Staffing Call Centers with Uncertain Arrival Rates and Co-sourcing
  In a call center, staffing decisions must be made before the call arrival rate is known with certainty. Then, once the arrival rate becomes known, the call center may be over-staffed, in which case staff are being paid to be idle, or under-staffed, in which case many callers hang-up in the face of long wait times. Firms that have chosen to keep their call center operations in-house can mitigate this problem by co-sourcing; that is, by sometimes outsourcing calls. Then, the required staffing $N$ depends on how the firm chooses which calls to outsource in real-time, after the arrival rate realizes and the call center operates as a $M/M/N+M$ queue with an outsourcing option. Our objective is to find a joint policy for staffing and call outsourcing that minimizes the long run average cost of this two-stage stochastic program when there is a linear staffing cost per unit time and linear costs associated with abandonments and outsourcing.   We propose a policy that uses a square-root safety staffing rule, and outsources calls in accordance with a threshold rule that characterizes when the system is "too crowded". Analytically, we establish that our proposed policy is asymptotically optimal, as the mean arrival rate becomes large, when the level of uncertainty in the arrival rate is of the same order as the inherent system fluctuations in the number of waiting customers for a known arrival rate. Through an extensive numerical study, we establish that our policy is extremely robust. In particular, our policy performs remarkably well over a wide range of parameters, and far beyond where it is proved to be asymptotically optimal. 
Yasar Levent Kocaga, Mor Armony and Amy R. Ward
math.PR math.OC