Leverage Deep Learning Tech to Improve Logistics Operations

Technologies such as deep learning and artificial intelligence are quickly transforming entire industries, including logistics. Consulting firm McKinsey even says deep learning could one day become “the secret sauce in many different business processes.”

A recent article from the Financial Times shines a light on deep learning, a technology that offers tremendous potential for supply chains and manufacturing. The term itself “refers to the use of artificial neural networks to carry out a form of advanced pattern recognition. Algorithms are trained on large amounts of data, then applied to fresh data that is to be analyzed,” says Richard Waters, the article’s author.

Think of deep learning as a subset of machine learning—a technology GlobalTranz employs within its TMS and other supply chain systems. According to Forbes, “Machine learning takes some of the core ideas of artificial intelligence (AI) and focuses them on solving real-world problems with neural networks designed to mimic our decision-making. Deep Learning focuses even more narrowly on a subset of machine learning tools and techniques, and applies them to solving just about any problem which requires ‘thought’ – human or artificial.”

The Power of Deep Learning in Logistics

One of the most common applications of deep learning and machine learning is an area called predictive analytics. Within the GlobalTranz TMS, deep learning technology is used to help shippers make better decisions. For example, if you’re looking at lane planning, a traditional analytical model would look at a fixed set of assumptions. Analytics based on deep learning can consider dynamic attributes like weather or traffic and self-evolve over time to recognize patterns that humans would not see.

We also use deep learning to help companies track financial forecasts, pace and flow of production, and order processing. These data points, combined with insights into carrier capacity and performance, allow companies to answer questions like, “How many more orders can we service within budget for a given set of lanes? Or how much can we increase manufacturing without going over our freight budget?”

In other areas of the supply chain, experts see more uses of deep learning in: “predictive equipment maintenance, yield optimization, procurement analytics and inventory optimization,” says Mr. Walters, Wired Magazine author.

Companies that are quick to adopt deep learning technologies could also reap gains in value. McKinsey says, “Depending on the industry, the value a company could gain from applying this technology could range from one to nine percent of revenues.”

How Can You Get Involved Without Spending a Fortune?

The good news is for you to take advantage of these emerging, cutting-edge tools, you don’t have to buy the technology. Instead, partner with a 3PL that owns a robust TMS with integrated deep learning and machine learning capabilities. GlobalTranz’s TMS gives users the capabilities they need to employ this nascent technology and deliver more informed suggestions that help automate logistics decisions and drive supply chain efficiency.