Last mile logistics is the final step of delivery process from distributor to end user. It involves product carriers to deliver products to consumers. As the technological advancement has helped e-commerce to continue dominating global retail and sales, last mile delivery is also growing due to widening consumers’ needs and preferences.
Focusing on end users, e-commerce that adopts last mile delivery might face some difficulties during the process. According to Enmovil, “Last mile delivery becomes difficult out of route problem, and delivery cost might dramatically increase with inefficient fuel usage.” Not only that, poor vehicle maintenance and safety guidelines are amongst problems faced by logistics industry in their last mile delivery.
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However, the aforementioned problems can be reduced or even eliminated by leveraging the use of machine learning in last mile delivery process. It can be one of key driver for suppliers to achieve safety in last mile delivery. Therefore, if you want to optimise your last mile delivery, Startus Insights has surveyed 100 machine learning and here are 5 best ones you can adapt.
Detrack offers a geocoding AI called George. This service provides accurate optimisation of road without any geographical limit. Last mile delivery is all about optimising time and itinerary for final step of supply chain. AI and algorithms of Detrack can optimise, collect, and analyse mapping and geolocation. As a result, you will get an efficient, convenient, and quickest way for transport to the end users. Moreover, Detrack’s system enable self-correcting process without the need of human touch/interaction.
Consumers could change the delivery time, decide when to cancel orders or change to new orders in a quick simple way from their smartphone. This problem might cause a wayward self-updated information for stakeholders. Here, ClearMetal uses AI integration to make it possible for you to update information quickly. It also advances real-time visibility of last mile delivery process and anticipates delivery as well as tracking details. As a result, there will no more daunting process when customers cancel or update their orders.
US-based startup Freightos offers an analytics solutions which shows how to minimise future expenses by analysing past expense rates. This analytic solution can help you anticipate purchases before the order is made. In another word, it helps you understand your customer better in terms of data purchases, deliveries, customer’s questions, frequency of orders, and other ecommerce details.
Package.AI will ease logistics work in terms of mobility. It develops a chatbot voice recognition that is useful during your last mile delivery process, including changing time of delivery, editing details, cancelling order, talking to recipients via social networks, and many more. It can be useful for a driver while delivering last mile delivery to the end consumers as they do not need to go online or pick up the phone to connect with consumers.
Robby.io provide self-driving robots for last mile delivery. Their robots can memorise roads, avoid obstacles easier, detect humans, and eventually optimise last mile delivery process. Robb technologies could ease your job when you need to deliver package in villages where no car can come in or even motorbike. With the help of manoeuvrable robotics, the package can reach to final customers. Additionally, the robots can interact with human and even apologise when they unexpectedly block the way.
Read also: DHL Study on Logistics Strategies in the Race to the Urban Consumer