Rockwell Automation Arena Contact Center Edition Users Guide - Manual (Page 18)

A RENA C ONTACT C ENTER E DITION U SER ’ S G UIDE
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Insight can be gained about which variables are most important to performance and
how these variables interact.
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A simulation study can prove invaluable to understanding how the system really
operates as opposed to how everyone thinks it operates.
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New situations, about which we have limited knowledge and experience, can be
manipulated in order to prepare for theoretical future events. Simulation’s great
strength lies in its ability to let us explore “what if” questions.
The simulation process
The essence or purpose of simulation modeling is to help the ultimate decision maker
solve a problem. Therefore, to learn to be a good simulation modeler, you must merge
good problem-solving techniques with good software engineering practice. The following
steps should be taken in every simulation study.
1. Problem Definition. Defining the goals of the study clearly so that we know the
purpose; i.e., why are we studying this problem and what questions do we hope to
answer? What is the business impact of these answers?
2. Project Planning. Being sure that we have sufficient personnel, management support,
computer hardware, and software resources to do the job with a relevant timetable.
3. System Definition. Determining the boundaries and restrictions to be used in defining
the system (or process) and investigating how the system works.
4. Conceptual Model Formulation. Developing a preliminary model either graphically
(e.g., block diagrams) or in pseudo-code to define the components, descriptive vari-
ables, and interactions (logic) that constitute the system.
5. Preliminary Experimental Design. Selecting the measures of effectiveness to be
used, the factors to be varied, and the levels of those factors to be investigated; i.e.,
what data need to be gathered from the model, in what form, and to what extent.
6. Input Data Preparation. Identifying and collecting the input data needed by the
model.
7. Model Translation. Formulating the model in an appropriate simulation language or
software package such as Arena Contact Center Edition.
8. Verification and Validation. Confirming that the model operates the way the analyst
intended (debugging) and that the output of the model is believable and representative
of the output of the real system.