The pressures that delivery drivers currently face have never been greater. In an age where next-day delivery is not only an option, but a guarantee from many businesses, the demand falls on drivers to make quotas within limited time frames. Most recently, Amazon has faced scrutiny over the alleged poor conditions that their drivers work in due to immense pressure to make deliveries.
Right now, the biggest challenge involves the logistics necessary to make deliveries in less than one hour. When factoring in the time-sensitive nature of certain perishables like food, catering, health, or corporate packages, the demand becomes even greater. But with the responsibility to make fast and efficient deliveries falling on businesses, as well as the drivers themselves, could artificial intelligence be the game-changing solution?
Using AI to Optimize Delivery Routes
Anar Mammadov is the co-founder of high-tech delivery platform Senpex, which uses AI-powered route optimization, and has a median delivery time of around 55 minutes. As part of the platform features, customers can send items to multiple destinations within a speedy timeframe. It allows users to upload addresses to a list, and select a preferred delivery date and time, which then is fed through a smart algorithm to evaluate vehicle types, road conditions, and weather reports to provide the best routing experience.
“If warehouses, distribution centers, third-party logistics, or different e-commerce marketplaces have more than 1,000 to 2,000 deliveries to be delivered within two to three hours with 25 drivers, that is a challenging task,” Mammadov says. “This is where we should implement in-depth logistics and routes optimization and planning tools.”
Poor Planning Creates Stressed Drivers
“Mainly, drivers have issues with inefficient driving distances, and because of that, they are unhappy,” says Mammadov. Although, currently, the line between management responsibility and driver expectations is somewhat blurred. Is it the driver’s shortcoming if parcels are not delivered in time, when a number of uncontrollables like roadworks, weather, and human error may affect their route? Additionally, when drivers are making deliveries with a van loaded with hundreds of parcels, especially with different types of goods, the expectation that they could single-handedly make a judgment call on how best to coordinate delivery is simply unrealistic.
“Another main problem,” Mammadov says, “is if different types of products need to be collected from multiple warehouses and delivered to multiple drop-off locations.” He explains that delivery drops within one shift that include food goods for some, and pharmaceutical supplies for others, inevitably make for an inefficient strategy. “Here, we should implement a proper scheduling and coordination process on the drivers’ apps,” he adds.
AI Enables Flexibility
It’s not unusual for warehouses to have more than 1,000 shipments or more to process in a day. The most challenging issue, Mammadov says, is labeling and QR scanning to facilitate an efficient route for drivers. While this is standard practice for most warehouses, AI optimization needs to be integrated with these processes, along with radio frequency identification technology, to ensure a streamlined process from the warehouse to last mile logistics.
Above all else, Mammadov says, is that even with the help of AI, the people at the heart of these operations are human, and they require flexibility. This is where AI can assist in facilitating dynamic route changes at the last minute. This can include pushing cheaper deliveries to evenings and weekends with less time pressure, and flexible business hours to make deliveries for non-working days. This is a win-win for all parties, as pricing structures can be optimized for various types of deliveries. The importance of this technology cannot be overstated in contexts like holiday seasons where there are hundreds of drivers out on the road, almost all of whom have large volumes of deliveries to make.
Communication Is Key
Artificial intelligence may improve delivery efficiency, but it’s only one part of the wider system. Mammadov insists that open communication channels between customers, couriers, and dispatch teams are vital. “Sometimes, there are changes on the routes at the last minute by customers, which can complicate the management of returns to the warehouses if no customers are found at the drop-off locations.” AI, he says, is key for handling changes and ensuring route optimization in any scenario, but also that parties should be able to communicate with one another. By using AI to enhance practices for delivery drivers — rather than rely on it entirely — it creates space for a hybrid approach that optimizes conditions for drivers, and helps restore confidence in businesses’ to deliver on their shipping guarantees.Find out more about Senpex here.
