Shippers around the world are scrambling to keep up with surging freight costs, and the logistics organizations that support them are being challenged in unforeseen ways. Ocean-freight rates to bring goods from China to U.S. West Coast ports have reached more than $20,000 per 40-foot container — multiples above the $1,590 pre-pandemic average.
New green regulations such as Fit for 55 and The Ocean Shipping Reform Act of 2021 in Europe and the U.S. bring further challenges to the industry, and add urgency to the need for quick and efficient solutions.
Nowadays, data is any industry’s most critical asset when it comes to navigating new hurdles as it gives insight into past, present, and future operations. Digital evolutions that utilize data introduce a new era of transparency in the shipping industry by using quantitative and historical information to help improve disparities. This migration shows how, where, and even sometimes when these costly disruptions might occur. Artificial intelligence (AI) is becoming a necessary adaptation for companies so that the supply chain doesn’t crumble under the current pressure.
Let’s explore the biggest problems in the global supply chain today, how compiling contingencies are affecting operations in shipping, and how predictive analytics through AI can help to provide solutions for challenges in modern-day logistics.
A New Look for Shipping
Nowadays, consumers are spending their money on material things because they aren’t traveling — leading to an explosion in e-commerce. This has resulted in service being so slow that it is causing customers to overstock on goods, manifesting insult to injury. The crux of the issue is that most of the containers are stagnant on the vessels and the vessels are waiting in ever-growing lines at ports to get offloaded — causing even more congestion, and in turn creating extreme bottlenecking all along the line of the supply chain.
According to exporters, containers are being left at the origin ports and not transported on time even after paying the high rates for timely transportation. This is coupled with the fact that there has been a 24.3% increase in costs in the parcel and last-mile segment of delivery from an escalation in e-commerce and home delivery. This means additional expenses for the companies providing the goods, as well as the shipping companies that are delivering them. Ultimately, this leads to consistently poor service levels as an unfortunate downside to this unprecedented situation in the transportation industry.
Month on month, the rise in freight costs has been growing 20% across the globe. There are even higher quotes being seen on the European route, with the cost of a shipment from the east coast of China to Rotterdam or Hamburg significantly greater than the journey from Shanghai to LA. With an insufficient number of workers and trucks and escalating incoming volume, once shipments actually arrive at ports congestion becomes unavoidable.This is skyrocketing shipping prices, with shipments costing more than six times what they did just last year.
Additionally, the growing list of shortages in essential materials is compounding the disarray for global supply chains. From computer chips to lumber, shortages are delaying deliveries and rising costs across the board. This will undoubtedly cause more uncertainty in shipping well into 2022.
As retailers head into the fourth quarter, inventory levels grow by the day, and warehousing space is becoming increasingly scarce. This is challenging logistics companies further in understanding what capacity is available on ships to transport these goods — causing many companies to overestimate space and further slowing down shipping times.
With the current level of container capacity staying idle on ships but not on land, it is vital for transportation companies to have a reserve of containers at ports that they frequent. Paradoxically, the current levels of idle containers at depots are still relatively high, showing that if some of them were repositioned, container management might be more efficient. The fact is, empty containers are still needed, but better decisions need to be made so that they are delegated more accurately and efficiently — taking considerations for containers needed to satiate demand, while also keeping containers for “just-in-case.”
The reality is that each one of the challenges that are meeting the shipping industry exacerbates the other. Furthermore, no one element is the determinant, with all of them combining to create the current hardships the shipping industry faces. Companies continue to attempt to navigate the current unpredictability, with a slippery slope of disconnection manifesting as every company involved with the supply chain takes desperate measures to keep up with constantly changing caveats.
There are some companies that are collaborating to try and fill this void, with alliances between shipping lines already taking place. With the current industry development pace, we will see the power and feasibility of inter-company cooperation grow every year.
The extreme need to traverse these nuances has propelled logistics companies to develop new solutions and expand services. Digital transformation through the adoption of AI innovations has been a beacon of hope to meet the necessary demands ensuring that companies all along the supply chain can literally and figuratively deliver.
An AI optimization model which takes into account all costs that occur during the container lifecycle is needed. Data analytics can provide visibility on the historical performance, health of current operations, and future costs based on predicted trends — telling companies whether or not a container should be express shipped or has time to wait in the port. This allows companies to employ methods that include moving empty containers back to high-demand locations just in time of need and furthermore saves on storage costs while mitigating empty stock imbalances at sites. With AI in forecasting, not only is the number of full containers clearer, but an estimation of available empty containers is also procured.
Logistics companies can automate the process of data extraction while machine learning algorithms can further enrich data quality. Leveraging this data allows strategies for container storage, repositioning, and planning to be utilized — increasing the capacity to not only raise the agility of fleets but also decreasing the volume of need. Through these predictive analytics, individual companies can then gain more visibility over operations resulting in healthy and optimal levels of safety stocks. With data authenticity and consolidation, predictive analytics can help better delegate shipping demands and thereby significantly slash costs.
Most importantly, when companies have better data management, one version of truth manifests a standard for the industry as a whole. By implementing digital transformations the supply-demand chain can navigate the compiling nuances of 2021.
Timely, incisive articles delivered directly to your inbox.