Ameha Mulugeta (PhD)Tola Kebede2025-10-222025-10-222018-09https://etd.aau.edu.et/handle/123456789/7513Improving production planning and operational efficiency in the beverage business requires accurate demand forecasts. In order to increase the accuracy of demand forecasting at NEHE Beverage Complex PLC, this study examines the use of time series analysis, namely the ARIMA (AutoRegressive Integrated Moving Average) model. By creating a trustworthy forecasting model using past sales data, the study seeks to address the issues of demand volatility, inventory imbalances, and production inefficiency. The results show that ARIMA modeling greatly increases demand prediction accuracy, offering a solid foundation for improved inventory control, resource allocation, and production scheduling. This lowers waste and operating expenses by allowing NEHE Beverage Complex PLC to better match its production procedures with consumer demand.en-USforecastingARIMA modeltime seriesproduction planningThesis