<![CDATA[Effective raw-material inventory management is critical for maintaining uninterrupted production, reducing operational costs, and ensuring manufacturing efficiency. Achieving these objectives requires accurate inventory records, timely replenishment, and inventory policies that account for demand variability and supplier lead times. This study presents a descriptive evaluation of digital inventory management using two complementary datasets obtained from a fertilizer manufacturing facility in North Aceh, Indonesia. The first dataset compares inventory performance before and after digitalization for fifteen critical raw materials by examining stockout frequency and inventory record accuracy. The second dataset summarizes twelve months of post-digitalization operations, including active stock-keeping units (SKUs), inventory value, inventory turnover, stock accuracy, and monthly stockout incidents. Comparative analysis of the material-level dataset shows that stockout events decreased from 74 under manual inventory management to 15 following digitalization, representing a descriptive reduction of 79.73%. Mean inventory record accuracy improved from 80.26% to 96.57%, an increase of 16.31 percentage points. The monthly operational dataset reports an average stock accuracy of 91.91%, a mean inventory turnover ratio of 4.43, and 15 stockout events across the twelve-month observation period, with six months recording no stockout occurrences. Because the before-and-after material comparison and the post-digitalization monthly performance series do not share a common implementation timeline, control facility, or standardized deployment protocol, the datasets are analyzed independently to avoid unsupported causal inference. The findings therefore identify favorable trends in inventory availability, record accuracy, and operational performance rather than demonstrating causal effects of digitalization. This study contributes a transparent evaluation framework integrating material-level availability, monthly inventory performance, lead-time segmentation, and implementation-governance considerations, providing a practical decision-support approach for reviewing digital inventory management and supporting continuous improvement in manufacturing supply-chain operations]]>
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