This is the exact kind of problem that separates a manual process from a scalable one. The user here has hit the wall that every spreadsheet power user eventually reaches: what works for a small dataset breaks the moment your data grows, your deadlines tighten, or your inputs get messy. The issue isn't the tool, it's the assumption that dates will be clean, consistent, and ready for lookup. That assumption rarely survives contact with real-world data.
We see this scenario play out constantly in pension admin and beyond. A team builds a macro or a lookup tool that depends on perfect inputs. It works beautifully in testing. Then the production data arrives with date formats that drift between dd/mm/yyyy and mm/dd/yyyy, or with missing entries, or with values entered as text instead of serial numbers. The tool fails silently or returns wrong results. The user becomes the human bridge, manually correcting dates so the automation can run. That bridge is fragile. It doesn't scale, and it burns time that should be spent on analysis, not janitorial work.
The practical answer for larger datasets is to stop correcting the source data and start building tolerance into your lookup logic. Instead of requiring exact date matches, use fuzzy matching or date-range lookups. Convert all incoming dates to a single canonical format with a preprocessing step before the lookup runs. If your tool won't do that, wrap it in a script that normalizes the data first. The goal is to absorb the noise at the boundary, not force it through every step. The user's instinct to ask the community is exactly right, this is a pattern problem, not a one-off fix.
What this user is really asking is how to move from hero-mode data cleaning to a system that handles inconsistency as a feature, not a bug. That shift is the difference between being the person who fixes spreadsheets and the person who builds workflows that don't need fixing. The answer isn't a better date picker. It's a smarter approach to how your tool ingests and interprets the data it receives. Start there, and your reconciliation work becomes something you trust, not something you babysit.