Full Answer Section

Identifying Limits on System Capacity and Defining Service and Interarrival Time Variability

The first step in optimizing the performance of an end user support organization is to identify the limits on system capacity. This includes identifying the number of support engineers available, the amount of time they have available to work on requests, and the resources they need to complete requests.

Once the limits on system capacity have been identified, the next step is to define the variability of service and interarrival times. Service time variability is the amount of time it takes to complete a request. Interarrival time variability is the amount of time between when requests are received.

The variability of service and interarrival times can be influenced by a number of factors, such as the complexity of the requests, the skill level of the support engineers, and the availability of resources.

Creating Scheduling Rules

Once the limits on system capacity and the variability of service and interarrival times have been defined, the next step is to create scheduling rules. Scheduling rules are used to determine how requests are assigned to support engineers.

There are a number of different scheduling rules that can be used, such as first-come, first-served, shortest job first, and priority-based scheduling. The best scheduling rule to use will depend on the specific needs of the organization.

Performing What-If Analysis

What-if analysis is a technique that can be used to evaluate the impact of changes to the system. This can be helpful for identifying potential bottlenecks and for optimizing the system for different scenarios.

For example, what-if analysis could be used to determine the impact of increasing the number of support engineers, decreasing the amount of time they have available to work on requests, or changing the scheduling rules.

Metrics for Optimizing Performance

There are a number of different metrics that can be used to optimize the performance of an end user support organization. These metrics can be used to measure the performance of the organization from both a user experience and a resource utilization perspective.

Some of the most important metrics include:

• Average wait time: The average amount of time it takes for a request to be completed.
• Number of requests in queue: The number of requests that are waiting to be completed.
• Number of requests abandoned: The number of requests that are not completed.
• Resource utilization: The percentage of time that support engineers are spending working on requests.

Differentiating Objectives of Performance Metrics

The objectives of performance metrics can be differentiated between phone call, online, and walk-in requests. For example, the objective for phone call requests may be to minimize the average wait time, while the objective for online requests may be to maximize the number of requests that can be completed per hour.

The objectives of performance metrics can also be differentiated based on the specific needs of the organization. For example, an organization that is trying to improve customer satisfaction may focus on metrics such as the number of requests abandoned or the number of requests that are not completed.

Open or Closed Queueing System

Service requests can be queued up for an end user support organization to form an open or closed queueing system. An open queueing system is one in which requests can enter and leave the queue at any time. A closed queueing system is one in which requests can only enter the queue at a specific time and can only leave the queue when they are completed.

The type of queueing system that is used will depend on the specific needs of the organization. For example, an organization that needs to be able to handle a large number of requests may use an open queueing system. An organization that needs to be able to guarantee that requests are completed within a certain amount of time may use a closed queueing system.

In my opinion, the service requests for my organization would form an open queueing system. This is because I want to be able to handle a large number of requests and I do not want to restrict the number of requests that can enter the queue.

I believe that this is the best option for my organization because it will allow me to provide the best possible service to my users.