Demand Forecasting And Inventory Control Based On Sales Data Of LT Company

With the rapid development of China, the people’s income level gradually hasincreased. There is a fast and good period for the Chinese food industry. However, theChinese food industry is also faced with more severe external environment and thedeteriorating internal development bottlenecks. It will show a long-term upward trend inthe various tangible and intangible costs. The approaches to improve the performancemanagement and optimize operation ability to reduce costs must be handled by eachrestaurant company.In this thesis, we used the quantitative method to analyze annual sales data of arestaurant company. Firstly, by classifying and adding up the sales data, we obtain the dataset with different fluctuation levels. We analyze product characteristics of the data anddivide all the raw materials into short shelf life raw materials, middle shelf life rawmaterials and long shelf life raw materials. Then, we count each class of raw materialsdaily demand data. Secondly, we focus study of materials demand data features and drawall kinds of raw materials time sequence diagram for the forecasting of demand. We useHolt exponential smoothing to get the raw materials forecasting model. Then, we usedhypothesis testing to test the forecasting model. Thirdly, the ABC inventory managementis used to optimize the company inventories. We give the safety stock and themaximum-minimum inventory management model for each class of stock goods. In thenumerical analysis section, we use the cigarette forecasting model passed the test topredict the next seven days demand, and we get the safety stock and minimum-maximuminventory. At last, we conducted a case study for LT Company. The reasons of demandsare analyzed and some reasonable proposals are put forward to enhance the corporate’operations management.