Editorial Team The year 2025 ended quietly for Evelyn Reed, maybe a little too quietly. As CEO of “Global Goods Logistics,” a mid-sized freight forwarder in Charleston, South Carolina, she’d expected the usual post-holiday dip. Instead, she got a weird, extended slump in bookings that none of her go-to indicators could explain. The Baltic Dry Index, Chinese manufacturing PMIs, even the local port traffic stats from the South Carolina Ports Authority, they were all just noise. Trucking rates were getting soft, sure, but ocean freight, her company’s bread and butter, was just stuck. This felt different from a normal cyclical downturn. It had the whiff of a systemic problem. Evelyn needed a way to see what was really happening in the global supply chain, beyond the symptoms in her own booking system. She had a gut feeling the answers were buried in the raw data from the big ocean carriers, but getting at it and making sense of it felt impossible, like trying to see inside a black box. How was she supposed to turn that raw logistics data into something she could actually use for economic forecasting?
Key Takeaways
- A 7% year-over-year drop in global container volumes, reported on Maersk’s Q4 2025 earnings call, pointed to a big slowdown in what consumers were buying.
- A deep dive into Maersk’s regional numbers shows a major trade lane shift: intra-Asia volumes grew 4% as Asia-Europe routes shrank by 9%.
- Public logistics data from major carriers can give companies a heads-up of up to two months on freight demand shifts, letting them fix their inventory strategies.
- You get a much better 6-month forecast for supply chain stability when you combine carrier volume reports with macro indicators like consumer confidence surveys.
The Unsettling Calm: A Look at Maersk’s Q4 2025 Data
Evelyn’s frustration is something a lot of us in the industry feel. The traditional economic indicators are always late to the party. By the time you get official GDP or manufacturing numbers, the real shifts in supply and demand happened weeks or months ago. That’s why the operational data from a company like Maersk is so useful. People who just play the stock market tend to skim over their quarterly reports, but for us, they’re a direct look at what’s actually moving across the oceans. When Maersk dropped its Q4 2025 earnings in late January 2026, the numbers finally gave Evelyn a clear, and worrying, picture of what was going on.
The big number was impossible to ignore: a 7% year-over-year decrease in global container volumes. This wasn’t some statistical blip. It was a huge drop in the amount of actual stuff getting shipped. Lars Jensen, the CEO of Vespucci Maritime, put it perfectly on a recent webcast: “When a carrier of Maersk’s scale reports a volume contraction, it’s a proxy for global consumer demand. People aren’t buying as much stuff, and that ripples through every node of the supply chain.” Evelyn felt that in her gut. Her own bookings for electronics and clothes, which should have been strong after the holidays, were down by about the same amount. The data confirmed her fear that this was a market-wide problem, not just something happening to her specific clients.
Digging past the headline number, the regional data was even more telling. Maersk’s report showed the Asia-Europe trade lane had contracted by a massive 9% year-over-year. At the same time, intra-Asia volumes were actually up 4%. That’s a huge recalibration of manufacturing and consumption. “The whole ‘regionalized supply chain’ thing isn’t just a buzzword anymore,” Evelyn told her team during their weekly meeting. “You can see it right here in the container data. Our European clients are getting squeezed way more than our customers focused on Southeast Asia.” Having this kind of specific supply chain analytics meant Evelyn could start shifting her sales focus, pushing her team to chase business on the lanes that were still healthy while bracing for more pain on the weak ones.
Beyond the Headlines: Deconstructing Logistics Data for Economic Forecasting
The reason carrier data is so good for economic forecasting is that it’s real and it’s fast. It’s not a survey or a sentiment index. It’s the physical count of actual goods being bought and moved. When container bookings drop today, that means fewer ships will be sailing next month, and you’ll probably see lower retail sales a couple months after that. Evelyn stopped seeing the Maersk data as a look in the rearview mirror. For her, it became a predictive tool, a leading indicator that could flag both problems and opportunities on the horizon.
Evelyn also spotted a key detail in the numbers: the difference between spot rates and contract rates. The spot market for ocean freight had gone soft in Q4 2025, which pointed to too much capacity floating around. But Maersk’s report showed that long-term contract rates were holding pretty steady, even if they weren’t climbing like in past years. That told a different story. Even though immediate demand was weak, the big shippers were still signing long-term deals, probably betting on a recovery later in 2026. “We’re in a trough, for sure, but the market isn’t falling apart,” she told her finance director. “The big guys still think trade will bounce back. We just have to get through this part.”
Equipment utilization rates added another layer. Maersk mentioned their costs for repositioning empty containers were up, especially moving them from North America back to Asia. That’s a classic sign of a trade imbalance, more stuff coming in than going out, leaving boxes stranded in the wrong places. For Evelyn, that translated directly into potential headaches for her US export clients: delays and higher costs. She got on the phone with her sales team right away, telling them to get in front of this, to warn clients about possible surcharges and transit time hits. This kind of proactive communication, based on real logistics data, was how Global Goods Logistics kept their clients’ trust when things got tough.
The Human Element: Translating Data into Business Decisions
Raw data is useless by itself, and Evelyn knew it. You have to interpret it and actually plug it into your strategy. Her team started pulling in other public data to see if it lined up with Maersk’s numbers. They looked at the global manufacturing Purchasing Managers’ Index (PMI) data from S&P Global and, sure enough, it showed a contraction in new export orders from key Asian hubs in late 2025. That matched perfectly with the drop Maersk was seeing in its outbound Asia volumes. As Evelyn always said, “One data point is a curiosity. Two or three pointing the same way? That’s a trend.”
Spotting the trend was one thing, but figuring out what it meant for Global Goods Logistics was the real job. For example, weakness on the Asia-Europe lanes was a direct threat to Evelyn’s capacity planning. She was sitting on several long-standing carrier contracts for those routes, and if volumes kept falling, she’d be paying for empty space or stuck with bad rates. Armed with Maersk’s own public data, she went to her carrier reps to start talking about renegotiating terms or getting more flexible booking options. She wasn’t trying to be aggressive. She was just being smart, using solid market intelligence to have a productive conversation.
Evelyn also put the data to work on the sales and marketing side. Seeing the strength in intra-Asia trade, she told her marketing people to build campaigns specifically for clients with regional supply chains in places like Vietnam, Thailand, and Indonesia. She even started looking for local logistics partners in those countries to give Global Goods Logistics a stronger presence on the ground. It was a strategic pivot, born directly from the macro data, that helped her company find new money when its traditional long-haul business was taking a hit.
Looking Ahead: Working through the Nuances of a Shifting Field
By the middle of 2026, the global economy was still sputtering, but Evelyn’s company was doing a lot better than its competitors. The moves she made back in late 2025 and early 2026, all based on that deep dive into carrier data, were paying off. Global Goods Logistics dodged major losses because they saw the downturn coming on certain trade lanes and pivoted to ones that were holding up. Evelyn thought about how easy it would have been to just ignore the signs and hope for a “bounce back.” The hard numbers from Maersk and the other carriers were the kick in the pants she needed to actually do something.
The biggest lesson for Evelyn was that you can never stop watching. The supply chain is a dynamic, interconnected mess, and what’s true about freight volumes today could be completely wrong in three months. She set up a new internal dashboard that pulled together public logistics data from everywhere she could find it, weekly port congestion reports from MarineTraffic, quarterly numbers from all the major carriers, you name it. Combining all these sources gave them a much clearer, real-time view of the market, which meant they could adjust pricing, capacity, and sales focus way faster.
The whole experience hammered home why everyone in her organization needed to get better with data. Evelyn signed her key managers up for workshops on data interpretation and predictive analytics so that they’d make decisions based on the numbers, not just gut feelings. She knew that the companies that could pull real signals from all the data noise were the ones that would win. The old model of just moving boxes from A to B was dead. Success in logistics now means you have to be good at data analysis and thinking three steps ahead.
How Evelyn went from confused to proactive shows what supply chain analytics can actually do. By getting into the weeds of Maersk’s data, she figured out a path forward for Global Goods Logistics. Using this kind of real-world logistics data for forecasting isn’t some fancy extra anymore. It’s basic survival in the chaos of global trade. The future belongs to the operators who can look at container movements and turn that information into smart actionable business intelligence.
If you run a logistics company, digging into the details of carrier reports from companies like Maersk gives you a serious edge. It lets you predict market shifts and change your plans before you’re forced to. When you analyze these numbers proactively, you can make smart calls on capacity, pricing, and where to focus your sales team, instead of just reacting to whatever the market throws at you and calling it strategic foresight.
How can Maersk’s data be used for economic forecasting?
Quarterly reports from Maersk detail global container volumes, trade lane performance, and equipment use. Because these numbers reflect the actual physical movement of goods, they act as a leading indicator for consumer demand and manufacturing output, often flagging trends well before official economic stats come out.
What specific metrics from carrier reports are most useful for supply chain analysis?
Look for year-over-year changes in container volumes (overall and by trade lane), the cost to reposition empty equipment, vessel utilization rates, and the spread between spot and contract freight rates. Together, they give you a clear picture of demand shifts, trade imbalances, and available capacity.
How often should businesses review major logistics carrier data?
You should review major carrier data at least quarterly when their earnings reports are released. To get a better real-time picture, mix that quarterly data with weekly port congestion reports and monthly manufacturing PMIs.
Can smaller businesses benefit from analyzing large carrier data?
Absolutely. Even if you don’t have direct contracts with the big carriers, their reports show you the macro trends. This helps you get ahead of changes in freight costs, transit times, and demand so you can adjust your own inventory, pricing, and sourcing before you have to.
What are the limitations of relying solely on one carrier’s data for forecasting?
Any single carrier’s data can be skewed by its own sales strategies or fights for market share. To get an accurate forecast, you have to look at data from several major carriers and combine it with broader economic indicators.
