What would you do if you could clone the best manager at your company? Lazer Logistics, a yard logistics company that helps major retailers and manufacturers manage freight from dock to warehouse, is doing just that with the help of artificial intelligence.
Mike Murphy, the company’s senior vice president of garden solutions and innovation, built an AI coaching tool embedded within the operating system. Melanie Sandlin, Lazer Logistics’ chief information officer, said the “Uncle Phil AI,” modeled after the company’s COO Phil Newsom, will give field managers access to the kind of organizational knowledge that previously existed only in Newsom’s head.
“You put Phil in any yard and within minutes you know what’s working, what’s not working and what exactly needs to be changed. Drivers love him. Field managers learn from him. He’s the guy we want every operator in our network to have access to every day,” Sandlin, who has 36 years of logistics experience, told Newsom’s Business Insider. “The problem is we have one Phil and 750 sites. So we asked ourselves, ‘What if we could change this?’
Uncle Phil AI pulls data from across Lazer Logistics’ connected systems that manage truck telematics, in-cabin video, maintenance, driver inspection reports, labor data, and yard management workflows on one platform. This gives site administrators access to real-time insights and actionable guidance that they wouldn’t otherwise see.
“Instead of managers having to open up four different systems and piece together the picture themselves, Uncle Phil reveals what’s important: This is what’s happening, this is why it’s happening, and what a good operator would do about this,” Sandlin said.
Unlike warehouses, which have become increasingly automated over the past few decades, yards, which manage the flow of trucks, trailers and containers into and out of a facility, are among the last parts of the supply chain to undergo technological upgrades, said Bart de Munck, a supply chain strategy advisor and independent consultant with more than 35 years of supply chain experience, including roles at Gartner, Project 44 and YMX Logistics.
“We have very clear KPIs when it comes to warehouses, we have very clear KPIs when it comes to transportation, and no one has KPIs when it comes to yards,” De Muynck said. “No one really understands how inefficient they are or what impact it really has on their organization.”
AI has the potential to help yard operators see their data during operations, enabling a shift from reactive to predictive decision-making, De Muinck said. And in a yard environment where conditions are constantly changing due to weather, equipment breakdowns, employee calls, spikes in cargo volume, and more, Sandlin says quick decision-making is everything.
“Most shipyard operations today still lack real-time awareness of what is actually happening across the site,” says Sandlin. “Where is that trailer? Why is that dock backed up? Which truck has been idle for two hours and why? If you don’t have answers to these questions every time they come up, you’re always reacting.”
AI turns operational knowledge into scalable assets
In order to be able to make quick and accurate decisions, it is important to have the knowledge to back them up. Sandlin said Lazer Logistics has found that typically only its most seasoned employees have that knowledge.
Sandlin said Uncle Phil AI is trained on Newsom’s 30 years of operational knowledge and can serve as a partner for operators who don’t have a reliable level of experience when managing issues. Sandlin says this works especially well because yard work is pattern-driven.
“The movements, sequences, and conditions that cause delays and incidents are not random. They follow patterns that can be learned. AI is very good at recognizing these patterns at a scale that human teams cannot manage across 750 sites simultaneously,” Sandlin said.
For field managers who make dozens of decisions every day, including where to prioritize trips, how to respond to breakdowns, when to change staffing levels, and whether drivers need coaching, this type of guidance makes a real difference in how trucks are handled, making operations faster, safer, and lower costs, Sandlin said.
Since implementing Uncle Phil, Lazer Logistics has seen operational results, and by digitizing vehicle inspection reports and eliminating paper from the process, field managers have regained more time in their day previously spent on manual entry, Sandlin said.
“These aren’t flashy AI numbers, but they represent something important: Our employees, our best assets, are spending less time on administrative friction and more time doing the work that actually matters: coaching drivers, serving customers, and running a better yard,” Sandlin said. “Clean, consistent, real-time data is flowing out of the field like never before. This is the fuel that makes Uncle Phil AI possible.”
Implementing AI requires a solid data foundation
Sandlin said that before Uncle Phil AI, Lazer Logistics had made investing in data infrastructure a priority. He said most companies looking to implement AI are often working with sparse, inconsistent, or siled data and wonder why they’re not performing well.
“Our choice was to first build the data foundation,” Sandlin said. “Connecting truck telematics, in-cab video safety systems, yard management workflows, maintenance and repair records, and workforce and schedule data into one controlled, trusted layer of data took a lot of discipline, but that’s why what we’re doing with AI really works.”
De Muink said updating data collection processes is the starting point for most companies’ technology efforts when it comes to yard operations. He added that using AI on bad data will only amplify bad suggestions and actions.
“Before, we only used data for business analysis, so even if the data was wrong, it was already in the past. But now we use data to predict things, prescribe actions, and automate workflows,” de Muink said. “If you build it on bad data, anything you get from it will be bad as well and can lead to bigger problems.”