Evaluation Of Extendsim

ExtendSim can be a great tool for a wide variety of companies and their decision makers. We used the software to create a model to provide information about employee utilization and average customer wait times that can be used by bank managers and human resources. Bank managers and HR can use the information provided by the model to find a combination of employees that improves their efficiency while also cutting down customer wait times, and overall improves the efficiency of bank operations.
In our first simulation we used a combination of 4 tellers, 2 loan agents, and 2 customer service representatives. Two key statistics we were evaluating during the simulation were utilization and average wait time. Utilization is simply how often an employee is working during their shift, with 1 being the highest possible outcome and being equivalent to working 100% of the time. The average wait time is the average number of minutes a customer waits in line before being served.
With 4 tellers the utilization for that section of the bank was .682 and the average wait was .726. In my opinion both of these numbers are low. When an employee is on the clock they should really only have about 10% down time, and in this scenario each of the tellers spent about 32% of their time doing nothing. Customers had to wait less than a minute to be served, which is great, but if a person walks into a bank I think they’d still be satisfied with a longer wait.
Two loan agents had a utilization of .726 and an average wait of 6.646 minutes. Once again the employees had too much down time, and the company is in a sense throwing money away. The loan process is also something that takes time, and I don’t customers expect a trip to bank to acquire a loan to be a quick “in and out” process. A longer wait time would be perfectly acceptable.
We also used 2 customer service representatives in this scenario, and they were utilized 33.2% percent of the time and customers waited for about 30 seconds before being served. The employees were basically doing nothing the entire day, and this utilization rate is by far the worst number in entire scenario. The average wait time of 30 seconds is great, but a longer wait would be perfectly acceptable.
In conclusion, this scenario of 4 tellers, 2 loan agents, and 2 customer service representatives failed in every aspect. Employees in all 3 sections were underutilized, and customers could have been served at a slower pace and still been happy.

Figure 1, Simulation 1

In the second simulation that we performed we used a combination of 1 teller, 1 loan agent, and 1 customer service representative. The teller in this situation had a utilization rate of 100% and customers had an average wait time of 28.33 minutes. A utilization rate of 100% would never work because nobody can work 100% of the time without taking breaks. Not only would they need to do it to do things like use the restroom, but employees have a legal right for a break. On top of this, the bank won’t have very many customers if they have to wait 28 minutes for a teller.
The loan agent in this simulation had a utilization rate of 92.3% and customers waited about 20 minutes. Working 92% of the time isn’t a bad number, although I’d personally like to give a person around 10% of downtime. One could argue that this is wasting money, but in the big picture the break allows employees to improve their quality of work. Waiting 20 minutes for a loan agent could be decreased by a little bit, but I think anyone applying for a loan knows that it’s not a quick process.
The customer service representative in this situation was utilized 42.7% of the time and customers waited 2.821 minutes in line. 2.81 minutes in line is a great number, but an employee who works less than half of the time is a waste of money. You can’t have less than 1 employee in the customer service section so obviously not much can be changed in that aspect.
The second

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