Using Data-driven Metrics to Overcome Port Blockages

While port congestion is always an issue at various times of the year, the current surge in consumer spending coupled with existing supply chain blockages are leading to some extreme situations. As individuals and small business owners purchase products that they've been unable to acquire for some time, international shipping organizations have had to work record numbers of hours to deliver said goods. This is causing vessels to wait unprecedented amounts of time to dock, which is leading back-end developers and statisticians to develop new metrics to calculate the odds of any port receiving greater levels of maritime traffic at any given time.

It's gotten to the point where some ships are facing four-week docking delays, which is particularly concerning for those who are attempting to ship time-sensitive cargo. Those looking to do so are increasingly using these innovative algorithms to reduce congestion.

Making Data-Driven Maritime Decisions

Shipping goods via maritime channels often requires very long lead times, but this hasn't deterred shippers by any means. Estimates claim that around 80 percent of all international trade is carried by ships, and this number has likely increased due to the current supply chain issues. That represents around 11 billion short tons of goods. Time-sensitive freight is often forgotten about in the mix-up, though a great deal of data has been collected on the processing of it in most larger ports.

A great deal of this data is currently unstructured, which has made it difficult to draw any conclusions from. Moreover, data analysts have been forced to disregard huge amounts of information merely because it's related to operations before supply problems became this bad. Some are using NVMe-based modules to speed up the rate of processing more recent information. Others have suggested using binary trees or other more sophisticated data structures to alter the way in which certain pieces of information were stored.

These solutions can help harbormasters predict which times of month will see the heaviest amounts of maritime traffic. While past performance isn't always an indication of the future, such studies are useful for recognizing patterns that might not always be immediately evident. Use of distributed computing hardware can further aid in speeding up the analysis process.

Making the right decision is still up to economists and supply chain experts, however. In some cases, it's also up to individual small business owners too.

Deciding on Individual Choices

To deal with the backlog, managers of small businesses are quickly turning to international parcel forwarding services like My UK Mailbox as well as those provided by local post offices. While these are often slower than traditional logistics systems, recent data has helped to illustrate their collective utility. They might be able to substitute for conventional methods until said methods are back to full working capacity.

Those who are keeping an eye on local International Monetary Fund maneuvers may know the best time to return to more conventional ways of doing business. Otherwise, however, it may prove helpful to work with one of these smaller organizations until the IMF gives the all clear signal for international trade in a specific region of the world. That's of particular importance for those based in areas that are currently suffering from some sort of credit crisis further made worse by port blockages and other related problems.

As data becomes increasingly structured over time, it's likely that this picture will be much clearer than it is today.

Framing a Decision with Points of Data

Policymakers who are working on making smarter decisions are also considering anecdotal evidence when making their considerations. For instance, they're keeping a close eye on annual new product releases, which could potentially spark a sudden interest in certain raw materials. Consumer spending traditionally hasn't impacted heavy industry that much, but current industry numbers suggest that it might start to very shortly. This is especially true in the electronic industry.

With large semiconductor manufacturing facilities going up in Korea, the idea that all economic data must be collected scientifically is rapidly diminishing as many industry analysts feel that purchases of automobiles as well as microelectronics will quickly make it impossible to move sufficient levels of semiconductors from these markets to international ones regardless of what official data has suggested. Some have gone so far as to propose heavy restrictions on consumer borrowing in order to curb some of the excesses that could result from this kind of market position.

Nevertheless, there are still questions about just how much of an impact these kinds of policies could ever make, though the influx of information could very well ensure their success.

This article does not necessarily reflect the opinions of the editors or the management of EconoTimes