The daily ritual of manually merging reports is a productivity trap, and it is long past time to stop treating it as inevitable. This user's struggle, facing thousands of rows across multiple financial and operational files, only to spend hours on the mechanical act of combining them before any real work begins, is a symptom of a deeper problem: tools that were never designed for the scale and speed of modern data work. Power Query helps, but when files grow large, even that becomes a bottleneck. The real issue is that the process itself is broken.
What this means in practical terms is that every hour spent clicking, sorting, and appending is an hour stolen from analysis, insight, and decision-making. For anyone in finance or operations, that trade-off is unacceptable. The user is right to ask for something better. The solution is not a cleverer workaround in Excel; it is a fundamentally different approach. AI-native spreadsheet tools can ingest multiple files automatically, recognize their structure, and merge them into a single, clean dataset without manual intervention. The data arrives ready for dashboards, pivot tables, or deeper modeling, not as a chore, but as a starting point.
This is not about replacing the user's expertise. It is about removing the friction that keeps them from applying it. When you no longer have to babysit a merge process, you can spend your energy on the questions that matter: What does this week's trend tell us? Where are the outliers? What should we act on tomorrow? The technology exists today to make that shift, and it does not require a team of engineers or a migration to a completely new platform. It starts with choosing a tool that treats automation as a default, not an add-on.
The user's question, "Is there a more efficient approach?", deserves a direct answer: yes, and it is already available. Stop treating manual merging as a necessary evil. Start expecting your tools to do the heavy lifting so you can do the thinking.