Forecasting demand and creating an inventory policy for Ecorus

For 8 SKUs and 3 product groups, seven forecasting methods are implemented. Forecasting involved classifying SKUs by trend and seasonality strength, with SES and ARIMA identified as superior methods, offering adaptable solutions capable of capturing diverse demand patterns. Implementing an (s,Q) policy based on accurate forecasts resulted in a 91% average fill rate. A sensitivity analysis explored the impact of safety factors and order quantities on total costs and fill rates, informing iterative refinement of inventory policies to balance cost efficiency and service levels.