The Eastland Plaza Branch of the Indiana University Credit Union was struggling to optimize staffing levels to match customer arrival patterns effectively. Some days saw an excess of tellers relative to customer traffic, resulting in idle staff, while on other days, the limited number of tellers led to long waiting lines as they struggled to keep up with customer demand.

The credit union manager, James Chilton, acknowledged the issue but lacked the quantitative skills he believed were necessary to devise a more efficient staffing solution. James identified three key components to solving the problem. First, he needed a reliable forecast of daily customer arrivals. Second, he required a method to translate these forecasts into appropriate staffing levels that balanced teller availability with customer waiting times. Lastly, he needed a strategy to assign specific work schedules to individual tellers based on these staffing levels.