There is a better way to do this, and the fact that your predecessor was doing it manually is exactly why AI-native tools matter. You are not being robotic or rude, you are asking the right question, and that instinct to find a formula instead of grinding through rows is what separates efficient data work from busywork.
The core problem is simple: you have multiple rows for the same package, and you need to keep only the row with the lowest stock level. In traditional Excel, this requires a multi-step dance, sorting, conditional formatting, manual deletion, or a combination of MINIFS with filtering. It works, but it is tedious and error-prone, especially when you have 100 packages with up to eight items each. The person who trained you is spending time on repetitive deletion that could be spent analyzing why certain items are at zero stock or reordering before a stockout occurs.
What AI simplifies here is the logic of "group by column A, find the minimum in column C, keep that row." Instead of writing nested formulas or recording a macro, you can describe the task in plain language: "Remove duplicate rows in column A, keeping only the row with the lowest value in column C." Modern spreadsheet tools with AI assistance can interpret that instruction, execute the deduplication, and deliver the clean result you showed in your finished spreadsheet. This is not about replacing your judgment, it is about removing the friction that keeps you from focusing on inventory decisions that actually matter.
Your example of the Double Burner with Tank (DD1683) having a zero on hand is a perfect case in point. That zero is important data. It tells you something urgent. But if you are spending your mental energy manually scanning rows to delete duplicates, you might miss the significance. An AI-assisted workflow lets you see that zero immediately, because the tool handles the mechanical sorting and filtering. The transformation here is not just speed, it is clarity. You get the answer you need, not the chore you were trained to do.