Demand Forecasting Simulator

Demand forecasting is the process of predicting future customer demand for a product or service using historical data, market trends, and statistical methods. Accurate forecasts help businesses optimize inventory levels, production schedules, staffing, and procurement.

This simulator uses a linear trend projection with optional seasonality. It calculates a trend line from your 12 months of historical data, applies a growth rate adjustment, and optionally overlays seasonal patterns derived from your data. The confidence interval widens over time to reflect increasing uncertainty.

Toggle the seasonality option on, and the tool will detect seasonal patterns from your historical data. It calculates seasonal indices by comparing each month to the overall average. These indices are then applied to the forecast to maintain seasonal highs and lows.

The confidence interval (shaded area in the chart) shows the range where actual demand is likely to fall. The band widens further into the future because uncertainty increases over time. A narrower band indicates more predictable demand; a wider band suggests higher volatility.

This is a simplified forecasting tool for planning purposes. Real-world accuracy depends on data quality, market stability, and external factors. For critical business decisions, combine this with domain expertise and consider using advanced methods (ARIMA, exponential smoothing, machine learning) available in ERP systems like Odoo.