First-Time Fix Rate & Callbacks

Every callback costs $350–$600 fully loaded. A 50-tech shop burning $20K/month on rework is a fixable data problem, not a people problem.

The root causes are already in your FSM — wrong part, incomplete diagnosis, skipped step, wrong tech assignment. A Spaid engineer finds them in the first 30 days and builds a system that prevents them before the truck rolls.

Why Callbacks Keep Happening

Why Your Callback Rate Stays High — And What’s Actually Causing It

Most operators track callback rate as a lagging metric. They know it’s too high. They don’t know which job types, which techs, which dispatch decisions, or which parts shortages are generating the most rework — and without that, there’s nothing to fix.

Wrong Part on the Truck

Same-day return trips for missing parts are the single largest preventable callback category. A tech arrives without the part that history says is needed on 40% of this job type. Returns to the warehouse. Drives back. Completes the job. The round trip was entirely preventable.

40% of callbacks involve a missing part or tool

Incomplete Diagnosis

Job closes as “repaired” but the underlying cause wasn’t addressed. Customer calls back within 30 days. Root cause: no diagnostic standard, no checklist, no flag for high-risk job types.

$350–$600 fully loaded per callback event

Wrong Tech Assignment

Some techs generate 3× more callbacks than others on specific job types. The data exists in the FSM. Nobody has run it. The same high-callback techs keep getting assigned to the same job types. Wrong tech assignment drives 3× callback rates on identifiable job categories.

3× callback rate variance by tech on specific job types
Why Existing Solutions Fail

Tracking callbacks vs. eliminating them.

Most operators log callbacks in their FSM. Very few have mapped callback rate by tech, job type, part, and dispatch pattern — which is the only way to find the actual fix.

What you've tried before

Callback tracking in FSM

You know the rate. You don’t know whether it’s a parts problem, a diagnostic problem, a tech-skill problem, or a dispatch problem.

Tech coaching

Addresses individual behavior but misses systemic root causes — wrong-part arrivals, job-type mismatches, missing documentation standards.

Monthly callback review

By the time the data is in the review, the callbacks have already happened. No mechanism to flag before the truck rolls.

Generic job checklists

Not customized to your job types, your most common failure points, your highest-callback parts combinations.

VS
What forward-deployed looks like

FSM API connector pulls callback history by tech, job type, and part

Identifies the highest-frequency root causes across 6–12 months in the first 30 days — before any process changes.

Operational knowledge graph codifies top-performer job execution

What they check, what they bring, how they diagnose — converted into a repeatable standard for every high-callback job type.

Pre-job briefing layer flags risk before dispatch

Surfaces parts checklist and prior job history at the address before the truck leaves — not after the callback.

Drift detection monitors callback rate daily by tech and job type

Flags spikes before they compound — 3–4 week window to address root cause rather than a monthly report after the damage is done.

Engineer + Software

How the engineer and software reduce callbacks.

Four tools. Root cause in 30 days, prevention before the truck leaves the yard.

FSM API Connector

Root cause in 30 days, not 6 months

Pulls 6–12 months of job records, callback flags, parts usage, and dispatch assignments from ServiceTitan, HCP, FieldEdge, or Jobber. Cross-references callback rate by tech, job type, part combination, and seasonal pattern. Identifies the highest-ROI fixes before anything changes.

Operational Knowledge Graph

Top performers’ job execution as the standard

Documents how your best techs diagnose and execute the highest-callback job types — what they check, what they bring, how they close. Converts that into a repeatable standard embedded in pre-job briefing for every tech. This is how top-performer knowledge reduces callbacks at scale.

Pre-Job Briefing Layer

Parts checklist and risk flag before the truck rolls

Surfaces recommended parts list for the specific job type and address history before dispatch. Flags jobs with high callback risk based on historical patterns. Delivered via existing FSM job card — no new app.

Drift Detection Engine

Daily callback rate monitoring by tech and job type

Monitors callback rate across all techs and job categories daily. Flags deviation from baseline before it becomes a trend. Connects back to dispatch assignment patterns — because callbacks are the second-largest component of revenue leakage in a typical 50-tech operation.

Measured Outcomes

What operators measure after 90 days.

Field
25–35
% Reduction
Overall Callback Rate
Across all techs and job types after root cause elimination and pre-job briefing deployment.
Field
$15–25K
/month Saved
Callback Cost Eliminated
Fully loaded cost savings from reduced return trips on a 50-tech operation.
Field
40
% Reduction
Wrong-Part Arrivals
Pre-job parts checklists based on historical job type data reduce same-day return trips.
Field
30
Days
Time to Root Cause Map
Full callback root-cause analysis by tech, job type, and part — delivered in the first audit phase.
Related Problems

Operators reducing callbacks also address:

The Measured Pilot Guarantee

If we don't identify $200K, you pay nothing.

Our Full-Operation Audit (Days 1–30) maps every revenue leak — field and back of house. If we don't identify at least $200,000 in recoverable annual revenue, we refund Phase 1 in full. You keep all audit deliverables.

After kickoff, we ask for about 30 minutes a week of your ops leader's time.

Zero risk. Full-operation visibility. Founding customer pricing: 40% below standard rates.
Start Here

45 minutes. Your data.
No commitment.

We'll start with a recent export or sample call data from your FSM and call system, show you the biggest leaks, and scope the engagement. Full access happens only if you proceed to the audit.

Accepting 2–3 founding operators · $20M–$100M revenue · 40–120 techs · On a modern FSM