The Eastland Plaza Branch of the Indiana University Credit Union was having trouble getting the correct staffing levels: Business Analytics Assignment, UiTM, Malaysia

The Eastland Plaza Branch of the Indiana University Credit Union was having trouble getting the correct staffing levels to match customer arrival patterns. On some days, the number of tellers was too high relative to the customer traffic, so tellers were often idle. On other days, the opposite occurred. Long customer waiting lines formed because the relatively few tellers could not keep up with the number of customers.

The credit union manager, James Chilton, knew that there was a problem, but he had little of the quantitative training he believed would be necessary to find a better staffing solution. James figured that the problem could be broken down into three parts. First, he needed a reliable forecast of each day’s number of customer arrivals. Second, he needed to translate these forecasts into staffing levels that would make an adequate trade-off between teller idleness and customer waiting. Third, he needed to translate these staffing levels into individual teller work assignments—who should come to work and when.

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