Analyze Your ITSM Ticket Data

Take a data-driven approach to service desk optimization.

EXECUTIVE BRIEF

Analyst Perspective

The perfect time to start analyzing your ticket data is now.

Benedict Chang

Advisory Director, Infrastructure & Operations
Info-Tech Research Group

Mahmoud Ramin PhD

Senior Research Analyst, Infrastructure & Operations
Info-Tech Research Group

Like with any practice, analyzing ITSM ticket data works best with a defined flow. For every valuable metric, you’re going to want to gather your data, meaning you need the right metrics matching ticket fields in your operational day to day. You’re going to want to extract and analyze your data in a systematic manner to extract insights.

Service desks improve their services by leveraging ticket data to inform their actions, but 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.

Of course, you’ll need to action the results of the ticket analysis, which can include celebrating successes when the dataset is looking good. If necessary, you can use the results to inform necessary larger changes to service desk strategy or process. And you’ll need to communicate the results to the right stakeholders, which can include anyone from end users to technicians to leadership.

Even though the examples provided in this blueprint are geared toward service desk metrics and metrics analysis, these principles are applicable to other service management practices as well.

Executive 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.

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%

36% of organizations are prioritizing ticket handling in IT

Source: SDI, 2021

12%

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.”

Source: Info-Tech survey, 2021; N=20

Common obstacles that prevent effective ticket analysis

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

Missing or Inaccurate Information

• Lack of information in the ticket
• Categories are too general/specific to draw insights
• Poor ticket hygiene

Missing Updates

• Tickets aren’t updated while being resolved

Correlating Tickets to Identify Trends

• Not sure where to start with all the data at hand

No Time

• No time to figure out the tool or analyze the data properly

Ineffective Categorization Schemes

• Reduces the power of ticket data

Tool Limitations

• Can’t be easily customized
• Too customized to be effective
• Desired dashboards unavailable

Source: Info-Tech survey, 2021; N=20

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

This blueprint’s key deliverable is a ticket analysis tool. Many of the activities throughout this blueprint will direct you to complete and interpret this tool.

ITSM Ticket Data Analysis Tool

Use this tool to identify trends and patterns in your ticket data to action improvement initiatives.

The other main deliverable is a stakeholder presentation template to help you document the outcomes of the project.

ITSM Ticket Data Analysis Report

Use this template to document the justification for addressing service desk improvement, the results of your analysis, and your next steps.

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

• Generate quicker resolutions to incidents and service requests.
• Ensure better expectations for the service desk and IT.
• Achieve better visibility into the current state, challenges, and goals of the service desk.
• Provide more effective support when contacting the service desk.

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

DIY Toolkit

"Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful."

Guided Implementation

"Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track."

Workshop

"We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place."

Consulting

"Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project."

Diagnostic and consistent frameworks are used throughout all four options.

Guided Implementation

What does a typical GI on this topic look like?

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.

Phase 1

Import Your Ticket Data

Phase 1

1.1 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

Analyze Your ITSM Ticket Data

1.1.1 Define your objectives for analyzing ticket data

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 for 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.

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 are 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.

ITSM Ticket Data Analysis Tool overview

The ITSM Ticket Data Analysis Tool will help you standardize your ticket data in a meaningful format that will allow you to apply common analyses to identify the actions you need to take to improve service desk operations.

TABS 1-3

INSTRUCTIONS & DATA ENTRY

Input at least three months of your exported ticket data into the corresponding columns in the tool to feed into the common analysis graphs in the other tabs.

TABS 4

TICKET SUMMARY DASHBOARDS

This tab contains multiple dashboards analyzing how tickets come in, who requests them, who resolves them, and how long it takes to resolve them.

TABS 5-7

INCIDENT, SERVICE REQUEST, CATEGORY, STATUS

These tabs each have dashboards outlining analysis on incidents and service requests. The category and status tabs will allow you to dive deeper on commonly reported issues and status reports.

TABS 8-11

TICKET DISTRIBUTION, STAFFING

These tabs each have dashboards outlining analysis on ticket arrival patterns and work breakdown to assess staffing requirements, which will help you allocate the right number of staff to tasks.