Your Method: "Okay, first item... copy. Paste. Now, what do I call this column? 'Notes'?"
My Method: "This list of customer feedback needs Feedback_ID, Original_Comment, Core_Issue_Category, Sentiment, and Action_Owner. I've already defined my Core_Issue_Category list of 12 allowed values. Any comment not fitting perfectly will be flagged."
This upfront schema design means zero rework, zero ambiguity, and zero "oops, I forgot a column" moments. You're building a house with no blueprint; I'm laying the foundation with precision.
I refuse to tolerate "Near Enough" data. If a category should be "Performance Issue," it won't sometimes brother cell phone list be "Perf Issue" or "Performance related problem" in my output.
Your Method: You've got "Customer Service," "Cust Svc," and "CS" all representing the same thing. Your pivot tables are crying. Your filters are failing. You're living in a world of duplicate data points that should be one.
My Method: I leverage dropdowns, pre-defined lookups, and robust validation rules. If the input doesn't conform, it gets flagged for review, not silently accepted into the data graveyard. My data can be aggregated, filtered, and analyzed with absolute confidence because every entry means exactly what it's supposed to mean.
3. I Automate the Mind-Numbing (You're Still a Human Robot)