What it means
The clock starts when the customer first contacts the business, such as opening a ticket, and stops when the issue is closed as solved. It therefore includes every wait along the way, such as time in a queue, time waiting for information from the customer and time passed between teams.
This is what makes it different from handle time, which counts only the minutes an agent actively works. From a customer's viewpoint, resolution time is what counts.
Someone with a broken payment system does not care that the agent spent only ten minutes on the ticket if the fix took three days. A long time to resolution is linked to frustration, cancellations and negative reviews.
For managers and finance teams, the measure helps with staffing, service levels and cost. Slow resolution suggests backlogs, handoffs between teams or a lack of skills, and it often leads to extra contacts as customers chase updates.
Service-level agreements, which are promises to customers about response and fix times, are usually written in terms of resolution time. The average can be misleading, because a few very old tickets can drag it up while most tickets are solved quickly.
Teams commonly look at the median and the 90th percentile, meaning the time within which nine out of ten tickets are solved, and report results by priority level. They also decide whether to measure in calendar hours or only working hours.
Improving the figure usually means better triage (sorting issues by urgency and type), clearer knowledge articles, empowered first-line staff and fewer handoffs. The aim should be resolving problems properly, not merely closing tickets quickly, so reopened tickets should be counted.
Time to resolution connects to cost in a less obvious way. Each day a ticket stays open increases the chance that the customer will contact the business again, and every extra contact carries a handling cost.
Fast, correct resolution therefore tends to lower the total cost of service, even if it requires more skilled and better-paid agents.
In practice
Real-world examples
Example 1
A payments company promises to resolve urgent issues within 4 hours. Its dashboard shows an average of 3.2 hours for urgent tickets and 26 hours for routine ones, so the support manager sets separate targets for each.
Example 2
A software-as-a-service provider finds that tickets passed between three teams take 40 hours on average, compared with 9 hours for tickets solved by the first team. It trains first-line agents to resolve more issues themselves.
Example 3
A hospital's IT desk measures time to resolution for staff computer problems. Delays directly affect patient care, so it prioritises faults that block clinical systems and reports the results to the board each month. The IT manager also measures how many tickets are reopened, to make sure speed does not come at the expense of quality.
Think of it
Resolution time is how long it takes to solve customer problems-speed of support.
Formula
Calculation
Average time to resolution = Total resolution time for all resolved tickets / Number of tickets resolved
Suppose a support team resolved 240 tickets in a month, and the elapsed time from opening to closing, added across all tickets, was 1,920 hours.
Average time to resolution = 1,920 / 240 = 8 hours.
If the team brings in a better triage process and the total falls to 1,440 hours for the same 240 tickets, the new average = 1,440 / 240 = 6 hours, an improvement of 25%.Case study
Seen in the real world
Clearwater Telecom is an illustrative, fictional broadband provider with 30 support agents. Its average time to resolution had crept up from 14 hours to 22 hours over six months, and cancellations were rising.
An analysis showed that the average was inflated by tickets waiting for engineers, which took 70 hours, while tickets solved at first contact took only 3 hours. The company created a rota that gave engineers a daily slot for escalated tickets and gave agents authority to arrange engineer visits directly.
Within three months the average fell to 12 hours, and monthly cancellations dropped by a fifth. The illustrative story shows that the headline average pointed to a problem, but the breakdown showed where to fix it. The finance team estimated that the faster resolution saved about 400 follow-up contacts a month, which paid for the new rota in under a quarter.
Watch out
Common mistakes
- Confusing time to resolution with handle time, when one measures elapsed time and the other measures active agent time.
- Counting a ticket as resolved when it is merely closed, which hides reopened issues and unhappy customers.
- Relying on the average alone, when a handful of very long tickets can distort the picture.
Questions
People also ask
What is a good time to resolution?
It depends on the industry and severity of the issue, so targets are normally set separately for urgent and routine tickets.
Should the clock run outside working hours?
Some businesses count calendar hours while others count only business hours, and the choice should match what the customer was promised.
How does it relate to cost?
Longer resolution times generate more follow-up contacts and customer churn, both of which increase the cost of service.
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