Abstract
Many queueing systems with time-dependent arrivals require time-dependent staffing to provide satisfactory service levels at reasonable cost. Feldman et al. (Manag Sci 54(2):324–338, 2008) proposed an iterative staffing algorithm designed to deliver time-stable performance in which successive iterations were evaluated via simulation experiments. In this paper we present and evaluate an analytical queueing model combined with an iterative staffing algorithm to be used for setting staffing levels to achieve time-stable performance in call centre type queues. Empirical results show that the method to be considerably faster than simulation based methods and considerably more accurate than the industry standard analytical methods.
Highlights
In this paper we develop and evaluate analytical methods to determine appropriate staffing levels in call centres and in other multi-server queueing systems with time-dependent arrival rates
To investigate how the Geometric discrete time modelling (DTM)-based iterative staffing algorithm (ISA) algorithm (Geo-DTM+ISA) performs, we apply the algorithm to a range of realistic call centre test cases
For each of the test cases we first use Geo-DTM+ISA to recommend staffing levels, and perform multiple discrete event simulation runs of the system of interest with the recommended staffing to investigate whether the target service levels are achieved
Summary
In this paper we develop and evaluate analytical methods to determine appropriate staffing levels in call centres and in other multi-server queueing systems with time-dependent arrival rates. Green et al (2007) showed that PSA-based approaches produce good approximations when service times are short (e.g. 3 min on average) and the quality-of-service standard is high, e.g. 90 % of the calls are answered immediately. Under such circumstances there is less likely to be a queue, and steady state can be achieved faster
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