|Title:||A sales forecasting system in marketing information system for a trading company|
|Subject:||Sales forecasting -- Data processing|
Marketing -- Management -- Data processing
Management information systems
Hong Kong Polytechnic University -- Dissertations
|Pages:||v, 78, : ill. ; 31 cm|
|Abstract:||Marketing Information System (MIS) is getting more popular in today's business organisations due to the rapid growth of information technology (IT). MIS can help management to make decisions in many different areas. However, there is not much literature placing emphasize on the interaction between sales forecasting and inventory management using IT. This paper describes how a sales forecasting system helps to make decision on purchasing goods. A trading company which sells about 100 different battery types is chosen for this study. The trading company currently is adopting an order driven approach in the purchase of goods. That means Purchasing Department will first gather customers' orders and later place purchase orders to its vendors. Such approach will lead to inflexibility in satisfying customers' orders immediately. It is an industry practice for many battery trading companies to keep a high level of inventories because of the long lead time of delivery required and making commitment to the delivery date requested by customer even though goods are received earlier than expected. Hence, a sales forecasting system is introduced to forecast monthly demand of various battery types by using ARIMA (Autoregressive Integrated Moving Average) model. In this research, six typical battery types are selected as illustrations. In order to help management to make purchasing decisions by using demand forecast, three replenishment strategies are compared to find out which one will lead to lowest inventory level with certain service level. They are Fixed Order Cycle (FOC), Fixed Order Quantity (FOQ) and Mix of FOC and FOQ with 10%, 20%, 30% safety margin (Minimax). Result of this research shows that Minimax will lead to the lowest inventory level with nearly 100% service level. Moreover, it will lead to 20%-70% savings on inventory for those six battery types by adopting this strategy. Therefore, an automatic sales forecasting system with suitable replenishment strategy will help management to make decision in purchasing and lower the inventory level to save cost. This methodology can then be extended to all other battery types to form a complete sales forecasting and replenishment system. Moreover, other similar industry can also make use of this methodology to help them to manage their inventory, especially for those holding thousands of different items. It is because only an automatic sales forecasting and replenishment system can help management to save time in inventory management.|
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