Managing data across endless spreadsheets used to feel like running blindfolded. Here's how we moved to structured AI workflows — and what actually changed.
Every growing business hits the same wall. It starts with one Google Sheet for tracking leads. Then another for project management. Then another for invoices. Before you know it, you have 40 spreadsheets, 3 of which are "the real one," and nobody trusts any of them.
Common symptoms:
The first step isn't building anything — it's mapping what you have.
We typically find:
That means roughly 80% of the spreadsheet work you do could be automated.
Where does data originate? Forms? Emails? APIs? Manual entry? Map every source.
Pick one system — a database, a CRM, an Airtable base — and make it the canonical source. Everything else reads from it.
For each data flow:
The 15-20% that needs judgment? This is where AI shines:
Before: A marketing team spent 6 hours every Monday compiling a weekly performance report from 5 different platforms into a Google Sheet, then formatting it for the executive team.
After: An automated workflow pulls data from all 5 platforms at 6 AM Monday, AI generates a summary with key insights and recommendations, formats it into a branded PDF, and emails it to the executive team. By the time anyone opens their laptop, the report is waiting.
Time saved: 6 hours/week → 0 hours/week
Teams that successfully migrate from spreadsheet chaos to structured workflows report:
Spreadsheets are great for exploration and one-off analysis. They're terrible for repeatable business processes. The sooner you recognize which of your spreadsheets are really "poor man's databases," the sooner you can free your team to do actual thinking work.