Overview
Most demand forecasting fails because teams use simple moving averages that ignore seasonality, trends, and external factors. They overstock slow-moving products and understock high-demand products, creating excess inventory costs and lost sales.
The Demand Forecasting System builds time series models that account for seasonality (weekly, monthly, yearly patterns), trends (growth or decline), and external factors (promotions, holidays, weather) — with inventory optimization recommendations and forecast accuracy tracking.
What you get: - Time series decomposition (trend, seasonality, residuals) - Forecasting model selection and training - Forecast accuracy metrics and confidence intervals - Inventory optimization recommendations (reorder points, safety stock) - Scenario planning for promotions and events - Forecast performance tracking and improvement
Built for: supply chain teams, inventory managers, and operations teams who need demand forecasts that optimize inventory — not guesses that create stockouts or excess inventory.