Inventory Optimization Based On Purchasing Planning: A Case Study Of Shopee Company

Abstract

The cycle of purchase order, inbound, storage and outbound products that meet customer demand is called inventory management, which is one of the key assets of the Shopee Ecommerce company. The aim of this study is to be found in the purchasing procedure, which consists of issues with customer service impacting on stock in the warehouse, and results in better purchase planning weekly by maximize the total expected profit. For this study, six months of business sales data were compiled, and different forecasting techniques were used to provide the most reliable forecasting performance of customer demand in weekly. Next, a mathematical model for inventory replenishment and purchase planning was developed to maximize the company's net profit. A Mixed-integer linear programming (MILP) model is proposed to achieve the primary objective of directly addressing non-stationary demand, arbitrary review periods, and SKU-specific lead times, while maximizing the net present value of the expected profit. The model was then solved by IBM CPLEX, giving the company an ideal weekly replenishment of the inventory, safety stock and purchase planning, resulting in a net profit greater than the current inventory method for the company. Additional research has shown that we have set up an optimized ordering strategy with order price where a service level of 99% is always maintained.