Stock Optimisation for an online business offering niche products

Abstract

ABC Company is a retail business that offers a wide range of niche products. The company is an online business and delivers its products to customers nationwide via a courier. The customers peruse the products on the company’s website and select the products that they wish to purchase, they then proceed to make an online payment and the products are delivered to them within four days. A key performance area for the company is inventory management because they pride themselves in having difficult to source products readily available. The purpose of this document is to define the problem that the company is currently experiencing and to develop a solution for the company. The solution is based on a literature review that was conducted on inventory management. The problem that the company is facing is that they do not have a formal stock process to manage their inventory. As a result, they have an oversupply of some products and an undersupply of other products. The oversupply of the items causes the company to have high carrying costs and the undersupply causes the company to order products frequently which leads to high ordering costs. In essence, not having a formal stock process has caused the company to have high inventory costs and frequent stock outs have led to unsatisfied customers. Two models (part A and part B) were formulated and built on MS Excel in order to solve the problem. Part A was the forecast model using multiple linear regression and part B was an inventory model using linear programming. The forecast model will predict the customer demand and will take into consideration the seasonality and trend that exists in the demand. The linear programming inventory model will take the demand and inventory costs as an input and will give as an output the size of the order and when to place the order.