How it is computed
Take the hours the technician was clocked on repair orders. Divide by the hours the technician was on the clock at the store. Express it as a whole percent. A technician in the building for eight hours and on cars for six is at seventy-five percent.
Why it matters
It is the shop's traffic and dispatch, measured one technician at a time. Low productivity across the shop is a drive that is not writing enough work or a dispatcher who is not moving it; low productivity on one technician is a dispatch choice.
It is the number that decides whether to hire. A shop at low productivity that adds a technician adds an idle technician.
How operators read it
- Read it with efficiency, always. The pair tells the story: high efficiency and low productivity is a good technician waiting for work; low efficiency and high productivity is a busy technician who needs training or better jobs.
- Read it against the appointment book. Productivity falls on the days the drive was light, and the cause is in the schedule, not the shop.
- Count attendance honestly. Training days, shop meetings, and lunch policies change the denominator, and a shop that strips them out will look more productive than the one next door that does not.
Questions people ask
Is one hundred percent productivity possible?
Not for long. Technicians move cars, wait on parts, consult, and clean up, and none of that is clocked to a repair order. The useful question is whether the shop's number is stable and where the gaps in the day are.
Why does productivity need a timekeeping feed?
Because attendance hours do not exist on a repair order. The repair-order feed gives flagged and clocked time; attendance comes from the time clock, and the two have to be joined by technician and by day.
How A.D.A.M. reads it
A.D.A.M. computes technician productivity as clocked hours over attendance hours from the timekeeping days joined to the repair-order feed, and never reads it apart from efficiency. He reads it beside the numbers it trades against, names what the gap is worth, and leaves the decision where it belongs. What an AI advisor should do, and refuse to do.