First-time fix rate
What is first-time fix rate: the metric explained
First-time fix rate is the share of service jobs resolved on the first visit, with no return trip needed for parts, information or a second technician. It is the headline productivity measure in field service, and the calculation is simple: divide the number of jobs fixed on the first visit by the total number of jobs performed.
You will see it written as first time fix rate, first-time fix rate, FTF and FTFR. Same metric. The hyphen argument is not worth having.
What does first-time fix rate actually mean?
The formula is easy. The definition is where teams quietly disagree with each other, and where most reported numbers stop being comparable.
Four decisions you have to make explicitly:
- What counts as fixed. Restored to service, or fully repaired to specification? A temporary bypass that keeps a line running is not the same as a repair.
- What counts as one job. If a planned follow-up is raised as a fresh work order, your FTF looks better without anything improving.
- Which jobs are in scope. Planned maintenance and installations behave nothing like emergency breakdowns. Mixing them produces a meaningless blended number.
- The measurement window. This one is the big trap, and it gets its own section below.
How is first-time fix rate measured?
The window matters more than most teams expect. Aquant recommends a 30-day window and warns that 7-day or 14-day windows split related repeat visits into separate tickets, making performance look better than it is (benchmarks and methodology summarised at the Aquant 2025 Field Service Benchmark Report).
In other words, a short window does not measure first-time fix. It measures how long you waited before looking.
Published benchmark figures, each with its source:
- Aquant, 2025 Field Service Benchmark Report, measured over 30 days: median 75 percent, top 20 percent at 86 percent, bottom 20 percent at 53 percent.
- Aberdeen Group: average near 75 percent, per Comparesoft's summary of the research.
- Service Council: around 77 percent, same source.
- Best-in-class operations: 88 to 90 percent or higher, with 80 percent the most widely cited round-number target.
Treat those as orientation, not as a target handed down from outside. A medical device team and a domestic appliance team are not playing the same sport, and a 30-day figure cannot be compared with a 7-day one.
First-time fix rate explained: a worked example
A regional HVAC team closes 400 jobs in a month. 292 are resolved on the first visit inside a 30-day window, so the FTF rate is 73 percent. Reviewing the 108 failures shows 41 were missing a specific control board, all on the same equipment family. That is not a technician problem. That is a stocking decision worth a couple of points on the metric.
What drives first-time fix up or down?
Almost every failed first visit traces back to a decision made before the technician arrived. The usual causes:
- Thin intake information. A symptom described over the phone rarely identifies the model, the error code or the real fault.
- Wrong parts on the van. The diagnosis was right, the stock was not there.
- Wrong skill dispatched. The job needed a specialist, and scheduling sent whoever was closest.
- Site not ready. No access, no isolation, no one available to open up.
- Lost information in handovers. What the customer showed the call centre is not what reaches the engineer.
The cost of getting it wrong is not just one extra trip. Aquant's 2025 report found that a failed first visit adds two additional visits on average and extends resolution timelines by 14 days (reported in 24x7 Magazine).
Customers notice, too. In a ServiceMax survey of 4,122 US and UK adults, more than three-quarters of those dissatisfied with a recent service experience named the problem not being resolved on the first visit, roughly twice as common as the next complaint, which was communication (Fortune).
How first-time fix differs from related metrics
Three metrics get confused constantly:
- First-time fix rate asks whether the visit that happened resolved the issue.
- Avoidable dispatch rate asks whether the visit should have happened at all. A perfectly executed visit to a non-fault is a first-time fix on paper and a wasted truck roll in reality.
- Mean time to resolution asks how long the customer waited, across however many visits it took.
Optimise FTF alone and you can cheerfully push the other two in the wrong direction.
Mistakes worth avoiding
Making it a technician scorecard. When FTF drives individual bonuses, jobs get closed optimistically and repeat visits get logged as new work orders. The number improves. The operation does not.
Comparing across definitions. Your 84 percent and a competitor's 84 percent are probably measuring different things over different windows.
Ignoring the tail. The jobs that took four visits do most of the damage to cost and to customer trust, and they hide inside a single-percentage headline.
Better pre-visit assessment and structured remote diagnostics are the two levers that move FTF without touching how anyone works on site.
Both of those depend on seeing the equipment before dispatch. Venta Capture, a product of VentaVid, does that with guided capture: you send a link, the person already on site records the specific views and answers your team asks for, and the case arrives ready for a specialist to review. Venta Capture reports that 4 out of 5 issues are handled and closed the same day on its customer support page, which is the vendor's own reported outcome rather than an industry benchmark. The platform does not diagnose the fault. It gives the person who can diagnose it something to look at.
