The impact of AI and machine learning on specific industries is undeniable. As was with mobility, different industries will utilize new technology and leverage it to increase revenue, optimize operations, and increase productivity. Through AI and machine learning, organizations can become faster, leaner, and drive growth.
The transportation industry relies and thrives on data. Companies such as Freightwaves are building entire platforms around data. Small amounts of insight can give companies indicators of how markets are moving (pricing, capacity, demand, etc.). The transportation industry has been ahead of the curve here as well. Companies have previously used satellite technology to track cargo across the world. Now, companies can use IoT technology to capture millions of data points and then use machine learning to put these data points into actionable insights to improve operational efficiency and ultimately deliver better customer experiences.
As we continue to gather more data around transportation, companies will be able to make informed decisions around buying behavior and begin leveraging predictive analytics into their business processes. For example, an organization may know when customers will be ready to order new freight capacity. This information is important for sales brokers, but it’s also importing for capacity planning. An AI platform in transportation will be able to automate information for logistics, supply chain and planning. AI and machine learning will also play a key role in truck maintenance. By compiling information across the fleet, maintenance will be able to determine when and where the trucks will need to undergo repairs and eliminate mid-shipment breakdowns. Avoiding such breakdowns are crucial to on-time delivery and helping save on costs.
One of the major costs centers for transportation companies is delays in cargo arrival. If a shipper has committed to a certain service level agreement, it’s crucial that they achieve it. In much the same way that services like Waze have revolutionized personal travel, AI will be able to automate route management for drivers to avoid traffic across their route. As AI systems continue to grow in knowledge, traffic management platforms will be able to predict traffic patterns across the entire fleet for maximum time (and cost) savings.
Truck wear and tear is certainly something that can create havoc for transportation companies. By applying AI and machine learning technology to fleet maintenance, repairs can be done at the opportune time, identifying the balance between avoiding breakdowns and keeping trucks on the road. The enables companies to avoid losing capacity by doing preventive maintenance at the appropriate time for maximum gains.
These are key questions that all transportation companies think about daily. An AI platform can take that information, apply machine learning, and produce actionable optimizations with which a company can apply to the business, improving locations of warehouses, support hiring decisions, creating meaningful cost savings, and more.
Companies that combine AI and machine learning with lean operations will be well prepared for the future. They’ll have actionable insights they can use to drive down costs while improving operations and increasing customer satisfaction. In transportation, data is a currency, and the earlier you have it, the faster it will grow.
For more information about the challenges (and solutions) facing the transportation & logistics industry today, check this blog post where we explore how T&L organizations are tasked with cutting transportation costs, improving inventory management, and offering segmented services to their customers.
