AI Demand Planning and Forecasting
DemandLabs refreshes forecasts daily at SKU-store level and measures each planner override against the model.
Demand Planning Capabilities
Forecasts Refreshed Each Hour
POS and weather signals refresh the near-term forecast, so a heat wave shows up in the plan the same day.
See demand sensing in the tourOne Consensus Number
Commercial and supply teams edit one forecast grid, and DemandLabs logs each change with its owner.
Request a demoKeep the Overrides That Add Accuracy
DemandLabs scores each override against the ML baseline, so your team can automate the ones that work.
Forecasts for Promotions and New Items
DemandLabs estimates uplift and cannibalization for each promotion and builds launch curves for new items from look-alikes.
Live in Eight Weeks
Bring 24 months of sales history. DemandLabs backtests the models against your current forecast before go-live.
Weeks 0 to 2
Connect Your Data
Sales history and calendars load from your ERP.
Weeks 3 to 6
Model and Backtest
Models train on your history and face your current forecast.
Weeks 7 to 8
First Live Cycle
Planners run consensus on real numbers.
Built for Your Industry
Demand Planning FAQs
How long does implementation take?
Eight weeks to the first live consensus cycle, with a value review with your CFO in week 10.
What data do we need?
About 24 months of sales history, plus your product and location hierarchy and calendars.
Which drivers does the forecast use?
The model uses price and promotion plans as explicit drivers. POS and weather signals refresh the near-term forecast each hour.
Can we forecast items with no sales history?
DemandLabs builds a launch curve from look-alike items with similar attributes.
Does it connect to supply and inventory planning?
The consensus forecast feeds supply planning and inventory optimization on the same decision graph.
Bring 24 Months of History and See the Difference
A 45-minute walkthrough on your own data.