Normalized Demand in inventory optimization and supply chain management refers to the process of adjusting raw demand data to account for external variables or anomalies, allowing for more accurate comparisons and analyses across different time periods, products, or locations. This transformation typically involves removing seasonal effects, promotions, outliers, and irregular spikes or dips caused by unusual events (such as supply chain disruptions or natural disasters). By converting raw demand data into a standardized format, normalized demand enables businesses to better understand the underlying, consistent pattern of customer needs. In supply chain planning, normalized demand is crucial for building reliable forecasting models and aligning supply with true market demand. It helps planners avoid overstocking or understocking by focusing on the “baseline” demand level that reflects actual customer behavior without distortion. With normalized data, organizations can more confidently make decisions on inventory levels, replenishment strategies, production planning, and resource allocation. Ultimately, normalizing demand leads to improved service levels, reduced carrying costs, and more agile and responsive supply chains.
