Enhancing Inventory Simulation Models for Retail

This study aims to propose an improvement to the simulation model of inventory management system in retail stores developed in the reference paper. This paper analyses the process flow of the original simulation model and also conducted an interview with a retail store owner. This study uses the customer arrival and customer demand distribution patterns and most of other parameter data from the reference paper. Both the original and the enhanced models are optimized for the lowest demand lost. Arena simulation software was used to perform the simulations for both models. The results of both models were then compared. When analysing the original model a design flaw was found. In the event where a customer come and demand a quantity that is more than the current inventory level, the original model will only report a stockout without reordering the product. If this event happened while there is no undelivered order to refill the stock, then all the following demand would go to the same route. Hence, from there on, no order will be fulfilled. In the interview, the store owner also shares about a part of the original model which is not a common practice, such as not offering the remaining stock to the customer who needs more than the current inventory level. The new simulation model was then developed. This study addresses critical design flaws in an inventory simulation model for retail stores. By leveraging insights from field interviews and utilizing Arena software, an enhanced model was developed, achieving a 26 % reduction in lost customers and a 35 % improvement in demand fulfilment. The findings provide actionable insights for optimizing inventory management systems in retail environments.