We surveyed a few thousand delivery businesses and found a shocking truth: 72% of them are still planning the routes for their delivery drivers manually.
If you still manually plan your routes, I would like to convince you that you can plant 86 trees a year for every driver that you employ, simply by adopting route optimization technology.
In this article, I will walk you through the methodology and the data that supports this rather bold claim. It might get a little technical at times, but bear with me. We felt it was necessary to be as transparent as possible because otherwise how would you know we weren’t making this up or just bad at math?
But first, here’s what 86 trees looks like (yes, you can count them yourself):
To calculate the environmental benefits of switching from manual route planning to route optimization technology, here are the steps we took:
- We first need to compare humans vs algorithms when it comes to planning routes.
- Then we translate this efficiency gain into reduced mileage for an average delivery business. With this number at hand, we can then proceed to translate that to an average fuel reduction per year per driver.
- We then looked at the typical fleet composition and the type of fuel they use to then arrive at the greenhouse gas reductions.
- And finally, how that CO2 reduction equates to the carbon offset of trees.
1. Humans vs algorithms
A 2017 paper studied how effective humans are with manual route planning. They presented a variety of puzzles to humans in a lab setting and were given 1 hour to complete. The puzzles looked like this:
On the easiest variant (the above picture), subjects found solutions that were on average only 9.8% away from optimal (with stdv of 7.79), whereas on the most complex variant of 39 nodes and 6 routes, subjects were on average 20.5% away from optimality (with stdv of 15.33).
Note that the lab-based puzzles on a sheet of paper are much simpler than the routing puzzles real businesses face. For one, real delivery businesses need to keep the real road network into account (as opposed to drawing straight lines). Also, the only constraint in the above experiment is capacity, whereas in the real world, business often have to consider customer time-windows, different vehicle types, and driver shifts to name a few.
The more important difference between this academic research and the real world is the fact that most delivery businesses have more than 39 addresses in a given day.
This paper showed that the larger the problem, the more inefficient humans are at solving them. We conducted a one-off study of a larger routing problem with 200 deliveries and 30 routes, and found that algorithms can find 37% shorter routes.
"Route optimization can give you 25% shorter routes as compared to your manually planned routes" - click to tweet
To summarize, humans stand no chance against algorithms. Route optimization can find routes that are 20%~40% shorter. Just to make the case of this article more convincing and believable, we stay conservative and say that route optimization can give you 25% shorter routes as compared to your manually planned routes.
2. The mileage of an average delivery driver
We took a snapshot of 200,000 routes that our customers optimized through Routific to get a sense for the average mileage a delivery driver covers in a year. Here’s what that data looks like:
The median route length we found is 39.61 miles (63.74 km). If we assume that these delivery drivers work 5 days a week, 52 weeks a year, that means that they run 260 routes a year. The total annual mileage for a single delivery driver is therefore 260 x 39.61 = 10,298.60 miles (16,572.40 km).
Now if we take the 25% efficiency gain number from the previous section and applied it, we can conclude that route optimization can reduce 2,574.65 miles a year for the average delivery driver (4,143.1 km).
"Route optimization can reduce 2,574.65 miles a year for the average delivery driver (4,143.1 km)" - click to tweet
3. Fuel savings and greenhouse gas reductions
Survey data across 2,512 delivery businesses showed that split between small vehicles (81.5%) – assumed to use gasoline – large trucks (16.8%) – assumed to use diesel – and hybrid vehicles (16.8%).
|g/km||Gasoline LDV (car)||Gasoline (low S) Hybrid Electric (e.g. Prius)||Diesel HDV (truck/bus)|
*Approved standards adopted by Canada, consistent with International Organization for Standardization (ISO) standards 14040 and 14044. See: https://www2.gov.bc.ca/gov/content/industry/electricity-alternative-energy/transportation-energies/renewable-low-carbon-fuels/fuel-lifecycle-assessment
Applying our estimated mileage savings, using the fleet composition data, and these greenhouse gas per kilometer numbers, we arrived at the GHG savings per driver per year:
4. How many trees is that?
To summarize, we’ve shown that by switching from manual route planning to route optimization technology, you can cut down the carbon emissions for your delivery drivers by 1.887 tonnes per year per driver.
To attach more meaning to this number, let’s compare it to the amount of carbon dioxide a mature tree can offset. An average mature tree can consume 48 pounds of carbon dioxide per year. Translating 1.887 tonnes into pounds, we get 4,160 pounds. So it takes 86 mature trees to offset 4,160 pounds of carbon dioxide.
So here’s how you can help the environment today: by by simply by switching from manual route planning to using route optimization technology, you’d essentially be planting 86 trees per year for every delivery driver you employ.
The numbers in this article have been reviewed by third-party environmental auditors during the due diligence process of the $1.8m grant in Clean Tech Funding From Sustainable Development Technology Canada that we were highly honored to receive.
If every business that employs drivers on the road in an urban setting would move away from manual route planning, together, we could make a very significant and positive impact on the environment.
Disclaimer: I’m the founder of Routific and we sell route optimization software. However, my goal is not to convince you to buy our software. My goal is to convince you that manual route planning is a big problem to our environment, with the hopes that you will adopt any route optimization software. In fact, here’s a review of competing route planning software, just to make your transition to technology easier.