Tickets aren’t updated while being resolved.Categories are too general/specific to draw insights.“I have no idea where to start with the amount of data I have.”Ĭommon obstacles that prevent effective ticket analysis We asked IT service desk managers and teams about their biggest hurdles Missing or Inaccurate Information.I have no time for ticket data analysis.” “My ITSM doesn’t have the capabilities I need to make informed decisions on shifting tickets left.”.“My technicians do not consistently update and close tickets.”.What your peers are saying about why they can’t start analyzing their ticket data: Shifting left to move tickets toward self-service is difficult when there is no visibility into which tickets should be shifted left.Comparisons may also be difficult if the data sets aren’t consistent. It’s difficult to aggregate data if the data is stored throughout various tools. ![]() Data, even if clean, can be housed in various tools and databases.Service desks end up either tracking too much data or not tracking the proper metrics. Not knowing where to start can lead to not analyzing the proper data. Finding time to properly analyze ticket data is a challenge.Your metrics should reflect those needs and expectations.ģ6% of organizations are prioritizing ticket handling in IT for 2021 (Source: SDI, 2021)ġ2% of organizations are focusing directly on service desk improvement (Source: SDI, 2021)Ĭommon obstacles Many organizations face these barriers to analyzing their ticket data: Different user groups will have different needs and different expectations of the level of service. You cannot improve the user experience without meaningful metrics that allow you to understand the user experience. Understanding – and improving – the user experience.The prerequisite to implementing proper SLAs is fully understanding the workload of the service desk. SLAs are meaningless if they are not met consistently. Showing the value of the service desk.Based on the metrics you’re analyzing, define ticket expectations and keep the data up to date. Collecting ticket data and keeping it clean.Your challenge This research is designed to help service desk managers analyze their ticket data Slow and steady improvement of the service desk only adds business value and will have a positive impact on customer satisfaction. Give yourself time to observe the new metrics and draw enough insights to make recommendations for improvement. Identify action items based on your ticket data.Īnalyze your ticket data to help continually improve your service desk.Start with common analyses using the cleaned data set.To reduce the noise, standardize your ticket data in a format that will ease analysis.Too many metrics are tracked to parse actionable insights from the noise. ![]() Service desk personnel are not sure where to start with analysis and are too busy to find time.Undocumented tickets from various intake channels prevents you from seeing the whole picture.Poor ticket hygiene and unclear ticket handling guidelines can lead to untrustworthy results.Properly analyzing ticket data is challenging for the following reasons: Communicate the current and future value of the service desk to the business.Gain efficiencies for your shift-left strategy.Design appropriate SLOs and SLAs to better service end users.Use a data-based approach to allocate service desk resources.Leverage your service desk ticket data to gain insights for improving your operations: Every month, you should be looking for patterns and trends. Every week, you should be evaluating how the past week went. Regularly analyze your data to drive improvements. ![]() You’re going to learn about the state of your environment, the health of your processes, and the quality of your services. Review the metrics regularly to stay on track.īy reviewing your ticket data, you’re going to get better organically. Track key tension metrics based on the out-of-the-box functionality in your tool. It’s tempting to wait for perfect data, but there’s a lot of value in analyzing your ticket data as it exists today. ![]() However, many organizations don’t know where to start. Service desks improve their services by leveraging ticket data to inform their actions. The perfect time to start analyzing your ticket data is now Research Director, Infrastructure & Operations Research Analyst, Infrastructure & Operations Step 3.2: Action and Communicate Your Ticket Data Step 3.1: Build Recommendations Based on Your Ticket Data Step 2.2: Analyze Incidents, Service Requests, and Ticket Categories Step 2.1: Analyze Your High-Level Ticket Data INFO-TECH RESEARCH GROUP Analyze Your Service Desk Ticket Data Take a data-driven approach to service desk optimization.
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