Phase 1: the spreadsheet
Below $3M revenue, a per-SKU rolling 4-week and 12-week average reorder model in a spreadsheet beats most tools. The discipline is doing it weekly and acting on the output, not the tool sophistication.
Most brands fail at forecasting because they skip the weekly review, not because the model is wrong.
Phase 2: ERP-led planning
Once you have an ERP (NetSuite, Brightpearl, Cin7), use its native demand planning module. It pulls historicals automatically, integrates with the inventory side, and removes the spreadsheet labor. Forecasting accuracy does not change dramatically; the operator hours saved do.
Phase 3: dedicated tooling
Cogsy (DTC-focused) and Streamline are the most common dedicated forecasting tools at our scale. They earn their fee once you cross 500+ active SKUs, have meaningful seasonality, or run promotions that distort baseline demand.
Below that, the ERP's planning module is usually enough.
Common forecasting mistakes
Three errors recur: 1) Forecasting at the wrong level (per-SKU when per-category would be more accurate, or vice versa). 2) Ignoring lead time variance, leading to either stockouts or overstock. 3) Not capturing promo lifts separately from baseline.
A specialist can save months of trial-and-error here.
Talk to a specialist
If you are facing this decision now, a free scoping conversation with a vetted Shop Operations Experts specialist usually saves weeks of back-and-forth. Tell us the situation and we will route you to someone who has shipped the work for a comparable brand.
No sales pitch, no lead-volume games — just a scoped recommendation within one business day.