A model relevant to a scenario is designed by bringing empirical data pertaining to that scenario. It is necessary for the data to be of a nature that allows the generation and observation of the data to be repeated. If the model is found to be inconsistent with the data, it is mandatory that the model is either redesigned or modified.
The manner adopted to design the model and the approach that is given to the foundation of the model is more than often reliant upon the requirements of the end user. However, when analyzing a model, it is necessary to understand that every model has a number of assumptions that justify the validity of that model. Modeling can be used and is brought into use in almost all developed areas of daily life. An example can be found in the US Postal Service that exercises numerous models to ensure efficiency in its operational framework. One of the most frequently used of these models is the Transportation Model the US Postal Service uses in order to reduce transportation costs (ILOG, 2008). This model has been generated by combining a number of networks together and has been made possible by collaboration between USPS and IBM.