Operational Reporting for Field Service Businesses

If you run a field service business — HVAC, electrical, plumbing, pest control, security, cleaning — you know the feeling. The trucks go out in the morning. Hopefully the right technician goes to the right job with the right parts. Hopefully the schedule holds. Hopefully nobody’s sitting idle while three other techs are double-booked.

“Hopefully” isn’t a management strategy. Operational reporting replaces hope with data.

Most field service businesses either don’t report on operations at all (they watch revenue and hope the middle bit works out), or they drown in data from their field management software without extracting anything useful. Here are the metrics that actually drive operational decisions.

Technician Utilisation: The Metric That Moves Everything

Utilisation is the percentage of available working hours your technicians spend on billable, revenue-generating work. It’s the single highest-leverage metric in field service operations.

How to calculate it: Billable hours / total available hours x 100.

If a technician is available for 8 hours and spends 5.5 hours on billable work, their utilisation is 69%. The other 2.5 hours go to travel, waiting for parts, paperwork, schedule gaps, and unplanned delays. Each category represents a different operational problem with a different solution.

Utilisation Range	What It Usually Means
Below 55%	Serious scheduling or demand problem
55% - 65%	Below benchmark. Poor route planning or inconsistent job flow
65% - 75%	Healthy range for most field service businesses
75% - 85%	Strong performance. Well-optimised schedule
Above 85%	Caution. No buffer for overruns or emergencies. Burnout risk

Job Completion Rate and First-Time Fix

Job completion rate measures whether scheduled jobs actually get done on the day they’re scheduled. First-time fix rate measures whether service jobs get completed on the first visit without needing a return trip.

These two metrics work together. If job completion is high but first-time fix is low, you’re completing visits but not completing jobs. The technician shows up, investigates, and says “I’ll need to come back with a part.” The visit happened. The problem didn’t get solved.

What drives first-time fix rate down:

• Parts availability. Stock vans based on historical job types and parts usage, not guesswork.
• Poor job information. The technician arrives without knowing the equipment model or actual symptoms. Better intake processes fix this.
• Skill mismatch. An apprentice gets sent to a job that needs a senior tech.
• Scope creep. A simple repair turns out to be a major problem. Better diagnostics at quoting catch this earlier.

SLA Compliance: Keeping Your Promises

If your business has service level agreements — response time commitments for maintenance contracts or commercial clients — SLA compliance is non-negotiable. Missing SLAs costs you contracts, reputation, and penalty payments.

What to track:

• Response time compliance. Percentage of jobs meeting the committed response time.
• Resolution time compliance. Percentage of jobs resolved within the committed timeframe.
• Breach rate by priority level. Are you meeting high-priority SLAs but consistently missing lower-priority ones?
• Near-miss rate. Jobs that met the SLA but only barely. If 40% of “on-time” responses arrive in the last 15 minutes of the window, you’re one traffic jam away from a breach.

Revenue Per Truck

Revenue per truck measures how much revenue each mobile unit generates. It’s a proxy for operational efficiency and capacity utilisation combined.

How to calculate it: Total revenue / number of active trucks for the period.

This metric matters because it tells you whether growth is efficient. Adding trucks and technicians while revenue per truck declines means you’re scaling costs faster than output.

Track this per truck and compare across your team. You’ll often find significant variation — one truck at $380,000 annually and another at $210,000. The gap might be territory, job type mix, or scheduling inefficiency. But you can’t investigate a gap you don’t know exists.

Estimated vs. Actual Job Duration

The gap between estimated and actual job duration has cascading effects. If you consistently underestimate:

• Schedules compress. Every job after the first one starts behind schedule.
• Customer satisfaction drops. “Between 10 and 12” becomes 1:30pm.
• SLAs get breached. The buffer evaporated in the first job of the day.

Track the average variance by job type. If residential service calls consistently run 40 minutes over estimate, fix the estimates. The schedule, utilisation numbers, and customer experience all improve as a result.

The Field Service Operations Dashboard

Daily view (dispatchers): Today’s schedule, live technician status, SLA countdown timers, jobs completed vs. scheduled.

Weekly view (ops managers): Utilisation by person, job completion and first-time fix rates, SLA compliance by priority, revenue per truck, duration variance.

Monthly view (leadership): Utilisation trend, first-time fix trend, SLA compliance by client, revenue per truck trend, cost per job.

Where to Start

If you’re not tracking any of these metrics, start here:

1. Technician utilisation. Even rough tracking — total billable hours divided by total available hours per week — tells you something useful.
2. Job completion rate. How many scheduled jobs actually get done on the day? This surfaces scheduling and estimation problems immediately.
3. Revenue per truck. Divide last month’s revenue by your number of active trucks. That’s your baseline.

These three numbers, tracked weekly, will surface the operational problems invisible when you only watch revenue. Revenue tells you the score. Operational metrics tell you how you’re playing the game.