The Use of Simulation with an Example: Simulation Modeling for Efficient Customer Service
This specific example may also be applicable to the more general problem of human and technical resource management, where companies naturally seek to lower the cost of underutilized resources, technical experts, or equipment, for example.
Finding the optimum number of staff to deliver a predefined quality of service to customers visiting a bank.
Firstly, for the bank, the level of service was defined as the average queue size. Relevant system measures were then selected to set the parameters of the simulation model - the number and frequency of customer arrivals, the time a teller takes to attend a customer, and the natural variations which can occur in all of these, in particular, lunch hour rushes and complex requests.
A flowchart corresponding to the structure and processes of the department was then created. Simulation models only need to consider those factors which impact the problem being analyzed. For example, the availability of office services for corporate accounts, or the credit department have no effect on those for individuals, because they are physically and functionally separate.
Finally, after feeding the model data, the simulation could be run and its operation seen over time, allowing refinement and analysis of the results. If the average queue size exceeded the specified limit, the number of available staff was increased and a new experiment was done. It is possible for this to happen automatically until an optimal solution is found.
Overall, multiple scenarios may be explored very quickly by varying parameters. They can be inspected and queried while in action and compared against each other. The results of the modeling and simulation, therefore, give confidence and clarity for analysts, engineers, and managers alike.
