Logistics and supply chain managers are getting smarter ... at least when it comes to using software intelligence to run their supply chains. Sixty-five percent of the respondents to a survey on supply chain software usage said they now use software for analysis.
That was one of the key findings of the annual study conducted for CSCMP's Supply Chain Quarterly's sister publication, DC Velocity. The findings are based on 167 responses received from readers of both publications. The survey, now in its third year, provides a snapshot of how logistics and supply chain managers are using software to improve their operations.
The breakdown of survey respondents resembled that of previous studies. As in past surveys, manufacturers made up the largest category of survey takers, at 35 percent of respondents. Next came third-party logistics service providers (3PLs), at 15 percent. Wholesale distribution, retail, and transportation each accounted for 9 percent, while the remaining 23 percent fell into the "other" category. A plurality of survey takers came from small companies, with 56 percent working for companies with under $500 million in annual revenue.
WMS still number one
So what software tools are readers using? As was the case in the past two surveys, warehouse management systems (WMS) topped the list, with 50 percent of respondents using this application. Because a WMS oversees distribution center operations, it's a mainstay application for any company running a logistics or supply chain operation.
[Figure 2] What are the hot areas for analytics in the supply chain?Enlarge this image
[Figure 3] Why don't companies take advantage of analytics?Enlarge this image
The second most commonly used application was also no surprise. Enterprise resource planning (ERP) software, which serves as the system of record for financial transactions, was used by 46 percent of the survey respondents. In third place were order management systems, used by 43 percent. Fourth on the list was transportation management software (TMS), used by 41 percent—an unsurprising result given that the software, which is used for managing carriers, is a mainstay of today's logistics operations. In fifth place, cited by 35 percent, was analytics, a software category that's gaining in importance. (For the full list, see Figure 1.)
The ranking of the software tools in the middle also came as little surprise. Although demand planning offers value to large companies selling or making thousands of stock-keeping units (SKUs), many of their smaller counterparts still aren't using sophisticated software tools for forecasting. Similarly, inventory optimization tends to be used by companies struggling to manage the inventory for thousands of SKUs across several locations.
The tools ranked on the bottom of this list are either of interest to a narrow base or are new technology. For example, distributed order management systems, used by 10 percent, is deployed by omnichannel retailers to determine whether to fill an online order from a store or from a warehouse/distribution center. Another application, the control tower system, also cited by 10 percent, is a nascent technology that's now only being deployed by multinational companies to manage their end-to-end supply chains. Ten percent of respondents were using trade management software, an application only of value to companies involved in cross-border trade, and 8 percent were using demand sensing, an advanced application used currently by consumer product companies to quickly discern changes in consumer buying preferences.
Thirty percent of respondents had bought new supply chain software in the past year. Most popular were WMS packages, which were bought by 33 percent, while 24 percent bought a new TMS. Interestingly, the third most frequently purchased type of software was analytics, cited by 15 percent—another indication that more companies are interested in using software intelligence to gain insights into their operations.
The payback struggle continues
The survey found that many companies are still struggling with the issue of return on investment (ROI) on their software purchases. Although 43 percent of respondents said they had received the expected payback from a purchase, an equal number said they were unsure as to whether they had recouped their investment. On the other hand, 14 percent were firm in their view that their company had not received the expected return on their supply chain software investment, not surprising considering that a supply chain software license or subscription can run into the thousands of dollars and entail additional fees for consulting, training, and systems integration.
As the survey made clear, when it comes to payback, expectations vary widely. At one end of the spectrum were companies that expected payback within three months (7 percent). At the other were those that were willing to wait more than three years (6 percent). The remainder expected a return within one year (23 percent), within two years (10 percent), within six months (8 percent), and within three years (5 percent). It should be noted that 38 percent of survey takers said they did not know what the time frame was for expected payback at their company.
Many companies have found that cloud-based software provides a faster ROI than the traditional on-premise deployments; in fact, 49 percent of the respondents that are using cloud software said that this deployment method had shortened payback. Cloud solutions do not entail added costs for installation, hardware, systems integration, maintenance, and custom coding, and their lower upfront costs can translate to a quicker payback.
With those benefits, it's no surprise that the percentage of users moving to the cloud has increased over last year. Forty-five percent of survey respondents said that they are using cloud deployment for at least one type of supply chain software tool, compared to only 33 percent in last year's survey.
Growing use of analysis
The survey results underscored the growing use of software intelligence to find answers to supply chain problems as well as some of the issues associated with using these tools. Sixty-five percent of respondents said they are now using software for analysis. What's interesting is that only 32 percent are using tools especially designed for that purpose. This suggests that many companies conducting software analysis are taking advantage of the embedded analytics that are increasingly found in more advanced TMS, WMS, and inventory optimization (IO) packages.
When it comes to using software intelligence, almost half of those doing analysis—49 percent—use their tools for diagnostics to identify the root cause of problems. Another 43 percent use software for either descriptive or predictive analytics. (Descriptive analytics details and compares performance, while predictive analytics generally takes the form of demand planning tools.) Surprisingly, 39 percent said they were engaging in "big data" analysis, which involves sifting through reams of information for operational insights. Only 13 percent were engaged in cognitive analytics, which uses self-learning and machine-intelligence technologies to mine data, while 12 percent were making use of prescriptive analytics, which proposes solutions.
As for where they're applying these tools, the survey found that 62 percent of those respondents who are using analytics were using them for demand planning or forecasting, a critical business issue for companies trying to determine what to manufacture and distribute. Second on the list was inventory management, another important business issue, as companies must balance the cost of buffer inventory against the potential loss of revenue from a missed sale. Third was transportation, an area of concern as shippers seek to control shipping costs. (See Figure 2 for the complete list.)
Although more companies are turning to analytics, 25 percent have yet to take the plunge and another 10 percent are unsure if their companies are making use of these capabilities. When the nonusers were queried about the reasons for their hesitation, the top reason was lack of information technology (IT) support, cited by 32 percent. (See Figure 3.) That response is not surprising given that one of the issues bedeviling analytics right now is that many of those tools are not easy to use and often require the expertise of data scientists to assist in interpreting the results. The lack of data-visualization capabilities (which would allow users to see the results in the form of charts and graphs) and the need to use third-party software like Tableau to provide any type of results visualization are among the factors hindering greater adoption of analytics in business disciplines like logistics and supply chain management.
The integration challenge
Survey takers were also asked to name the biggest challenge they face to the successful deployment of a supply chain software application. As was the case last year, the number one challenge was systems integration, cited by 28 percent. Clearly, companies still find it difficult to get disparate systems to exchange information. Next on the list was the lack of IT resources, cited by 21 percent of respondents. Inadequate support from upper management, named by 17 percent, was the third most frequently cited challenge. (See Figure 3 for the complete list.)
Overall, the survey's findings underscore two themes in the business world in regard to information technology that, not surprisingly, are influencing supply chain software. Companies are increasingly turning to cloud deployments for software tools to receive a faster ROI and justify the expense. And despite obstacles such as the lack of data visualization, companies are starting to apply more analytics to gain insights into their operations in an effort to cut costs and boost profits.
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."