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Performance Analysis Techniques and Metrics

Overview

You’ve just been promoted to be the performance engineering manager of the end user support organization for your company. Your company has employees working from home with laptop computers and some still in the office using laptop and desktop computers. End user requests come in around the clock, at various rates, and via calls, online requests, or walk-ins.

Requirements

Write a 3–5-page paper in which you:

· Describe a method you would use for each of the following:

To identify limits on system capacity and define service and interarrival time variability.
To create scheduling rules.
To perform what-if analysis.

· Discuss the types of metrics you would implement to optimize the performance of your organization from both a user experience and a resource utilization perspective.

· Explain how you would differentiate the objectives of your performance metrics between phone call, online, and walk-in requests.

· Describe whether service requests are queued up for your organization to form an open or closed queueing system, and fully justify why they follow this format.

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Sample Answer

Sure, I can help you with that. Here is a paper in which I describe the methods I would use to identify limits on system capacity and define service and interarrival time variability, create scheduling rules, perform what-if analysis, discuss the types of metrics I would implement to optimize the performance of my organization from both a user experience and a resource utilization perspective, explain how I would differentiate the objectives of my performance metrics between phone call, online, and walk-in requests, and describe whether service requests are queued up for my organization to form an open or closed queueing system, and fully justify why they follow this format.

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

The first step in performance engineering is to identify the limits on system capacity. This can be done by understanding the number of users, the types of requests they make, and the resources required to service those requests. For example, if my company has 100 employees, and each employee makes an average of 10 requests per day, then the system must be able to handle at least 1000 requests per day.

Full Answer Section

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 service a request. Interarrival time variability is the amount of time between requests. Variability can be caused by a number of factors, such as the complexity of the request, the skill of the support engineer, 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 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.

Performing What-If Analysis

What-if analysis is a technique that can be used to predict the impact of changes to the system. This can be helpful in identifying potential bottlenecks and ensuring that the system can handle future demand. For example, I could use what-if analysis to predict the impact of adding new employees, increasing the complexity of requests, or reducing the availability of resources.

Metrics for Performance Optimization

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 both user experience and resource utilization.

For user experience, some of the important metrics include:

Mean time to resolution (MTTR): The average time it takes to resolve a request.
First-time resolution (FTR): The percentage of requests that are resolved on the first attempt.
Customer satisfaction (CSAT): The percentage of customers who are satisfied with the support they receive.

For resource utilization, some of the important metrics include:

Utilization: The percentage of time that resources are being used.
Wait time: The average time that users wait for a support engineer to become available.
Overhead: The amount of time that is spent on non-productive activities, such as administrative tasks.

Differentiating Performance Metrics Between Phone Call, Online, and Walk-In Requests

The objectives of performance metrics can be different for phone call, online, and walk-in requests. For example, for phone call requests, the objective may be to minimize the wait time. For online requests, the objective may be to maximize the number of requests that can be processed per day. For walk-in requests, the objective may be to minimize the number of customers who have to wait in line.

Open vs. Closed Queueing System

Service requests for my organization would form an open queueing system. This is because new requests can arrive at any time, and requests can be completed at any time. An open queueing system is more complex than a closed queueing system, but it is more realistic for a real-world system.

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