Financial Assessment on Designing Inventory Policy by Considering Demand, Lead Time, and Defective Product Uncertainties: A Monte Carlo Simulation

Inventory is one of the main components in supply chain. However, it is not easy to design inventory policy under uncertainties. The frequent occurrence of overstocks increases the company's financial expenditure. Otherwise, stockout decreases customer satisfaction and damage the company's image. This study aims to provide monte carlo model to design inventory policy with the aim of maximizing net income with a variety of uncertainties, one of the uncertainties is defective product because of the travel from suppliers. To handle the complexity and uncertainty of problem, a Monte Carlo simulation is used with spreadsheet-based representation. To test the reliability of the model, guitar company is used as relevant use case with uncertainty adhered ‘the greater number of order quantity, the greater likely the defective guitar will be’. The verification & validation process, experimental design, and alternative selection are also done with statistical tests. Based on the simulation result, it is known that changing the reorder point to 80 and the order quantity to 90 gives the best result which can increase net income by 0.44% compared to the initial net income. In addition, the number of stockouts has decreased.