Forecasting breaks when it becomes a manual job.
If your team is exporting CSVs every week, you’re not forecasting—you’re maintaining a spreadsheet.
The good news: you can keep the flexibility of Sheets without relying on Sheets for data ingestion.
The “3-layer forecast” model that works
Layer 1 (facts): what already happened
- Orders, refunds, and fulfillment status (Shopify)
- Actuals: revenue, COGS, expenses (QuickBooks)
Layer 2 (work in flight): what is likely to happen next
- Projects, milestones, launch dates, blockers (Asana)
Layer 3 (assumptions): what you want to be true
- Scenarios, targets, and one-off assumptions (Sheets)
This division keeps your forecast flexible while keeping your reporting dependable.
What you get immediately
- Forecast vs actual that updates automatically
- “What changed this week?” variance drivers
- A risk list: which projects are slipping and what that will affect
- Product mix shifts (and the downstream impact on margin and returns)
The hidden cost of DIY forecasting pipelines
DIY breaks at the edges:
- Taxonomy changes (new SKUs, new categories, new projects)
- Backfills when you reclassify costs or update mapping rules
- Ownership risk when the person who built it leaves
Our managed data platform keeps ingestion reliable and lets you iterate safely—without rebuilding your forecast every quarter.