This paper proposes practical modeling and analysis methods to facilitate dynamic stang in a telephone call center with
the objective of immediately answering all calls. Because of this goal, it is natural to use innite-server queueing models.
These models are very useful because they are so tractable. A key to the dynamic stang is exploiting detailed knowledge
of system state in order to obtain good estimates of the mean and variance of the demand in the near future. The near-term
stang needs, e.g., for the next minute or the next 20 min., can often be predicted by exploiting information about recent
demand and current calls in progress, as well as historical data. The remaining holding times of calls in progress can be
predicted by classifying and keeping track of call types, by measuring holding-time distributions and by taking account of
the elapsed holding times of calls in progress. The number of new calls in service can be predicted by exploiting information
about both historical and recent demand.