"Customer and Supplier Portfolios: Can Credit Risks Be Managed Through Supply Chain Relationships" by Matthew A. Schwieterman of Michigan State University and Thomas J. Goldsby and Keely L. Croxton of The Ohio State University. Published in the May 2018 issue of the Journal of Business Logistics.
THE UPSHOT
The nature or structure of a company's relationships with its customers and suppliers can have a direct impact on its financial performance. For example, if a prominent customer lengthens its payment terms, a supplier may see a decrease in its liquidity. Similarly, previous research has shown that a firm's share prices can be affected by the performance of its key customers.
Is there a similar link between the external market's perception of a company's supply chain relationships and the company's credit rating? This research sought to find out. The researchers chose to look specifically at two key ways to characterize a firm's portfolio of relationships with its suppliers and customers: concentration and balanced portfolio dependence. Concentration is defined as the portion of a firm's sale revenue that is received from its primary customers and the percentage of its purchasing spend that is allocated to its primary suppliers. Dependence relates to how much a company relies on its customer or supplier for its financial success. In some relationships, there is a power imbalance, where one party is more dependent on the other than the other is on it. In other relationships, the level of dependence is more equal. Balanced portfolio dependence is defined as the average degree of balance in dependence (based on the percentage of business each party allocates to the other) across the top customer and supplier relationships for a firm.
Previous research has found that these two characteristics can influence a company's financial outcomes. But is there a correlation between high customer or supplier concentration and a company's credit rating? Is there a correlation between a balanced portfolio dependence and a company's credit rating? The article's corresponding author, Matthew A. Schwieterman, explained to Supply Chain Quarterly Executive Editor Susan K. Lacefield what he and the rest of the research team found out and what it means for supply chain managers.
Q: What was the impetus for this research? Why were you interested in studying the relationship between supply chain portfolio characteristics and credit risks?
Based on the massive interest from the business community, supply chain relationships have been researched extensively in recent years. A variety of supply chain relationship issues have been explored, and a multitude of financial outcomes have been examined. For example, return on assets; return on sales; and earnings before interest, taxes, depreciation, and amortization margin have all been said to be influenced by supply chain structure.
As the popularity of supply chain management has grown, a variety of other outcomes have been proposed as being related to a company's supply chain strategy and practices. For example, concentrating sales to several large customers leads companies to hold excess cash to hedge against risks associated with loss of relationships. Similarly, these companies are likely to receive less favorable loan terms from banks and longer payment terms from customers. Given the large amount of interest in supply chain outcomes, we wanted to explore whether supply chain structure also affected a company's credit risks.
Q: Why did you choose to look at "concentration" and "balanced portfolio dependence" specifically?
Various studies in business and economics over the years have shown that these characteristics impact firm performance. However, these studies generally only considered financial performance. Based on our belief in the importance of supply chain structure, we wanted to extend the use of these characteristics to include other outcomes, such as credit ratings.
Q: What affect did your research show that concentration and balanced portfolio dependence had on credit ratings?
In a nutshell, both customer concentration and balanced customer portfolio dependence were shown to be beneficial to a company's credit ratings. However, supplier concentration and balanced supplier portfolio dependence had no significant effect. In plain terms, all else being equal, companies with several large, key customer relationships had better credit ratings than those that did not. Likewise, credit ratings were better for companies that had balanced relationships with customers, where each party represented relatively the same percentage of business to the other.
Q: Were any of the results surprising? Why, or why not?
We were happy to show that customer relationship characteristics were related to credit ratings but initially perplexed that supplier relationship characteristics were not. In hindsight though, this made sense as credit ratings are measures of a company's ability to meet its financial obligations. As such, revenue would be of key importance. The supplier characteristics, while important to other outcomes, would likely not feature a direct link to revenue as would the customer characteristics. The importance of supplier relationships on various supply chain outcomes would be a great area for more investigation in the future.
Q: How do you think that companies can apply your findings?
Companies can benefit from an awareness of the importance of supply chain structure to their overall performance, including credit ratings. Credit ratings are an important outcome, as they can impact the credit terms extended to companies.
Additionally, the findings point to the importance of managing customers and suppliers as a portfolio, with an awareness of how customers and suppliers are contributing to a company's strategy. When considering customer portfolio characteristics, companies should think about the possible benefits of large, prominent customers, especially as signals of future revenue to external evaluators, such as credit-rating agencies. Finally, balanced relationships may be important to success, and should be considered when possible.
Q: Do you think companies in general think about the effect that their supply chain relationships could have on their credit rating? Should these concepts of concentration and dependence affect who they choose to be suppliers and who they choose as customers?
We believe companies will continue to become more aware of the effect supply chain characteristics have upon various outcomes, including credit ratings. It makes sense to consider concentration and balanced dependence within customer portfolios when pursuing various customers. However, as with all key business decisions, many factors will need to be considered.
Q: What would you say is the key takeaway message of your research?
To put it broadly, supply chain structure is important! The decisions made by supply chain managers impact more than immediate financial metrics and have implications for a company's long-term success. Specifically, balanced relationships with large, key customers are associated with stronger credit ratings.
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."