EXECUTIVE BRIEF

Analyst Perspective

Benedict Chang Research Analyst, Infrastructure & Operations Info-Tech Research Group

Ken Weston ITIL MP, PMP, Cert.APM, SMC Research Director, Infrastructure & Operations Info-Tech Research Group

The perfect time to start analyzing your ticket data is now

Service desks improve their services by leveraging ticket data to inform their actions. However, many organizations don’t know where to start. It’s tempting to wait for perfect data, but there’s a lot of value in analyzing your ticket data as it exists today.

Start small. Track key tension metrics based on the out-of-the-box functionality in your tool. Review the metrics regularly to stay on track.

By reviewing your ticket data, you’re going to get better organically. You’re going to learn about the state of your environment, the health of your processes, and the quality of your services. Regularly analyze your data to drive improvements.

Make ticket analysis a weekly habit. Every week, you should be evaluating how the past week went. Every month, you should be looking for patterns and trends.

Executive Summary

Your Situation

Leverage your service desk ticket data to gain insights for improving your operations:

1. Use a data-based approach to allocate service desk resources.
2. Design appropriate SLOs and SLAs to better service end users.
3. Gain efficiencies for your shift-left strategy.
4. Communicate the current and future value of the service desk to the business.

Common Obstacles

Properly analyzing ticket data is challenging for the following reasons:

• Poor ticket hygiene and unclear ticket handling guidelines can lead to untrustworthy results.
• Undocumented tickets from various intake channels prevents you from seeing the whole picture.
• Service desk personnel are not sure where to start with analysis and are too busy to find time.
• Too many metrics are tracked to parse actionable insights from the noise.

Info-Tech’s Approach

Info-Tech’s approach to improvement:

• To reduce the noise, standardize your ticket data in a format that will ease analysis.
• Start with common analyses using the cleaned data set.
• Identify action items based on your ticket data.

Analyze your ticket data to help continually improve your service desk.

Slow down. Give yourself time.

Give yourself time to observe the new metrics and draw enough insights to make recommendations for improvement. Then, execute on those recommendations. Slow and steady improvement of the service desk only adds business value and will have a positive impact on customer satisfaction.

Your challenge

This research is designed to help service desk managers analyze their ticket data

Analyzing ticket data involves:

• Collecting ticket data and keeping it clean. Based on the metrics you’re analyzing, define ticket expectations and keep the data up to date.
• Showing the value of the service desk. SLAs are meaningless if they are not met consistently. The prerequisite to implementing proper SLAs is fully understanding the workload of the service desk.
• Understanding – and improving – the user experience. You cannot improve the user experience without meaningful metrics that allow you to understand the user experience. Different user groups will have different needs and different expectations of the level of service. Your metrics should reflect those needs and expectations.

36% of organizations are prioritizing ticket handling in IT for 2021 (Source: SDI, 2021)

12% of organizations are focusing directly on service desk improvement (Source: SDI, 2021)

Common obstacles

Many organizations face these barriers to analyzing their ticket data:

• Finding time to properly analyze ticket data is a challenge. Not knowing where to start can lead to not analyzing the proper data. Service desks end up either tracking too much data or not tracking the proper metrics.
• Data, even if clean, can be housed in various tools and databases. It’s difficult to aggregate data if the data is stored throughout various tools. Comparisons may also be difficult if the data sets aren’t consistent.
• Shifting left to move tickets toward self-service is difficult when there is no visibility into which tickets should be shifted left.

What your peers are saying about why they can’t start analyzing their ticket data:

• “My technicians do not consistently update and close tickets.”
• “My ITSM doesn’t have the capabilities I need to make informed decisions on shifting tickets left.”
• “My tickets are always missing data”
• “I’m constantly firefighting. I have no time for ticket data analysis.”
• “I have no idea where to start with the amount of data I have.”

Common obstacles that prevent effective ticket analysis

We asked IT service desk managers and teams about their biggest hurdles

Info-Tech’s approach

Repeat this analysis every business cycle:

• Gather Your Data
  Collect your ticket data OR start measuring the right metrics.
• Extract & Analyze
  Organize and visualize your data to extract insights
• Action the Results
  Implement low-effort improvements and celebrate quick successes.
• Implement Larger Changes
  Reference your ticket data while implementing process, tooling, and other changes.
• Communicate the Results
  Use your data to show the value of your effort.

Measure the value of this blueprint

Track these metrics as you improve

Use the data to tell you which aspects of IT need to be shifted left and which need to be automated

Your data will show you where you can improve.

As you act on your data, you should see:

• Lower costs per ticket
• Decreased average time to resolve
• Increased end-user satisfaction
• Fewer tickets escalated beyond Tier 1

See Info-Tech’s blueprint Optimize the Service Desk With a Shift-Left Strategy.

Info-Tech’s methodology for analyzing service desk tickets

Insight summary

Slow down. Give yourself time.

Give yourself time to observe the new metrics and draw enough insights to make recommendations for improvement. Then, execute on those recommendations. Slow and steady improvement of the service desk only adds business value and will have a positive impact on customer satisfaction.

Iterate on what to track rather than trying to get it right the first time.

Tracking the right data in your ticket can be challenging if you don’t know what you’re looking for. Start with standardized fields and iterate on your data analysis to figure out your gaps and needs.

If you don’t know where to go, ticket data can point you in the right direction.

If you have service desk challenges, you will need to allocate time to process improvement. However, prioritizing your initiatives is easier if you have the ticket data to point you in the right direction.

Start with data from one business cycle.

Service desks don’t need three years’ worth of data. Focus on gathering data for one business cycle (e.g. three months). That will give you enough information to start generating value.

Let the data do the talking.

Leverage the data to drive organizational and process change in your organization by tracking meaningful metrics. Choose those metrics using business-aligned goals.

Paint the whole picture.

Single metrics in isolation, even if measured over time, may not tell the whole story. Make sure you design tension metrics where necessary to get a holistic view of your service desk.

Blueprint deliverables

Blueprint benefits

IT Benefits

• Discover and implement the proper metrics to improve your service desk
• Use a data-based approach to improve your customer service and operational goals
• Increase visibility with the business and other IT departments using a structured presentation

Business Benefits

• Quicker resolutions to incidents and service requests
• Better expectations for the service desk and IT
• Better visibility into the current state, challenges, and goals of the service desk
• More effective support when contacting the service desk

Info-Tech offers various levels of support to best suit your needs

Diagnostics and consistent frameworks used throughout all four options

Guided Implementation

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is 3-4 calls over the course of 2-3 months.

What does a typical GI on this topic look like?

Phase 1

• Call #1: Scope requirements, objectives, and your specific challenges. Enter your data into the tool.

Phase 2

• Call #2: Assess the current state across the different dashboards.

Phase 3

• Call #3: Identify improvements and insights to include in the communication report.
• Call #4: Review the service desk ticket analysis report.

PHASE 1

Import Your Ticket Data

This phase will walk you through the following activities:

• 1.1.1 Define your objectives for analyzing ticket data
• 1.1.2 Identify success metrics
• 1.1.3 Import your ticket data into the tool
• 1.1.4 Update your ticket fields for future analysis

This phase involves the following participants:

• Service Desk Manager
• ITSM Manager
• Service Desk Technician

1.1.1 Define your objectives for analyzing ticket data

Input: Understanding of current service desk process and ticket routing

Output: Defined objectives for the project

Materials: Whiteboard/flip charts, Ticket Analysis Report

Participants: Service Desk Staff, Service Desk Manager, IT Director, CIO

Use the discussion questions below as a guide

1. Identify your main objective for analyzing ticket data. Use these three sample objectives as a starting point:
   • Demonstrate value to the business by improving customer service.
   • Improve service desk operations.
   • Reduce the number of recurring incidents.
2. Answer the following questions as a group:
   • What challenges do you have getting accurate data for this objective?
   • What data is missing for supporting this objective?
   • What kind of issues must be solved for us to make progress on achieving this objective?
   • What decisions are held up from a lack of data?
   • How can better ticket data help us to more effectively manage our services and operations?

Document in the Ticket Analysis Report.

1.1.2 Identify success metrics

Select metrics that will track your progress on meeting the objective identified in Activity 1.1.1.

Input: Understanding of current service desk process and ticket routing

Output: Defined objectives for the project

Materials: Whiteboard/flip charts, Ticket Analysis Report

Participants: Service Desk Manager, IT Director, CIO

Use these sample metrics as a starting point:

Document in the Ticket Analysis Report.

Inefficient ticket-handling processes lead to SLA breaches and unplanned downtime

Analyze the ticket data to catch mismanaged or lost tickets that lead to unnecessary escalations and impact business profitability

• Ticket Category – Are your tickets categorized by type of asset? By service?
• Average Ticket Times – How long does it take to resolve or fulfill tickets?
• Ticket Priority – What is the impact and urgency of the ticket?
• SLA/OLA Violations – Did we meet our SLA objectives? If not, why?
• Ticket Channel – How was the issue reported or ticket received?
• Response and Fulfillment – Did we complete first contact resolution? How many times was it transferred?
• Associated Tasks and Tickets – Is this incident associated with any other tasks like change tickets or problem tickets?

Encourage proper ticket-handling procedures to enable data quality

Ensure everyone understands the expectations and the value created from having ticket data that follows these expectations

• Create and update tickets, but not at the expense of good customer service. Agents can start the ticket but shouldn’t spend five minutes creating the ticket when they should be troubleshooting the problem.
• Update the ticket when the issue is resolved or needs to be escalated. If agents are escalating, they should make sure all relevant information is passed along within the ticket to the next technician.
• Update user of ETA if issue cannot be resolved quickly.
• Ticket templates for common incidents can lead to fast creation, data input, and categorizations. Templates can reduce the time it takes to create tickets from two minutes to 30 seconds.
• Update categories to reflect the actual issue and resolution.
• Reference or link to the knowledgebase article as the documented steps taken to resolve the incident.
• Validate with the client that the incident is resolved; automate this process with ticket closure after a certain time.
• Close or resolve the ticket on time.

Info-Tech Insight

Ticket handling ensures clean handovers, whether it is to higher tiers or back to the customer. When filling the ticket out with information intended for another party, ensure the information is written for their benefit and from their point of view.