Flexport Reportedly Plans to Lay Off 20% of Staff

Supply chain logistics company Flexport is reportedly embarking on another sweeping round of job cuts.

The firm plans to cut almost 20% of its staff — about 500 workers – in a bid to regain its momentum after a dip in shipping demand, The Wall Street Journal (WSJ) reported Friday (Jan. 26), citing a source familiar with the matter.

PYMNTS has contacted Flexport for comment but has not yet received a reply. 

These apparent layoffs follow another 20% reduction of staff in October, part of a larger restructuring plan at the company, which itself followed a major leadership change.

In September of last year, CEO Dave Clark stepped down following a year at Flexport, replaced by founder and former chief executive Ryan Petersen.

Since his return, Petersen has overhauled the company’s leadership team, with the job cuts leading to a 25% reduction in expenses.

As noted here in October, Peterson has set a goal of turning a profit by the end of this year or early 2025. This could hold up Flexport’s plans for an initial public offering (IPO), although Petersen remains committed to some day taking the company public.

The WSJ report said that many of these changes follow a drop in freight rates which impacted the company. Flexport serves as a go-between, purchasing space on containerships, and earns profits on the spread between shipping company list prices and the rates it charges clients.

Last year brought reports — which Flexport dismissed as untrue — that the company was working to rebuild trust following complaints from customers.

Elsewhere in the logistics space, PYMNTS on Friday spoke with Yoav Amiel, chief information officer for freight brokerage platform RXO, about the use of artificial intelligence (AI) in the field.

“I’ve been in the artificial intelligence and machine learning space for more than 20 years now,” Amiel told PYMNTS during a conversation for the “AI Effect” series. “I’ve seen the evolution of the field. And there are three areas where today’s AI capabilities differ from previous predictive machine learning solutions.”

First, Amiel explained, the ease of creating AI models has gotten better with the availability of AI platforms and open-source tools.

And the ability to build AI systems has allowed AI algorithms to become more complex, offering a greater depth of possibility and context around the results AI can generate and derive from the information.

Finally, Amiel said the adoption of AI has increased due to a more widespread availability of training datasets and other technical resources.

“It has democratized AI development,” he said.