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Port congestion is a growing concern among supply chain professionals, but how often is it generalized inaccurately? The truth is that congestion at a port doesn’t necessarily apply to all the terminals or all the vessels at that port. While disruptions are a legitimate threat to the movement of goods, the finer details, such as terminal-specific bottlenecks, are often overlooked, leading to overestimated fears.
In this blog, we’ll discuss some common misconceptions about port congestion and explain why it’s essential to examine terminal-level data more precisely to gain a better understanding.
Understanding the Layers of Port Congestion
When you hear that a port is congested, the immediate assumption is that every terminal and every vessel at that port is experiencing delays. But that’s not always the case. Ports are massive ecosystems of multiple terminals, each with its own operations, equipment, and logistical processes. While one terminal might be overwhelmed with vessels waiting to dock, another terminal at the same port may operate at normal capacity, handling cargo efficiently. Likewise, some vessels arriving at a congested port may still berth on schedule, depending on their assigned terminal or berthing sequence.
For example, imagine a container ship bound for the Port of Shanghai. The vessel’s ETA may suggest delays at the port due to congestion. However, after closer inspection, you will find that the delays primarily affect just two of the port’s terminals. If your shipment is routed through an unaffected terminal, your cargo could be processed on time despite the reported “port congestion.”
This nuance is critical. Global trade and logistics networks have grown increasingly complex, and generalizing port congestion can lead to unnecessary panic, costly rerouting, and flawed decision-making.
The Inaccuracy of Terminal-Level ETA Estimates
One of the most significant pain points for supply chain managers today is the lack of precise Estimated Time of Arrival (ETA) data at the terminal level. Most systems rely on generalized ETAs based on vessel traffic and historical data at a port, not specific terminals.
Such ETA estimates may not always be accurate because they don’t take into account terminal-specific factors like gate delays, workforce availability, or varying vessel handling speeds. This often leads to a scenario where shippers are left with an ambiguous understanding of when their cargo will actually arrive at its destination terminal.
Consider a situation where a vessel has an ETA of 12 hours to arrive at the Port of Rotterdam. However, upon closer analysis, you discover this estimate is based on historical data from another terminal within the port, where operations are slower. If your cargo is bound for a terminal with more optimized handling processes, the vessel may dock and unload much sooner than the ETA suggests.
This inaccuracy at the terminal level means that relying on general ETA predictions without real-time terminal-specific data can result in misguided supply chain planning, potentially causing missed deadlines and higher operational costs.
Not All Congestion Is Created Equal
It’s important to recognize that even when congestion does occur, it doesn’t affect all vessels or cargo equally. Larger vessels with more extensive cargo operations might experience longer dwell times at a congested terminal, while smaller feeder vessels could move in and out relatively quickly. This variability further complicates the idea of “port congestion” because the impact differs depending on the type of vessel and terminal in question.
For instance, the congestion at a container terminal might severely delay cargo destined for large manufacturers, while a nearby bulk terminal may be unaffected. Understanding this distinction can help shippers make informed decisions and avoid unnecessary diversions or delays.
How to Mitigate Port Congestion Challenges
To effectively mitigate congestion challenges, it’s essential to move beyond the generalized notion of “port congestion” and instead focus on terminal-specific insights. Here’s how:
1. Leverage Real-Time Terminal Data: Invest in tools that provide accurate, real-time data on terminal operations. Understanding terminal-specific performance allows for better planning and reduces the likelihood of relying on inaccurate ETA estimates.
2. Use Predictive Analytics: Technologies like AI and machine learning can help supply chain professionals predict congestion patterns more accurately by incorporating terminal-level data, weather forecasts, and port operations data to give a holistic view of potential disruptions.
Real-Time Example: French Port Strikes & Misleading Congestion Reports
During the Le Havre port strikes in early 2025, various sources reported severe congestion, with estimated delays of up to 10 days due to terminal closures and overbooked delivery slots. Many logistics teams braced for widespread shipment disruptions, assuming delays across the entire port.
However, Portcast’s real-time data revealed a more accurate picture:
- The congestion was not uniform. While Terminal De France GMP was heavily impacted, with vessels waiting 3–6 days due to 85–90% yard utilization, other terminals—like Terminal de l’Atlantique and TNMSC—saw minimal disruptions, with many vessels berthing without delays.
- Portcast’s congestion index remained precise, reflecting a median congestion of 1.1 days, with only the most affected 10% of vessels experiencing delays of over 5.6 days.
- Carrier websites lacked updated ETD information, creating uncertainty. Portcast’s predictive models compensated for these gaps, providing a more reliable estimate.
A clear example of this was MSC Mombasa, initially scheduled to depart from Le Havre, but later rerouted to Ashdod. The shipment was transferred to Zim America, which, contrary to widespread congestion reports, was calling at TNMSC and remained on track for its scheduled departure on March 8, 2025.
How Portcast’s Granular Congestion Analysis Helped Shippers
Rather than relying on broad congestion reports, Portcast’s multi-layered congestion indices helped users make informed decisions:
- Weekly Congestion Index: This index showed that while the median waiting time was low, only the worst 10% of vessels faced severe delays (5+ days).
- Daily Traffic Indices: Enabled real-time tracking of vessel movement, identifying congestion spikes by monitoring the ratio of berthed vs. waiting vessels and total wasted hours at anchorage.
By providing terminal-level accuracy, Portcast helped customers avoid unnecessary disruptions, ensuring only affected shipments were flagged while preventing panic across all operations.
Focus on Terminal-Level Precision
Port congestion is real, but it’s not always as widespread as reported. Supply chain managers and logistics professionals must stop generalizing port-wide delays and start digging into terminal-level data to make informed decisions. By doing so, they can avoid unnecessary costs, mitigate delays, and keep their supply chains running efficiently.
Get Accurate, Real-Time Port Data with Portcast
At Portcast, we integrate port congestion insights across multiple solutions to ensure you have the most accurate, real-time data. Our Port Congestion dashboard provides key congestion metrics for major global ports, allowing you to compare congestion levels and make informed decisions.
We also factor port congestion into our ETA prediction models, ensuring that observed disruptions directly impact calculated ETAs—helping you anticipate and manage delays effectively. Additionally, our system identifies port disruptions as incidents, integrating them into both our API and Web Application at the container level, so you can proactively monitor and flag at-risk shipments.
Get in touch with our team at Portcast to start leveraging our congestion insights. Whether through our Web Application or seamless API integration, Portcast makes it easy to track congestion at the ports that impact your supply chain the most.
