GlobalTranz, a top 10 tech-enabled freight brokerage and third-party logistics provider, announced the roll-out of GTZamp, the latest evolution of its technology platform. GTZamp is a digital freight matching solution designed for enterprise customers that uses robust big data inputs to build multi-movement shipments.
GTZamp represents the next iteration of GlobalTranz’s technology by incorporating more carrier attributes like hours of service, performance including on-time and bounce and roll percentages, cost and driver preference into its automated decision-making. Route characteristics including weather, construction, traffic and delays can be used to seamlessly generate deviations and keep freight flowing.
FreightWaves spoke to Greg Carter, chief technology officer at GlobalTranz, about the release. GlobalTranz’s ambition to build individual digital personae at the driver level is one of the most impressive elements of the new technology platform. The digital persona is part of a developing trend of digital freight brokerages thinking more like social media networks.
Sophisticated modeling of individual drivers, who have their own preferences, expertise, equipment and performance histories will be crucial to keeping them in the GTZamp platform and continuing to improve asset utilization and capacity reliability.
“We have been, at GlobalTranz and through our acquisitions, capturing an enormous amount of data,” Carter said. Carter explained that while earlier versions of GlobalTranz’s software was focused on using Carrier Affinity to recommend carriers likely to cover a load to brokers and reduce the number of telephone calls, GTZamp automates that process and tries to build multi-load routes.
“We can not only match one load at a time, but we can take a carrier and because we know its behavior, match it with as many possible loads at a time,” Carter said.
The problem that GTZamp attempts to solve is the fundamental problem at any freight brokerage – getting the right capacity in the platform, keeping it there and making it available at the best cost.
“The digital persona at the driver level is nascent,” Carter said. “A critical part of being able to even dream of something like that is to make sure when you build your model it’s not fragile, that you have a machine and a model that can be added to. Every day we’re getting more data sources that we need to feed into the machine, on carrier performance, compliance, shippers and errors.”
Over the past 13 years, experienced freight brokers at GlobalTranz have acquired an enormous wealth of tacit knowledge – details about facilities, carriers, shipper requirements and ways to creatively use equipment to cover non-standard loads – and GTZamp seeks to ingest that knowledge and put it to work algorithmically.
“We have operational experience, not just software experience; thousands of brokers in our network and hundreds in our company have been feeding us all of this information,” Carter said.
Carter cited a recent example in which a brush fire in Florida caused delays on I-75, and GlobalTranz was able to automatically build new routes around the obstruction before their drivers were tied up. One issue with building robust data sets on routes is that there are no good standardized data sets for physical infrastructure – while maritime and air cargo carriers have great data for ocean and atmospheric conditions, road conditions, highway throughput and labor actions at ports and rail yards have not been quantified in an easily digestible way. Yet.
GTZamp isn’t just about modeling carrier and driver behavior – Carter also said that on the customer side, GlobalTranz is integrating with specific instances of SAP and other enterprise resource management systems so that it has upstream visibility into freight demand. GTZamp can see shipments being built by manufacturers before they’re ever tendered and begin automatically positioning assets so that they are available on demand.
“One of the things we’re trying to do is not only incorporate our own data, but ask the customer, if you have budget data, forecast data, whatever, we would like to figure out how to incorporate that data into the machine, which just further contributes to the explosion in available prediction,” Carter said.
GlobalTranz wants to make digital brokerage more than just automated load-matching and pricing by creating real-time models of capacity availability and marketplace dynamics. Its load-to-truck ratio, for instance, is not based on posts to load boards, but uses seasonal models that are adjusted every day based on current conditions. That allows GlobalTranz to move assets ahead of time into markets like Mexico, Texas and Florida to take alleviate capacity imbalances during agricultural harvests.
“GTZamp is part of the roll-out of GTZconnect, our core platform for our shipper and 3PL TMS [third-party logistics providers’ transportation management systems],” Carter said. “The engine is really what’s going to drive the next generation of automation, predictability and price management; it’s part of a much broader set of things we’re releasing.”