Your 2-Van Fleet Is Leaking Fuel: The Route Planning Fix You Need

Jan de Vries · 2026-07-13

The last mile now accounts for 53% of total shipping costs, up from 41% in 2018. For a two-van operation, that figure shows up in the day's results. The gap between a route that finishes by 3 p.m. and one that runs past dark, burns an extra tank, and pushes a driver into overtime often comes down to a single planning decision. Small teams feel this faster than large carriers do, because they have fewer trucks to absorb a bad plan. Most small delivery operations still build routes by hand. A dispatcher looks at the day's stops, groups them by rough geography, and hands each driver a list. The method works until the stop count climbs past a dozen, at which point the human brain stops finding the shortest path and starts defaulting to the order the addresses were entered. ### The Real Cost of a Hand-Built Route Two numbers explain why manual planning gets expensive. Delivery vehicles in stop-and-go urban work average about 6.5 miles per gallon and burn close to a gallon of fuel per idling hour. Empty miles, the distance driven with nothing to deliver, reached 16.7% of all miles logged in 2024. A route that doubles back, or sends a driver across town and then back to a stop two blocks from the depot, generates both problems at once. A small team cannot spread that waste across a hundred trucks. Five extra miles per driver per day, across three drivers and 250 working days, comes to 3,750 miles a year of avoidable driving. At urban delivery economy, that translates into fuel burned and hours paid that the operation never gets back. Labor is the largest line in last-mile work, close to 50% of the total, so every extra hour on the road is paid twice. > "A good route plan is like a good recipe: you follow the steps, but you also know when to adjust for the heat of the kitchen." ### The Math Behind Stop Sequencing Route planning tools solve a version of the traveling salesman problem, which asks for the shortest path that visits every stop once and returns to the start. A person can solve this for five or six stops by eye. Past that, the number of possible orderings grows too large to check by hand. A computer checks them in seconds. The savings are documented at scale. UPS built its own routing system, ORION, which evaluates more than 200,000 route options for a single driver's day before it settles on one, and reported cutting roughly 100 million miles a year, which the company tied to about $300 million in annual savings. ### Mapping Software in a Small Operation A small fleet does not need a custom system built by a logistics department. It needs a tool that imports a list of addresses, plots them, and returns a drivable order. This is the practical role of mapping software for a team that may run anywhere from two to twenty vehicles, alongside the spreadsheets and printed manifests a dispatcher already works from. Its job is to replace the guesswork in the sequencing step while leaving the rest of the operation alone. The setup is usually a matter of uploading a spreadsheet. Most tools accept a column of addresses, geocode them onto a map, and let a dispatcher set constraints such as a depot start point, a return point, and time windows for stops that must land in a certain part of the day. Geocoding accuracy matters here. An address placed on the wrong side of a divided highway can add ten minutes to a stop, so a tool that flags its low-confidence matches saves a driver from a wasted loop before the day even starts. ### Constraints Beyond Raw Distance A customer who only accepts deliveries before noon changes the order. A van with a weight limit changes which stops can ride together. A driver who knows that one bridge backs up at 8 a.m. has information the map does not. Good planning tools let a dispatcher encode these rules rather than fight them. Time windows, vehicle capacity, and required stop order become inputs the optimizer respects. Traffic is the variable that breaks a clean plan, and it is getting worse: the average American driver lost 43 hours to congestion in 2024. A sequence that is shortest among the routes that are actually drivable is worth far more than the mathematically shortest one that ignores reality. - Time windows for specific customers - Vehicle capacity limits - Known traffic bottlenecks - Driver preferences and local knowledge The bottom line? A small team can cut fuel costs by up to 20% and reduce overtime by 15% with the right mapping software. It's not just about saving money; it's about getting your drivers home before dark and keeping your operation running smoothly.