What the service desk sees is only part of the employee’s interruption. The rest often happens before the ticket is opened.
A closer look at why ticket data can be accurate and still miss the full business impact.
THE HIDDEN 40 MINUTES
IT resolves the issue in 11 minutes. The employee has already spent 40 minutes trying to get there. The dashboard shows 11. The business experiences 51.
The ticket marks the response, not the interruption
Imagine it’s Tuesday morning. An employee opens their laptop and finds they can’t get into a critical application.
They restart the device. No luck. They check their connection, try signing in again, and ask a colleague whether they’re seeing the same thing. Next, they search the support portal, work through a few suggested fixes, and finally submit a ticket.
Forty minutes have passed before IT sees anything.
The support team diagnoses the issue and restores access in 11 minutes. From an IT service perspective, that’s a strong result. The ticket was handled quickly, the SLA was met, and the employee is back online.
But the business didn’t lose 11 minutes. It lost 51.
“The dashboard isn’t wrong. It simply starts counting too late.“
Most traditional service metrics begin when a ticket or incident record is created. Response time, resolution time, first-contact resolution, and SLA attainment all measure what happens after the employee reports a problem.
These metrics are useful. They show whether the support team is responsive and whether issues are resolved efficiently. But they don’t capture everything the employee went through before asking for help.
“In practice, the employee becomes the organization’s first monitoring system.“
They detect the issue, test possible fixes, decide whether it’s serious enough to report, and then figure out where to go for support.
Only after that does the clock start.
That gap matters because employees don’t experience an interruption as a ticket. They experience it as lost time, broken concentration, and work that isn’t getting done. If the same issue happens repeatedly or affects a customer-facing role, the impacts spreads well beyond the person who opened the ticket.
A fast response is still valuable. It just doesn’t tell you how much of the interruption happened before IT could see it.
The delays hiding outside the ticket
The time between an interruption beginning and IT starting work usually includes three types of delay.
1. The reporting delay
Most employees don’t open a ticket the moment something goes wrong. They try to solve the problem themselves first.
Sometimes that’s a quick restart. Other times, it becomes a string of attempts involving passwords, settings, online searches, and questions to coworkers. Each step feels reasonable on its own, but the minutes add up.
This delay is rarely visible in service reporting because it happens before the incident exists in the system. Yet it may represent the largest share of the employee’s lost time.
2. The navigation delay
Employees don’t always know who owns the issue.
A login problem may look like IT and actually involve HR access permissions. A workplace application may depend on facilities, security, or another business team. The employee submits a request, gets redirected, provides the same information again, and waits while ownership is sorted out.
Each team may hit its own service target. From the employee’s perspective, however, there’s only one problem and it still isn’t fixed.
When service data sits in departmental silos, the organization misses the full journey. Every individual handoff looks acceptable while the overall experience remains slow and frustrating.
3. The workaround delay
Some employees never open a ticket at all.
They find another way to get the work done, using a personal device, asking a colleague to complete a task, saving information outside the approved system, or avoiding the process entirely.
That makes ticket volumes look better, but the interruption hasn’t disappeared. It’s moved outside the support record.
Workarounds carry their own risks. Data ends up in the wrong place, controls get bypassed, and inefficient habits become part of the normal workflow. Because no ticket was submitted, none of this appears on the service dashboard.
What this changes for the CIO’s scorecard
“Green SLAs are good news. They show that IT responds effectively once an issue reaches the team. They don’t mean employees are experiencing fewer interruptions.“
A more complete scorecard should show what happens before, during, and after the ticket. That means looking beyond service speed to understand:
- How often the same issue returns for an employee, device, application, or location
- How much effort employees spend trying to get help
- How often requests involving several teams get completed without the employee routing the work
- Which interruptions could have been detected and resolved before anyone noticed
- How much employee time prevention protected, and what that time is worth to the business
That last measure is the one most scorecards are missing, and it’s the one that travels outside IT. Prevention that can’t be expressed as recovered capacity stays an IT story.
With that said, none of this requires abandoning existing measures. Response time, resolution time, and SLA performance still play an important role. The goal is to put them in the right context.
For example, an 11-minute resolution looks excellent on its own. When paired with 40 minutes of unrecorded employee effort, it tells a different story. The support team performed well, but the organization still had an opportunity to detect the issue sooner, simplify the support path, or prevent the interruption from happening at all.
That’s where the conversation becomes more useful. Instead of asking only how quickly the ticket closed, IT leaders can ask:
- When did the employee first lose the ability to work?
- What happened before the ticket was created?
- Could we have identified the condition earlier?
- Did we fix the cause or only restore access?
These questions give CIOs a clearer view of the employee experience and the true business impact of an interruption. They also shift the focus from handling demand efficiently to reducing how much avoidable demand enters the system in the first place.
Start the clock when the interruption begins
The ticket tells you when the support process started. It doesn’t tell you when the employee’s problem began.
That distinction is easy to overlook when service dashboards are green and SLAs are being met. But if employees are still losing time before they receive help, the organization is measuring only part of the experience and calling it the whole thing.
Measuring the full interruption is where this starts. It isn’t where it ends. Once you can see the time an interruption costs, you can begin asking which of those issues the system should have caught on its own, and you can prove it when it does.
At your next service review, look beyond when the ticket was opened. Ask when the interruption began, what the employee had to do before IT could see it and whether the issue could have been prevented.
The answers tell you more than the ticket ever could.
MEASURE THE FULL INTERRUPTION
Learn how to put this into practice.
Read The Ticket Is the Lagging Indicator: Why the Future of IT Is Zero Avoidable Interruption to see how IT leaders can measure an interruption from the moment it begins, and how prevention becomes something you can prove.
