Forecast accuracy assessment guide. How to evaluate your forecasts?
Evaluating forecast accuracy is crucial for reliable business decisions. Metrics like MAE, SMAPE, MASE, and RMSE help measure prediction errors, while assessing bias and combining multiple indicators ensures forecasts align with operational goals and provide actionable insights.
Understanding time series forecasting: 10 models and tools
Article reviews ten key time series forecasting models and tools—from classical methods like ARIMA and exponential smoothing to machine‑learning approaches such as XGBoost, LGBM, and neural networks—helping readers choose appropriate techniques for accurate future predictions
New whitepaper released: we break down Demand Forecasting
We would like to announce the launch of our latest whitepaper: Prognozowanie popytu: Wykorzystanie technologii AI i ML z klasycznymi metodami statystycznymi w nowoczesnym łańcuchu dostaw written by our in-house expert, Magdalena Foltyn, PhD.