Demand Intelligence.
Forecast accuracy is the most-tracked, least-actionable metric in supply chain. Better forecasts do not produce better decisions unless the variability the forecast hides is priced into the planning solve.
Probabilistic Demand Forecasting
Point forecasts hide what they don't know. Demand teams operate as if the future has one value; the business carries variance silently in safety stock, expedites, and missed revenue.
Read card →Demand Sensing on Short Horizons
Monthly forecasts cannot react to last week’s Point-of-Sale (POS) data, retailer-shared inventory positions, or channel mix shifts. By the time the next forecast cycle runs, the opportunity has closed.
Read card →Causal Demand Modeling
Forecasts treat price, promotion, weather, holidays, and competitive moves as exogenous noise. The business runs price and promotion calendars in a separate system from forecasts, and the two never align.
Read card →New Product Introduction Forecasting
New products have no history. New Product Introduction (NPI) forecasts are made by analogy, gut, or committee, and they're usually wrong in both directions — overbuy and write off, or underbuy and miss the launch window.
Read card →Forecast bias cut in half. Safety stock right-sized to actual variability. Promotional uplift captured before competitors react. NPI launches that hit first-quarter ramp without write-offs.
See how Demand Intelligence lands in your own enterprise. A PULSE workshop scores your AIR baseline and frames the roadmap from here.
Book your PULSE workshop →