Empirical Study on Sales Forecasting– A Case Study of X Company

• Main Authors: Shen Chiu Yen, 沈秋延
• Other Authors: Singa Wang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/7dt5e7

碩士 === 朝陽科技大學 === 企業管理系 === 102 === Sales forecasting is an integral part of business management. It refers to the process of evaluating what the firm’s sales will be in the future. A good prediction of sales will help managers make better business decisions on inventory management, cash flow, resource allocations, and firm’s growth. Carton industry is an interesting industry in Taiwan. The industry’s sales are affected by a number of factors, such as seasonality, irregularity, trend, and cyclicality. Thus sales forecasting is especially important for manager’s decision making in this industry. Using sales data on four product categories of company X in the period 2010-2012, the present study empirically analyzes and conducts different sales forecasting models: simple moving average model, weighted moving average model, exponential smoothing model, least squares model, and trend adjusted for seasonal effects model. The results of this study show that carton sales are affected by seasonal effect and present a stable growth trend. The five sales forecasting models show a very similar forecasting result, but trend adjusted for seasonal effects method is the best model that can generate the most precise forecasting results for carton sales. The results of this study provide importance contributions to both academic research and business managers in making better sales forecasting decisions.