Managing and using internal and external data to drive key business decisions is critical to companies in many industries. Transportation leaders focused on those tasks met at the recent McLeod Software Artificial Intelligence/Business Intelligence (AI/BI) Conference in Birmingham, Alabama.
The overarching theme of the conference was the importance of data quality (and not just data collection) to enable useful business intelligence projects.
Several speakers highlighted that great data visualization and BI starts with data quality. The approaches to achieving data quality varied. Most favored leading with data collection and quality. However, Houston Vaughn, Chief Operating Officer of P&S Logistics, took a contrarian approach. He said, “Once you start showing the data, and talking about it every day, people tend to pay more attention to the quality of their data.” Every major decision at P&S is driven by good data, because what worked with a few dozen trucks is not viable with a fleet larger than 3,000 power units. Vaughn continued, “Today, we’d rather have a fresh logistics business graduate ready to use data and technology than a 20-year veteran who can barely turn on a computer.”
Vice President of Special Projects for McLeod Software Ken Craig gave an overview of AI and highlighted areas in the logistics industry where AI is making an impact, including predictive analytics, big data, machine vision, robotics, and autonomous trucking.
Tom Curee, Senior Vice President of Strategy and Innovation for Kingsgate Logistics, discussed how his team is recording and using natural language software to transcribe calls between Kingsgate representatives and customers. “We analyze how much of the call is small-talk, and how much is business, and then compare results. This helps us coach reps on optimal strategy,” Curee said. Kingsgate is also integrating external data, including FreightWaves SONAR data, into its McLeod interface.
Kingsgate is piloting its new external data augmentation with a small group of brokers, and early indications have been promising. Curee gave several examples of alternative data about specific loads that were presented inside the McLeod platform that were more accurate than the experience-based, gut-feeling and long-held maxims of seasoned brokers.
McLeod’s data science and analytics team presented a practical overview of AI techniques in a panel led by Jonathan May, McLeod’s Director of BI. The traditionally operations-focused software company has made major investments in data science and analytics over the last 24 months. Their Data Science and Business Intelligence teams now boast more than 20 members.
I was invited to speak about FreightWaves, and the company’s use of AI and BI. AI, machine learning and deep learning are fascinatingly powerful technologies, but they’ve transcended their mathematical roots and have become marketing terms. Machine learning at its core is just brute force math. For certain problems, where accuracy and cost are more important than explainability, machine learning shines. A great example, and one used at FreightWaves, is image recognition. It doesn’t matter how our model determines that a photograph contains a truck or a car, simply that it gets the right answer most of the time. When it comes to forecasting, machine learning can achieve impressive results, but most people want an explanation of the underlying forces driving rates up or down. Traditional regression techniques are more suited to explaining the drivers behind a forecast.
Other speakers included Tiffany Giekes, Vice President of Business Process & Technology with Decker Truck Line; Brandon Exley, Director of Business Development at Barnhart Transportation; and Jesse Woods, Engagement Manager with StrategyWise.
Explaining McLeod’s rationale for hosting the event, Craig said, “We have seen tremendous innovation in the use of BI and advanced analytics on the part of our carrier and brokerage customers. McLeod Software’s goal for this conference was for each company in attendance to leave with at least one good and practical idea to take home and start working on. We believe we succeeded.”