The IRS set the 2026 business standard mileage rate at 76 cents per mile, effective July 1, up from 72.5 cents at the start of the year. That figure, intended as a standardized deduction and reimbursement benchmark, is a useful floor for costing drive time. For companies running pickup trucks or vans, the default vehicle class for canvassing and field service, the real number is higher. AAA’s 2025 Your Driving Costs analysis puts a pickup truck’s full ownership and operating cost at roughly 98.5 cents per mile at 15,000 miles a year, about 76% more than a small sedan’s 55.87 cents.
Multiply either figure across a fleet of ten to thirty vehicles driving unoptimized routes five or six days a week, and windshield time stops being a scheduling inconvenience. It becomes one of the largest line items a field operation can actually control. Those miles are a byproduct of how jobs get grouped and sequenced, a decision your field service CRM either makes well or hands to whoever builds tomorrow’s schedule by hand. This guide gives you a formula for quantifying that cost, a framework for sizing territories to reduce it, and a plain comparison of manual versus algorithmic route sequencing.
What Windshield Time Actually Costs
“Windshield time” is any hour a rep or technician spends driving rather than performing revenue-generating work, whether that’s knocking a door, running an inspection, or completing a service call. It has four distinct cost components, and treating them separately makes the total easier to attack.
Non-Billable Labor
A technician or canvasser is paid for the full day, but only a portion of that day is spent on activity that generates revenue. Every hour spent driving between stops, rather than at a stop, is fully loaded labor cost with no output attached to it.
Vehicle Operating Cost
Fuel, scheduled maintenance, tire wear, and depreciation all scale with miles driven, not miles productive. A route that covers 20% more distance than necessary to hit the same stops carries roughly 20% more of every mileage-linked cost line, regardless of whether those extra miles produced a single additional sale or completed job.
Overlapping Territory Coverage
When territory boundaries aren’t clearly assigned and tracked, two reps frequently canvas overlapping blocks without realizing it, and one rep’s trip becomes partially redundant with another’s. This isn’t a mileage problem so much as a coverage-efficiency problem: the company pays for two drive trips to generate the coverage one well-planned trip could have delivered.
Inefficient Dispatch Sequencing
Jobs and leads are frequently assigned in the order they were created, or the order a dispatcher happened to see them, not the order that minimizes total drive distance across the day’s full stop list. This is the routing inefficiency most directly solvable with sequencing logic, and it’s the largest lever available once territory boundaries themselves are already reasonably sound.
The Windshield Time Cost Formula
The following formula lets an operations team calculate their own annual drive-time cost using their actual fleet data rather than an industry-average estimate.
Step 1: Daily Vehicle Cost
Daily Vehicle Cost = Daily Miles Driven × Cost per Mile
Use 0.985/mile (AAA’s full-cost pickup truck benchmark) if you want to capture true ownership cost rather than just the standardized reimbursement rate.
Step 2: Daily Non-Billable Labor Cost
Daily Labor Cost = Non-Billable Drive Hours × Fully Loaded Hourly Labor Cost
“Fully loaded” should include wages, payroll tax, and benefits, not just base hourly pay.
Step 3: Daily Windshield Time Cost per Vehicle
Daily Windshield Cost = Daily Vehicle Cost + Daily Labor Cost
Step 4: Annualized Fleet-Wide Cost
Annual Windshield Cost = Daily Windshield Cost × Working Days per Year × Number of Vehicles
Worked Example (illustrative, substitute your own dispatch data):
A 15-vehicle field team, each vehicle averaging 65 miles per day, with technicians spending roughly 2.5 hours daily driving between stops, at a fully loaded labor cost of $32/hour, driving 240 working days per year:
● Daily Vehicle Cost: 65 miles × 64.03
● Daily Labor Cost: 2.5 hrs × 80.00
● Daily Windshield Cost per Vehicle: $144.03
● Annual Fleet-Wide Cost: 518,508/year**
That figure represents the fully loaded cost of drive time alone, before accounting for a single dollar of lost revenue capacity from stops that were never reached because the day ran out of hours.
What Route Optimization Actually Recovers
Not all of that $518,508 is recoverable. Some drive time is unavoidable regardless of how well a route is sequenced. The recoverable portion depends on how inefficient the current routing actually is, which is why any specific savings percentage should be benchmarked against a company’s own historical mileage data rather than assumed.
Published research gives a wide but useful range. A Department of Energy funded study on network-wide eco-routing, published in Transportation Research Part D, found fuel savings of 3.3% to 9.3% when routing was optimized against standard shortest-time routing in simulated urban traffic. That figure reflects congestion-aware routing on its own, a conservative lower bound, because it doesn’t count multi-stop sequencing gains (the order in which a day’s stops are visited), which is a separate and often larger source of waste in field sales and service routing. Fleet telematics research from Geotab reports that the average field service technician loses more than 40% of the workday to travel, idle time, and scheduling inefficiency, a figure at the high end that likely reflects operations with little or no route planning in place.
A defensible planning range for most field sales and service operations sits between these figures. A 10% to 20% reduction in daily mileage is a reasonable target for an operation moving from ad hoc or manually sequenced routes to structured, algorithmic stop sequencing, with results varying by territory density and current routing discipline.
Additional Capacity from Time Recovered
Rather than citing an industry-average “extra jobs per day” figure, this is more accurately calculated directly:
Additional Stops per Route = Minutes of Drive Time Recovered ÷ Average Minutes per Stop
If the worked example above recovers 15% of its 2.5 daily drive hours (22.5 minutes) and the average stop (door-knocked or job completed) takes 12 minutes including setup, that’s about 1.875 additional stops per rep per day. Across 15 reps and 240 working days, that comes to roughly 6,750 additional stops per year without adding headcount or vehicles.
Industry Benchmarks for Fleet and Route Cost
For teams building their own model, these three sources provide the most defensible inputs currently available:
● IRS 2026 Standard Mileage Rate: 76 cents/mile (effective July 1, 2026), useful as a conservative, standardized per-mile cost floor.
● AAA Your Driving Costs (2025): pickup trucks run roughly 98.5 cents/mile in full ownership and operating cost at 15,000 miles/year, the more accurate figure for teams that own or lease their fleet outright rather than reimbursing personal mileage.
● DOE-funded eco-routing research: 3.3% to 9.3% fuel savings from route optimization in controlled network simulations, a defensible conservative floor for the “optimization savings” variable in any internal model.
A Step-by-Step Territory Boundary Framework
Route optimization only works as well as the territory structure underneath it. A rep assigned an oversized or poorly shaped territory will generate inefficient routes no matter how good the sequencing algorithm is. Territory sizing should be driven by addressable density, not arbitrary geography like zip codes or municipal boundaries.
Step 1: Establish Total Addressable Volume
Count the total addressable doors (for canvassing) or serviceable properties (for field service) within a candidate region.
Step 2: Set a Target Daily Capacity per Rep
Based on historical performance data, determine how many doors a canvasser can realistically knock per day, or how many jobs a technician can realistically complete, at a sustainable pace rather than a best-case one.
Step 3: Determine Cycle Time
Decide how frequently the full territory should be covered (for example, every 10 working days for a canvassing sweep, or as-needed for service dispatch).
Step 4: Calculate Required Rep Count
Reps Needed = Total Addressable Volume ÷ (Daily Capacity per Rep × Cycle Days)
Step 5: Draw Boundaries Along Natural Travel Barriers
Once headcount is set, divide the territory using natural geographic boundaries such as major roads, rivers, and rail lines, rather than straight lines through a map. Straight-line divisions frequently split neighborhoods and force reps to cross barriers that add drive time without adding coverage.
Step 6: Audit for Overlap Quarterly
Territory boundaries drift as reps are added, removed, or reassigned. A quarterly audit comparing actual GPS-logged coverage against assigned boundaries catches overlap before it compounds into a recurring cost.
Windshield Time Audit Table: Unoptimized vs. Optimized
| Metric | Unoptimized (Manual/Ad Hoc Routing) | Optimized (Structured Sequencing) |
| Daily miles per vehicle | Determined by rep’s own judgment or lead order | Sequenced to minimize total distance across all stops |
| Territory boundaries | Static, rarely audited, often overlapping | Density-based, reviewed quarterly |
| Dispatch order | First-in, first-assigned | Proximity- and priority-weighted |
| Drive-time visibility | Estimated from odometer readings or self-reported logs | Tracked in real time against planned routes |
| Route replanning | Manual, reactive to cancellations or reschedules | Automatic resequencing as the day’s stop list changes |
| Cost attribution | Aggregated fleet spend, not tied to individual routes | Cost-per-route and cost-per-stop calculable |
Manual Tools vs. Structured Route Logic
Spreadsheets and basic point-to-point navigation apps share the same structural limitation: they optimize for a single leg of a trip, not the full sequence of a day’s stops. A navigation app will find the fastest route from Stop A to Stop B, but it has no visibility into Stops C through J, and no mechanism for reordering the full list to minimize total distance. A dispatcher manually sequencing stops in a spreadsheet is solving a version of the classic vehicle routing problem by hand, a problem that scales in complexity extremely quickly as stop count grows, and one that most manual processes solve only approximately, if at all.
Structured route-sequencing tools solve for the full stop list at once, which is the mathematical distinction that produces the savings modeled above. This is a logistics-optimization function, not a mapping function. One tells you how to reach a single place; the other tells you what order to visit them all.
How Map-Based Software Executes This in Practice
The framework above works regardless of what tools a team uses to execute it, but the execution layer matters, because manually applying a territory framework and re-sequencing routes daily is itself a labor cost if done by hand in a spreadsheet.
Knockio is one example of software built around this specific function: territory dropping lets managers define and adjust boundaries directly on a map rather than through address lists, live rep tracking gives visibility into actual GPS-logged coverage versus planned coverage (the same data needed for the quarterly overlap audit above), and route planning applies sequencing logic to a day’s full stop list rather than one leg at a time. Field logs capture drive and stop-time data that can feed directly back into the cost formula outlined above, replacing estimated inputs with actual figures.
For teams evaluating this category of tool, Knockio’s Prospect plan is oriented toward canvassing and route-based territory work, with core route optimization and territory features included. Teams needing job-level dispatch routing in addition to canvassing typically look at the Organize tier. Native integrations with Zapier, Salesforce, and Google Calendar allow route and territory data to sync with scheduling and CRM systems already in place, rather than requiring a standalone system.
None of this replaces the underlying math. A tool can execute sequencing logic and surface real-time tracking data, but the territory boundary framework, the cost formula, and the discipline of a quarterly overlap audit are operational decisions a platform can support but not make on a team’s behalf.
Closing the Loop
Windshield time is one of the few cost centers in field operations that’s fully quantifiable with data. Most companies already have mileage logs, labor rates, and stop counts. Running the formula above against actual fleet data, rather than assuming an industry-average savings percentage, gives operations leaders a specific, defensible number to target, and a way to verify, quarter over quarter, whether territory and routing changes are actually recovering that cost or merely feeling more organized.
Frequently Asked Questions
What is windshield time?
Windshield time is any hour a rep or technician spends driving instead of doing revenue-generating work like knocking doors or completing service calls. It carries non-billable labor and vehicle operating costs, and it grows worse when territories overlap or dispatch orders ignore distance.
How do you calculate the cost of windshield time?
Add the daily vehicle cost (daily miles × cost per mile) to the daily non-billable labor cost (drive hours × fully loaded hourly rate), then multiply by working days and number of vehicles. Use 0.985/mile for AAA’s full pickup-truck ownership cost.
How much can route optimization save?
Benchmark against your own mileage data rather than an industry average. Controlled studies show 3.3% to 9.3% fuel savings from congestion-aware routing, and a 10% to 20% reduction in daily mileage is a reasonable target when moving from ad hoc routes to structured stop sequencing.
How big should a field territory be?
Size territories by addressable density, not by zip code. Divide total addressable volume by daily capacity per rep multiplied by cycle days to get the rep count you need, draw boundaries along natural barriers like major roads and rivers, and audit for overlap quarterly.
Sources
Internal Revenue Service, “IRS Sets 2026 Business Standard Mileage Rate,” and subsequent mid-year adjustment to 76 cents/mile effective July 1, 2026, per IRS Announcement 2026-11.
AAA, Your Driving Costs 2025. Annual analysis of new-vehicle ownership and operating costs across nine vehicle categories, including pickup trucks, based on 15,000 miles driven per year.
Ahn, K. & Rakha, H., “Network-wide impacts of eco-routing strategies: A large-scale case study,” Transportation Research Part D: Transport and Environment, vol. 25 (2013), pp. 119-130. DOE-supported research on network-wide fuel consumption savings from optimized routing versus standard shortest-time routing.
Geotab, “Why field service routing decisions are costing you more than fuel.” Fleet telematics research on technician workday loss attributable to travel and routing inefficiency.
Author Info:
Waqar Hussain leads SEO and digital media at Knockio, a field sales and field service management (FSM) platform for businesses managing sales reps, field teams, jobs, and customer appointments. He focuses on content strategy, search growth, and digital media to help more teams discover better ways to manage leads, jobs, and field operations.