North Carolina based bank Wachovia recently appointed a manager for its Piedmont operations center. A. M. Davis is in charge of the largest statewide operations center, “Piedmont” that services 58 branches in 10 cities, with a primary responsibility to receive and process checks and other documents averaging $220 million a day (Bodily et al., 1998). The operation center is responsible for processing documents received from couriers throughout the day and expected to be processed in the same day. Due to increasing volume over the past two years, from 38.
01 million to 42.975 million, scheduling of workers has become challenging for the center.
The uneven nature of the work volume, management utilizes additional part time staff to cover peak loads. The current staffing stands at 14 full time and 22 part-time proof operators. Each operator processes at least 1000 items per hour. The challenge for Mr. Davis is to determine how many part-time hours to schedule for the upcoming week. To do this, Mr. Davis must develop a forecast of the number of documents to be processed based on historical data, and then he must take into account the costs of under/overscheduling hours.
In order to make an effective decision, Mr. Davis has two alternatives to determine how many part-time hours to be scheduled for the upcoming week. To do this, he should develop a forecast and model of the number of checks to be processed based on historical data, and then he must take into account the costs of under/overscheduling hours. Another alternative is to utilize previous data provided by his predecessor and utilizing the experience of the past managers.
Among these alternatives, the long run average method can be considered as the best possible option because this alternative provides with years of experience and represents the weekly volume. Looking at the prior week’s volume method does not provide an accurate forecast for future volume despite having current data.
Reference
Bodily, S., Carraway, R., Frey, Jr, S., & Pfeifer, P. Quantitative Business Analysis: Text and Cases. 1988. Boston: McGraw Hill Custom Publishing.
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