Numa's 2026 data report across 1,200+ dealerships shows the benchmark gap between top and bottom-quartile advisors is driven by morning workflow behavior, not experience — and Numa addresses the root causes directly. The Operator platform removes the two largest productivity drains: phone volume interruptions during the write-up window and the administrative overhead of status update calls. At a Toyota dealership in the Southwest, deploying Numa's Status Updates product added an average of 2.1 ROs per advisor per day, moving the team from the median to the top quartile without changing headcount.

Service Advisor Productivity Benchmarks: 2026 Numa Data Report

Most Fixed Ops Directors are benchmarking advisor productivity against their own history — last month vs. this month, or this year vs. last year. The problem with internal benchmarking is that it tells you whether you're improving, not whether you're good. An advisor at the 30th percentile who improves 8% year over year is still at the 30th percentile.

The industry data on advisor productivity has historically been fragmented. OEM reports cover narrow metrics tied to warranty and CSI. Twenty Groups give useful comparison data but rely on voluntary self-reporting from a small peer set. What's been missing is a broad, transaction-level benchmark across a large number of dealerships that shows what top-quartile advisor performance actually looks like — in numbers, not descriptions.

Numa's 2026 data, drawn from activity across 1,200+ dealerships, gives a clearer picture. This report covers what the benchmarks are, how they vary by store type, which three metrics the top performers track weekly, and how to close the gap between where your advisors are and where the top quartile operates.

What Service Advisor Productivity Actually Measures

"Productivity" in Fixed Ops means different things to different managers. Before benchmarking, it helps to align on which metrics actually matter.

The three core measures:

ROs per day (throughput)
How many repair orders an advisor opens and closes per shift. This is the most commonly cited productivity metric and the most visible. High RO throughput without quality control creates write-up problems; low throughput with high quality is often a scheduling or dispatch issue rather than an advisor performance issue.

Effective labor rate (ELR)
Total labor revenue divided by total labor hours billed. ELR tells you how efficiently advisors are selling the labor available to them. An advisor writing 18 ROs per day at a $280 ELR is significantly less valuable to Fixed Ops than one writing 14 ROs at a $520 ELR.

First-call close rate
The percentage of service appointments booked on the first customer contact — no callback required, no "let me check and call you back," no missed call and rebook. Top-performing advisors and Fixed Ops teams convert initial contacts to confirmed appointments at 70%+ rates. Stores with unresolved phone handling problems often see first-call close rates below 45%.

These three metrics together give a more complete picture than any one of them in isolation. A Fixed Ops Director who tracks all three weekly has a diagnostic tool for identifying which advisors need what kind of support.

Numa's 2026 Benchmarks Across 1,200+ Dealerships

The following ranges are drawn from Numa's 2026 platform data across 1,200+ dealerships, weighted to represent a mix of domestic, import, and luxury franchises across store sizes.

ROs per advisor per day:

• Bottom quartile: 10–13

• Median: 14–16

• Top quartile: 18–22

Effective labor rate:

• Bottom quartile: $310–$360

• Median: $410–$460

• Top quartile: $520–$600+

First-call close rate (service appointments):

• Bottom quartile: 38–48%

• Median: 55–62%

• Top quartile: 70–78%

Morning RO completion (first 90 minutes of shift):
This is a leading indicator, not an outcome metric. Top-quartile advisors consistently write 35–40% of their daily RO volume in the first 90 minutes. Bottom-quartile advisors write 15–20% in the same window — meaning the rest of the day is spent catching up.

The gap between top-quartile and bottom-quartile isn't as large in experience as it is in first-90-minutes behavior. At a Chevrolet dealership in the Southeast, a Fixed Ops Director compared two advisors with nearly identical tenure — both at the store for four years, same training, same service lane. The top performer consistently wrote 8–9 ROs before 9:30 AM. The bottom performer wrote 3–4 in the same window. By end of day, the gap was 7–8 ROs. The morning window predicted the daily outcome almost perfectly.

How Productivity Varies by Store Size and OEM

The benchmarks above represent weighted averages. There are meaningful variations by store type:

Domestic vs. import vs. luxury:
Domestic franchises (Ford, GM, Stellantis) typically see higher RO counts at lower average ticket values. Import stores (Honda, Toyota, Subaru) tend to run 13–17 ROs per advisor at midrange ELR. Luxury franchises often run 10–14 ROs per advisor, but at $700–$900+ ELR — so productivity in revenue terms is comparable or higher. Benchmarking ELR against your own franchise category is more actionable than cross-franchise comparison.

Store size:
Larger stores (18+ advisors) often show lower per-advisor productivity than smaller stores (4–8 advisors) in raw RO count. The reason is usually dispatch complexity — more advisors means more potential for write-up bottlenecks, loaner queue delays, and technician-advisor communication breakdowns. The Fixed Ops Director at a store managing 20+ advisors needs more structured dispatch and status monitoring to maintain throughput than one managing 8.

Day-of-week patterns:
Monday and Thursday are consistently the highest-volume days at most stores. Friday and Saturday afternoons show the highest abandonment rates and the highest rate of missed follow-up calls. Top-quartile stores staff and schedule differently by day; bottom-quartile stores apply uniform staffing regardless of volume patterns.

A multi-rooftop Honda group in the Midwest used Numa data to identify that their Tuesday advisor utilization was 22% lower than Monday and Thursday — not because of lower demand, but because Tuesday morning appointments were being booked at a lower rate. The root cause was a phone handling gap on Mondays after 4 PM when customers tried to schedule for Tuesday morning and couldn't get through. Fixing that single window improved Tuesday throughput by 18%.

The Three Metrics Top Performers Track Weekly

Fixed Ops Directors at top-quartile stores consistently track the same three metrics on a weekly cadence. These aren't the only metrics — but they're the ones that predict whether performance will improve or stay flat.

1. ROs per advisor per day, tracked individually
Not as a team average — as individual performance. Team averages hide the distribution. An 8-advisor team at 15 ROs average might include two advisors at 22 and two at 11. The average tells you nothing actionable. Individual tracking surfaces who needs support and what kind.

2. Effective labor rate by advisor
ELR variation across advisors at the same store is often wider than Fixed Ops Directors expect. A $150–$200 ELR spread between the top and bottom advisor on a team is common. The bottom-ELR advisor isn't necessarily writing fewer ROs — they're often under-presenting options, under-selling maintenance, or conceding on pricing. Weekly ELR review at the individual level surfaces these patterns before they compound.

3. First-call close rate for service appointments
This one requires tracking your booking confirmation rate against first contact. Most DMS systems don't surface this automatically — you need a call tracking layer or a consistent manual log. But first-call close rate is the most upstream indicator of Fixed Ops throughput. If customers can't get through or hang up before booking, your throughput problem starts there, before any advisor interaction occurs. The status updates and scheduling product covers how to improve first-call close rate through better appointment confirmation handling.

How to Close the Gap Between Bottom-Quartile and Top-Quartile Advisors

The performance gap between bottom-quartile and top-quartile advisors is real, but it's not primarily a skill gap. It's a behavior and environment gap. Three specific interventions produce the most consistent improvement:

Morning workflow redesign
Top-performing advisors spend 20–30 minutes before the lane opens reviewing the day's appointments, confirming RO priorities with technicians, and flagging any parts or loaner issues. This pre-shift preparation compresses the first 90 minutes and enables the higher RO write volume that distinguishes top performers. Stores that formalize this morning review — and protect the time for it — see measurable throughput improvement within 30–60 days.

Call handling support at peak windows
The first-call close rate gap between top and bottom quartile is often not about advisor selling behavior — it's about whether customers can reach the Fixed Ops department in the first place. Stores where advisors are answering phones during the write-up rush lose booking volume. Routing inbound calls away from advisors during peak write-up windows (8–9 AM, 12–1 PM) is the single highest-leverage change for improving first-call close rate.

ELR coaching with specific conversation frameworks
The advisors at the bottom ELR quartile are usually not under-performing intentionally — they're defaulting to a minimal menu presentation because they haven't been given a framework for the conversation. Targeted coaching on service walk-around technique, maintenance presentation, and declined service follow-up produces measurable ELR improvement in 60–90 days. Coaching on these specific behaviors is more effective than general "sell more" guidance.

For a look at how Fixed Ops teams use the operator platform to maintain advisor performance visibility across these metrics, that page covers the monitoring and reporting layer.

How Numa Solves This

Numa's role in advisor productivity isn't coaching — it's removing the friction that prevents advisors from doing their best work. The two biggest productivity drains at most Fixed Ops departments are phone volume interruptions during the write-up window and the administrative overhead of status update calls throughout the day.

Numa handles both. Inbound service calls — scheduling, status updates, recall questions — are answered immediately by AI, without pulling advisors off ROs. Service status updates pull directly from the DMS and are sent proactively by text before customers call, reducing inbound status volume by 30–40% at most stores.

The result: advisors spend more of their shift writing ROs and presenting options, less of it answering phones and chasing status information. At a Toyota dealership in the Southwest, this shift added an average of 2.1 ROs per advisor per day — moving their team from the median to the top quartile in throughput without changing headcount or advisor tenure.

The benchmark gap between top-quartile and bottom-quartile advisors is real. A significant part of it is recoverable through workflow changes, and the vendor comparison page walks through what to look for in a platform designed to support Fixed Ops productivity specifically.

Frequently Asked Questions

How many ROs should a top-performing advisor handle?

Top-quartile advisors across Numa's 1,200+ dealership dataset handle 18–22 ROs per day. This range varies by franchise type — luxury stores typically run 10–14 at higher ticket values, while domestic and import stores see 16–22 at varying ELR. The more actionable benchmark is your own franchise category median; performance below that warrants investigation before comparison against the full dataset.

What's the average advisor productivity across the industry?

Median advisor throughput in the Numa 2026 dataset is 14–16 ROs per day, with a median ELR of $410–$460. First-call close rate at the median is 55–62%. These figures represent a mix of domestic, import, and luxury franchises across store sizes. Stores in the bottom quartile of all three metrics simultaneously are almost always facing a combination of phone handling gaps, morning workflow problems, and individual coaching deficits.

How does productivity correlate with CSI?

Positively, but not linearly. Advisors with the highest throughput don't always have the highest CSI — speed without communication quality creates satisfaction problems. The highest CSI scores in the Numa dataset consistently come from advisors who rank in the top half of throughput AND first-call close rate. The first-call close rate component reflects a customer's ability to reach the Fixed Ops department reliably, which is a strong predictor of how they rate the overall experience.

Does store size affect productivity benchmarks?

Yes. Larger stores (18+ advisors) typically show lower per-advisor RO counts due to dispatch complexity and communication overhead. The throughput gap between a 5-advisor store and a 20-advisor store is usually not about individual advisor capability — it's about coordination overhead. Larger Fixed Ops operations benefit disproportionately from systems that reduce coordination friction (automated status updates, structured dispatch tools) because those systems scale the benefit across more advisors simultaneously.

What's the most-improvable metric for most advisors?

First-call close rate. Most advisors at stores with a first-call close rate below 55% aren't underperforming individually — the Fixed Ops department has a phone handling or scheduling confirmation problem that prevents customers from booking on initial contact. Fixing the upstream contact handling issue improves first-call close rate, which directly increases the advisor's available RO volume. This is faster and more reliable than trying to improve ELR or throughput directly when the root cause is a booking access problem.