RETAIL SALES FORCE SCHEDULING BASED ON STORE TRAFFIC FORECASTING

Although retailers acknowledge the impact of sales force scheduling de cisions on store profits and customer service, current scheduling meth ods may fail to capture the sales potential of customers who enter the ir premises. These methods do not recognize the effect that the sales staff availability has upon the customer purchasing, thus leaving sign ificant opportunity for additional sales volume unrealized To resolve this problem, we propose a model which sets store sales potential as a function of store traffic volume, customer type, and customer respons e to sale force availability. We test our model for a profit minimizin g sales force schedule with data providing hourly data of store sales, store traffic and staff head count. The solution for this optimal sch edule indicates that the store may be seriously understaffed and that expanding the number of salespersons would both generate higher profit s and provide customers with better service. Our scheduling method als o provides a tool for identifying the time periods when service is mos t heavily demanded by customers.