The system used by the federal government to identify and grade high-risk commercial motor carriers is "conceptually sound" but has flaws in its implementation, the National Academy of Sciences (NAS) said today in releasing a long-awaited study of the controversial system.
NAS urged the Federal Motor Carrier Safety Administration (FMCSA), which designed and implemented the existing "Safety Measurement System" (SMS), to spend the next two years developing a more "statistically principled" approach to evaluate carrier safety. Specifically, the agency should rely on a sophisticated empirical model called "item response theory" that has been used to, among other things, influence policy decisions in other areas, such as hospital rankings. Supporters of this measure, which include the American Trucking Associations (ATA) and the Transportation Intermediaries Association (TIA), which represents property brokers, said the model replaces an approach based on ad-hoc subject-matter expertise with one that focuses on hard data.
If the model performs well in spotting motor carriers whose safety performance is suspect enough to require an FMCSA intervention, the agency should use it to replace SMS, according to the report, which was mandated by Congress in 2015 under a five-year transport-spending law and was nearly two years in the making.
Under the original system developed in 2010, each carrier is measured under seven performance categories and assigned one of three safety ratings—satisfactory, conditional, and unsatisfactory—through the SMS. In January 2016, FMCSA proposed to change the three-tier model and create just an "unfit" rating. The rating is arrived at by analyzing five of seven performance criteria. FMCSA would then either conduct a full investigation of selected carriers or use a combination of on-road safety data and investigative information to come up with a fitness determination.
FMCSA said at the time that the proposal would allow it to maximize finite investigation and enforcement resources. However, critics attacked it as being based on the same flawed methodology that's been in place for years. The agency also drew fire for issuing a revamped proposal before the NAS study was completed. The proposal was withdrawn soon after President Trump took office. Most of the trucking industry wants the FMCSA to take responsibility for determining a motor carrier's safety with a simple "fit" or "unfit" rating.
Trucking companies claim the agency has instead foisted its obligation onto brokers and carriers, leaving them open to massive liability exposure should a carrier they select be involved in an accident.
As part of a recommended emphasis on analytics, NAS said that FMCSA should collaborate with states and other agencies to improve the collection of data on vehicle miles traveled and on crashes, data which are often missing or of unsatisfactory quality. For example, by including data on vehicle miles travelled by state and month, the SMS can account for varied weather conditions in different regions and their impact on driver and carrier performance.
FMCSA should also research ways to collect data on what NAS called "carrier characteristics," the report said. This includes driver turnover rates, type of cargo hauled, and the method and level of driver compensation. Well-compensated drivers and drivers who are not paid based on miles travelled, have fewer crashes, the report said. The additional data collection would require greater collaboration between FMCSA and the states to standardize the effort and to protect carrier-specific information, the report said.
FMCSA has 120 days to develop new methodology that incorporates the NAS findings.
NAS said it was unable to determine whether SMS rankings should be made public because it would require a formal evaluation to understand the consequences of such a step. Congress in 2015 ordered FMCSA to withdraw rankings from public view. However, lawmakers allowed the agency to keep the raw data used to compile the scores on its site. ATA said the data should remain private. TIA echoed that view, saying the information yielded by the new approach could lead to disastrous liability consequences for 3PLs, brokers, and shippers responsible for selecting motor carriers.
Editor's note: An earlier version of this story misstated the amount of time FMCSA has to develop a new safety-determination methodology. DC Velocity regrets the error.
Logistics real estate developer Prologis today named a new chief executive, saying the company’s current president, Dan Letter, will succeed CEO and co-founder Hamid Moghadam when he steps down in about a year.
After retiring on January 1, 2026, Moghadam will continue as San Francisco-based Prologis’ executive chairman, providing strategic guidance. According to the company, Moghadam co-founded Prologis’ predecessor, AMB Property Corporation, in 1983. Under his leadership, the company grew from a startup to a global leader, with a successful IPO in 1997 and its merger with ProLogis in 2011.
Letter has been with Prologis since 2004, and before being president served as global head of capital deployment, where he had responsibility for the company’s Investment Committee, deployment pipeline management, and multi-market portfolio acquisitions and dispositions.
Irving F. “Bud” Lyons, lead independent director for Prologis’ Board of Directors, said: “We are deeply grateful for Hamid’s transformative leadership. Hamid’s 40-plus-year tenure—starting as an entrepreneurial co-founder and evolving into the CEO of a major public company—is a rare achievement in today’s corporate world. We are confident that Dan is the right leader to guide Prologis in its next chapter, and this transition underscores the strength and continuity of our leadership team.”
The New York-based industrial artificial intelligence (AI) provider Augury has raised $75 million for its process optimization tools for manufacturers, in a deal that values the company at more than $1 billion, the firm said today.
According to Augury, its goal is deliver a new generation of AI solutions that provide the accuracy and reliability manufacturers need to make AI a trusted partner in every phase of the manufacturing process.
The “series F” venture capital round was led by Lightrock, with participation from several of Augury’s existing investors; Insight Partners, Eclipse, and Qumra Capital as well as Schneider Electric Ventures and Qualcomm Ventures. In addition to securing the new funding, Augury also said it has added Elan Greenberg as Chief Operating Officer.
“Augury is at the forefront of digitalizing equipment maintenance with AI-driven solutions that enhance cost efficiency, sustainability performance, and energy savings,” Ashish (Ash) Puri, Partner at Lightrock, said in a release. “Their predictive maintenance technology, boasting 99.9% failure detection accuracy and a 5-20x ROI when deployed at scale, significantly reduces downtime and energy consumption for its blue-chip clients globally, offering a compelling value proposition.”
The money supports the firm’s approach of "Hybrid Autonomous Mobile Robotics (Hybrid AMRs)," which integrate the intelligence of "Autonomous Mobile Robots (AMRs)" with the precision and structure of "Automated Guided Vehicles (AGVs)."
According to Anscer, it supports the acceleration to Industry 4.0 by ensuring that its autonomous solutions seamlessly integrate with customers’ existing infrastructures to help transform material handling and warehouse automation.
Leading the new U.S. office will be Mark Messina, who was named this week as Anscer’s Managing Director & CEO, Americas. He has been tasked with leading the firm’s expansion by bringing its automation solutions to industries such as manufacturing, logistics, retail, food & beverage, and third-party logistics (3PL).
Supply chains continue to deal with a growing volume of returns following the holiday peak season, and 2024 was no exception. Recent survey data from product information management technology company Akeneo showed that 65% of shoppers made holiday returns this year, with most reporting that their experience played a large role in their reason for doing so.
The survey—which included information from more than 1,000 U.S. consumers gathered in January—provides insight into the main reasons consumers return products, generational differences in return and online shopping behaviors, and the steadily growing influence that sustainability has on consumers.
Among the results, 62% of consumers said that having more accurate product information upfront would reduce their likelihood of making a return, and 59% said they had made a return specifically because the online product description was misleading or inaccurate.
And when it comes to making those returns, 65% of respondents said they would prefer to return in-store, if possible, followed by 22% who said they prefer to ship products back.
“This indicates that consumers are gravitating toward the most sustainable option by reducing additional shipping,” the survey authors said in a statement announcing the findings, adding that 68% of respondents said they are aware of the environmental impact of returns, and 39% said the environmental impact factors into their decision to make a return or exchange.
The authors also said that investing in the product experience and providing reliable product data can help brands reduce returns, increase loyalty, and provide the best customer experience possible alongside profitability.
When asked what products they return the most, 60% of respondents said clothing items. Sizing issues were the number one reason for those returns (58%) followed by conflicting or lack of customer reviews (35%). In addition, 34% cited misleading product images and 29% pointed to inaccurate product information online as reasons for returning items.
More than 60% of respondents said that having more reliable information would reduce the likelihood of making a return.
“Whether customers are shopping directly from a brand website or on the hundreds of e-commerce marketplaces available today [such as Amazon, Walmart, etc.] the product experience must remain consistent, complete and accurate to instill brand trust and loyalty,” the authors said.
When you get the chance to automate your distribution center, take it.
That's exactly what leaders at interior design house
Thibaut Design did when they relocated operations from two New Jersey distribution centers (DCs) into a single facility in Charlotte, North Carolina, in 2019. Moving to an "empty shell of a building," as Thibaut's Michael Fechter describes it, was the perfect time to switch from a manual picking system to an automated one—in this case, one that would be driven by voice-directed technology.
"We were 100% paper-based picking in New Jersey," Fechter, the company's vice president of distribution and technology, explained in a
case study published by Voxware last year. "We knew there was a need for automation, and when we moved to Charlotte, we wanted to implement that technology."
Fechter cites Voxware's promise of simple and easy integration, configuration, use, and training as some of the key reasons Thibaut's leaders chose the system. Since implementing the voice technology, the company has streamlined its fulfillment process and can onboard and cross-train warehouse employees in a fraction of the time it used to take back in New Jersey.
And the results speak for themselves.
"We've seen incredible gains [from a] productivity standpoint," Fechter reports. "A 50% increase from pre-implementation to today."
THE NEED FOR SPEED
Thibaut was founded in 1886 and is the oldest operating wallpaper company in the United States, according to Fechter. The company works with a global network of designers, shipping samples of wallpaper and fabrics around the world.
For the design house's warehouse associates, picking, packing, and shipping thousands of samples every day was a cumbersome, labor-intensive process—and one that was prone to inaccuracy. With its paper-based picking system, mispicks were common—Fechter cites a 2% to 5% mispick rate—which necessitated stationing an extra associate at each pack station to check that orders were accurate before they left the facility.
All that has changed since implementing Voxware's Voice Management Suite (VMS) at the Charlotte DC. The system automates the workflow and guides associates through the picking process via a headset, using voice commands. The hands-free, eyes-free solution allows workers to focus on locating and selecting the right item, with no paper-based lists to check or written instructions to follow.
Thibaut also uses the tech provider's analytics tool, VoxPilot, to monitor work progress, check orders, and keep track of incoming work—managers can see what orders are open, what's in process, and what's completed for the day, for example. And it uses VoxTempo, the system's natural language voice recognition (NLVR) solution, to streamline training. The intuitive app whittles training time down to minutes and gets associates up and working fast—and Thibaut hitting minimum productivity targets within hours, according to Fechter.
EXPECTED RESULTS REALIZED
Key benefits of the project include a reduction in mispicks—which have dropped to zero—and the elimination of those extra quality-control measures Thibaut needed in the New Jersey DCs.
"We've gotten to the point where we don't even measure mispicks today—because there are none," Fechter said in the case study. "Having an extra person at a pack station to [check] every order before we pack [it]—that's been eliminated. Not only is the pick right the first time, but [the order] also gets packed and shipped faster than ever before."
The system has increased inventory accuracy as well. According to Fechter, it's now "well over 99.9%."