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Route optimization for small delivery teams: what it does and when it pays off

20 October 2026 · 3 min read

Route optimization sounds like something only large fleets need. For a small team doing several stops per run, it is often the quickest way to fit more deliveries into the same day. For a team doing one drop per trip, it barely matters. Here is how to tell which you are.

What it is, and what it isn't

Route optimization decides the order of the stops, and, with several drivers, which driver takes which stops, so the total time or distance is as low as possible. It respects your constraints: delivery time windows, how much a vehicle can carry, and that a pickup has to happen before its drop-off.

It is not turn-by-turn navigation. Google Maps or Waze still gets the driver from one stop to the next. Route optimization decides what "the next stop" should be.

When it pays off

• Several stops per run. With five or more stops, the number of possible orders explodes, and even an experienced driver's guess is rarely the best one.
• Stops spread across an area. The more scattered the stops, the more a bad order costs in backtracking.
• Time windows. Fitting "between 10 and 12" and "after 3" into one route by hand is where people make mistakes.
• New drivers. Someone who doesn't know the area yet benefits most from a good order.

When it doesn't

• One or two drops per trip, such as hot food from a restaurant. There is little to reorder.
• Fixed sequences, like a route your customers expect in a set order every day.

What it needs to work well

An optimizer is only as good as what you give it. Most disappointing results come from the inputs, not the algorithm.

1. Accurate locations. A pin in the wrong place sends the driver the wrong way, however good the order. Check addresses that geocode to the street rather than the building, and fix them once.
2. Realistic stop times. Two minutes at a house and fifteen at a shopping centre make a different best route.
3. Time windows, where customers really have them, and not where they don't. Unnecessary constraints make routes worse.
4. Vehicle capacity if your vehicles fill up before the day ends.
5. Where the driver starts and ends, usually the depot or the driver's home.

Practical tips

• Optimize when the day's jobs are mostly in, and again if a batch of new jobs arrives. A route planned at 7am around half the jobs won't be the best one at noon.
• Show drivers the order, in their app, so they follow it without a phone call.
• Let drivers flag problems. A closed road or a gate code the optimizer doesn't know about is worth recording for next time.
• Don't over-constrain. Each rule you add removes options. Start with the essentials and add more only when a real problem shows up.

How to measure the difference

You don't need to take anyone's word for the savings. For a week or two, compare the same kind of day with and without optimization and track three numbers:

• Distance driven, from the odometer or fuel receipts;
• Deliveries per hour per driver;
• Late deliveries, against promised time windows.

If the routes are long and the stops scattered, the difference usually shows within days. If it doesn't, your runs may simply be too short for it to matter, and that is useful to know too.

How Coodrop does it

Coodrop's Pro plan includes route optimization for a driver's stops in one step, built on open-source routing and OpenStreetMap road data. The driver sees the stops in order in the driver app and opens each one in their usual navigation app.