A time series forecast is useful only when it arrives at the right horizon, at the right level of detail and with enough evidence for someone to act. A lower error score is not automatically a better business forecast. It may conceal leakage, perform poorly during peaks or predict a quantity that does not match the real planning decision.<\/p>\n
This article explains an eight-step time series forecasting process using EPW\u2019s FORECAST framework<\/strong>. It covers the full path from decision framing and simple baselines to temporal validation, uncertainty, deployment and monitoring. The process applies whether the final model is statistical, tree-based, neural or an ensemble.<\/p>\n