I build a system that respects the data." The pivot table they mentioned is a clue, it shows they're already thinking in terms of summarization and outcome, not just calculation. But the missing piece is a way to structure the comparison so that it's inherently scoped. Instead of computing every possible pair, you compute only the pairs that matter: same work order, closest timestamp. That's a filter-first approach, and it's the difference between a sheet that crawls and one that stays responsive even as the data doubles. The user shouldn't have to choose between accuracy and speed. They should be able to expect both.
The practical takeaway is this: if you're hitting a wall with a formula that compares every row to every other row, stop optimizing the formula and start restructuring the layout. Use helper columns to isolate the matching keys. Use dynamic ranges that expand with the data. And if the tool you're using can't handle that without manual tweaking, that's not a limitation of your idea, it's a limitation of the tool. The user here is asking the right questions. The next step is to stop asking "can I do this" and start asking "what's the cleanest structure that makes this inevitable?" Because once the structure is right, the computation becomes trivial. That's the real unlock.