Inventory Management of Saline using Forecasting Techniques in A Hospital Case Study

Abstract

The purpose of this research is to efficiently manage the saline inventory system of the hospital by reducing storage and control problems according to patients' demands. First, all saline types in stock were grouped by value using the ABC technique which yielded an “A” cluster that accounted for 59.92% of the total saline stock value. Second, demand forecasting of group “A” saline by means of various forecasting techniques. In this study, the techniques applied were Moving Average, Weighted Moving Average, and Exponential Smoothing. The Mean Square Error (MSE) and the Mean Absolute Percentage Error (MAPE) were used to measure the forecast errors. And it was discovered that Exponential Smoothing is the most appropriate technique. Third, planning and analysis of the saline stock were fulfilled by implementing the periodic review inventory system at a 99 percent service level. With review policy, the maximum stock of group "A" saline was defined. Finally, inventory costs between "before" and "after" was compared, and found that 8.84% of costs can be reduced.