Optimizing Inventory Control and Operational Efficiency Using Holt-Winters Forecasting in a Warehouse Management System

Abstract

Inventory management plays an important role in ensuring product availability and supporting effective warehouse operations in distribution companies. PT. Tuberkita Maju Sejahtera Kudus still experiences inventory management challenges due to manual recording processes, which may lead to overstocking and stockout and reduce the effectiveness of inventory control. Therefore, this study aims to implement the Holt-Winters Multiplicative method within a warehouse management system to improve forecasting accuracy and support data-driven inventory planning. The method was selected because it considers three essential time-series components, namely level, trend, and seasonality, enabling it to capture demand fluctuations over time. Historical sales data collected from January 2023 to December 2025 were processed using the Holt-Winters Multiplicative method with fixed smoothing parameters (α = 0.3, β = 0.2, and γ = 0.2). Forecasting performance was evaluated using the Mean Absolute Percentage Error (MAPE). The results indicate that the seasonal component has the greatest influence on forecast variations, demonstrating that product demand is strongly affected by recurring seasonal patterns. The forecasting evaluation produced a MAPE value of 5.22%, indicating very good forecasting accuracy. These findings demonstrate that the proposed forecasting approach can generate reliable demand forecasts and provide decision support for inventory planning, procurement scheduling, and warehouse management, thereby helping organizations make more informed inventory decisions.