Optimizing Company Performance in Water Manufacturing: The Synergistic Impact of Inventory Turnover and Demand Forecasting
Abstract
Inventory turnover and demand forecasting, two specialized disciplines in inventory management, are considered highly critical to business success, particularly in the water production sector. However, much research remains to be done on these factors and their joint effect on project success. This study examines the under-researched dilemma of inventory turnover demand forecasting and its impact on organizational performance in the water manufacturing industry. A study spanning 14 months on operational data from a bottled water company reveals that various operational dynamics are more pronounced in small plastic bottles than in glass bottles and large gallon containers. The main results show that inventory turnover has striking differences, with the glass bottle outperforming by far (ratio: 96.35) given the low outgoings associated with carrying it, whereas small plastic bottles were markedly lower in turnover (20.50), influenced by demand fluctuations. This investigation shows that ARIMA outperforms DES in forecasting accuracy, with MAPE values ranging from 10.5 to 23.53% and R² values ranging from 0.717 to 0.833. The EOQ optimization indicated that large orders for glass bottles (22,112 units) are now optimal, even with setup costs of $5,933.44. In contrast, safety stock settings (e.g., 9,557 units of glass bottles at a 95% service level) have effectively reduced stockouts. This study is theoretically valuable because it connects inventory turnover measures to forecast algorithms within established performance frameworks, and it shows, practically, how ARIMA-informed, size-specific EOQs and reorder points can improve delivery reliability, cost efficiency, and resource utilization. The study then concludes by encouraging the adoption of real-time forecasting systems and by changing inventory policies to operate more effectively in an exceptionally volatile marketplace
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This work is licensed under a Creative Commons Attribution 4.0 International License.

