In logistics, profitability, provability frame IoT adoption

Predictive Analytics

Predictive analytics is tied into tracking and tracing technologies that are now commonplace, especially since electronic logging devices for truckers was mandated by the US government. The data is available. It’s just a matter of collecting, collating and analyzing past performance to help determine future action.

“There are times when it’s as simple as [being] connected to a device in a cab,” explained Bob Boyle, a vice president with managed logistic services at Odyssey. Or, he added, connection involves an app linked to a driver’s cellphone.

This has obvious applications to performance. Technology providers can aggregate the data and run them through algorithms that predict, in the most basic terms, whether the shipment will arrive in time. Other analytics enable drivers and trucking operators to make more informed decisions about time and route.

“We’re always looking for better efficiencies,” said Midkiff. “And in this world of data, now that we have collected so much data how can we use it better. “there are many avenues out there that we’re currently exploring.”

5G can — and undoubtedly will — up the ante considerably. Coverage outside metropolitan areas will be much more dependable. The amount of information that can be analyzed will increase substantially. Latency — the delay between the time a request for data is made and that data is transferred — will drop dramatically. “The ability to have greater visibility and transparency is probably the critical element that’s viable sooner rather than later,” Boyle said.

This will benefit both shippers and transport operators, he added, and in obvious ways. Shippers want delivery as quickly as possible, or, at the very least, don’t want to be surprised by late arrivals. On the other hand, “If I’m operating a fleet, I get paid when the fleet is moving,” Boyle said. “I want that truck or those assets to be moving as much as possible.”

Logistics-related data analytics isn’t a new phenomenon. However, it’s being applied in different and more compelling ways as data collection is bolstered and speeded up. For example, various data points have been channeled into specific areas, for example, procurement, safety, operations. Now, said Boyle, there’s realization that the data serves cross-purposes and these individual silos are no longer relevant. “If the data is going to come quicker and it’s going to be more relevant then it’s likely going to touch more than one functional area,” he explained. “What we’re seeing is that if those walls are not broken down [yet] they’re going to be broken down really soon because it’s an entire ecosystem that has to operate through this.”

The digital freight marketplace is one such broad-based application. Technology companies such as Freightos now match carriers and shippers through online portals, which automate freight rate management, capacity, pricing, availability and routing. This threatens to upend traditional contracted shipping, although it’s now being used to supplement rather than replace existing relationships.

“Why not take the opportunity to lower the cost and gain the service capacity as well? You’re getting that data because there are trucks right there,” said Boyle. “It’s going to be somewhat of a fundamental shift in how we look at our commercial activity in the transportation space.”

Some carriers may try to resist this data-heavy exercise, but they do so at their own peril, Midkiff, for one, warned. “In the next two to three years, you’re going to start seeing a rationalization of carriers. Several will disappear because they have not been able to or they’ve made the decision that they did not want to dive into the data pool,” he said. “You have to do minimal things to play. And I think that those carriers that have decided not to move forward as some of their competitors have in the world of data will disappear.”