What is Average Resolution Time?

Average resolution time is the average time to fully resolve a ticket and reflects both support efficiency and issue complexity. It is a key SLA metric and a driver of customer satisfaction. Pausing the resolution clock inconsistently (for example while awaiting customer reply) makes the figure unreliable. For context, set targets against SLA tiers by priority; benchmark each priority level separately rather than using one blended figure. Treat an external benchmark as a reference point rather than a universal target: company stage, sector, customer mix, pricing model and measurement definitions can materially change what “good” looks like. Read Average Resolution Time alongside First Response Time, FCR and SLA Compliance; together these measures provide a more balanced view and reduce the risk of optimizing one number at the expense of the wider outcome.

Make sure the numerator and denominator cover compatible populations and periods, and avoid dividing by a partial or unusually small base. Document business-hours rules, bot interactions, reopened tickets, pending time and the event that marks a case as resolved. Split the measure by channel, priority, issue type, customer tier and business-hours policy so that ticket mix does not create a misleading average. A dashboard should show the current value, prior-period comparison and a trend rather than presenting one isolated reading.

Improve the measure by diagnosing demand and flow: remove repeat contact causes, strengthen knowledge content, route accurately, balance staffing to arrival patterns and coach from quality reviews. Common pitfalls: pausing the clock inconsistently. Record the definition beside the dashboard, review it when systems or processes change, and annotate unusual events so future readers can distinguish a genuine performance shift from a data or timing effect.