Supply chain visibility is not a new concept. Various forms of visibility have been in existence—with varying degrees of
efficacy—for a long time. Today, however, we are seeing a renaissance in visibility capabilities that is being driven by
three primary forces.
The first is the emergence of the consumer-centric supply chain. Consumers have increased power and choice, allowing them to
buy virtually anything, anytime, across a variety of methods. This has put tremendous pressure on supply chains that were
originally designed for volume and scalability to become agile, responsive, and fluid.
Consequently, the second force is the transformation of previously linear supply chains devoted to shipping pallets and full
truckloads to grid-based, or many-to-many, nodal value chains, thus enabling a higher degree of consumer responsiveness. This, in
turn, has led to smaller and more frequent shipments, an emphasis on network throughput, and an increase in complexity in providing
inventory visibility.
Lastly, we are continuing to see an acceleration of technological innovation that is enabling paradigms of visibility we could
not have imagined before. Beyond leveraging ubiquitous technologies such as geographic positioning system (GPS) signals, we are
moving into a world where the Internet of Things and the sensors that enable it are pervasive, and where advanced processing power
and machine learning allow the mining and processing of insights from massive amounts of unrelated data. To take full advantage of
the exciting possibilities these developments offer, however, supply chains will have to create a new kind of collaborative
"ecosystem" that incorporates multiple technology solutions.
Pairing visibility with action
For years, individual, closed networks that offer direct connectivity to suppliers and logistics providers have provided a certain
level of supply chain visibility. Certainly that visibility continues to be available, but it is becoming widely recognized that
this type of network is cumbersome and expensive. Now, as the three forces described above continue to converge and spark
innovation, we are seeing the emergence of several new approaches to achieving visibility:
The aggregated networks. One of the more widely available forms of visibility is provided by network aggregators.
These usually manifest themselves in the form of supplier portals or mode-specific carrier networks (ocean or truck networks,
for example). They often offer more than just "current state" visibility; for example, by providing transactional processing
into and out of the network.
The real-time trackers. Similar in some ways to an aggregated network, this form of visibility focuses on tapping into
near real-time location tracking, "bread crumbing" (visually representing a travel path), and geo-fence manipulation to get a
better picture of assets in motion.
The insight creators. The newest generation of visibility capabilities takes a step beyond simply understanding where
something is and instead seeks to understand where it is going to be, consequently moving from real-time tracking to being
predictive in nature. This approach combines multiple streams of seemingly unrelated structured and unstructured data. Using a
combination of advanced processing power and algorithms, it looks to formulate and communicate predictive rather than reactive
states.
While the growth of visibility technology is exciting and presents tremendous opportunities, technology alone will not achieve
the ultimate goal of supply chain fluidity and resiliency. Visibility without intelligent action is of limited value. Just like a
car with advanced sensors and warnings but poor brakes and steering will have difficulty avoiding an identified potential
collision, a supply chain with advanced visibility but poor planning and execution systems will have challenges responding
to identified disruptions.
The collaborative ecosystem
It is this concern that underpins the argument for creating a new type of arrangement: collaborative technology partnerships. We
can envision such a partnership as a hierarchical pyramid. The bottom tier represents available structured and unstructured
inputs, including data about suppliers, carriers, transactions, events, social media, GPS transmissions, weather, and so forth.
This data is ubiquitous, pervasive, continues to grow, and is becoming limited only by one's ability to frame "the art of the
possible"—in other words, to imagine new yet practical ways to acquire it.
The second tier represents the different visibility aggregators and insight-generation technologies. Here the spectrum of
available and potential technology can vary greatly. Supplier and carrier portals are a treasure trove of transactional and event
visibility, but they are often limited to just that, focusing more on data cleansing and integration than on advanced data
science. It is in this latter area, which is a difficult core competency to create or acquire, where we move from data aggregation
to the creation of correlations and insights.
The top of the pyramid represents the operational solutions spanning supply chain planning and execution that would "digest"
the inputs from the previous tiers and provide the ability to discern and execute intelligent action in a responsive and resilient
way. This top tier represents another core competency that is difficult to acquire. While some might say that supply chain
planning and execution solutions are mature and widely available, it takes a higher degree of solution maturity and openness to
be able to not just consume but also intelligently act upon this new generation of insights. This top tier requires specific
industry context (for example, fashion retail has different operational flows and metrics than industrial manufacturing),
sophisticated constraint representation, rapid solving capabilities, and open connectivity.
By leveraging this conceptual model, it becomes easy to understand that the larger the base of the pyramid, the more innovative
the insights generated, and that the more sophisticated the actionable solutions, the greater the visibility provided—and,
consequently, the greater the resiliency and value generated. For there to be true supply chain visibility, then, all tiers of the
pyramid need to be represented and work together; it cannot be achieved by a single solution providing only one aspect of
visibility.
Strategically speaking, this is where supply chain technology is headed over the next decade, evolving to incorporate disparate
streams of readily available data from best-of-breed technology solutions providers. This will allow supply chain participants to
make more active, dynamic decisions that reduce network latency while increasing supply chain resiliency and protecting profit
margins. That, in turn, will give them a competitive advantage, as the availability of a broad spectrum of real-time data enabled
by a supply chain visibility ecosystem will allow them to improve their responsiveness.
In our view, by increasing real-time visibility across the comprehensive set of supply chain resources discussed above, these
collaborative solutions will support a new level of speed and agility—and they will do so while providing a factual basis for the
decisions that deliver the most profit without compromising service. For companies that keep pace with technology improvements and
match them with new ways of working, a significant competitive advantage will be possible as we look toward the next few years.
Benefits for Amazon's customers--who include marketplace retailers and logistics services customers, as well as companies who use its Amazon Web Services (AWS) platform and the e-commerce shoppers who buy goods on the website--will include generative AI (Gen AI) solutions that offer real-world value, the company said.
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."