OPTIMIZING INVENTORY MANAGEMENT OF PT SAM ADI KARYA BY DEMAND FORECASTING AND INVENTORY POLICY

• Main Author: Ashidiqi, Zimmy
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/49429
• Institution: Institut Teknologi Bandung

Managing inventory is one of the most important aspect to every business that movement of their goods is being the major activities of their business operational. An appropriate inventory management will lead the company to have optimized operational cost. It could be implemented by conducting demand forecasting to predict future demand and designing the most efficient inventory policy in order to know the amount of stock that is safe and know the time to order material. Firms routinely forecast sales to help guide management decisions in inventory management. By combining forecast, will reduce the cost of over-stocks and minimize the frequency of out-of-stocks. PT Sam Adi Karya (SAK) is one of the company that rely the movement of their product as the basis of the business operation. PT SAK is operating as a chemical distributor, especially chemicals for water treatment such as Poly Aluminium Chloride (PAC), Sodium Hypochlorite, Industrial Salt, Soda Ash Dense, Ferric Chloride, Hydrochloric Acid (HCl), which has a base in Sidoarjo, East Java. PT SAK faces a problem in managing their inventory. The management recognizes that there is no organized forecast and inventory management system for their products, causing operational costs to swell. The management state that the company only using subjective estimation for predicting the future demand. But, the company wants to fulfil all demand from customer to avoid customer disappointment. Therefore, the company will insist to keep their stocks is safe and this decision leads the company to overstock. This overstock condition generates additional costs to the company. The company should bear the cost to place an order to the supplier of the company and do treatment for the products stored in the inventory. Therefore, it results consequences that the company should pay the higher operational cost. The purposes of this research are to determine the root cause of the problem and propose the most efficient inventory policy to minimize PT SAK operational cost. The methods that used in this research are Time Series Forecasting, Probabilistic Model, Economic Order Quantity, and Simulated using Material Requirement Planning (MRP) to find out when is the best time to place an order. This research generates the most appropriate inventory policy that could be applied by PT SAK to minimize their operational cost. The result of this research showed that Probabilistic Model and Economic Order Quantity with Averaged Weekly Demand MRP Simulation deliver the most efficient inventory policy. Probabilistic Model resulted Reorder Point and Safety Stock while Economic Order Quantity with Averaged Weekly Demand MRP Simulation resulted the amount that should be ordered and when the product should be ordered. Thus, Demand Forecasting, which the Winter’s model provide the most accurate forecasts compared to other method and Implementation of the proposed inventory policy conducted to give guidance for PT SAK to operate their business in Jan – Apr 2020. Therefore, PT SAK should implement Winter’s Forecasting Method to predict the future demand and Probabilistic Model and Economic Order Quantity with Averaged Weekly Demand MRP Simulation in managing the inventory to give the lowest cost for the company. Keywords : Chemical, Demand Forecasting, Inventory Policy, Probabilistic Model, Economic Order Quantity, Material Requirement Planning, Overstock