The Forecasting Window refers to the period into the future for which demand forecasts are generated. It can vary from short-term (e.g., days or weeks) to long-term (e.g., months or years), depending on the business context and product characteristics. In inventory optimization, the forecasting window significantly influences replenishment decisions, safety stock levels, and production planning. A short forecasting window may be more accurate but less useful for long-lead-time items. Conversely, a long window enables strategic planning but often carries higher uncertainty. Selecting the appropriate forecasting window requires understanding the lead time, demand volatility, and customer service expectations. Balancing the forecasting window is critical to avoid mismatches between supply and demand. For example, a fashion retailer might use a short-term window to adapt to trends quickly, whereas an industrial manufacturer may require longer-term forecasts for sourcing raw materials globally. Technologies such as demand sensing and machine learning can dynamically adjust forecasting horizons based on real-time data, improving forecast agility and inventory efficiency.
