TL;DR
- Most contractors track revenue and job count — but the dispatch KPIs that predict profitability are different: first-visit resolution, drive time ratio, and schedule accuracy.
- Tracking the wrong metrics creates perverse incentives; tracking the right ones surfaces operational problems before they become financial ones.
- Each KPI has a calculation formula, an industry benchmark range, and a set of diagnostic questions when you fall outside it.
- You don't need to track all 7 simultaneously — start with the 2–3 most relevant to your current operational challenges.
- AI dispatch platforms make these metrics available automatically; manual tracking requires deliberate data collection discipline.
Dispatch is one of the most operationally complex parts of running a field service business — and one of the least measured. Revenue gets tracked. Jobs per day gets tracked. But the metrics that actually explain why profits are eroding, why callbacks are increasing, or why technicians are burning out often go uncounted.
This guide covers the 7 dispatch KPIs that actually matter, with formulas and benchmarks you can use immediately.
KPI 1: First-Visit Resolution Rate (FVRR)
What it measures: The percentage of jobs resolved completely on the first technician visit, without a callback, return trip, or follow-up appointment required.
Formula:
FVRR = (Jobs completed on first visit ÷ Total jobs) × 100
Industry benchmark: 78–88% for residential; 82–90% for commercial maintenance
Why it matters: Every callback costs $120–$200 in additional labor and logistics, plus the customer satisfaction impact. A 1-percentage-point improvement in FVRR on 200 monthly jobs is 2 avoided callbacks — roughly $300–$400/month. At scale, this is the single highest-impact dispatch quality metric.
Diagnostic questions when below benchmark:
- Are technicians arriving with the wrong parts? (Parts/inventory problem)
- Are the right technicians being sent? (Skill-matching problem)
- Are job types being misdiagnosed at booking? (Intake problem)
KPI 2: Drive Time Ratio (DTR)
What it measures: The proportion of a technician's working day spent driving versus working at a job site.
Formula:
DTR = (Total drive time ÷ Total working hours) × 100
Industry benchmark: 20–30% for urban/suburban routes; 30–40% for rural or spread-out territories
Why it matters: Drive time is cost without revenue. Every percentage point above benchmark is direct margin erosion. DTR also reveals route optimization opportunity — if your DTR is consistently above 35%, you have material route efficiency to capture.
Diagnostic questions when above benchmark:
- Are jobs being grouped geographically? (Routing problem)
- Are technicians returning to the shop mid-day unnecessarily? (Scheduling problem)
- Is the service territory too spread out for current team size? (Capacity planning problem)
See route optimization ROI for the full financial impact calculation.
KPI 3: Schedule Adherence Rate (SAR)
What it measures: The percentage of jobs completed within the promised time window.
Formula:
SAR = (Jobs completed within promised window ÷ Total jobs) × 100
Industry benchmark: 85–92% for scheduled appointments; lower for reactive/emergency work
Why it matters: Schedule adherence is the customer's experience of reliability. Late arrivals drive negative reviews, customer churn, and call volume (customers calling to check on their technician). It's also a proxy for schedule quality — if jobs consistently run over their windows, your job duration estimates are wrong.
Diagnostic questions when below benchmark:
- Are job duration estimates accurate? (Estimation problem)
- Are travel times accounting for traffic? (Routing problem)
- Are too many jobs being stacked in a day? (Capacity problem)
KPI 4: Technician Utilization Rate (TUR)
What it measures: The percentage of available technician hours spent on billable or revenue-generating work.
Formula:
TUR = (Billable hours ÷ Available hours) × 100
Industry benchmark: 65–75% for field service (accounting for drive time, admin, and breaks)
Why it matters: Utilization below 60% usually means scheduling inefficiency — jobs aren't being filled into available slots. Utilization above 80% is a different problem: your team is at or near capacity, callbacks and rescheduling are stressing the system, and burnout risk is elevated.
Diagnostic questions when outside benchmark:
- Below 60%: Are you filling schedules effectively? Is demand actually lower, or is it a scheduling gap?
- Above 80%: Are you hiring behind demand? Is overtime increasing? What's the FVRR trend?
KPI 5: Emergency Response Time (ERT)
What it measures: Time from emergency call received to technician on-site.
Formula:
ERT = Technician on-site timestamp − Call received timestamp
Industry benchmark: Under 90 minutes for P1 emergencies; under 4 hours for P2
Why it matters: Emergency response time is a contractual SLA component for commercial maintenance agreements and a key differentiator for residential retention. Slow emergency response is cited in 31% of commercial contract non-renewals (Field Service Journal, 2024).
Diagnostic questions when above benchmark:
- Is technician availability data current in real time? (GPS/status tracking problem)
- Is emergency triage happening correctly? (Classification problem)
- Is the on-call rotation working? (Coverage problem)
For the mechanics of AI emergency dispatch, see AI emergency dispatch.
KPI 6: Dispatch-to-Revenue Ratio (DRR)
What it measures: Revenue generated per dispatch decision — essentially, how much revenue each scheduling action produces.
Formula:
DRR = Total revenue ÷ Total jobs dispatched
Why it matters: DRR is a composite metric. It rises when you're sending the right techs (higher first-visit completion rate → higher average job value), routing efficiently (more jobs per tech per day possible), and matching skill to job complexity (complex high-value jobs going to qualified technicians rather than being deferred).
DRR doesn't have a universal benchmark — it's relative to your service mix and pricing. Track it as a trend metric and investigate when it drops. A falling DRR often surfaces before revenue drops, making it an early warning indicator.
Diagnostic questions when DRR is falling:
- Are more jobs getting split across multiple visits? (FVRR problem)
- Are technicians taking longer per job than expected? (Duration estimation problem)
- Are more jobs getting canceled or rescheduled? (Schedule quality problem)
KPI 7: Workload Distribution Variance (WDV)
What it measures: The degree of unevenness in job load across technicians over a period (typically weekly or monthly).
Formula:
WDV = Standard deviation of jobs per tech ÷ Mean jobs per tech × 100
A WDV of 0 would mean every technician has exactly the same job count. A WDV above 25–30% signals meaningful imbalance worth investigating.
Industry benchmark: WDV under 20% for balanced operations; WDV consistently above 30% is a burnout and retention risk.
Why it matters: High WDV correlates with technician turnover, which costs $15,000–$30,000 per incident. This metric makes workload inequity visible before it becomes a resignation.
Diagnostic questions when WDV is high:
- Is skill-based filtering creating too narrow an eligible pool for some job types? (Matching problem)
- Are customer preferences concentrating on specific technicians? (Preference management problem)
- Is emergency/on-call distribution uneven? (Rotation problem)
For a full discussion of workload balancing, see dispatch workload balancing and the AI dispatch guide.
How to Build a Dispatch KPI Dashboard
You don't need expensive analytics software to start tracking these metrics. The minimum viable setup:
For manual tracking (10 or fewer techs):
- Google Sheets with weekly input of: jobs completed, drive hours, worked hours, callbacks, SLA met/missed, overtime by tech
- Monthly review meeting using the sheet as the agenda
- Set 3-month baseline before drawing conclusions about trends
For automated tracking (10+ techs):
- GPS-enabled FSM software that captures drive time automatically
- Job completion with outcome flags (resolved/callback required)
- Time tracking at the job level
- Reporting dashboard with the 7 metrics above as default views
Reporting cadence:
- Weekly: FVRR, ERT (operational metrics — fast feedback needed)
- Monthly: DTR, TUR, SAR, DRR (trend metrics — need 4+ weeks of data to be meaningful)
- Quarterly: WDV (structural metric — slow-moving, needs longer timeframe)
FAQ
Which of these 7 KPIs should I start with if I'm tracking nothing right now? Start with FVRR and DTR. First-visit resolution tells you about dispatch quality; drive time ratio tells you about routing efficiency. Together they cover the two highest-impact dimensions of dispatch performance. Once you have 60 days of baseline on these two, add TUR and SAR.
How do I get technicians to support KPI tracking without feeling like they're being surveilled? Transparency is the key. Share the metrics with the team, explain what you're measuring and why, and — critically — connect improvements to tangible benefits for the technicians: fewer overtime hours, less wasted windshield time, fairer workload distribution. KPIs framed as "we're looking for ways to make your days more efficient" land very differently than "we're checking whether you're working hard enough."
Can these KPIs be gamed by technicians who know they're being measured? Some can be manipulated on the margins (marking jobs "resolved" when they technically required a follow-up call). The protection is multi-metric visibility — gaming one metric typically shows up as anomalies in others. If FVRR improves but customer satisfaction scores decline, that's a signal worth investigating.
The Bottom Line
Dispatch KPIs are not administrative overhead — they're the operational early-warning system that surfaces inefficiency before it becomes unmanageable. The companies that grow their service businesses profitably are the ones that know these numbers cold and act on them consistently.
Start with two metrics, build the tracking habit, then expand. The discipline of measurement compounds over time.
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