The DataQs system enables carriers and drivers to challenge inspection violations and crash reports, but many in trucking have complained of its shortcomings.photo by Max Heine
Haney, safety director for the 130-truck Payne Trucking, and Chris Turner, of the Commercial Vehicle Safety Alliance, were joined by moderator Todd Dills, Overdrive senior editor. The live-streamed session followed from Overdrive's recent "Setting the Record Straight" series, which details the often painstaking process of challenging and correcting even simple errors on carriers' records of inspections and accidents.
Underscoring the importance of the data made public under the Compliance, Safety, Accountability (CSA) program, which DataQs is used to correct, Haney pointed to a piece of information that is outside the bounds of the DataQ program, and so it's not contestable even when it's in error. Haney noted the accident record that is made public always discloses whether the truck's driver was cited or not, yet it doesn't specify the citation or other details.
As people involved in trucking, “we understand and know what that means, but my insurance company doesn’t, the plaintiff’s attorney doesn’t,” he said. “What about the customers I’m losing that see it, that don’t reach out for an explanation, and say, ‘No, I don’t want to deal with these guys.' We’ve been tried and convicted without even a voice to offer our objection. When this is made public, you’re inviting a wide variety of interpretation.”
Turner agreed that DataQs needs improvement, and said CVSA is working with the Federal Motor Carrier Safety Administration and industry stakeholders to do that. FMCSA last year rejected CVSA’s initial proposal to test an appeals process at a national level that involves both enforcement and industry representatives, but asked the enforcement coalition to continue exploring how to improve the system.
“Our goal is to establish a panel at a national level,” Turner said. It will likely begin with a pilot program using two or three states, and will focus on DataQs that were rejected, then appealed and lost, and then are appealed yet again.
