Supply Chain Disruptions: How Predictive Visibility Can Help Mitigate Risks of the Next Suez Canal-Like Blockage

As yet another vessel ran aground and disrupted traffic in the Suez Canal this week, logistics and transport managers closely watched to see how it would impact their cargo. This situation was resolved within a day, but it was another reminder of the importance of the Suez Canal and the importance of data-driven decision-making to manage potential risks.

Additionally, the global economic downturn is putting pressure on companies to optimize costs and improve their supply chain and logistics efficiency. This becomes even more important when the fees on megamax vessels going through Suez might total as much as USD 1 million and more vessels are taking a detour via South Africa now.

How Can Predictive Transportation Visibility Help?

The combination of a turbulent economy and ‘black swan’ events results in many new conditions under which companies need to operate.

There is currently a partially surprising situation when a detour via South Africa is economically rational for many vessels departing for or returning from Asia rather than passing through the Suez Canal and paying the recently increased fees. At the same time, there is a chance of the Suez being blocked for several days because of a vessel running aground.

From a shipper's point of view, these conditions require extra knowledge and well-done ‘homework’ because delays are most likely to happen and we need to properly prepare.

Predictive transportation visibility is the way how data and analytics can be used to provide an additional layer of information on the status of shipments. This can help companies track shipments in real-time, identify potential bottlenecks, and anticipate future issues.

Here is an example of a recent HMM Dublin journey scheduled from Antwerp via the Suez Canal to Busan:

According to the screenshot, the vessel is taking a detour via South Africa, which may be due to the reasons mentioned above. As predicted by Portcast, this detour will delay the containers on the vessel by an estimated 17 days from their original scheduled arrival date.

The bitter part of cases like HMM Dublin is the possible dark days for shippers and everyone else waiting for updates from carriers. The carrier’s website often doesn’t reflect any update or delay for several days or even a week, leaving shippers, logistics companies, and their clients unaware of the expected delay.

With predictive and real-time visibility, you can spot routes or vessel detours earlier, monitor the situation with live vessel location, and forecast new expected times of arrival that may differ from the original carrier schedule. This allows for greater control and accuracy in the shipping process.

Reactive and Proactive Actions

Disruptions are continuing to happen and we need to proactively invest in solutions for faster adaptation and data-driven evaluation of alternatives. This is a scenario where predictive visibility can play a crucial role, because AI can process huge amounts of data faster, and provide outputs including estimated arrival times and possible delays, along with new alternatives (for example, pick the best nearest port for cargo to reroute when port congestion is too high).

In this case, such an analysis could allow shippers to react while being backed with the new predicted ETA and manage both customers’ expectations and own processes better, as well as plan for possible contingencies.