December 7, 2022

Is AI the future of last-mile deliveries?

The implementation of AI in everyday technology has only seen recognition in the past two decades or so. The recognition however has been very exponential with every other company using the word “AI” in their processes nowadays. Whether it’s a smartphone company or a company that sells processed food, using AI to ease the job appears to be the new trend around every industry. Just like the majority of industries, the logistics industry has also started taking the help of AI to meet customer’s high requirements and short deadlines. We’ll leave the argument of “how much AI can help in supply chain management” to the experts for now, as we’ll focus more on the impact of AI on the visible part of the logistics industry–the last mile. So, Is AI the future of last-mile deliveries?

In a way. Yes.

AI and Optimized Routes:

One of the main ways through which AI can help last-mile delivery companiesin providing efficient last-mile solutions is Route Optimization. Now, Route Optimization might sound like a simple term on the surface but when we take a closer look, optimizing routes for delivery can make a huge difference. AI and ML-enabled systems can be very helpful for a logistics company when it comes to cutting costs.

AI can help last-mile delivery companies devise routes for their delivery executives that would be much more efficient and cost-effective when compared to manual routing. Usually, when a delivery executive goes out to make deliveries, they carry a number of packages for a particular area. Sometimes with manual routing, the delivery personnel might have to travel an otherworldly number of miles to deliver the product. However, if the route is optimized by an AI and ML-enabled system, the chances of encountering a time and fuel consuming delivery because route would be minimized.

AI can also optimize routes based on real-time activities going on in an area — traffic congestion, road closures — which would be close to impossible with manual routing. Not only can AI be useful while a delivery person is en route, but the AI can also be useful pre-and post- last-mile delivery. Confirming a successful delivery, taking feedbacks, analyzing those feedbacks. Assigning a vehicle to the delivery executive based on the geographical requirements of their delivery. For example, the AI can assign an escooter to the delivery person when they need to make deliveries in highly polluted areas. Similarly, the AI can assign a van or a mini-truck when the delivery packages are very big in size.  All of this can be very cost-effective, fuel-efficient, and time-saving when compared to manual delivery.

AI and Trends:

It is believed the more data you have, the accurate your results will be. Thus, feeding your AI some raw and incomplete data to get more accurate outcome –Data that can further help the employees in making crucial decisions — can turn out to be very useful.

Analyzing data to predict future events or Predictive Analysis is something that a lot of last-mile delivery companies can make use of. Real-Time analysis of data can also prove very helpful because, with the help of such analytics, one can eliminate a lot of inconsistencies. Problems and inconsistencies that could otherwise ruin a perfectly efficient last-mile delivery.

With the help of AI, company superiors can keep track of a delivery person’s performance. AI can compile assessment reports of employees that consist of their successful vs. failed delivery ratio, the average time taken per delivery, and the average of their overall ratings. AI can also assign jobs and deliveries based on this data, where deliveries with high customer requirements are given to delivery personnel with higher performance scores. In a way, AI-enabled system like this will also create a healthy competitive spirit amongst employees which could help them produce better results.