The use of "big data" is taking on bigger relevance among shippers and their logistics providers.
"The 21st Annual Third-Party Logistics Study," which canvassed 342 shippers and their
third-party partners on issues impacting their businesses and partnerships, found that 98 percent of third-party logistics
providers (3PLs) and 93 percent of shippers believed data-driven decision-making was essential to the future of supply chain
activities. About 86 percent of 3PLs and 81 percent of shippers said the massive data sets—and a process known as "analytics" used to leverage the data in an effort to improve organizational processes—would become a core competency of their supply chain organizations.
Among 3PLs, 71 percent said big data's most valuable attribute lies in improving process quality and performance. About 70 percent said it is most important in enhancing logistics optimization, and 53 percent said it is optimally used to create better integration across the supply chain.
Similarly about 60 percent of shippers said big data and analytics would work best to improve supply chain integration. About 55 percent said it would have the most impact on enhancing data quality. About 52 percent said it would have the most value in improving process quality and performance.
However, there is a modest disconnect between the importance that shippers attach to big data, and the perceptions held by
their partners about their interest in the subject, according to the survey. About 79 percent of shippers said they see
significant value of big data and analytics. About 65 percent of their providers—a 14 percentage-point drop—reported their customers thought the subject was key to their supply chain performance. This gap may indicate that 3PLs are understating the importance of the big data process inside their customers' organizations.
Also, shippers have become more pragmatic about how much their partners can hope to achieve through their efforts. About 35
percent of shippers surveyed said they believed 3PLs could support their big data initiatives, down from 44 percent in 2014.
Tom McKenna, senior vice president, engineering and technology for Reading, Pa.-based 3PL Penske Logistics, said the supply
chain is still just beginning to understand how to process the avalanche of data as well as how to then properly evaluate where it would have the biggest bang for the buck. In an interview earlier this week at the Council of Supply Chain Management
Professionals (CSCMP) annual global meeting in Orlando, McKenna said one of the challenges faced by shippers and 3PLs alike
is that each side collects its own mountain of data, which then must be merged to gain the most visibility into a problem and its execution.
Penske uses the process to support what McKenna called its "strategic accounts," which are larger companies with deep,
long-term relationships that are not based on transactions, but on the overall value a company sees in the relationship.
The survey's core finding—a broad gauge of how the two sides feel about their relationships—appeared to bring
modestly encouraging news. About 91 percent of shippers and 97 percent of 3PLs said their relationships were mutually successful and the work was yielding positive results. About 86 percent of shippers and 98 percent of 3PLs said their efforts led to improvements in customer service.
At the same time, 90 percent of 3PLs said they brought innovative solutions to the table, while about 73 percent of shippers felt that way. In addition, 93 percent of 3PLs said the joint work yielded cost reductions, while 75 percent of shippers thought was the case, the survey found.
The two sides were deeply divided on how much value stems from collaborating with other companies, even rivals, to achieve
greater overarching value. About 86 percent of 3PLs thought collaboration with outsiders would be beneficial, while only 44
percent of shippers surveyed felt that way. The gap may underscore that a 3PL is quite comfortable working with multiple
shippers, some of who may compete with each other, while shippers are loath to see much positive coming from deep dives with
the competition.
McKenna said the broad outcome of the survey is that shippers increasingly see more value in their 3PL relationships. This, in turn, is narrowing the long-standing perception gap between shipper's views on a 3PL's value, and how effectively the 3PL believes it's performing.
The survey was produced by Capgemini Consulting, Penn State University, and Penske Logistics. Shippers comprised 44 percent of respondents, providers accounted for 43 percent, and so-called nonusers made up the rest. About 54 percent of respondents worked for companies with more than $1 billion in sales, while 21 percent represented firms with annual sales of $25 billion or more.
Supply chain planning (SCP) leaders working on transformation efforts are focused on two major high-impact technology trends, including composite AI and supply chain data governance, according to a study from Gartner, Inc.
"SCP leaders are in the process of developing transformation roadmaps that will prioritize delivering on advanced decision intelligence and automated decision making," Eva Dawkins, Director Analyst in Gartner’s Supply Chain practice, said in a release. "Composite AI, which is the combined application of different AI techniques to improve learning efficiency, will drive the optimization and automation of many planning activities at scale, while supply chain data governance is the foundational key for digital transformation.”
Their pursuit of those roadmaps is often complicated by frequent disruptions and the rapid pace of technological innovation. But Gartner says those leaders can accelerate the realized value of technology investments by facilitating a shift from IT-led to business-led digital leadership, with SCP leaders taking ownership of multidisciplinary teams to advance business operations, channels and products.
“A sound data governance strategy supports advanced technologies, such as composite AI, while also facilitating collaboration throughout the supply chain technology ecosystem,” said Dawkins. “Without attention to data governance, SCP leaders will likely struggle to achieve their expected ROI on key technology investments.”
The U.S. manufacturing sector has become an engine of new job creation over the past four years, thanks to a combination of federal incentives and mega-trends like nearshoring and the clean energy boom, according to the industrial real estate firm Savills.
While those manufacturing announcements have softened slightly from their 2022 high point, they remain historically elevated. And the sector’s growth outlook remains strong, regardless of the results of the November U.S. presidential election, the company said in its September “Savills Manufacturing Report.”
From 2021 to 2024, over 995,000 new U.S. manufacturing jobs were announced, with two thirds in advanced sectors like electric vehicles (EVs) and batteries, semiconductors, clean energy, and biomanufacturing. After peaking at 350,000 news jobs in 2022, the growth pace has slowed, with 2024 expected to see just over half that number.
But the ingredients are in place to sustain the hot temperature of American manufacturing expansion in 2025 and beyond, the company said. According to Savills, that’s because the U.S. manufacturing revival is fueled by $910 billion in federal incentives—including the Inflation Reduction Act, CHIPS and Science Act, and Infrastructure Investment and Jobs Act—much of which has not yet been spent. Domestic production is also expected to be boosted by new tariffs, including a planned rise in semiconductor tariffs to 50% in 2025 and an increase in tariffs on Chinese EVs from 25% to 100%.
Certain geographical regions will see greater manufacturing growth than others, since just eight states account for 47% of new manufacturing jobs and over 6.3 billion square feet of industrial space, with 197 million more square feet under development. They are: Arizona, Georgia, Michigan, Ohio, North Carolina, South Carolina, Texas, and Tennessee.
Across the border, Mexico’s manufacturing sector has also seen “revolutionary” growth driven by nearshoring strategies targeting U.S. markets and offering lower-cost labor, with a workforce that is now even cheaper than in China. Over the past four years, that country has launched 27 new plants, each creating over 500 jobs. Unlike the U.S. focus on tech manufacturing, Mexico focuses on traditional sectors such as automative parts, appliances, and consumer goods.
Looking at the future, the U.S. manufacturing sector’s growth outlook remains strong, regardless of the results of November’s presidential election, Savills said. That’s because both candidates favor protectionist trade policies, and since significant change to federal incentives would require a single party to control both the legislative and executive branches. Rather than relying on changes in political leadership, future growth of U.S. manufacturing now hinges on finding affordable, reliable power amid increasing competition between manufacturing sites and data centers, Savills said.
The number of container ships waiting outside U.S. East and Gulf Coast ports has swelled from just three vessels on Sunday to 54 on Thursday as a dockworker strike has swiftly halted bustling container traffic at some of the nation’s business facilities, according to analysis by Everstream Analytics.
As of Thursday morning, the two ports with the biggest traffic jams are Savannah (15 ships) and New York (14), followed by single-digit numbers at Mobile, Charleston, Houston, Philadelphia, Norfolk, Baltimore, and Miami, Everstream said.
The impact of that clogged flow of goods will depend on how long the strike lasts, analysts with Moody’s said. The firm’s Moody’s Analytics division estimates the strike will cause a daily hit to the U.S. economy of at least $500 million in the coming days. But that impact will jump to $2 billion per day if the strike persists for several weeks.
The immediate cost of the strike can be seen in rising surcharges and rerouting delays, which can be absorbed by most enterprise-scale companies but hit small and medium-sized businesses particularly hard, a report from Container xChange says.
“The timing of this strike is especially challenging as we are in our traditional peak season. While many pulled forward shipments earlier this year to mitigate risks, stockpiled inventories will only cushion businesses for so long. If the strike continues for an extended period, we could see significant strain on container availability and shipping schedules,” Christian Roeloffs, cofounder and CEO of Container xChange, said in a release.
“For small and medium-sized container traders, this could result in skyrocketing logistics costs and delays, making it harder to secure containers. The longer the disruption lasts, the more difficult it will be for these businesses to keep pace with market demands,” Roeloffs said.
Jason Kra kicked off his presentation at the Council of Supply Chain Management Professionals (CSCMP) EDGE Conference on Tuesday morning with a question: “How do we use data in assessing what countries we should be investing in for future supply chain decisions?” As president of Li & Fung where he oversees the supply chain solutions company’s wholesale and distribution business in the U.S., Kra understands that many companies are looking for ways to assess risk in their supply chains and diversify their operations beyond China. To properly assess risk, however, you need quality data and a decision model, he said.
In January 2024, in addition to his full-time job, Kra joined American University’s Kogod School of Business as an adjunct professor of the school’s master’s program where he decided to find some answers to his above question about data.
For his research, he created the following situation: “How can data be used to assess the attractiveness of scalable apparel-producing countries for planning based on stability and predictability, and what factors should be considered in the decision-making process to de-risk country diversification decisions?”
Since diversification and resilience have been hot topics in the supply chain space since the U.S.’s 2017 trade war with China, Kra sought to find a way to apply a scientific method to assess supply chain risk. He specifically wanted to answer the following questions:
1.Which methodology is most appropriate to investigate when selecting a country to produce apparel in based on weighted criteria?
2.What criteria should be used to evaluate a production country’s suitability for scalable manufacturing as a future investment?
3.What are the weights (relative importance) of each criterion?
4.How can this methodology be utilized to assess the suitability of production countries for scalable apparel manufacturing and to create a country ranking?
5.Will the criteria and methodology apply to other industries?
After creating a list of criteria and weight rankings based on importance, Kra reached out to 70 senior managers with 20+ years of experience and C-suite executives to get their feedback. What he found was a big difference in criteria/weight rankings between the C-suite and senior managers.
“That huge gap is a good area for future research,” said Kra. “If you don’t have alignment between your C-suite and your senior managers who are doing a lot of the execution, you’re never going to achieve the goals you set as a company.”
With the research results, Kra created a decision model for country selection that can be applied to any industry and customized based on a company’s unique needs. That model includes discussing the data findings, creating a list of diversification countries, and finally, looking at future trends to factor in (like exponential technology, speed, types of supply chains and geopolitics, and sustainability).
After showcasing his research data to the EDGE audience, Kra ended his presentation by sharing some key takeaways from his research:
China diversification strategies alone are not enough. The world will continue to be volatile and disruptive. Country and region diversification is the only protection.
Managers need to balance trade-offs between what is optimal and what is acceptable regarding supply chain decisions. Decision-makers need to find the best country at the lowest price, with the most dependability.
There is a disconnect or misalignment between C-suite executives and senior managers who execute the strategy. So further education and alignment is critical.
Data-driven decision-making for your company/industry: This can be done for any industry—the data is customizable, and there are many “free” sources you can access to put together regional and country data. Utilizing data helps eliminate path dependency (for example, relying on a lean or just-in-time inventory) and keeps executives and managers aligned.
“Look at the business you envision in the future,” said Kra, “and make that your model for today.”
Turning around a failing warehouse operation demands a similar methodology to how emergency room doctors triage troubled patients at the hospital, a speaker said today in a session at the Council of Supply Chain Management Professionals (CSCMP)’s EDGE Conference in Nashville.
There are many reasons that a warehouse might start to miss its targets, such as a sudden volume increase or a new IT system implementation gone wrong, said Adri McCaskill, general manager for iPlan’s Warehouse Management business unit. But whatever the cause, the basic rescue strategy is the same: “Just like medicine, you do triage,” she said. “The most life-threatening problem we try to solve first. And only then, once we’ve stopped the bleeding, we can move on.”
In McCaskill’s comparison, just as a doctor might have to break some ribs through energetic CPR to get a patient’s heart beating again, a failing warehouse might need to recover by “breaking some ribs” in a business sense, such as making management changes or stock write-downs.
Once the business has made some stopgap solutions to “stop the bleeding,” it can proceed to a disciplined recovery, she said. And to reach their final goal, managers can use the classic tools of people, process, and technology to improve what she called the three most important key performance indicators (KPIs): on time in full (OTIF), inventory accuracy, and staff turnover.