Forecasting Model for Promotional Sales

Abstract

This thesis aims to study the relationship of factors which are expected to impact promotional sales and this will lead to develop a suitable forecasting model for each product category. The result of this research will improve the accuracy of forecasting sales so that the business can manage inventory level effectively. The case study of a retailer who sales variety of products through different type of branches. This study focuses on 4 product categories which are Pillow and Bolster, Bed set, Container and Storage and Hanger, covering March 2016 to February 2018. Multiple Linear Regression Analysis was applied in this research. The results show that there were different factors which impact promotional sales in each product category thus the business cannot consider the same factors to forecast all categories and, as the result, there were different forecasting model in each product group when it was sold in different store format. The models were applied in order to verify forecasting accuracy by comparing with traditional forecast. It turned out that applied models can reduce forecasting error which Hanger has the highest error reduction which accounted for 36.44% in average.