Artificial Intelligence
Artificial intelligence is a broad term, McLeod noted, but he shared examples of what it can do for trucking and brokerage businesses.
In a subset of AI, machine learning, he said, the machine, or computer, “makes a recommendation based on certain data and parameters, then takes the outcome of that recommendation and adds that to the database and is able to improve on those recommendations.”
In the freight world, he cited two main areas where AI and machine learning can be applied: Pricing decisions and putting the right truck on the right load in less time.
Machine learning can help with pricing decisions not only on longer-term basis such as rate and bid requests for contract freight, but also on the individual load level in the spot freight market, McLeod said.
“When it comes to putting the right truck on the right load in less time,” he noted, “this is one area we’ve been at work.”
Other areas where AI can help, he said are in hiring the right driver, calling the right customer, and getting insight into drivers who need help, who may be unhappy and thinking about leaving the company.
Machine learning can help leverage actionable insights, McLeod said, citing as an example its McLeod IQ business intelligence platform, with real-world dashboards developed by customers.
He also cited the TopOrder module in McLeod’s Loadmaster TMS, where data is used to develop a star rating for each load. When a load comes in, users can see the rating and determine what they need to do, in terms of load planning or rate negotiations, to increase the score. “It can help you make better, more profitable decisions in real time.”
Improving the Driver Experience
Technology also can be used to improve the driver experience, McLeod said. He specifically cited two new modules McLeod is rolling out in LoadMaster: a new Driver Choice Module and Trip Management.
“Would your drivers feel more involved if they had something to say about the loads they’re being assigned?” McLeod asked.
The Driver Choice module has a profile for each driver, with their preferences in areas such as length of haul, time home, areas they don’t want to go, minimum revenue for owner-operator loads, etc. “We use that information to make recommendations for the next loads for that driver, so the driver’s getting assignments that fit,” McLeod explained.
On top of that, fleets can customize the amount of control the driver has of his or her loads. Owner- operators may be able to make their own selection from all of the recommended loads. Company drivers typically would have fewer options, but having choices, from loads already designed to fit their personal profile parameters, can go a long way in driver satisfaction.
McLeod later told reporters that one large customer using primarily owner-operators has been using Driver Choice since January and has found it to be such a competitive advantage, it didn’t want to share details about how well it has been working.
Trip Management helps drivers plan better and make better use of the time they have to drive, McLeod said. Using a driver’s hours-of-service and position information, a trip plan is created and displayed in LoadMaster. By taking into account road conditions, live and historical traffic patterns, and driver breaks, fleets can get more accurate, real-time estimated time of arrival (ETA) at customer stops and actual arrival time at locations, giving the planners and driver managers the ability to proactively deal with any potential service incidents at future stops.
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