  We analyze call center data on properties such as agent heterogeneity,
customer patience and breaks. Then we compare simulation models that are
different in the ways these properties are modeled. We classify them according
to the extend in which they approach the actual service level and average
waiting times. We obtain a theoretical understanding on how to distinguish
between the model error and other aspects such as random noise. We conclude
that modeling explicitly breaks and agent heterogeneity is crucial for
obtaining a precise model.
