How Port of Montreal is managing supply chain pressures

We started this program, CargO2ai, as a non-revenue-generating project focused on medical supplies and other humanitarian needs, but there’s definitely a phase two to the project. We’re basically able to enter any commodity code into the application, so tomorrow it could be auto parts, microchips, or hazardous materials.

There could be a scenario where General Motors or Ford or John Deere comes to us and says, “I want to accelerate the delivery of vehicles or parts or microchips, and I’m willing to pay extra to get that box out of there very quickly.”

It’s an important role, using data and machine learning, for example, to streamline operations.

Over the last two years, we have been working on an artificial intelligence program to better predict and synchronize vessel and train arrivals. Imagine a ship leaving Rotterdam and a train leaving Winnipeg. In an ideal world, they’d arrive at the same time. Vessels are notoriously late, especially in the last two years, and I don’t mean two hours late, more like 10 days or two weeks.

Our algorithm will better predict vessel arrivals and simulate all sorts of scenarios. Then we can have rail cars delivered on time and labor dispatched properly. We’re just starting deployment, and it’s a kind of a dashboard that becomes a single source of truth.

The entire ecosystem of the port, the terminal operators, the rail carriers, everyone will be looking at the same metrics and recommendations to help them make decisions.

We launched a trucking portal in 2016 after surveying our truckers about the maximum time they thought was acceptable for their transaction, from the moment they enter the port, pick up or drop off a container, and then leave the port. They told us that 60 minutes was the threshold. With the trucker portal, we’re monitoring and measuring the whole process in real time and relaying that to the trucking community. A green bar means the trucker can get in and out in 60 minutes or less; a red bar is 75 minutes or over.

We also have machine learning predictions that tell truck drivers how long they’re going to wait if they come now, or how long if they come in, say, 12 hours. We don’t have a reservation system here in Montreal. Truckers are free to come anytime they wish, so that’s why this tool really makes a difference.

We’ve been able to flatten the curve so we don’t have peaks and valleys of traffic. We’re also very proud to now have a quarter of trucks come to us during non-peak hours, from 3 pm to 11 pm.

Decarbonization and net zero is probably going to become the biggest challenge our industry has faced in modern history. The International Maritime Organization’s goal is to reduce the industry’s carbon emissions by 50% by 2050, versus the baseline of 2008.

That’s a tremendous objective, and we’re going to need a lot of creative solutions, digital and otherwise, to help us with this agenda.