Every Friday I used to lose an hour pulling numbers into a spreadsheet, writing a summary, and formatting it into something my team could actually skim. Here’s exactly how I automated it down to about five minutes of review time.
The old process
Export data from three tools, paste into a spreadsheet, manually calculate week-over-week changes, write a summary paragraph, format it for Slack. Repeat every single week, rain or shine, whether the numbers were interesting or not.
Step 1: Get the raw data into one place
I didn’t automate the exports themselves at first — I just made sure all three data sources landed in one spreadsheet automatically each Friday morning using each tool’s built-in export/schedule feature. Small win, but it removed the most tedious manual step.
Step 2: Let AI draft the summary
I feed the week’s numbers to an AI assistant with a standing prompt: “Here’s this week’s data compared to last week: [data]. Write a 3-sentence summary highlighting the biggest change, one thing worth watching, and one recommendation. Keep it casual, for a Slack update.”
Step 3: Review before it goes out
This is the one step I never skip. The draft lands in front of me, not the team. I check the numbers are right and the recommendation makes sense, tweak a sentence if needed, then post it myself. Ninety percent of the time it needs zero edits.
The result
What used to take an hour now takes about five minutes, and the summaries are more consistent than when I was writing them tired on a Friday afternoon. The lesson that generalizes: automate the drafting, keep the reviewing.
If you want the broader framework for finding what else is worth automating, check out our Automating Your Workflow with AI guide.
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