The adoption of advanced data analytics is already reshaping the ocean shipping industry, bringing transformative improvements in information management, operational efficiency, and decision-making.
The past year has seen an unprecedented amount of change in the ocean shipping industry. Carrier bankruptcies, mergers, and large-scale reconfiguration among carrier alliances have reshaped the container industry at an astonishing pace. While the pace of acquisitions is unlikely to slow soon, there are even bigger changes afoot, some of which will lead to greater transformations than those we've seen this year.
After riding out a turbulent first half of 2016, rates steadily recovered from dismal levels for ocean container carriers. Drewry's World Container Index, a composite of container freight rates on eight major routes between the United States, Europe, and Asia, dipped below $700 in March of 2016 before turning around to peak at over $1,800 in January of 2017. (See Figure 1.) For most of this year, by contrast, rates on the index have been rangebound between $1,400 and $1,600—more than double the rates seen in the previous year.
Ports are seeing volume increases compared with the previous year. The news organization Reuters, looking at U.S. government data, reported that export shipments of coal have risen more than 60 percent this year. Container volumes are also up, and inbound volumes have risen in every major U.S. port; in June, Houston, Savannah, and Charleston all reported double-digit growth. Exports were also up in every U.S. port except Long Beach for that same month.
For the first time in many years, capacity is keeping pace with demand. Scrapping and newbuilds are expected to net out to around 3 percent in 2017 per Drewry, and capacity is forecast to grow 3 to 5 percent over the next couple of years. The current overhang in capacity remains, and competition for business is likely to keep rates steady for the next few years.
Ocean shipping is one of the oldest industries around, and you can see that today in the way its business is managed. Transactions are manual, data is distributed across parties and geographies, and many basic processes have remained the same for centuries. However, all of that is about to change as transformative ways of analyzing data quickly make their way into the industry.
Data moves front and center
Over the past few years, shippers have become much more savvy regarding the application of digital solutions to the management of their supply chains. Yet many have found that, though they have ample logistics data, it is siloed between geographies, transportation modes, or business units and is seldom available on a real-time basis.
To solve this problem, many shippers now are building advanced "data lakes" (storage repositories for raw data) to help them combine different types of information across functions, borders, and modes. While there are commercially available tools to coordinate visibility of assets in transit, shippers frequently find that non-transportation data is siloed across functions, making it difficult to make global planning and inventory decisions, implement them, and measure their impact. Accordingly, industry leaders are applying data science techniques to join data across functions into single data sources. This enables these organizations to implement metrics for measuring network performance in real time.
Innovation by key players in the ocean shipping industry like Maersk may soon ease shippers' difficulty in managing global transactions. Cloud-based ledger (also known as blockchain) platforms, essentially new and more secure ways of sharing data within and across the shipping ecosystem, will enable seamless and secure virtual document workflows that support real-time collaboration between trade partners as well as governmental, financial, and commercial stakeholders. Successful implementation will require alignment across a very wide array of stakeholders, but conceptually this nascent technology could drastically simplify complex processes and data flows that shippers and carriers struggle with daily.
Another area of analytical transformation is in container ports themselves. For a variety of reasons, ports have developed a reputation for inefficiency and opacity. In the United States, everything from labor agreements to lack of investment can be cited as root causes of this issue. However, the tide has begun to turn toward automation and digital transformation in port operations.
For example, the immediate benefits of this shift, such as lower costs and faster throughput, are already being realized at port facilities like the Middle Harbor terminal in Long Beach and the highly automated TraPac terminal in Los Angeles. Another example is the increasing use of technology to help manage terminal congestion. Truck appointment systems are becoming more prevalent on both coasts. In Los Angeles and Long Beach, an initiative with GE Transportation to create a portal for sharing information on container availability will help the ports better handle the large container volumes associated with bigger vessels. Artificial intelligence will enable greater control and flexibility in loading and unloading ships. Coupled with decentralized ledgers, this will enable shippers, carriers, and ports to plan across entities and provide differentiated service offerings such as expedited discharge.
But port automation is not universally welcomed. As the labor slowdown in response to a new automated gate system at the Port of Charleston in early 2017 showed, actions by labor unions concerned about the impact of automation on their members will increase the cost of investing in automated technologies.
Partnerships go digital
Even the ways in which shippers and carriers do business together are going digital. Traditional negotiation processes have been in place in bulk shipping since the 1950s. Negotiating a spot tender has required shippers to maintain a panel of brokers who communicate pricing from their ship owners via phone, text, or even fax and telex. Given the more dynamic market environments for both commodities and shipping, there has been a move away from longer-term contracts of affreightment to reliance on spot charters to address last-minute changes in demand. This has led to the oversimplification of procurement processes (especially compared with what is seen in other modes, like trucking) and brute-force application of resources to manage manual processes.
The metals, mining, and petroleum company BHP Billiton changed that earlier this year by launching a freight portal to communicate directly with ship owners, enabling them to reach a broad audience in a short amount of time. Reportedly, this happened at rates below the market and without the need for brokers as intermediaries. BHP is not alone; others are experimenting with new platforms designed to speed up a process that has long sapped a considerable amount of shippers' attention and resources.
Analytics help to manage risk
In the container world, shippers are employing advanced analytics to manage costs, service, and risks. The Hanjin Shipping bankruptcy in 2016 was a reminder to shippers that host countries are increasingly reluctant to bail out failing ocean carriers. In the face of accelerating merger and acquisition activity and realignment among carrier alliances, shippers are using predictive modeling in addition to cost optimization tools to balance carrier financial risk, network disruption potential, and service performance to determine the best overall value of a carrier contract portfolio, rather than narrowly focusing on linehaul cost.
Simply stated, the amount of change the industry has recently experienced is staggering. Rate variability and the restructuring of the market through mergers, bankruptcies, and carrier realignment has arguably never been greater. However, like many other industries, ocean transportation is in the early stages of a digital transformation that will lead to even greater change. Successful participants can expect to deliver increased visibility, efficiency, and value. While the carriers and shippers that are able to adapt the fastest in this new environment will yield the best results, this promises to be a time in which all parties can benefit.
The launch is based on “Amazon Nova,” the company’s new generation of foundation models, the company said in a blog post. Data scientists use foundation models (FMs) to develop machine learning (ML) platforms more quickly than starting from scratch, allowing them to create artificial intelligence applications capable of performing a wide variety of general tasks, since they were trained on a broad spectrum of generalized data, Amazon says.
The new models are integrated with Amazon Bedrock, a managed service that makes FMs from AI companies and Amazon available for use through a single API. Using Amazon Bedrock, customers can experiment with and evaluate Amazon Nova models, as well as other FMs, to determine the best model for an application.
Calling the launch “the next step in our AI journey,” the company says Amazon Nova has the ability to process text, image, and video as prompts, so customers can use Amazon Nova-powered generative AI applications to understand videos, charts, and documents, or to generate videos and other multimedia content.
“Inside Amazon, we have about 1,000 Gen AI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” Rohit Prasad, SVP of Amazon Artificial General Intelligence, said in a release. “Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities.”
The new Amazon Nova models available in Amazon Bedrock include:
Amazon Nova Micro, a text-only model that delivers the lowest latency responses at very low cost.
Amazon Nova Lite, a very low-cost multimodal model that is lightning fast for processing image, video, and text inputs.
Amazon Nova Pro, a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
Amazon Nova Premier, the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models
Amazon Nova Canvas, a state-of-the-art image generation model.
Amazon Nova Reel, a state-of-the-art video generation model that can transform a single image input into a brief video with the prompt: dolly forward.
Economic activity in the logistics industry expanded in November, continuing a steady growth pattern that began earlier this year and signaling a return to seasonality after several years of fluctuating conditions, according to the latest Logistics Managers’ Index report (LMI), released today.
The November LMI registered 58.4, down slightly from October’s reading of 58.9, which was the highest level in two years. The LMI is a monthly gauge of business conditions across warehousing and logistics markets; a reading above 50 indicates growth and a reading below 50 indicates contraction.
“The overall index has been very consistent in the past three months, with readings of 58.6, 58.9, and 58.4,” LMI analyst Zac Rogers, associate professor of supply chain management at Colorado State University, wrote in the November LMI report. “This plateau is slightly higher than a similar plateau of consistency earlier in the year when May to August saw four readings between 55.3 and 56.4. Seasonally speaking, it is consistent that this later year run of readings would be the highest all year.”
Separately, Rogers said the end-of-year growth reflects the return to a healthy holiday peak, which started when inventory levels expanded in late summer and early fall as retailers began stocking up to meet consumer demand. Pandemic-driven shifts in consumer buying behavior, inflation, and economic uncertainty contributed to volatile peak season conditions over the past four years, with the LMI swinging from record-high growth in late 2020 and 2021 to slower growth in 2022 and contraction in 2023.
“The LMI contracted at this time a year ago, so basically [there was] no peak season,” Rogers said, citing inflation as a drag on demand. “To have a normal November … [really] for the first time in five years, justifies what we’ve seen all these companies doing—building up inventory in a sustainable, seasonal way.
“Based on what we’re seeing, a lot of supply chains called it right and were ready for healthy holiday season, so far.”
The LMI has remained in the mid to high 50s range since January—with the exception of April, when the index dipped to 52.9—signaling strong and consistent demand for warehousing and transportation services.
The LMI is a monthly survey of logistics managers from across the country. It tracks industry growth overall and across eight areas: inventory levels and costs; warehousing capacity, utilization, and prices; and transportation capacity, utilization, and prices. The report is released monthly by researchers from Arizona State University, Colorado State University, Rochester Institute of Technology, Rutgers University, and the University of Nevada, Reno, in conjunction with the Council of Supply Chain Management Professionals (CSCMP).
Specifically, 48% of respondents identified rising tariffs and trade barriers as their top concern, followed by supply chain disruptions at 45% and geopolitical instability at 41%. Moreover, tariffs and trade barriers ranked as the priority issue regardless of company size, as respondents at companies with less than 250 employees, 251-500, 501-1,000, 1,001-50,000 and 50,000+ employees all cited it as the most significant issue they are currently facing.
“Evolving tariffs and trade policies are one of a number of complex issues requiring organizations to build more resilience into their supply chains through compliance, technology and strategic planning,” Jackson Wood, Director, Industry Strategy at Descartes, said in a release. “With the potential for the incoming U.S. administration to impose new and additional tariffs on a wide variety of goods and countries of origin, U.S. importers may need to significantly re-engineer their sourcing strategies to mitigate potentially higher costs.”
Grocers and retailers are struggling to get their systems back online just before the winter holiday peak, following a software hack that hit the supply chain software provider Blue Yonder this week.
The ransomware attack is snarling inventory distribution patterns because of its impact on systems such as the employee scheduling system for coffee stalwart Starbucks, according to a published report. Scottsdale, Arizona-based Blue Yonder provides a wide range of supply chain software, including warehouse management system (WMS), transportation management system (TMS), order management and commerce, network and control tower, returns management, and others.
Blue Yonder today acknowledged the disruptions, saying they were the result of a ransomware incident affecting its managed services hosted environment. The company has established a dedicated cybersecurity incident update webpage to communicate its recovery progress, but it had not been updated for nearly two days as of Tuesday afternoon. “Since learning of the incident, the Blue Yonder team has been working diligently together with external cybersecurity firms to make progress in their recovery process. We have implemented several defensive and forensic protocols,” a Blue Yonder spokesperson said in an email.
The timing of the attack suggests that hackers may have targeted Blue Yonder in a calculated attack based on the upcoming Thanksgiving break, since many U.S. organizations downsize their security staffing on holidays and weekends, according to a statement from Dan Lattimer, VP of Semperis, a New Jersey-based computer and network security firm.
“While details on the specifics of the Blue Yonder attack are scant, it is yet another reminder how damaging supply chain disruptions become when suppliers are taken offline. Kudos to Blue Yonder for dealing with this cyberattack head on but we still don’t know how far reaching the business disruptions will be in the UK, U.S. and other countries,” Lattimer said. “Now is time for organizations to fight back against threat actors. Deciding whether or not to pay a ransom is a personal decision that each company has to make, but paying emboldens threat actors and throws more fuel onto an already burning inferno. Simply, it doesn’t pay-to-pay,” he said.
The incident closely followed an unrelated cybersecurity issue at the grocery giant Ahold Delhaize, which has been recovering from impacts to the Stop & Shop chain that it across the U.S. Northeast region. In a statement apologizing to customers for the inconvenience of the cybersecurity issue, Netherlands-based Ahold Delhaize said its top priority is the security of its customers, associates and partners, and that the company’s internal IT security staff was working with external cybersecurity experts and law enforcement to speed recovery. “Our teams are taking steps to assess and mitigate the issue. This includes taking some systems offline to help protect them. This issue and subsequent mitigating actions have affected certain Ahold Delhaize USA brands and services including a number of pharmacies and certain e-commerce operations,” the company said.
Editor's note:This article was revised on November 27 to indicate that the cybersecurity issue at Ahold Delhaize was unrelated to the Blue Yonder hack.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."