How Route Optimization Reduces Delivery Costs (and How to Measure It)
Route optimization reduces delivery costs by cutting the driving time and kilometres needed to visit the same stops, and by cutting the time someone spends planning routes by hand. Used with good stop notes and proof of delivery, it also reduces failed and repeat deliveries. The size of the saving depends on how your routes are planned today, so measure it against your own baseline, not vendor averages.
This article breaks delivery costs into parts, shows which ones optimization affects, gives a worksheet with clearly stated assumptions, and explains how to measure the saving honestly.
Where delivery costs come from
For most small delivery operations, the cost of one drop is made up of:
| Cost component | What drives it | Does route optimization affect it? |
|---|---|---|
| Driver time | Wages or your own time; driving plus time at each stop | Yes, the driving part |
| Vehicle running cost | Fuel, tyres, servicing, depreciation, registration, insurance | Yes, the per-kilometre part |
| Tolls | Toll roads used | Yes, if the tool can avoid tolls or compare |
| Failed and repeat deliveries | No one home, wrong address, no access | Indirectly: notes, access codes, proof, retry planning |
| Planning and admin time | Ordering stops, writing run sheets, answering "where's my parcel?" | Yes, planning time |
| Overtime and extra vehicles | Routes that do not fit in a shift | Yes, by fitting more stops in a shift |
| Software | Subscriptions, add-ons | It is a new cost; see what software should cost |
Cost-per-drop worksheet
Use your own numbers. The example below uses stated assumptions, not data:
Prefer to do it on screen? The free cost per drop calculator does the sums with your own numbers, and the ATO cents-per-kilometre calculator shows the tax-deduction rate for your kilometres.
- One driver, 100 stops a day, 220 days a year.
- Driver cost A$35 an hour (assumption).
- Vehicle running cost 91 cents per km. This is the ATO's 2026-27 cents-per-kilometre rate, which the ATO says covers all car expenses including fuel, maintenance, registration, insurance and depreciation. It is a tax figure for cars, used here only as a rough proxy; vans and heavy vehicles cost more.
- Before optimization: 7 hours driving + 5 hours at stops, 180 km a day.
| Line | Calculation | Per day |
|---|---|---|
| Driver time | 12 h × A$35 | A$420 |
| Vehicle running | 180 km × A$0.91 | A$163.80 |
| Total | A$583.80 | |
| Cost per drop | A$583.80 ÷ 100 | A$5.84 |
Now suppose optimization saves 45 minutes and 25 km a day on this driver's routes (an illustration; measure your own):
| Line | Saving per day | Saving per year (220 days) |
|---|---|---|
| Driver time | 0.75 h × A$35 = A$26.25 | A$5,775 |
| Vehicle running | 25 km × A$0.91 = A$22.75 | A$5,005 |
| Total | A$49.00 | A$10,780 |
That would bring the cost per drop from A$5.84 to about A$5.35. Your result could be larger or smaller: a driver who already plans well will save less; a new driver in an unfamiliar area may save more.
Which levers reduce costs the most?
1. Better stop order
The direct effect of optimization: the same stops in less driving time and fewer kilometres. The gain is largest when stops are entered in manifest order or ordered by eye. Map distance misleads; in our 24-stop test, ordering stops by straight-line distance took about 20 minutes longer than the optimized order.
2. Fewer failed deliveries
A failed delivery costs a second trip, or a parcel back to the depot. Reduce failures by:
- Storing access codes, gate instructions and "call on arrival" notes on the stop.
- Recording a reason for every failure, so repeat problems (a business closed on Mondays) become visible.
- Capturing proof of delivery so "not received" claims can be checked.
3. Less planning time
If someone spends 30 minutes each morning ordering stops by hand, that is around 110 hours a year for one route (30 minutes × 220 days). Optimization takes seconds.
4. Fewer kilometres per stop
Fuel and wear scale with kilometres. Choosing time-efficient routes usually cuts kilometres too, but not always; see fuel-efficient routes for when they differ.
5. Tolls
Toll roads can save time on long legs and waste money on short ones. Compare the same route with tolls on and off.
6. Routes that fit the shift
If routes regularly run into overtime, optimization can bring them back inside the shift. If they still do not fit, the honest answer may be more drivers or fewer stops per route.
How to measure the saving honestly
- Record a baseline. For two weeks, log kilometres (odometer), hours and stops per route, using your current method.
- Optimize for the next two to four weeks with the same areas and similar volumes.
- Compare per stop, not per day: kilometres per stop and minutes per stop. Volume changes otherwise hide the effect.
- Note what changed besides routing: new drivers, new areas, school holidays, weather.
- Treat vendor percentages as marketing until you measure. For example, Routific's pricing page says it has seen "anything from 15%~40% reduction in mileage, drive time, and fleet size"; that is a company-stated range across its customers, not a forecast for your routes.
How MiliRoute helps you measure it
MiliRoute is an AI route optimization app for couriers, delivery drivers and small delivery fleets. When you optimize, it records the distance and estimated driving time of the order you entered and of the optimized order, both from the same Google road-routing data. Then:
- Each route's analytics show distance saved and time saved, deliveries per hour, average time per delivery and estimated time at each stop, and can be exported as a PDF.
- Your Profile totals the distance saved across routes and, using the fuel cost per km you set in App Settings (in AUD), shows an estimated amount saved on expenses.
These figures compare the optimized order with the order you typed in, so they are a fair measure only if you would otherwise have driven in that order. Stop-entry tools (camera scanner, favourites) cut planning time, and stop notes, access codes and proof of delivery help reduce failed deliveries. MiliRoute is free for routes of up to 10 stops; Premium is A$15/month.
Conclusion
Delivery costs are mostly driver time and vehicle kilometres, and route optimization reduces both by finding a better order for the same stops. The other big lever, failed deliveries, depends on information at the door. Build a simple cost-per-drop worksheet, measure a baseline, and judge any tool on your own numbers. Then read about planning a multi-stop day or the wider guide to route optimization for delivery fleets.
Measure it on your own runs: create a free MiliRoute account, optimize a route and open its analytics.
Frequently asked questions
How does route optimization reduce delivery costs?
It finds a stop order that takes less driving time and distance for the same stops, reduces time spent planning, and helps routes fit within a shift. Fewer kilometres also mean lower fuel and wear costs.
How do I calculate cost per delivery?
Add the day's driver cost (hours × hourly cost) and vehicle running cost (km × cost per km), plus tolls and other direct costs, and divide by the number of stops delivered.
How much can route optimization save?
It depends on your starting point. Measure a baseline for two weeks, then compare kilometres and minutes per stop after optimizing. Vendor percentages are averages across customers, not predictions for you.
What causes failed deliveries?
Common causes are no one home, wrong or incomplete addresses, no access to the building, and business closures. Notes, access codes and recorded failure reasons help reduce repeats.
Is the ATO cents-per-km rate my real vehicle cost?
No. It is a tax-deduction rate for cars (91 cents for 2026-27). It is a reasonable rough proxy for small cars, but use your own fuel, servicing and depreciation figures where you have them.
Does route optimization reduce fuel costs?
Usually, because shorter driving time often means fewer kilometres. Routes optimized for time are not always the shortest in distance; see our fuel-efficiency guide.