The market size for autonomous last-mile delivery is intensifying day by day and is expected to grow to almost 85 U.S. billion dollars by 2030. The demand for autonomous last-mile delivery occurred at an even faster pace than we expected back in 2016. For example, autonomous robots and drones were conceptual in 2016, and now, we see the large-scale deployment of robotics and drones in last-mile deliveries.
The last-mile delivery process is coined as the most integral part of present-day shipping companies. Today logistic companies’ are not only focusing on shipments from the transport hub, but they are also testing a series of technology solutions at every stage of last-mile delivery. This kind of extensive growth makes the last-mile carrier a strength for all retail companies, not a setback. The goal will be to deploy technology solutions that could minimize the delivery time, ensure transparency, and minimize cost with smart vehicles for last-mile operations.
The New Generation of Last-Mile Delivery
As a share of operational shipping costs, the last-mile delivery costs are substantial and 53% overall. New technologies, software, and tools, including artificial intelligence and machine learning, can quickly identify inefficiencies in the last-mile algorithms. In this post, you’ll see how AI can be applied in practical situations to minimize problems in last-mile delivery. The new generation of AI will give retailers the ability to optimize their last-mile carrier, leading to the simplification of processes and performance.
To survive the market competition, supply chain enterprises are only left with the option of optimizing last-mile delivery with technology solutions, including AI and machine learning. Successful last-mile strategy pillars are determined by speed, accuracy, efficiency, transparency, and, most importantly, a positive customer experience. Covid-19 and lockdown have changed the usual shopping ways and added more pressure on supply chain companies to ensure faster and more quick last-mile deliveries for customers.
Technology trends, especially AI in the last-mile, stood out during this disruptive phase of the pandemic. Whether big or small, supply chain enterprises must implement AI technology for improved last-mile operations in the future. We’ve all heard of stories of deliveries not showing up on time. This puts pressure on logistics companies to make it right. In this line, NextBillion AI, an industry-leading startup, recently announces custom map API solutions for telematics and last-mile logistics. The global geocode API solutions handle factors such as inconsistency in managing hours of operations, drive-pattern, and drive-time by using the advanced ML algorithm.
Let’s speak about the Amazon delivery that has begun using AI-equipped cameras across its delivery fleets. This allowed Amazon to scale up their last-mile deliveries as cameras are equipped with artificial intelligence software capable of detecting 16 different safety issues, including distracted driving, hard braking, and whether the driver is not wearing a seatbelt.
A Constantly Changed Landscape of AI in Last-Mile
Smarter ways of last-mile delivery are coming up. Implementation of AI in last-mile logistics is gaining momentum. In the coming years, there will be increased adoption of artificial intelligence for improved last-mile fulfillment. Smart tech optimizes not-mile operations and reduces human dependency that can fetch great business results in the long run. Today, enterprises consider investing in Artificial Intelligence to optimize their last-mile operations. Here is how it works.
Artificial Intelligence processes machines and software systems using human intelligence. AI has changed the ways businesses handle their logistics. This technology has the maximum impact on a company’s last-mile operations and, in the process, optimizes issues such as routing, visibility, allocation of resources, and parcel sorting. Here we will see how AI in the last-mile delivery can help logistics companies make significant optimization to compete effectively.
AI Led Geocoding
The complexity of the supply chain process increases with the number of drop locations. As the shipping volume increases, the last-mile deliveries can get complicated when distributions to be done in remote areas. The customers also write unclear addresses. Location is crucial to logistics companies and service providers looking to tailor the final steps of last-mile delivery to their customers. With Artificial Intelligence and algorithms-led geocoding, even the unclear of addresses can be converted into precise locations on a map. Accurate AI-enabled geocoding helps delivery companies to reach customer destinations faster, which leads to a higher delivery rate.
Geocoding helps to maintain accurate address information to improve accuracy in the final steps of delivery to customers in the digital age. On the other hand, inaccurate data can result in late or no deliveries and poor communication with customers.
Geocoding provides you not only precise location data but also enables the validation of pickup and delivery addresses. Geofencing is another critical component of a delivery network that ensures real-time pickup and delivery notification, reducing wait time for drivers and lowering shippers’ costs. Ingeocoding, AI aims to find and gather insights to build the best possible geospatial data by detecting patterns, outliers, and trends and understanding the distribution of data across cities, states, or countries.
The second thing is to get the data on a map. The technology helps create a map with a location that can be the center point of your data. Users can add the points to the map. With these technological features, we can make critical decisions to gather data insights.
Using AI in Geocoding, businesses can identify segmentation patterns and plot points on a map more effectively. Also, it is useful in fraud prevention by identifying unusual activity on a customer location.
AI-Backed Route Planning & Optimization
Thanks to Artificial Intelligence, route planning, and optimization are simpler and more useful than ever. AI route planning facilitates on-time deliveries even when companies deal with a high volume of packages and heavy traffic congestion. Route optimization is one of the most important advancements within logistics technology, coupled with continued improvements in Artificial Intelligence and machine learning. The ability to automatically plan optimal last-mile delivery routes is significantly improving than ever before.
As the eCommerce supply chain and logistics industry experienced the onslaught of the Covid-19 pandemic, those involved in the business realized the importance of planning and preparing better for the future. Traditionally eCommerce companies relied on zip codes for the last-mile delivery of shipments. But today, companies started creating their zones or warehouses for last-mile deliveries. However, for delivery during the festive season, hefty volumes throw off the company’s zones. This is why companies search for route optimization software that guarantees optimal delivery routes and automated recommendations for the best-suited vehicle based on the volume of shipment, delivery requirements, geographical conditions, and shipment type.
One central area of AI in route planning and optimization is creating plans and routes according to driver requirements. With Artificial Intelligence and machine learning, logistics companies can plan routes based on the driver’s performance and multiple variables. This technology trend will set companies to ensure faster last-mile delivery by utilizing real-time data and historical patterns for planning and optimization. This saves time, and more importantly, less time spend on route planning and optimization means less expenditure, fewer drivers paid hours, and less demand for delivery vehicles.
AI to Gain Last-Mile Visibility
Last-Mile visibility is the ability to track products during transit. Today, 93% of consumers want to stay more informed about their products’ location throughout the delivery process. This puts pressure on organizations to gain last-mile visibility from in-transit status to final delivery of products. Last-mile visibility is backed by AI and machine learning that allows for tracking and tracing parcels in real-time and identify issues in the process, thereby allowing companies to take proactive action to prevent customer pain.
According to a survey by Capgemini, 83% of shippers believe that last-mile visibility is a crucial factor for growth. The technology-backed solution for fleet tracking offers multiple checkpoints for tracking a package when it is received or transferred to its final destination. Customers will be alerted with emails and notifications that provide visibility throughout the delivery stages in real-time. For example, FedEx uses a tracking tool, InSight, that utilizes reference numbers for tracking orders. Amazon delivers a MapTracker to guide a delivery driver about the dropoff destination. Amazon Locker is a tool that alerts customers via text messages and emails when their package is dropped off at their residence or any other location for pickup.
As AI continues turning businesses around, it has been proven that companies have nothing to fear for unpredictability in tackling routes, weather, and address related issues. As the market moves toward a more automated future, retailers will need to tackle these challenges with technology-backed solutions to work toward perfecting their last-mile delivery, which can further refine their last-mile visibility and transparency. If done well, this results in improved accuracy and profits and proves to be a competitive advantage for any organization.
Conclusion: Think Outside the Box
The future of your eCommerce business is in your hands now. To stay competitive, retailers will need to invest in AI-backed last-mile strategies. Several useful AI and ML applications exist in today’s landscape that aid a shipping company to ensure that deliveries are completed with full transparency and visibility. So, think out of the box with AI and machine learning that simplifies human efforts in the last-mile logistics operations and ultimately paves the way for businesses.