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Craig Fuller Unveils SONAR 5.0: Multimodal Data And Trucking Rate Forecasting

Craig Fuller Unveils SONAR 5.0: Multimodal Data And Trucking Rate Forecasting

On Tuesday, Nov. 12, FreightWaves founder and chief executive officer Craig Fuller unveiled SONAR 5.0, the latest version of the company's freight market data platform, on stage at FreightWaves LIVE Chicago.

SONAR 5.0 marks FreightWaves' ascent to the premier global, multimodal freight market platform – the densest set of railroad, air freight and ocean cargo data available in a single place. 

"Our first index was based on [trucking] tender data," Fuller said, "and the goal was always to understand the supply and demand characteristics of the market. We realized that a lot of the data we presented in SONAR left an incomplete look at the market. The ELD mandate was coming into use and nearly every truck in America was going to be visible. We had the opportunity to aggregate real-time GPS pings and analytics on about 800,000 assets so we could attack the driver detention issue."

Getting better visibility into trucking capacity – supply – was only one part of the equation, though. Market participants also needed to know about freight demand, which in the United States' consumption-driven economy, often originates in large-scale infrastructure sites like container ports and airports. SONAR 5.0 has aggregated detailed information about commodity flows, rates and capacity for both ocean and air cargo, and also has a new seasonality calendar that predicts demand based on commodity type, whether it's lumber, apples or bottled water.

"The core of what we wanted to do focused on the speed of the data flow, but also about the user experience," Fuller explained. 

SONAR users wanted access to customized, relevant information even if they weren't logged in to the platform, so FreightWaves built an alerts functionality that automatically generates animated videos updating companies on the indices they select. More data than ever before is tied together through maps, allowing users to shift quickly between modes.

Another tool new in 5.0 was originally built for internal FreightWaves use – a correlation matrix that calculates which indices are associated with volatility in supply and demand. 

"The correlation matrix allows users who are more quantitative to see how things are moving and looks for anomalies inside the data," Fuller said.

Maps are now three-dimensional, which lets users compare metrics across freight markets, but also consider the magnitude or size of the market. 

"The world's not flat, but there are maps that are color-coded but don't provide depth," Fuller explained. "Green River, Wyoming is one of the most volatile markets in the country, but no freight moves out of there unless you're in mining."

Fuller added, "We've taken the same concepts and strategy behind domestic surface freight movement and applied it to all modes of traffic. In the new SONAR, for instance, there are ship and aircraft locations." He explained that "our goal is to aggregate freight across all modes, so that power users have the world's economy at their fingertips."

Finally, Fuller introduced SONAR 5.0's powerful new trucking rate prediction tool, which uses mathematical calculations to generate rates for thousands of origin-destination pairs for the current day, a week in advance, and up to a year in advance. What makes this rate predictor unique is that its algorithm uses a complex set of inputs including previous rates, current capacity and demand from SONAR, but users can also upload their own data to predict their customers' and transportation providers' behavior.

"This is not a quarterly report that comes out, it's a real-time data analytics platform that brings it all together so you can see how it all works," Fuller said. He stressed that SONAR's rate predictor was not an assessment of actual transactions, but a mathematically calculated forecast that can be fed by any data source, including third-party rate assessments used by shippers and transportation providers.

Image by Jeff Chabot from Pixabay


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