Optimizing Pharmaceutical Logistics through Sales Forecasting of Black Cough Syrup 100 ml to Support Competitive Advantage at PT "X"
DOI:
https://doi.org/10.31004/jestm.v5i1.225Keywords:
Pharmaceutical Logistics,, Sales Forecasting,, Inventory management,, Supply Chain,, Competitive AdvantagesAbstract
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.
References
Demand Forecasting and EOQ for Inventory Management in the Pharmaceutical Sector,” IEOM Conf. Proc., 2024. [Online]. Available: https://ieom.org/proceedings/2024/inventory-forecast
E. Tucker and M. Daskin, “Pharmaceutical Supply Chain Reliability and Effects on Drug Shortages,” J. Supply Chain Syst., vol. 7, no. 4, pp. 211–219, 2021.
H. Haider, “The Application of EMA Model in Forecasting Pharmaceutical Sales and Supply Chain Planning,” J. Sci. Eng. Res., vol. 9, no. 6, pp. 45–52, Jun. 2022. [Online]. Available:https://www.jsaer.com/download/vol-9-iss-2-2022/JSAER2022-9-2-156-160.pdf
I. Merkuryeva, J. Grabis, and A. Romanov, “Improving Public Health Supply Chains: Time Series Techniques for Medication Demand Forecasting,” Health Supply J., vol. 6, no. 1, 2025.
James, P., 2025. End-to-End Visibility as a Competitive Advantage in Disrupted Pharma Supply Chains. PharmaLog Journal, May.
J. Paul, A. Rahman, and M. Yusuf, “Comparative Analysis of Demand Forecasting Methods to Optimize Logistics Performance in Pharmaceutical Firms,” Int. J. Contemp. Soc. Res. Rev., vol. 9, 2024.
Kechagias, P., Miloulis, D., Chatzistelios, G., Gayialis, S. and Papadopoulos, G.A., 2021. Applying a System Dynamics Approach for the Pharmaceutical Industry. Systems Research and Behavioral Science, 38(1).
L. Chen and A. Singh, “A New Key Performance Indicator Model for Demand Forecasting in Pharma Distribution,” J. Sci. Ind. Eng., vol. 13, no. 3, pp. 55–67, 2023.
Merkuryeva, I., Grabis, J. and Romanov, A., 2025. Improving Public Health Supply Chains: Time Series Techniques for Medication Demand Forecasting. Health Supply Journal, 6(1).
M.L. Sabogal De La Pava and E.L. Tucker, “Effects of Geopolitical Strain on Global Pharmaceutical Supply Chain Design,” J. Logist. Global Trade, vol. 11, no. 2, pp. 77–88, 2023.
N. Wardah and H. Iskandar, “Sales Forecasting Analysis Using Moving Average and Exponential Smoothing Methods,” J. Technol. and Management, vol. 12, no. 1, pp. 15–22, Jan. 2020. [Online]. Available: https://doi.org/10.14710/jati.11.3.135-142
P. James, “End-to-End Visibility as a Competitive Advantage in Disrupted Pharma Supply Chains,” PharmaLog J., May 2025.
P. Kechagias, D. Miloulis, G. Chatzistelios, S. Gayialis, and G.A. Papadopoulos, “Applying a System Dynamics Approach for the Pharmaceutical Industry,” Syst. Res. Behav. Sci., vol. 38, no. 1, 2021.
R. Fildes, S. Ma, and S. Kolassa, “Retail Forecasting: Research and Practice,” Int. J. Forecast., vol. 38, no. 4, pp. 1283–1318, 2022.
Rizaldy, F. Permana, S. Yuliani, and A. Hartono, “Hybrid Forecasting Model for Optimizing Pharmaceutical Supply Chains,” PharmaHealth Group Research Paper, vol. 8, no. 2, pp. 123–135, May 2025. [Online]. Available:https://www.pharmahealthgroup.org/research/hybrid2025
Sabogal De La Pava, M.L. and Tucker, E.L., 2023. Effects of Geopolitical Strain on Global Pharmaceutical Supply Chain Design. Journal of Logistics and Global Trade, 11(2), pp.77–88.
S. Lee, “5-Year Forecast: Evolving Supply Chains in Pharma & Healthcare,” NumberAnalytics Report, Mar. 2025.
S. Raharjo, H. Prasetya, and R. Wulandari, “Investigating Demand Forecasting Practices in Pharmaceutical SMEs,” J. Supply Chain Management Indonesia, vol. 6, no. 1, 2025.
Tucker, E. and Daskin, M., 2021. Pharmaceutical Supply Chain Reliability and Effects on Drug Shortages. Journal of Supply Chain Systems, 7(4), pp.211–219.
V. Gaspersz, Production Planning and Inventory Control, Jakarta: Gramedia Pustaka Utama, 2019, pp. 123–135.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Yovita Yulia M. Zai
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
