Configuring Forecasting Techniques and Supply Chain Strategies to Enhance Resilience and Minimize Pharmaceutical Shortages in the Ethiopian Public Supply Chain
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Date
2025-06
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Addis Ababa University
Abstract
The availability of essential medicines is a cornerstone of a functional healthcare system, directly influencing health outcomes and healthcare quality worldwide. Accurate demand forecasting plays a critical role in ensuring that medicines are consistently available where and when needed, preventing stockouts and minimizing wastage. In Ethiopia, the pharmaceutical supply chain faces considerable challenges, including frequent medicine shortages, long procurement lead times, and data quality issues. These problems are exacerbated by the lack of skill and training of workforce in advanced forecasting methods. Given the dynamic nature of healthcare demands and the complexity of supply chains, advanced forecasting techniques, including machine learning, are becoming indispensable for improving accuracy and resilience. This PhD study aims to explore how forecasting techniques and other supply chain strategies can be configured to improve demand forecasting practices within Ethiopian Pharmaceutical Supply Services (EPSS), with the ultimate goal of enhancing supply chain performance and ensuring reliable access to essential medicines
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Keywords
Forecasting, Accuracy, Simple forecasting methods, Machine learning, Active strategies, Proactive strategies