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Route Optimization Google Maps vs Roadie vs Onfleet

Reference Operations Updated Jun 19, 2026

Why this matters

Most service businesses with 3 or more techs are leaving 10 to 15 percent of windshield time on the table by sequencing jobs in customer-call-order instead of geographic-order. The fix is not always buying optimization software; for a 2-truck shop, the dispatcher with a regional map and good geographic instinct beats most algorithms. The decision tree is: how many trucks, how many stops per truck per day, how dynamic is the day (lots of mid-day adds and reschedules), and what does the field tech see on their device. This article frames the trade-offs between three commonly evaluated approaches: native Google Maps with manual planning, Roadie or similar crowdsourced delivery integrations (mostly irrelevant for service trades but often misunderstood), and a true field service optimization layer like Onfleet, Routific, or your FSM's built-in optimizer.

Approach 1: Google Maps Platform (manual planning)

Google Maps with the Directions and Distance Matrix APIs is what most dispatchers actually use, often through a free consumer app rather than the paid platform. Strengths: zero learning curve, accurate traffic data, every tech already has it on their phone, no monthly software bill beyond pay-as-you-go API calls if you wire it into your own dispatch board. Limits: it does not optimize sequence for you; the dispatcher orders the stops, then Google routes between them in the order given. The Directions API supports a waypoint optimization flag (set optimize=true in the request) that will reorder up to 25 waypoints by shortest total distance, which is usable for a single-tech day but not for multi-truck assignment problems.

When this is the right choice: 1 to 3 trucks, day fairly stable (mostly pre-scheduled service calls, few adds), a dispatcher who knows the territory. The dispatcher does the assignment by hand and Google handles turn-by-turn.

Approach 2: Roadie and crowdsourced delivery (usually wrong for trades)

Roadie, DoorDash Drive, and similar crowdsourced delivery networks are designed for one-way last-mile parcel delivery. They are not multi-stop optimizers and not designed for technicians who need to be at a job for an hour. They show up in trade evaluations because owners confuse "delivery routing" with "service routing." Skip unless you are running an actual parts-delivery side business. The one legitimate trade use case: same-day part runs from a supply house to a tech on a job site, where dispatching a paid courier is cheaper than pulling the closest tech off their current call.

Approach 3: Field service route optimization (Onfleet, Routific, your FSM optimizer)

Purpose-built service-routing platforms (Onfleet, Routific, OptimoRoute, and the optimizers built into FSMs like ServiceTitan, Housecall Pro, and similar) solve a different problem: given N techs with skills and time windows, M jobs with skills required and time windows, geographic distribution, and start/end depots, produce an assignment and sequence that minimizes total drive time or maximizes jobs completed. They handle skill matching (only send the licensed gas tech to a gas job), time-window constraints (customer is available 10 to 2), and re-optimization mid-day when a job runs long.

When this is the right choice: 4 or more trucks, 5 or more stops per truck per day, dynamic day (frequent reschedules, mid-day adds), techs with differentiated skill sets. The break-even where optimization software pays for itself is usually around the 4-truck threshold, where dispatch time savings plus 8 to 12 percent drive-time reduction covers the subscription.

Decision factors that actually matter

  • Skill differentiation: if every tech can run every call, geographic clustering is the only optimization variable and Google Maps with manual assignment works fine. If you have one tech who runs gas and one who runs water heaters and one who runs HVAC, software pays back faster because the constraint set is harder.
  • Dynamic day percentage: if 30 percent or more of today's work was not on the schedule at 7 AM, you need re-optimization, not initial optimization. Most FSM optimizers and Onfleet support live re-route; Google does not (it routes between stops you give it, not stops it picks).
  • Tech device discipline: any optimizer is useless if the tech does not mark "arrived" and "completed" in real time. If your techs do not update status reliably, the optimizer is dispatching against a fictional board. Fix the discipline before buying software.
  • Depot model: do techs start and end at home (the typical "take-home truck" model) or at a central shop? Take-home truck models change the depot per tech per day; some optimizers handle this and some assume a central depot.

Implementation realities

If you adopt a true optimizer, do not deploy it on a Monday morning. Run it in parallel for 2 weeks: dispatcher continues to assign by hand, optimizer produces a shadow schedule, and at end-of-day you compare drive time, on-time arrival, and revenue per truck. Most shops find the optimizer beats the dispatcher on geographic spread but the dispatcher beats the optimizer on customer relationships ("this customer wants Mike, not whoever is closest"). The keeper is the dispatcher with the optimizer as a recommendation engine, not as the boss of the board.

Hours-of-service constraint reminder

For any tech driving a vehicle subject to FMCSA 49 CFR Part 395 hours of service rules (most service trucks under 10,001 lbs GVWR are exempt; the threshold and exemptions are case-specific), the optimizer must respect HOS limits. If you run vehicles over 10,001 lbs GVWR or carry hazmat in placardable quantities, your route plan must show 30-minute breaks after 8 hours of driving and the 11-hour driving limit. Most service-trade optimizers do not enforce this by default; the dispatcher is the safety net.

References

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