This user's problem is a perfect example of how a simple workflow can become a maintenance trap. The core issue isn't complex, they need the latest status column and the static transaction data, but their source file grows a new column every week while archiving old ones. The instinct to manually remove those historical columns is understandable, but it is the wrong solution. It treats a recurring data problem as a one-time cleanup task, which is exactly the kind of friction that undermines productivity over time.
Power Query is more than capable of handling this automatically, and the answer lies in shifting the logic from column names to column position. Since the most recent "current status" column is always the last column in the file, the user can write a query that removes all columns except the static ones and the final column. A simple approach is to use `Table.LastColumn` or to filter columns by index, keeping the first column (Transaction) and the last column. This eliminates any need to know the date of the latest update. The query will work the same way whether the file has two columns or twenty, because it targets the structural pattern rather than a specific header name.
What this means in practice is freedom from weekly manual intervention. The user can set up the query once, refresh it each week, and the output will always contain only the transaction ID and the most recent status. No more right-clicking, no more deleting, no more worrying about breaking the process for colleagues who still need the old columns. The technique also scales: if multiple files follow the same pattern, the same logic can be applied to all of them in a single query. This is the kind of small automation that pays back its setup time many times over.
The broader lesson here is that data workflows should be designed for how data actually behaves, not how we wish it would stay still. Legacy tools like manual column deletion force users to adapt to the tool. A thoughtful approach, using Power Query's ability to read structure and position, makes the tool adapt to the user. The user's instinct to ask "can this be automated?" is exactly right. The answer is yes, and the implementation is straightforward. Stop deleting columns manually. Let the query do the thinking.