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TexasCase Study: Staffing a Call Center

Arizona Children’s Hospital has been receiving numerous customer complaints because of its

confusing, decentralized appointment and registrati on process. When customers want to make

appointments or register child patients, they must contact the clinic or department they plan to visit.

Several problems exist with this current strategy. Parents do not always know the most appropriate cl inic

or department they must visit to address their chil dren’s ailments. They therefore spend a significant

amount of time on the phone being transferred from clinic to clinic until they reach the most appropriate

clinic for their needs. The hospital also does not publish the phone numbers of all clinics and depar tments,

and parents must therefore invest a large amount of time in detective work to track down the correct

phone number. Finally, the various clinics and dep artments do not communicate with each other. For

example, when a doctor schedules a referral with a colleague located in another department or clinic, that

department or clinic almost never receives word of the referral. The parent must contact the correct

department or clinic and provide the needed referra l information.

In efforts to reengineer and improve its appointmen t and registration process, the children’s

hospital has decided to centralize the process by e stablishing one call centered devoted exclusively to

appointments and registration. The hospital is cur rently in the middle of the planning stages for the call

center. Harry Sullivan, the hospital manager, plan s to operate the call center from 7 A.M. to 9 P.M. during

the weekdays.

Several months ago, the hospital hired an ambitious management consulting firm, Unexpected

Results International, to forecast the number of ca lls the call center would receive each hour of the day.

Since all appointment and registration-related call s would be received by the call center, the consult ants

decided that they could forecast the calls at the c all center by totaling the number of appointment an d

registration-related calls received by all clinics and departments. The team members visited all the clinics

and departments, where they diligently recorded eve ry call relating to appointments and registration.

They then totaled these calls and altered the total s to account for calls missed during data collection. They

also altered totals to account for repeat calls tha t occurred when the same parent called the hospital

many times because of the confusion surrounding the decentralized process. Unexpected Results

International determined the average number of call s the call center should expect during each hour of a

weekday. The following table provides the forecast s.

Work Shift Average Number of Calls

7 A.M. – 9 A.M. 25 calls per hour

9 A.M. – 11 A.M. 75 calls per hour

11 A.M. – 1 P.M. 45 calls per hour

1 P.M. – 3 P.M. 100 calls per hour

3 P.M. – 5 P.M. 80 calls per hour

5 P.M. – 7 P.M. 15 calls per hour

7 P.M. – 9 P.M. 12 calls per hour After the consultants submitted these forecasts, Ha rry became interested in the percentage of

calls from Spanish speakers since the hospital serv ices many Spanish patients. Harry knows that he ha s

to hire some operators who speak Spanish to handle these calls. The consultants performed further data

collection and determined that on average, 20 perce nt of the calls were from Spanish speakers.

Given these call forecasts, Harry must now decide h ow to staff the call center during each 2 hour

shift of a weekday. During the forecasting project , Unexpected Results International observed the

operators working at the individual clinics and dep artments and determined the number of calls operato rs

process per hour. The consultants informed Harry t hat an operator is able to process an average of six

calls per hour. Harry also knows that he has both full-time and part-time workers available to staff the

call center. A full-time employee works 8 hours pe r day, but because of paperwork that must also be

completed, the employee spends only 4 hours per day on the phone. To balance the schedule, the

employee alternates the 2-hour shifts between answe ring phones and completing paperwork. Full-time

employees can start their day either by answering p hones or by completing paperwork on their first shift.

The full-time employees speak either Spanish or Eng lish, but none of them are bilingual. Both Spanish-

speaking and English-speaking employees are paid $8 .50 per hour for work before 5 P.M. and $10 per

hour for work after 5 P.M. The full-time employees can begin work at the beginning of the 7. A.M. to 9

A.M. shift, 9 A.M. to 11 A.M. shift, 11 A.M. to 1 P .M. shift, or 1 P.M. to 3 P.M. shift. The part-time

employees work for 4 hours, only answer calls, and only speak English. They can start work at the

beginning of the 3 P.M. to 5 P.M. shift or the 5 P. M. to 7 P.M. shift, and like the full-time employee s, they

are paid $8 per hour for work before 5 P.M. and $9. 50 per hour for work after 5 P.M.

Harry needs to determine how many full-time employe es who speak Spanish, full-time employees

who speak English, and part time employees he shoul d hire to begin on each shift. Unexpected Results

International advise him that linear programming ca n be used to do this in such a way as to minimize

operations costs while answering all calls. Formul ate a linear programming model of this problem.