THE STUDY OF COST EFFICIENCY IN HORTICULTURE WHOLESALER BY APPLYING PERISHABLE INVENTORY POLICY AND DEMAND FORECAST - Jonathan Brata, Elbert
Inventory management is one of the most important aspects in operation management for every business. Low cost efficiency in managing inventory could lead to financial loss. In agricultural industries, inventories could be perished and lost their value. At the end, they become wastages and counted as expenses, instead of revenue. To reduce inventory cost, the firm should apply suitable demand forecast method and inventory review policy. PT. Bimandiri Agro Sedaya is a fruit and vegetable wholesaler to various retailers across Jakarta and West Java. Currently, they have 500 kilograms of perished inventories every day. The firm are unable to predict future demand. Moreover, accurate forecast demand is important to apply suitable inventory review policy. As now, they only use naïve forecast to predict future demand. Even worse, they do not have any inventory review policy. It affects their order amount and time into uncertain condition. Thus, applying inventory review policy could help them achieve lower inventory cost by reducing perished inventories. To apply new forecast method for PT. Bimandiri Agro Sedaya, researcher uses time series analysis to predict future demand. Time series analysis is related to the historical demand. The forecast method with lowest error will be chosen as new forecast method for the firm. Before applying new forecast method, researcher chooses inventory review policy between continuous and periodic review policy. The policy with the lowest inventory cost is chosen to be implemented in the future. Forecast result is useful to provide recommendation for the firm to apply the inventory review policy. The result of analysis sums up that periodic review policy has the lowest inventory cost. The policy just urges the firm to spend Rp,2,031,107,223 if they decided to use the policy in 2019. Number of perished inventories and order up to level are reduced, which lead to lower annual inventory cost. For new forecast method, Winter exponential smoothing has the lowest error from actual demand in 2019. The result of forecast is used for calculating inventory cost for first quarter in 2020. Researcher gives the recommendation to the firm, just to spend Rp.721,801,493. They should order to suppliers until inventory reaches its desired level, which is 2,213 kilograms. To conclude, the firm has successfully reduced inventory cost from existing inventory cost throughout 2019.