Tracking Technology For All Shipments
Some leaders in the shipping space argue that this view is shortsighted—and could cost companies far more than they realize. Without the data that tracking technology could provide, they believe, many shippers lose out on important insights into their general cargo—data that could significantly improve travel timelines and ultimately justify that initial cost.
Two of these leaders are Maersk, a provider of transportation and logistics services, and Tive, a global leader in supply chain and logistics visibility technology. Both organizations felt that the potential value of tracking insights into general cargo was too important to overlook. So when Erez Agmoni, global head of innovation at Maersk, and Krenar Komoni, founder and CEO of Tive, crossed paths at a supply chain event at MIT a few years back, it was no surprise that they found a common purpose.
Both Agmoni and Komoni knew that tracking technology was too costly to be used across every type of cargo. “Unless it’s valuable, perishable cargo,” says Agmoni, “nobody will want to just go and track every single container, every single shipment—especially considering a few years ago, when it was really expensive.” Agmoni and Komoni knew they needed to develop a more affordable solution that could provide data that was actually relevant to all types of general cargo shipments.
A Successful Proof of Concept
In the years following the MIT event, Agmoni and Komoni explored alternatives that could offer the value they sought at a price point shippers would accept. The first step in their experiment was to design a proof of concept. The team at Maersk took on the task, beginning with outreach. “We went to customers, we brought them in, we started some discussions,” says Agmoni. “We looked into what could help them improve their supply chains.” Over the course of their research, customers commonly expressed frustration with transit times: They were unreliable, inaccurate, and did little to help them plan around the situation at hand.
That’s when Agmoni had an idea. Instead of tracking each individual shipment—which, as customers were saying, wasn’t providing the information they actually needed—they could also track aggregated data.
The Maersk Innovation Center designed a proof of concept for a means of keeping tabs on thousands of shipments without having to view each one individually. In other words, they would track aggregated data from thousands of shipments, starting with a route from Los Angeles to Memphis.
Tive, meanwhile, started building the hardware and the backend technology. Once the product was ready, Tive ensured that all of the trackers were properly installed at the warehouse in Los Angeles, and that each of them was linked to the appropriate shipment and order.
From there, Tive’s data science and data analytics teams, with input from Maersk, went to work analyzing the data from the trackers—looking at which algorithms they wanted to run on the dataset to figure out what insights they could gain. “Working together, we were able to find some really interesting things,” says Komoni. In the end, the higher-level view yielded surprising insights.
Aggregated Data Shows the Way
On the drive from Los Angeles to Memphis, there are two main routes from which truckers can choose: a southern route, which runs near the U.S.–Mexico border, and a northern route, which is a slightly more direct line from point A to point B. On all navigation systems, the northern route is estimated to be two hours faster than its counterpart. But when Maersk and Tive started looking at the aggregated data, they learned something that they couldn’t have known from individualized tracking information.
“When we started to look at the aggregated data,” says Agmoni, “we found out that the northern route is taking six days, plus or minus two—so four to eight days.” Though Google Maps will estimate the drive to be 32 hours, it’s expected that drivers will need to stop and rest along the way, stretching the trip out into several days. But when they looked at the presumably slower, southern route, the average driver was completing the trip in four to six days. Not only was this faster, but the driving estimate was more precise.
To understand why this was, they had to go back to the data. Using a collection of tools and graphs that they’d custom built for this purpose, Tive began to calculate the idle times along each route. “What we said is, ‘why don’t we figure out where the trucks are stopping for the longest time?’” says Komoni. “And then we mapped that out, and we saw these big red spots on areas where they’re stopping on the southern route and also where they’re stopping on the northern route.”
It quickly became clear from the data that drivers on the northern route were stopping much more frequently than on the southern route. “We couldn’t know why they’d do that,” says Agmoni, “so we had to call some of them. And we learned a very interesting thing.”
Driving Route Decisions with Data
After speaking with some of the drivers, they learned that rest stops on the northern route are small and, more often than not, completely full. “It’s a very busy route,” says Agmoni. “They don’t trust that there will be space at the rest stop when they’ve reached the maximum hours of driving. So they start looking two or three stops beforehand. If there is one, they stop; if not, they’ll go to the next on the route.” On the southern route, however, the stops are more reliable. Drivers can trust that when they need to make a stop, there will be space for them to do so—allowing them to maximize the number of hours that they can drive, and shortening the total transit time altogether.
“That really helped us to change the way we route things. You can’t find this information if you follow one shipment at a time; you really need the aggregated data,” says Agmoni.
“It’s great insight,” Komoni adds, “because now you finally have value that you can sell. You can justify the cost on all types of general cargo—and not just on time-sensitive, temperature-sensitive, high-value shipments.”
Maersk and Tive’s proof of concept was a clear success, allowing them to move forward in the development of their product.
Data Uniformity = Increased Visibility
Using what they learned, Maersk has since developed a new product called Ocean + Transload, a solution for cargo transportation that improves transit time variability, reduces carbon emissions, and helps minimize detention and demurrage charges.
“It’s a replacement for the inland port solutions that carriers sell,” says Agmoni. Typically with intermodal travel, carriers see a lot of fluctuation in transit times. “The intermodal connection of international containers is not to the level of our customer expectation,” he says.
With Ocean + Transload, they can take containers and translate them into trailers by putting them back on the rail or on the road. “And of course we are adding visibility trackers to all those shipments at no extra cost—to provide our customers with a solution that first, gives them a much more precise time, and second, sends alerts way in advance when the shipment is about to arrive.”
Armed with this increased visibility into their shipments, customers no longer need to follow up to receive updates on the status of their shipment. Updates come to them directly.
According to Komoni, the uniformity of the data made possible by the collaboration was a central component to the solution’s success. “I think that uniformity is the real value that allows Maersk to do aggregated analytics and understand insights for their customers. There is tremendous value in uniformity,” he says.
What started as a shared frustration at the lack of tracking information on general cargo shipments resulted in not only a successful collaboration between two companies—it also provided a much-needed advancement in tracking technology and shipping analytics that will help companies make smarter and more cost-efficient decisions across the supply chain.
