Asset & Inventory Management

The most expensive parts in field service aren't the ones in the warehouse. They're the ones that weren't on the truck when the tech needed them.

A Spaid engineer pulls parts usage history from your FSM, maps the parts combinations that generate the most same-day returns and callbacks, and builds a pre-job stocking standard that prevents the wrong-part arrival before the truck rolls.

The Truck Stock Problem

What wrong-truck inventory costs you.

Inventory management tools optimize warehouse stock. The field service inventory problem isn't in the warehouse — it's in the truck. The same parts generate 60–70% of same-day return trips, and the data to prove it is already in your FSM.

Same-Day Return Trips

A tech arrives without the part that job history says is needed on 40–60% of this job type. Returns to the warehouse. Drives back. Completes the job. The round trip costs $150–$300 in labor and fuel — entirely preventable with a parts history analysis.

$150–$300 per avoidable same-day return trip

Callback-Generating Parts Gaps

Some wrong-truck arrivals don't trigger a return trip — they trigger an incomplete repair and a callback. The tech improvises a partial fix, closes the job, and the customer calls back in 5–10 days. Parts gap shows up as a callback, not an inventory problem.

30–40% of callbacks trace to missing parts or tools

Seasonal Stock Mismatches

Parts demand changes by season. Summer generates a different parts profile than winter for HVAC. Parts that were stocked correctly in March are wrong in July. Without a seasonal pattern analysis, techs consistently arrive with March's truck in July.

40% increase in same-day returns during seasonal transitions
Why Existing Solutions Fail

Warehouse optimization vs. truck stock intelligence.

Most inventory tools optimize what's in the warehouse. The field service inventory problem is which parts are on which truck for which job type on which day.

What you've tried before

Warehouse management system

Optimizes reorder points and warehouse stock levels. Doesn't address which parts are on the truck for the specific job type today.

Standard truck stock list

Based on management's experience, not historical job data. Updated annually if you're lucky. Doesn't account for job-type mix or seasonal patterns.

Tech discretion on truck stock

Your best tech knows what to bring. Your average tech doesn't. Variance between top and average performer truck stock mirrors the variance in callback rate.

Same-day return tracking

You can see returns in the FSM. You can't see which parts caused them, which job types generate them most, or which techs have the highest rate without a cross-system analysis.

VS
What forward-deployed looks like

FSM API connector pulls parts usage history by job type, tech, and season

Identifies which parts generate the most same-day returns and callbacks across 6–12 months — the data needed to build a real truck stock standard.

Pre-job briefing surfaces recommended parts list before the truck rolls

Based on job type and address history — the parts most commonly needed for this job type at this address type. Delivered via existing FSM job card.

Operational knowledge graph codifies top-performer truck stock by job type and season

Your best tech's truck stock standard converted into a systematic recommendation — by job type, by season, by branch location.

Drift detection monitors callback rate attributed to missing parts

Tags callbacks with root cause — parts gap, diagnostic failure, wrong-tech assignment. Monitors parts-related callback rate daily and flags when it's rising.

Engineer + Software

How the engineer and software fix truck stock.

Parts usage history from 6–12 months. Pre-job recommendations before the truck leaves the yard.

FSM API Connector

Parts usage history across all jobs and techs

Pulls parts usage records, return trip logs, and callback flags from ServiceTitan, HCP, FieldEdge, or Jobber. Identifies which parts generate the most same-day returns by job type, which techs have the highest wrong-truck rate, and how parts demand shifts by season.

Pre-Job Briefing Layer

Recommended parts list before the truck leaves

Surfaces parts recommendations for the specific job type based on historical usage data — before dispatch. Tech sees the list in the existing FSM job card. Address history adds context: prior work at this address, parts used last visit, common failure patterns.

Operational Knowledge Graph

Top-performer truck stock as the standard

Documents your best tech's truck stocking logic by job type and season — what they carry, what they always bring on X job type, how stock changes between summer and winter peak. Converts tribal knowledge into a systematic recommendation for every tech.

Drift Detection Engine

Parts-related callback rate monitored daily

Tags callbacks with root cause and monitors parts-attributed callback rate across all techs and job types. Flags rising patterns — a job type where wrong-truck arrivals are increasing, a tech whose parts-gap callback rate is above baseline, a seasonal transition creating stock mismatches.

Measured Outcomes

What operators measure after 90 days.

Field
40
% Reduction
Same-Day Return Trips
Pre-job parts recommendations based on historical job type data reduce wrong-truck arrivals.
Field
30–40
% Reduction
Parts-Attributed Callbacks
Callback root cause monitoring surfaces and addresses the parts combinations generating rework.
Field
$150–300
Saved/trip
Per Avoidable Return Eliminated
Fully-loaded cost savings per same-day return trip prevented.
Field
30
Days
Time to Parts Pattern Map
Full parts usage analysis by job type, tech, and season — delivered in the first audit phase.
Related Problems

Operators fixing parts and inventory 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