JATJay Templeton Consulting
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home-services · Dispatch · AugmentBuy it

AI dispatch & route optimization

01 — The scenario

A home-services business where this lands in Operations.

The friction
routingfueldispatchschedulingfield-service

02 — What is actually going wrong

Jobs get assigned by whoever is loudest on the radio and whoever the dispatcher remembers is nearby. Vans cross the city past each other. Fuel and windscreen time are the second-biggest cost in the business and nobody owns the number.

How it works

Overnight, the system takes tomorrow's job list, each technician's skills and start location, and the time windows customers were promised, and produces a run order per van. Through the day it re-sequences when a job overruns or an emergency lands.

What good looks like

Miles per completed job drops and stays down. Dispatchers stop spending their morning on the phone reshuffling, and the "can you squeeze one more in" call gets a real answer instead of a guess.

03 — The problem, in money

$12,600$592,875/ yr at stake
Modeled
  • Field technicians8 people51 peoplePlaceholder — not a validated benchmarkStarting point
  • Miles saved per tech per day12 miles40 milesPlaceholder — not a validated benchmarkStarting point
  • Cost per mile0.7 USD1.55 USDPlaceholder — not a validated benchmarkStarting point

04 — The options

Buy$300–$800 / moOff-the-shelf tooling, live sooner.
Bin$0Do nothing — and accept the leak.

05 — The call

Buy it

Buy it. An off-the-shelf tool wins this one — it gets you live faster, and the math does not justify building from scratch.

06 — How this goes wrong

  • Optimising for distance when the business is actually constrained by technician skill. The shortest route that sends the wrong person is a second truck roll.
  • Ignoring the customer promise. A route that is 12% tighter but misses two time windows is a net loss once you count the callbacks.
  • Technicians silently routing around it. If they do not trust the sequence they will drive their old route and close jobs out of order — watch for that in week one.
  • Buying a standalone optimiser when your field service software already has one you have not turned on.

07 — How you would actually do it

  1. 01Get one month of actual job locations, durations and travel times out of your existing system.
  2. 02Build the skills matrix honestly — who can genuinely do what, not who is signed off on paper.
  3. 03Run the optimiser in shadow mode against last month and compare its routes to what actually happened.
  4. 04Pilot with two vans and a dispatcher who is willing to be wrong.
  5. 05Fix the time-window and skill constraints before rolling wider.
  6. 06Track miles per job, not miles saved — the denominator keeps you honest.

08 — Tools worth looking at

ServiceTitanDispatch optimisation built into the platform most established trades already run.
Jobber / Housecall ProLighter routing for smaller crews; often enough under ten vans.
Routific / OptimoRouteStandalone optimisers if your FSM software has none worth using.

Named for orientation, not endorsement. No affiliate arrangements, and nothing here has been paid for.

09 — Run it on your numbers

Start from industry averages, then drag the inputs to match your business. The number moves live.Drag each input to your number — the starting points are neutral midpoints, not industry data. The number moves live.

Worth to your business
$12,600per year
Modeled — industry averages
Revenue$0Modeled
Cost savings$16,800Modeled
Hours / week0Modeled
Industry averages
8 people
Industry avg: 8 peoplePlaceholder — not a validated benchmark
12 miles
Industry avg: 12 milesPlaceholder — not a validated benchmark
0.7 USD
Industry avg: 0.7 USDPlaceholder — not a validated benchmark

10 — The evidence · what others report

No hard numbers reported.

Reported numbers are third-party claims, source-attributed — not verified by me, and never blended into the model above.

11 — Questions owners ask

Every figure is Modeled — computed from industry-average benchmarks against the scenario’s formula. Move the sliders to your own inputs and the numbers recalculate live. Nothing here is a promise; it is a starting estimate you can pressure-test.
The library is organized by department, outcome, effort and readiness so you can find what fits. Add scenarios to your plan, tune the inputs, and see the combined picture on your plan dashboard.
Want this to be a Projected number? That's what the Audit produces — my forecast on your real data, with my name on it.
Build means a custom system is the right move; Buy means an off-the-shelf tool wins; Bin means the math does not justify doing it at all. Binned scenarios can be favorited for reference but never enter a plan.

Is this your business?

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