The Data Economy: Driving Efficiencies and Sustainability Through Machine Learning

The Data Economy is a video podcast series about leaders who use data to make positive impacts on their business, customers, and the world. To see all current episodes, explore the podcast episodes library below.


Over the last several months, we’ve all learned about how hard it is to ship goods, about the backups at the Los Angeles commercial ports, and the trucking bottlenecks all over the country. Convoy is one company using real-time data, machine learning, mobile applications, the internet of things (IoT), smart trailers, and other technologies to drive supply chain efficiency, sustainability, and trucker happiness. 

Dorothy Li, CTO of Convoy, explains the trucking industry’s challenges in The Data Economy, a podcast presented by Redis and hosted by Michael Krigsman of CXOTalk. She says, “We are at a real pivotal moment, and Convoy’s digital freight network aims to solve the toughest problems in this massive $800 billion industry.”

Dorothy describes the challenges of modernizing the trucking industry, which meant going from the old days of operating with very little data and still using carbon paper forms to today’s transformation into a modern digital freight network. 

Convoy’s goals include providing meaningful services to shippers, carriers, brokers, truckers, and the entire supply chain that depends on delivering goods efficiently, sustainably, and safely.

For CIOs and CTOs driving digital transformation, Convoy’s mission and accomplishments illustrate how focusing on customer satisfaction and end-user experiences helps create new market opportunities.

Building a digital ecosystem? Start by improving the experience

Dorothy describes several industry pain points, including the 61 billion “empty” miles—35% of the 187 billion miles driven annually—meaning when truckers drive between jobs without carrying a haul. Convoy’s mobile application and IoT-outfitted smart trailers are two ways Convoy collects real-time data to help better connect truckers with nearby job opportunities. “One of the key ways we solve the empty mile problem is with automated reload, where we’re able to batch multiple shipments together,” she says.

Saving empty miles is not just an operational efficiency, and it’s one of Convoy’s sustainability efforts that helps the environment and makes the industry more enticing for truckers. Convoy also helps truckers get paid faster, reduce their time waiting at the dock or for appointments, and learn which roadside facilities have restrooms. 

Improving the trucker experience is core to Convoy’s mission. “Trucking shortage is really at the center of why we’re seeing a lot of the supply chain issues today,” says Dorothy. “And to make that profession much more sustainable, we need to improve efficiencies and make truckers’ lives better.”

Leverage machine learning to develop a multi-sided marketplace

There are several key ingredients to transforming an industry. Identifying the pain points, improving the experiences, defining broader sustainability goals, and seeking to address inefficiencies are all important starting points. But having a good business strategy needs to lead to an intelligently sequenced technology strategy. 

A key technology capability that underpins industry transformations is identifying how collecting real-time data and leveraging machine learning capabilities helps address issues for all sides of the marketplace. For Convoy, that means making life easier for truckers, providing services to the 300 thousand truck drivers in its network, and enabling flexibilities for shippers. 

Here’s one example. As technologists, we all understand elastic capacity, and it’s one reason CIOs and IT leaders modernize large-scale databases for hybrid applications and target multicloud architectures. In trucking, elastic capacity means a shipper can seek services from carriers in Convey’s network when there is peak demand and not get locked into constraining long-term contracts during soft markets. 

Dorothy explains how providing value to truckers and shippers enables them to collect the necessary data, develop machine learning algorithms, and create multisided marketplaces. “For truckers, we use machine learning to recommend the best loads for them, taking a lot of the truckers’ past preferences into consideration. And for the shippers, we provide real-time pricing and bidding information again, using real-time market conditions.”

Creating the marketplace requires a real-time mindset on what data you’re collecting, what value you’re providing to customers, and how you’re using the data to provide real-time value. That strategy gets backed into the architecture, and Convoy’s technology includes a mobile application, integrations with transportation management systems (TMS), IoT streams from smart trailers, relational databases, a cloud data warehouse, and an event-based platform that does streaming. 

And the implementation is only possible by recruiting the top data science talent away from some of Silicon Valley’s most advanced technology and data companies. You might wonder how a company in the trucking industry—historically not bleeding edge when it comes to technology—succeeds in building a platform and recruiting amazing talent.

My answer is that it starts with great leadership, a worldly mission around sustainability, a focus on improving people’s lives, and demonstrating a commitment to investing in people, technology, and data science. 

Tune in to the podcast to hear more of Dorothy’s insights on how Convoy is transforming the trucking industry, innovating a sustainable approach to improve working conditions, and using machine learning to develop its digital freight network.


Watch more episodes of The Data Economy podcast.