Optimizing Pharmaceutical Logistics through Sales Forecasting of Black Cough Syrup 100 ml to Support Competitive Advantage at PT "X"

The pharmaceutical industry faces increasing pressure to maintain efficient supply chain operations amid dynamic market conditions. This study aims to identify the most accurate sales forecasting method to optimize pharmaceutical logistics and support the competitive advantage of PT “X” in producing Black Cough Syrup 100 ml. Using historical monthly sales data from August 2023 to January 2025, the study applies four quantitative forecasting techniques: Single Moving Average (SMA), Weighted Moving Average (WMA), Single Exponential Smoothing (SES), and Linear Regression. Forecast accuracy is evaluated using Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The results reveal that the 3-period SMA method yields the lowest forecast error (MAD: 954; MAPE: 21.09%) and is the most suitable model for the case. These findings highlight the strategic importance of integrating forecasting methods into pharmaceutical logistics to improve production planning, reduce stockout risks, and enhance customer satisfaction. By adopting accurate forecasting tools, PT “X” can strengthen interdepartmental coordination, improve inventory turnover, and build a sustainable competitive edge in the pharmaceutical market.