Prepare history
Pin the sales history, validate coverage and remove known bad periods.
Industry blueprint
Demand forecasting
Retail, CPG and distribution. Retrain when the evidence says so, not every quarter.
Thousands of SKU-by-store series drift with promotions and demand shifts. Teams retrain on a fixed three-to-six-month schedule, wasting compute in stable periods and missing fast drift. This design retrains on evidence and publishes only what a planner approves.
Illustrative pipeline
Train candidates
Run the partner's forecasting method on the pinned history.
Compare on held-out periods
Score the candidate against the current model on the same held-out weeks.
Planner approves
Publish only after a planner reviews error and stability against the agreed threshold.
What the record keeps
The history version, horizon and assumptions, the forecast artifacts, the error and stability report, and the approver.
Partner brings
- Forecasting operator (gradient boosting or statistical)
- Error and stability metrics
- Connector to the planning system
Cairn brings
- Pinned history and quality checks
- Held-out comparison
- Bounded retrain loop with approval
- A record of every published forecast
Business value to test
Forecast error, forecast stability and planning cycle time.
Keep the decision explicit
A forecast is published only after a planner reviews it. Record the horizon, the assumptions and the approver.
Close the feedback loop
A forecast that misses its threshold starts a reviewed retrain. The approved plan stays in use until a candidate proves itself.
Reference design, not a shipped domain pack. A partner brings the domain model and data access; Cairn brings the governed process.
See how failure can trigger a reviewed improvement cycle →Give planners forecasts they can check.
Talk about your demand history, horizon and planning systems.