Rockwell Automation Arena Contact Center Edition Users Guide - Manual (Page 17)

2 • I NTRODUCTION TO S IMULATION
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chosen to achieve a specific purpose. The model developed should be as simple as the
stated purpose will allow.
The types of simulations of interest here are those used to develop an understanding of the
performance of a system over time. We typically use simulation models to help us
explain, understand, or improve a system. To be effective, simulation must concentrate on
some previously defined problem (otherwise, we do not know what elements to include in
the model or what information to generate and collect). We typically use models to predict
and compare—that is, to provide a logical way of forecasting the outcomes that follow
alternative actions or decisions and (we hope) to indicate a preference among them.
Although this use of models is important, it is by no means its only purpose. Model build-
ing also provides a systematic, explicit, and efficient way to focus judgment and intuition.
Furthermore, by introducing a precise framework, a simulation model can effectively
communicate system configuration and assist the thought process.
Advantages of simulation
Because its basic concept is easy to comprehend, a simulation model is often easier to
justify to management or customers than some of the analytical models. In addition,
simulation might have more credibility because its behavior has been compared to that of
the real system or because it has required fewer simplifying assumptions and thereby has
captured more of the true characteristics of the real system.
Virtually all simulation models are so-called input-output models; that is, they yield the
output of the system for a given input. Simulation models are therefore “run” rather than
“solved.” They cannot generate an optimal solution on their own as analytical models can;
they can only serve as tools for the analysis of system behavior under specified condi-
tions. (The exception is a simulation model used to find the optimum values for a set of
control variables under a given set of inputs.)
We have defined simulation as experimentation with a model of the real system. An
experimental problem arises when a need develops for specific system information that
isn’t available from known sources. The following list describes some of the benefits
associated with simulation.
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In a contact center, the impact of new types of contacts, new agent schedules, modi-
fied contact priorities, contact volumes, and other key inputs can be explored without
disrupting ongoing operations.
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New routing scripts or transfer logic can be tested before committing resources to
implementation.
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Hypotheses about how or why certain phenomena occur can be tested for feasibility.
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Time can be controlled: it can be compressed, expanded, etc., allowing us to speed up
or slow down a phenomenon for study.