What is Machine Learning?

For today’s logistics professionals, machine learning is more than a buzzword. If you’re shipping goods anywhere in the world, there’s a chance you’re already the beneficiary of machine learning technology – an innovation that is helping reshape the logistics and supply chain industry.

But you don’t have to be in the industry to experience machine learning. Every time you order from Amazon or watch a series on Netflix, you experience machine learning. Algorithms passively monitor your habits and serve up similar products and content with now familiar suggestions like “You might like this,” and “Recommended for you.” Machine Learning is the adaption of the computer or software to learn, without being directly programmed what to do.

Machine Learning Helps Shippers Make Better Decisions

In the logistics industry, we are using machine learning to make quicker and better decisions that help shippers optimize carrier selection, rating, routing, and quality control processes that save costs and improve efficiency. With its ability to gather and analyze thousands of disparate data points, machine learning can help you solve a problem you don’t know is there.  Analytics based on machine learning can consider dynamic attributes like weather or traffic and self-evolve over time to recognize patterns that humans would not see.

The power of machine learning comes from leveraging data across multiple systems and data sets. We can combine all the data we have with outside data sources like GPS systems, historical pricing performance and FMCSA to help shippers more accurately predict demand, analyze trends in supply chains, monitor seasonal calendars, and track daily patterns within lanes. Overall, this intelligence can help shippers lower risk, optimize routes and even learn new lanes at lightning speeds. 

Natural Language Processing Saves Shippers Time

Natural language processing, another form of machine learning, is also drastically improving the efficiency of supply chains by speeding up data entry and auto-populating form fields.

When integrated with a transportation management system and email, chat, text and voice communication, NLP systems monitor and learn from these exchanges. Over time, the system recognizes the behaviors of specific users and begins to anticipate what they want by auto-populating shipping orders, bills of lading, and other transactions, which saves the shipper valuable time.

The benefit of using natural language processing technology is that it’s always learning. This “unsupervised learning” also improves the classification accuracy of tracking status by analyzing inputs such as weather conditions and traffic patterns.