Free tool

How much windshield time are you burning every week?

Plug in your stops per day, your average drive minutes between stops, and how many days a week you run. We'll show how much time an optimized route could save — and what the upper-bound looks like.

Skip ahead to the calculator See route optimization

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Sample result

6.5 hrs / week saved

Based on 12 stops/day, 14 min between stops, 5 days/week.

Windshield time now 14.0 hrs / wk

Optimized route 7.5 hrs / wk

Hours back per week 6.5 hrs

Calculator

Your inputs → your weekly windshield time.

Numbers update live as you type. Nothing is sent to our server unless you choose to email yourself a copy.

Inputs

Stops per day per truck

Average number of jobs/stops a single truck visits in a normal day.

Please enter a number from 2 to 60.

Average drive time between stops (minutes)

Door-to-door minutes from one stop to the next, on a typical day.

Please enter a number from 1 to 120.

Days per week you run routes

Please enter a number from 1 to 7.

Number of trucks (optional)

Multiplies the savings across your fleet. Leave at 1 to see per-truck numbers.

Please enter a number from 1 to 50.

Your result

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Type your inputs to see the windshield-time band.

Current weekly drive time —

Conservative savings (15%) —

Upper-bound savings (25%) —

Annual hours back (conservative) —

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Methodology

How the math works.

How we estimate your weekly drive time

We combine your numbers in three steps:

Take stops per day and subtract 1. That’s how many between-stop drives one truck makes in a day. We skip the very first leg from the shop or home—you’d drive that either way.
Multiply by average drive minutes between stops, then by days per week, then by number of trucks. That’s total drive minutes for the week.
Divide by 60 to get hours of driving per week (your “windshield time” baseline).

Why the 15–25% optimization band?

The savings range maps to the two optimization paths Grunlo actually runs, applied to typical service-business work distributions:

Lower bound (15%) — a greedy nearest-neighbor pass that orders stops by driving proximity. It runs instantly in your browser-fast and is the fallback Grunlo uses when a full solver run isn’t available.
Upper bound (25%) — a hosted vehicle-routing (VRP) solver, Google’s Cloud Route Optimization, which weighs drive time, time windows, and crew skills across the whole day’s stops. Grunlo calls it for the primary plan.

Real-world savings depend on geography, density, time-window constraints, and how dispatched the existing route already is. A truck running a perfectly stacked tight neighborhood is closer to 5–10%; a truck doing scattered service calls across a metro is closer to 25–35%. We pick a middle band so the number you see is honest, not promotional.

Annual conversion

We multiply weekly hours saved by 50 working weeks (allowing two weeks for holidays and weather) to get the annual estimate. The annual figure uses the conservative (15%) savings estimate, not the upper bound.

Adjacent features

If the savings look real, here’s what runs them.

Route optimization

Drag-and-drop schedule with a one-click optimize that orders stops by drive time, time windows, and crew skills — powered by a hosted VRP solver (Google Cloud Route Optimization) with a built-in nearest-neighbor fallback, the same approach the savings band above is calibrated against.

See route optimization →

GPS tracking

Live truck positions, route progress, and arrival ETAs the office can see. Identifies trucks that are off-route or running long without anyone radioing in.

See GPS tracking →

Recurring jobs

Build a weekly mowing or service visit cadence once and let the schedule populate forever. Optimization runs across recurring + one-off jobs together.

See recurring jobs →

FAQ

Route-savings questions, plain answers.

Everything you need to know before getting started.

It’s a middle band. Tight, dense routes (a single neighborhood per crew per day) tend toward the low end or below. Routes scattered across a metro with no inherent ordering tend toward the high end. We deliberately don’t quote 30%+ as a default because that requires both a chaotic baseline and a serious solver run.

They map to the two optimization paths we actually run: a greedy nearest-neighbor ordering (the floor, which runs instantly) and a hosted vehicle-routing solver, Google’s Cloud Route Optimization (the ceiling). The methodology section above links the underlying solver.

No — this is a pure drive-time estimate. Real-world route optimization layers in time windows, equipment, crew skill, and SLA priority, which can either narrow or widen the savings depending on how constrained your jobs already are.

The drive from home or depot to the first stop happens whether you optimize or not, and the “between-stops” drive is what an optimizer can actually re-order. Counting the depot leg would inflate the savings number on small-stop-count days.

Correct — the calculator runs entirely in your browser. The only data we receive is what you optionally type into the “email me a copy” form, and that goes into our standard contact-request inbox.

Stop driving past stops you should be hitting.

The calculator gives you a number. Grunlo gives you the route plan and the dispatcher who sends it to the truck.

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