Cross-Staffing Problem

March 7th, 2012

Client: Carrollton Concentralogo_concentra1
Team: Daniel Olivares, Beverly Ross, Devin Kyles
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation

Concentra presented the problem of cross-staffing some of its employees throughout its centers. The problem addresses a potential decision of staffing methods of which the options were to staff to the market or create a cross-staffing model. These decisions relied upon the variability of patient visits among the centers and the ability to schedule based on future forecasted patient visits. Ultimately, the question was to find if there is an opportunity to staff across all centers or must it be dynamically adjusted based on forecasting by center. A solution to this problem would potentially decrease patient wait times and turnaround times (a patient’s check-in time to checkout time), idle times in which staff members are not performing any duties, and times in which centers experience a heavier traffic flow.

In analyzing the issue presented, many models were considered. The data provided covered a month’s pay period and the number of visit types in the month of January for fourteen Concentra centers in the Dallas/Ft. Worth area. Initially, trends were sought and developed by the data. We used a mapping tool to cluster centers that were close to each other in order to seek a potential relation between number of visits and geographical area. Then, we used a moving average to forecast number of visits and decided that although there is a strong potential that forecasting might be accurate enough to base scheduling of staff around it, the degree of variance of patient visits per day for each center within each cluster was too large at times.

We feel that in order to maintain customer satisfaction, a combination of using forecasting to schedule staff and a cross-center staffing method will be better suited. This would allow to staff in a more efficient manner but also be flexible enough to adjust to any unforeseen patient visit number.

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