R Forecasting Playground — Supply Chain Demand

Compare Excel's linear forecast against R's forecasting toolkit. Adjust demand patterns, toggle models, and see which method wins. All math runs live in your browser.

Demand Pattern

Forecast Settings

Models

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Best Model
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Best MAPE
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Excel MAPE
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Improvement

Advisory Panel

Reference: Hyndman, R.J. & Athanasopoulos, G. (2021) Forecasting: Principles and Practice, 3rd ed., OTexts. Models: Excel Linear (OLS regression = FORECAST.LINEAR), Naive (random walk), Seasonal Naive (SNAIVE), SES (ETS(A,N,N)), Holt's Linear (ETS(A,A,N)), Holt-Winters Additive (ETS(A,A,A)). Smoothing parameters optimized via grid search. Prediction intervals: Holt-Winters via forecast error variance. Default scenario: 36 months (Jan 2023 – Dec 2025), trending+seasonal demand, base=2000, trend=15/mo, seasonal amplitude=400, noise SD=40, train/test split 24/12.