Logistics technology has evolved significantly in the past 10 years, putting an increasing emphasis on workflow and process automation. The data that feeds the decision logics and algorithms in modern logistics platforms has also had to evolve: It’s become richer and more contextualized.

Take the example of trucking spot rate data: A decade ago, an average rate per mile with optional fuel surcharge based on the last few weeks of transactions on a lane was a standard offering. The human freight broker consuming the data would then be expected to use his or her expertise to adjust the rate for a certain customer, facility or pickup time or if he or she knew that the trucking capacity had loosened or tightened since the rate was published. This basic rate data could be wielded effectively in the right hands, but it was too bare and insufficiently contextualized to support sophisticated automation.

Today, customers of trucking rate data want a range of rates for a lane, confidence scores, capacity trends and other attributes to help inform the decision layers driving their automated processes. Two of SONAR’s recent integrations, with Hubtek and Trucker Tools, illustrate how rich trucking rate data can be used to achieve new levels of automation at freight brokerages.