Introduction
AI in logistics is no new trend! AI and Machine Learning are taking the logistics industry and supply chain processes by storm. From analyzing customer experience, optimizing delivery routes, and accurate demand forecasting to optimizing warehouse management and assisting in customer inquiries, Artificial Intelligence & Machine Learning have been changing everything and optimizing logistics operations. In fact, AI technologies also help manage delivery vehicles for faster deliveries. As per the research, the global AI in logistics market size is going to hit $707.75 billion by 2034.
Artificial Intelligence is also revolutionizing manual carrier allocation so businesses can achieve a competitive edge while meeting customer demands and ensuring customer satisfaction.
In this article, we’re going to discuss what exactly AI-powered carrier allocation is. We’ll also look at how Artificial intelligence and Machine Learning are improving courier allocation efficiency to enhance customer satisfaction and help achieve faster deliveries.
What Is Automated Carrier Allocation?
Automated carrier allocation is the process of using Artificial Intelligence and Machine Learning algorithms to smartly assign carriers to shipments for last mile delivery. Unlike the manual selection process, this AI-powered carrier allocation system analyzes different factors, like cost, delivery speed, and shipment types, to fetch the most suitable carriers for your orders. This further improves the efficiency of delivery processes and boosts customer satisfaction.
Challenges in the Manual Carrier Allocation Process
Efficient courier selection is the first stepping stone towards faster deliveries and an improved customer experience. In fact, it’s one of the most important steps of supply chain management. However, if you go for traditional methods, you may encounter lots of challenges that lead to a negative customer experience. These are:
➡ Human errors: In traditional methods, you can select an overpriced carrier instead of a cost-effective one or choose a carrier with poor service quality. These can lead to issues like higher operational costs, delivery delays, poor customer experience, and even missed delivery windows. Plus, it hampers overall delivery efficiency.
➡ Time-consuming procedure: When you manually select carriers, you need to conduct extensive research on logistics companies available in the logistics industry, compare their prices, and go through their services, which is highly time-consuming. It also causes delays in the delivery process. Because of this, you fail to meet customer expectations, which negatively impacts customer satisfaction and results in significant costs because of higher fuel consumption.
➡ Lack of real-time data: With the manual carrier allocation process, it becomes difficult to access the real-time data like delivery windows and performance metrics of the logistics companies. With this poor data quality, you may end up choosing the wrong carrier. It also hinders you from assessing the latest traffic patterns, and you may face issues with choosing optimal delivery routes. Not only does it affect customer satisfaction, but it also leads to inefficient fuel consumption.
➡ Higher operational costs: Last but not least, you need more manpower in manual decision-making, assessment of traffic patterns, and data collection. More manpower means more labor costs. Plus, it also increases the operational costs.
5 Ways Artificial Intelligence and Machine Learning Improve Courier Allocation Efficiency
Artificial intelligence and Machine Learning in carrier allocation improve the overall delivery efficiency, so you can better meet customer expectations by optimizing delivery windows. In fact, these AI algorithms also help you achieve significant cost savings. Let’s check out how it’s evolving the carrier allocation in the logistics industry and easing the supply chain & delivery process.
1. Real-time data analysis
Artificial intelligence and Machine Learning-powered carrier allocation systems come pre-integrated with numerous courier companies and last mile delivery service providers. As a result, they can fetch real-time shipping data, historical sales data, and market trends across logistics companies. These AI algorithms sometimes leverage natural language processing to analyze carrier reliability, delivery times, success rates, inventory levels, fuel consumption rates, and the efficiency of the delivery vehicles to interpret logistics data. It also uses demand forecasting for route planning. This further helps in optimizing the delivery process and improving delivery speed and customer satisfaction.
2. Optimization of operational costs
These AI-powered carrier allocation systems fetch the most cost-effective carriers so you can reduce operational costs, lower transportation costs, and gain a competitive edge. They analyze data on traffic patterns to suggest customer availability, bulk shipping options, and optimize delivery routes. It helps in cost reduction by lowering fuel consumption and inventory management. On top of that, if any carrier offers discounts on shipping, AI algorithms can choose it for your shipments to reduce costs and help with operational efficiency.
3. Manual error reduction
When you opt for AI-powered carrier allocation software, you get rid of manual errors in your supply chain that can lead to delivery delays, higher fuel consumption, failed deliveries, etc. Not only will these mistakes affect your operational workflow, but they’ll also hamper customer satisfaction in the long run. With an Artificial Intelligence and Machine Learning-powered carrier allocation engine, you can eliminate such mistakes, reduce costs, save on labor costs with autonomous delivery vehicles, and ensure a smooth delivery process and maximised delivery efficiency.
4. Customization for business needs
AI-powered carrier allocation systems prioritize business needs and customer expectations to select a carrier. These AI technologies analyze various business-specific factors, such as cost, delivery zones, RTO%, SLA, traffic patterns, customer data, delivery windows, etc., to offer personalized services. These AI systems even let businesses choose the best logistics provider as per their customer preferences. Based on these, the AI technologies select the most appropriate carrier with personalized services that can better improve customer satisfaction and reduce operational costs by lowering fuel consumption.
5. Dynamic reallocation and smart load balancing
When you employ an AI-powered carrier allocation system, you can analyze traffic patterns and make adjustments in transit. In fact, these AI systems come integrated with a route planning feature that helps you fetch the most efficient delivery routes for an optimized delivery process and reduced delivery times. Historical data plays a crucial role in optimizing delivery routes. AI-powered systems analyze this historical data for route optimization. Consequently, you can reach your customers on time and reduce fuel consumption. This further helps improve delivery speed and customer satisfaction.
Plus, these AI systems distribute shipments across carriers and ensure that no carrier is overburdened. Plus, it also optimizes the use of delivery vehicles and streamlines the delivery process. This, in turn, reduces shipping delays and helps meet customer demands.
Achieve Operational Efficiency with ClickPost’s Machine Learning and AI-Powered Carrier Allocation System
ClickPost is an Artificial intelligence and Machine Learning-powered logistics intelligence software. It offers a bunch of integrations to help businesses streamline their logistics operations and gain a competitive edge. As of now, it’s connected with over 500+ carriers, WMS, and OMS systems. It also offers integrations with communication gateways to handle customer inquiries.
ClickPost’s successful AI implementation in the carrier allocation is specially designed to improve the delivery process, enhance supply chain management, reduce costs indirectly, and ensure improved customer satisfaction. It also indirectly helps reduce operational costs.
And the best part is, these AI systems continuously learn from new data, the latest market trends, and historical data to better meet customer expectations. It also offers data-driven insights into the carrier’s performance and delivery operations.
Conclusion!
AI in logistics has been proven to be a game changer. The biggest advancement in AI in logistics is AI-powered carrier allocation. If you’re a budding business, manual carrier allocation might work for you.
However, when your order volume grows from 100 to 1000 a day, you need to be very strategic and adopt Artificial Intelligence and Machine learning in carrier allocation for an optimized delivery process. Artificial Intelligence and Machine Learning-powered carrier allocation systems are quite beneficial in this case. With it, you can allocate the most suitable carrier that will make delivery operations a breeze, help in cost reduction, and improve customer satisfaction.