Forecasting Simulator
Explore trend, seasonality, forecasting methods and uncertainty assumptions, then observe how each choice changes the forecast path.
Forecasts are shaped by pattern, method, assumptions and horizon.
This simulator uses deterministic monthly demand data so learners can change the historical pattern, forecast method, trend adjustment, seasonal strength, horizon and uncertainty growth while seeing the effects immediately.
Forecasting Simulator — Step by Step
Eight locked stages move from the forecasting context through historical pattern, method, trend, seasonality, horizon, a recent-demand shock and management review.
Historical Demand, Forecast Path and Uncertainty
Reveal the forecasting context to begin.
Interpret forecast structure and validation evidence.
Build Your Own Forecast Scenario
Experiment Mode is isolated from the guided demonstration. Change pattern, method, trend, seasonality, horizon and uncertainty without affecting guided progress.
Test forecasting judgement.
Forecasting cues
Trend
Persistent upward or downward movement. Stress-test whether the historical slope is likely to continue.
Seasonality
Recurring calendar or cycle effects. Use only when there is evidence the pattern may continue.
Backtest Error
MAE and MAPE show how the method performed on known historical observations held out from fitting.
Forecast Horizon
Longer horizons usually carry more uncertainty because more unknown events and assumption errors can accumulate.
Uncertainty Range
Use a plausible range around the central estimate rather than treating the point forecast as certain.
Shock Interpretation
Determine whether a recent change is temporary, structural or anomalous before embedding it permanently in the trend.
Use historical structure, method choice, sensitivity analysis and backtesting together to support planning without pretending the future is known precisely.