Decision Support System
DSS for Inventory Management
About Project
Problem Definition
The problem can be mainly described as, lack of a decision support system which help merchandisers optimize the inventory level in the stores and in the main warehouse, while maximizing sales and profits. Nezih keeps too much inventory to meet uncertain demand and every transaction is done manually. The orders, coming from the local stores, need to be examined in the central office, before placing the final orders to the distributors. They do not have a proper system, which checks if the order is appropriate or not. All the controls of the orders coming from local stores are done one by one and manually. If necessary, order sizes are changed by the sales department. Store managers sometimes place orders without considering the outstanding orders in the system. There is no process to forecast upcoming sales and they may not meet the stores’ demand on time. Consequently, some of the commodities in stores are out of stock leading to lost sales or customers’ goodwill.
Scope of the Project
Our Objectives
As the main objective, we are aiming to develop a decision support system (DSS) by regarding the main constraint, to keep the service level at 99%. This DSS is expected to be implemented in a software solution, including a user-friendly interface supported by accurate forecasting and inventory models. In consequence of this DSS mainly regards 99% customer service level, we will also target to reduce inventory levels. The DSS will include forecast and inventory model approaches for both regular and seasonal products. In addition, we will regard other constraints of Nezih, such as supply chain lead time and minimum stock levels in the stores. Moreover, especially for the employees, we aim to provide reduction on planning workload. Automated DSS will prevent human based errors, which reduces both the efficiency of replenishment procedure and the service level. Finally, the use of mathematical models will provide a transparency of existing and future demand. In addition, planning workload, spent for replenishment time and quantity, will be reduced.
At the beginning, the system will be developed for the category of painting goods. After working on painting category, a system that fits to other segments and categories will be run. The painting category has 498 SKUs, whose sales and stock levels were provided by the company. It was decided that it would be more efficient to focus on rather than the whole product portfolio. The company will provide weekly data of the painting category for the last 3 years.