Optimize Your Route Planning with AI

Fun fact for logistics operations: the field of AI research has its own “last mile problem,” which describes the process of taking research innovations and turning them into applications that people and businesses can actually use. In the era of new generative artificial intelligence platforms like ChatGPT and DALL-E, the spotlight on the process of turning breakthrough innovations into usable tools that help businesses get smarter and more efficient has never been more intense. 

When it comes to logistics in general—and last mile delivery in particular—it’s easy enough to imagine possible impacts of AI breakthroughs: self-driving trucks, semi-autonomous supply chains, Logistics 4.0, and others come to mind. But it can be a lot harder to separate the pipe dreams from the new technologies that are actually ready to impact logistics. 

Route optimization is already a complex problem. Calculating all of the possible routes from even a small number of stops can quickly become too time consuming to be practical. This is especially true once you add time window requests into the equation.

How are businesses currently leveraging AI-powered route optimization algorithms to optimize route planning? Below are just a few of the ways…

How AI Optimizes Route Planning

Reduced Time Lost to Traffic

A report released in 2016 revealed that traffic congestion costs the trucking industry as much as $74.5 billion every year. That's the equivalent of equivalent to 1.2 billion hours of lost productivity. Traffic congestion costs are close to $6,500 per truck per year.

That was multiple years ago. Since then, demand for last mile delivery has only increased, and meeting customer demands hasn't gotten any easier.

Route planning solutions represent one of the best ways of avoiding lost fuel and travel time in spite of worsening traffic conditions. While human planners might have a sense of where the traffic is worst at what times, AI route optimization can offer more than that. It can learn about traffic patterns over time and automatically take them into account while routing.

This means that your drivers can avoid traffic jams more effectively. At the same time, you can more easily account for inevitable traffic delays when calculating ETAs. 

Faster Delivery Times

Competing with big brands like Amazon means offering faster delivery options. Even if you’re in a B2B industry, expectations have changed. That’s why it's crucial to optimize routes to ensuring the efficient delivery of orders within the right delivery windows.

Route optimization helps ensure that your drivers are spending less time on the road for each order. It makes this happen by taking road conditions, traffic, service times, driver skill levels, and more into account simultaneously.

Human planners can’t really find the routes with the shortest distances between stops unaided. And true efficiency only becomes more unlikely when last minute orders and cancellations start to pile up. But if you can reroute orders on the fly using AI and machine learning, you can start by finding the most efficient routes and then keep them time-efficient. 

Help in Discovering New Potential Routes

Route optimization also means making use of all available resources or infrastructure. When route planning has to be done by hand, the easiest thing is to stick with what you know and churn out similar routes on a regular basis—even if changing conditions are rendering those routes less optimal.

After all, road conditions change over time. Traffic patterns change and evolve. Only with AI route planning can you easily track the efficiency of your routes and find alternative routes when needed.  

Saved Time

The less time a vehicle spends on the road the more you can power the reduction of fuel cost and hours. Getting off the road an hour early can save money, which adds up when you compound it over every route. 

But driver hours aren’t the only source of saved time. When you have AI-powered route optimization, you effectively automate away the manual effort that goes into figuring out the right arrangement of stops. 

Saved time is obviously equivalent to saved money—which is exactly the goal of implementing this kind of technology. But it’s also about more than that: decreased time on vehicle routing means increased agility at every stage of delivery. It would be virtually impossible to manually reroute a day’s shipments based on order cancellations in a timely fashion.

But if you’re stuck with your current routes, you don’t have the freedom to accommodate customers’ last minute needs. On the other hand, if you can reroute rapidly, all of a sudden you’re empowered to delight your customers with agile delivery experiences.  

How to Choose a Solution That Will Optimize Route Planning

So far, we’ve mostly discussed the benefits you gain when you optimize route planning. But to provide the benefits we’ve been discussing, does it really need to be AI-powered? 

Yes. Yes it does. Why? Because so many different factors can impact drive time for trucks (everything from what the cargo is to who’s actually driving) that it’s not enough to simply calculate ETAs based on distances.

You need a system that gathers large quantities of information and learns from them over time—i.e. a machine learning- or AI-powered route planner. In this way, your routes will actually improve over time. Otherwise, they'll slowly get less efficient because the software can’t keep up with changing conditions. 

This is how you create workflows that actually account for the differences between trucks and cars, for instance. By the same token, it’s the easiest way to adjust ETAs based on who’s driving—or based on how traffic patterns have changed over the course of the year.

In this way, you don’t just optimize delivery routes in terms of distance, you also ensure that your ETAs are precise and accurate. This, in turn, forms the foundation of high quality customer experiences that will ensure repeat business and great reviews.  

Demand for last mile delivery is growing, and any business looking to compete must ensure that drivers use optimal routes. Otherwise, enterprises will lose money because of idle time, higher fuel consumption, and more driver hours. Fortunately, AI and machine learning are now being bundled into intelligent delivery management software, so you can leverage AI route planning to ensure fast, on-time, and cost-effective deliveries.