Retail sales force scheduling based on store traffic forecasting

Although retailers acknowledge the impact of sales force scheduling decisions on store profits and customer service, current scheduling methods may fail to capture the sales potential of customers who enter their premises. These methods do not recognize the effect that the sales staff availability has upon the customer purchasing, thus leaving significant 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 response to sale force availability. We test our model for a profit minimizing sales force schedule with data providing hourly data of store sales, store traffic and staff head count. The solution for this optimal schedule indicates that the store may be seriously understaffed and that expanding the number of salespersons would both generate higher profits and provide customers with better service. Our scheduling method also provides a tool for identifying the time periods when service is most heavily demanded by customers.