Automating reporting and analysis: stop rebuilding the same report.

Name the report’s reader and decision.

A report nobody acts on is a candidate to stop, not to automate. Before building anything, write down who reads it and what they decide with it. If you cannot, ask them.

Automate the pull.

Pulling numbers from the same sources into the same layout is mechanical. Scheduled exports, a connected spreadsheet, or a dashboard can do it. Keep a visible “last updated” and a note of the source for every figure.

Let AI draft the first read.

Give an assistant the table and ask: “What changed compared with last period? What looks unusual? What would you want to check before reporting this?” The goal is a draft narrative and a list of questions, not conclusions.

Add the human layer.

You know about the campaign that paused, the data glitch, the seasonal spike. Add the context, the recommendation, and the caveats. A number with no interpretation is just a number.

Check the pipeline.

Automated reports fail quietly. Compare one report against a manual calculation each month, and set an alert for when a source returns nothing. The weekly reporting workflow shows a careful version of this.