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The logistics industry has evolved from its military background and is at the core of the global supply chain. It facilitates numerous transactions, from doorstep food delivery to shipping tons of raw materials across the globe.
One of the most significant upcoming developments in logistics is integrating artificial intelligence (AI) into the process. Courier companies are adopting AI elements like LIDAR (light and detection ranging) technology, semantic segmentation, object detection, 3D mapping, image classifications and segmentation, and machine learning into their operations.
So what are AI’s benefits to courier companies? Keep reading to learn more about AI integration advantages to B2C and b2b courier companies.
Efficient Fleet Management
Inefficiency is among the most prominent factors affecting courier companies’ profitability. One market research report established that companies across the board lose 20%-30% of ther annual revenue to inefficient processes and procedures. So, how can courier companies counter operational inefficiencies and maximize profits?
Fortunately for courier business stakeholders, AI integration offers viable solutions to streamline operational procedures, maximizing efficiency and profitability. Below are the primary ways AI can optimize efficient fleet management for courier companies.
First, AI technology facilitates route mapping optimization for fleets to minimize the time courier vehicles spend on the road. Several factors, including traffic jams, departure times, and unfamiliarity with road networks, increase the time courier vehicles take to ferry cargo from one point to another.
However, AI technology can utilize its route mapping function to eliminate the inefficiencies experienced while ferrying cargo. Route mapping entails using an AI algorithm to establish the shortest, traffic-free route between two points.
The AI algorithm delivers the route mapping data in real-time, helping courier fleet drivers and fleet managers for self-driving logistical vehicles to avoid unprecedented situations like car accidents by taking alternative routes. Moreover, the AI docs and parking lot occupancy detection feature helps drivers and fleet managers spend less time looking for parking and identify the most efficient parking spot for the task at hand. Route mapping optimization helps save time and lower fuel costs.
Besides saving time and money, optimized route mapping improves customer satisfaction, enhancing customer retention and referrals. Moreover, less time spent on the road means courier companies are reducing their carbon emissions. According to one US environmental report, transport accounts for 27% of the US’s carbon emissions and is the country’s highest greenhouse gas emission industry.
Also, a significant portion of courier companies’ revenue goes into vehicle repair and maintenance and time on repair downtime. However, AI’s predictive analytics maintenance feature predicts when courier fleet vehicles require maintenance and recommend preventative maintenance to avoid the time and resource wastage associated with unprecedented downtime.
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Security And Risk Detection
Besides inefficiency, cargo theft is a significant hurdle to the courier service industry and the global supply chain. According to a 2022 cargo theft intelligence report, the US is experiencing an increase in cargo theft incident volume and value of stolen goods per incident. Moreover, the situation is somewhat similar across the globe.
Cargo theft typically occurs while the goods are in transit or at a storage facility. However, courier companies can counter cargo theft by integrating AI security features into their operational procedures.
One such feature is the intrusion and theft detection function. Unlike standard intrusion detection systems, AI-centric systems have the advantage of deep learning, an AI-driven data processing mechanism that imitates human brain functioning to process data.
Therefore, AI-driven risk detection systems monitor security camera footage and isolate the location, size, and movement of the images in the footage to establish suspicious activity. Deep learning helps AI anti-theft systems accurately detect potential theft activity and accelerate incident reporting.
Second, AD-driven security systems also feature the product location and identification or recognition feature. The feature helps track stored goods’ location at all times, lowering theft risk.
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Enhanced Warehouse Management
Warehouses are crucial in the supply chain, helping to store goods at a convenient central location and facilitating inventory control. However, poor warehouse management can lead to losses from poor goods storage and damage. Therefore, AI integration is crucial for a courier service to maintain order in its warehouses, and it does so by utilizing the features below.
The first feature is order prediction, which predicts how fast goods move into and out of the warehouse. Therefore, it enables warehouse managers to organize the space, placing fast-moving goods closer to the exit to eliminate time wastage during storage and retrieval.
Second, warehouse managers may use AI-automated guided vehicles (AGV) to move goods, especially heavy products, from point to point in a warehouse. AGVs feature AI programming that instructs them to move across a predetermined path, carry a designated goods quantity and return to their charging stations when necessary.
Third, AI-driven warehouse management also entails utilizing automated sorting systems. Such sortation systems organize goods in a warehouse by identifying the items in a conveyor system using barcodes and sending the items to designated warehouse locations. Such systems help improve picking, packing, and shipping.
Proper data management is crucial in any courier company, helping maintain consumer records and prevent losses. The Bill of Lading (BoL) is among the essential documents in the supply chain that logistics companies service and functions as a legally-binding contract between a shipper and a consignment owner. Therefore, any errors or loss of BoL documentation can spell disaster for the supply chain.
AI utilizes machine learning to flag human errors in the BoL and maintain record backup. Besides record-keeping, AI-driven data management tools can use the BoLs to facilitate data aggregation for analytics and data-driven decision-making.
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Last-mile Delivery Optimization
Last-mile delivery is the final step before a courier delivers a package to its destination. Although its the most crucial step in the supply chain, last-minute delivery has numerous challenges.
Such challenges include limited visibility on the receiver’s end, high delivery costs passed onto the customer, and inefficiency, causing delayed deliveries. However, implementing the strategies above helps iron out the kinks synonymous with last-mile delivery and improves customer satisfaction. Moreover, AI technology can facilitate real-time order tracking on the customer’s end.
Courier delivery service is elemental to commerce as we know it today. The sector constantly embraces technology to meet consumers’ growing need for convenience. AI integration is the latest technology, with the potential to propel courier companies into the next frontier.
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