AI Station

First-time fix rate: the service metric that decides your margin

First-time fix rate shows how often a technician resolves a job on the first visit. How to define and calculate it, why it drives margin, and what to change first.

Field servicePublished 3 minute read

Key points

  • First-time fix rate is the share of jobs resolved on the first visit. It only works as a metric if the definition is written down.
  • Each repeat visit costs travel, another labour block, parts delay and customer goodwill, so small gains add up.
  • The usual levers are complete job information, the right parts on the truck and a fast feedback loop from the technician to the office.

Define it before you measure it

First-time fix rate (FTFR) is the number of jobs completed on the first visit divided by the total number of jobs. The formula is simple. The definition is where companies disagree. Before you report the number, agree on:

  • Which jobs count. Usually installations, repairs and maintenance visits, excluding jobs cancelled by the customer.
  • What "fixed" means. The problem is resolved and the customer has accepted the work, not just that the technician left the site.
  • How callbacks are handled. For example, a return visit for the same issue within 7 or 14 days counts as a repeat.

A metric with a loose definition will be argued about rather than used.

Why it decides margin

Every repeat visit is a full job delivered twice. It uses a technician's time, a second truck roll, and often a second parts delay. It also costs goodwill, and the customer's next booking is less likely to come to you.

A worked example (illustrative numbers)

Suppose a company completes 400 jobs a month and has a first-time fix rate of 75%, which means 100 repeat visits. If each repeat visit costs about $250 in technician time, travel and the rescheduling effort, repeat visits cost $25,000 a month.

Raising first-time fix to 85% reduces repeat visits to 60. That saves $10,000 a month, or $120,000 a year, from the same volume of work and without hiring anyone. The gain comes from doing the existing work correctly the first time.

What moves it

  • Information before the visit. Job history, photos, error codes and the customer's own description. A technician who knows what they are walking into brings the right tools.
  • The right parts on the truck. Stock the vehicle by job type, based on what repeat visits most often needed. Track the jobs that failed for lack of a part separately.
  • Skills that match the job. Sending a technician who lacks the certification or experience for a job is one of the most avoidable causes of a repeat. When you hire for these skills, a structured process helps; see the JHRE Talent Platform.
  • Feedback from the field. A short note from the technician on what was missing lets the office fix the next job, not just this one.
  • Realistic time windows. A two-hour slot for a job that takes four hours is a repeat visit that has been scheduled in advance.

Track it without blaming the wrong people

Report first-time fix rate weekly, by technician and by job type. Record the reason for each repeat, because a part that was not on the truck is an office problem, and a technician who did not follow procedure is a coaching problem. Mixing the two makes the number useless and can drive good technicians away.

If you want to see how dispatch decisions affect repeat visits, our Dispatch product suggests assignments that match skills, location and time windows, and every suggestion is approved by a person. The guide to what an AI dispatcher should and shouldn't do covers the boundaries in more detail.