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PEER TO PEER: THE QUARTERLY MAGAZINE OF ILTA | FALL 2016
BEST PRACTICES
Service Desk Metrics: Best Practices for
Data Analysis and Reporting
Service Desk Metrics: Best Practices for Data Analysis and Reporting
It can sometimes take longer to log a service desk ticket than it does to resolve a customer issue. Why do we
spend so much time and effort logging tickets? What value do we get from storing years of data? How can we use data
analysis techniques to gain insight, streamline our processes and prevent future issues? The following best practices
will help you dive deeper into service desk metrics.
» We log service desk tickets to maintain visibility on recurring issues and frequent service requests. Analyzing
collected data allows IT to address customer issues and complete requests proactively, which improves service
delivery and increases customer satisfaction.
» Accurate ticket categorization and including the right amount of detail are essential for effective data mining.
Consider including the following ticket classification fields:
• Incident vs. service request
• Affected item, product or service
• Category of incident (not responding, slow, error message) or request (how to, access, install)
• Priority (low, medium, high)
by Peter Qumsiyeh
