ROI calculator

Find the cost savings hiding in utility field service

See how smarter scheduling and routing can reduce your drive time, increase technician capacity, and improve margins.

Scenario
Your fleet

Per technician, after holidays and leave.

A normal shift per technician per day
hrs
hrs
hrs
km

Including the depot round trip.

Cost

Gross salary.

/ km

Cost reduction per year, same work done
Annual cost reduction 0

A technician’s day Driving On site Admin
Today
With Timefold

    How this calculator works

    Methodology

    Same fleet, 25% less travel. Nothing else is assumed.

    The calculator holds your workload fixed. It does not assume you win more customers, sell the freed time, or grow into new capacity. It answers one question: what does this year's work cost after optimization instead of before?

    - today = technicians × salary + distance × cost per unit
    - after = fewer technicians × salary + less distance × cost per unit
    - saving = today − after

    One mechanism: shorter travel per job

    Optimization cuts the travel each job carries. Time on site does not change, and neither does admin. So the shift is the same length, but less of it is spent driving, which means more jobs fit into it. More jobs per day means the same yearly work order volume takes fewer technician-days, and fewer technician-days means fewer technicians.

    That is the only mechanism in the model. It is arithmetic on your shift, not a claim about what you do with spare time.

    - jobs per day rise by: driving × cut / (on site + driving × (1 − cut))
    - technicians saved: technicians × rise / (1 + rise)

    What moves the answer, and why

    - Hours driving is the biggest lever. It is the only thing being compressed, so the more of the day it takes, the more days you shed. At two hours a day the saving is roughly half of what it is at four.
    - Distance driven
    sets the fuel and vehicle saving on its own. Hours drive labor, distance drives vehicle cost, and the two are separate inputs because a slow urban route and a fast rural one cost very differently per hour.
    - Shift length and admin time
    change how much of the day is productive, which changes how many days the same work needs.
    - Salary and vehicle cost per unit of distance price the two savings.
    - Jobs per technician per day
    sets your volume and your cost per work order, but not the total saving. That is correct rather than an oversight: what matters is how much of the day is travel, not how the same day is sliced into jobs.

    Only the travel gain is counted

    Timefold deployments usually see a bigger throughput gain than this page shows, because optimization also matches the right technician to the right job, cuts waiting and idle time, and reduces failed visits. None of that is counted here. The calculator derives its uplift from shorter travel alone, which is why it typically lands below the 10 to 25% more jobs per day that live deployments report.

    Deliberately conservative

    Salary is used without employer charges. The vans, insurance, and depot capacity that go with the technicians you no longer need are left out. Overtime, agency hours and subcontracting are ignored, even though they are usually the first thing a shorter route bill removes. Every one of those omissions pushes the number down, not up.

    How the saving is realized

    Fewer technician-days becomes cash in whichever form fits your operation: less overtime, fewer agency and subcontractor hours, or not backfilling attrition. If you would rather grow than shrink, the same gain lets the team you already have absorb more work.

    What this is not

    These are estimates from averages. A free proof of concept runs a shadow optimization on your own historical work orders, technicians, skills, time windows and SLAs, which replaces every number on this page with a measured one.