Global supply chain challenges continue to plague manufacturers, retailers and logistics companies. New developments in the Red Sea and the Panama Canal are making it harder are adding even more delays.
According to the BBC, more than $1 trillion in cargo, or 12% of global trade travels through the Red Sea yearly. With Hourthis now attacking ships and threatening those routes, major shipping firms are now rerouting vessels traveling between Asia and Europe from the Suez Canal to around the Cape of Goog Hope, adding significant delays as captains adds thousands of miles to their journeys.
On the other side of the ocean, the drought in Panama, compounded by the El Nino Winds, has created a backlog of cargo ships sitting outside the Panama canal waiting to pass, or preparing to divert and journey around Cape Horn. Aside from adding significant days to delivery time, rerouting around the Horn forces captains to navigate through some of the most dangerous waters on the planet.
Simultaneously, the war in Ukraine has also affected shipments traveling on the Black Sea.
Shipping and logistics companies are scrambling. Rerouting enormous container, thousands of miles off their original course is a logistical nightmare. As the Panama Canal adjusts the rate of shipping spots day-to-day, companies are left guessing when they'll be able to pass. These uncertainties tie up shipping and delivery schedules, and the effect permeates through to material suppliers, manufacturers, wholesalers, retailers and more. When supply routes are choked, many segments timelines and revenues are dramatically affected.
Add to this, recent data from CargoNet that shows cargo thefts soaring by 57% in 2023 vs. 2022, and the story gets more troubling.
In my recent Inc.com column, Anticipating Market Shifts With Supply Chain Predictive Analytics, I discussed the importance of predictive analytics for supply chain management. Using novel ways to anticipate how these challenges and factors will affect your unique supply chain situation is more critical than ever. From predictive modeling to sophisticated algorithms and statistical methods to cognitive analytics to AI, companies are leveraging the latest technology in an attempt to combat supply chain challenges. Yet all these tools require that the data they're based on is accurate and up-to-date. Often that's not the case.
Companies must also invest in taking paper based logging, warehouse records and delivery sign-offs digital. With virtually every warehouse employee, dock worker and deckhand holding a own mobile device, the opportunities for better and more timely data collection are tremendous. And the impact of better, more autonomous data collection is significant.
As I reported in my article:
"Once you have established dependable data, the integration of A.I. and machine learning in supply chain management, especially for consumer packaged goods companies, offers significant performance improvements...McKinsey recently reported that autonomous supply chain planning, which combines big data and advanced analytics, has been shown to increase revenue by up to 4 percent, reduce inventory by up to 20 percent, and decrease supply chain costs by up to 10 percent, which proves its value-generating contributions."