In modern networked supply chains, the increasing number and frequency of severe supply chain disruptions means that "business as unusual" has become business as usual. According to a survey conducted last year, more than eight out of 10 surveyed companies have been hit by a supply or demand disruption during the past two years, with almost half of those firms suffering a loss of sales or revenue, and more than one-third having experienced lower profits as a result of a disruption. 1 While the reporting of natural disasters over ubiquitous social media channels tends to skew trends toward modern times, occurrences of large-scale natural disasters, such as the Thai floods, the Icelandic volcanic eruption, the Japanese tsunami, and more have in fact increased over the last century, as is evident in Figure 1. It is no secret that disasters are on the rise and are a reality of a globalized world.
Although the exact consequences of disruptions are hard to measure, the financial impact of such disruptions—both natural and man-made—can be indirectly estimated at both the macro and the micro level. One way to assess the impact of large-scale disruptions is to follow the trends in the stock indices that are specific to the country that has been most directly affected. For example, the Japanese earthquake and tsunami resulted in the Nikkei Index dropping by over 17 percent in the three days following the disaster; the September 11, 2001, terrorist attacks caused the Standard & Poor's index to lose nearly 12 percent over four days after the stock markets reopened following the incident. Supply chain disruptions can have a drastic impact at the organizational level too. A study by Singhal and Hendricks identified a considerable impact on revenue following a disruption, with 30 percent of surveyed firms estimating losses of at least 5 percent of annual revenue as a result of supply chain disruptions.2
Clearly, supply chain disruptions can have a domino effect on organizations and on global commerce. Natural disasters first cause disruption at the macro level. That can then affect an organization's supply chain as disruptions first impact the organization itself, and then cause a chain reaction spreading across suppliers, customers, partners, and the shared value chain. (See Figure 2.) In addition to a direct bottom-line cost impact, supply chain disruptions can also result in unhappy customers, loss of reputation, civil and criminal penalties, and even bankruptcy.
Supply chain disruptions are no doubt hard to predict, but organizations can control the extent to which these disruptions could impact their companies. Toward that end, it is increasingly important for organizations to develop mature risk assessment capabilities and techniques such as supply chain segmentation, quantitative risk assessment, and scenario planning. These tools allow supply chain executives to better understand supply chain risks and develop appropriate risk mitigation strategies.
Supply chain segmentation Supply chain segmentation is both a strategic and an operational exercise. For the purposes of this article, it is defined as a SCOR (Supply Chain Operations Reference model) methodology that identifies distinct supply chains within an organization based on geography/market channel and product offerings. It can be used to identify unique supply chains and develop risk assessment and mitigation strategies for each of them.
As a precursor to assessing risks in the supply chain, it is important to first understand the unique supply chains within the organization. This is especially important in large organizations that have multiple product offerings that are managed via multiple distribution channels. While high-level risks can be assessed at the organization level, it is ideal to first segment the supply chain and then develop risk assessment programs for each unique supply chain.
One way to segment the supply chain is to use the SCOR framework, specifically the SCOR supply chain definition matrix. The supply chain definition matrix helps define the number of supply chains in relation to a company's customers and products or services. The columns in the matrix are focused on demand—markets, channels, and customers, while the rows in the matrix are focused on supply—business lines, products, locations, and suppliers.
Consider the example shown in Figure 3. A hypothetical company has three main product lines: food products, technology products, and durable products. Food products are distributed across five channels (U.S. retail, U.S. distributor, U.S. direct, U.S. government, and international). Tech products are distributed across three channels (U.S. retail, U.S. original equipment manufacturers [OEM], and international), and durables are distributed across two channels (U.S. direct and U.S. home). In effect, this organization has 10 unique supply chains, each with its own inherent supply chain risks.
It may not be practical for organizations to conduct a risk assessment on all of their supply chains, hence it is important to identify the most important ones using a "Supply Chain Priority Matrix" like the example shown in Figure 4. To set up this matrix:
List all of your company's unique supply chains as identified in the previous step, and then identify key performance indicators (KPIs) that are most important to your organization. In this example, the organization cares most about rank in terms of revenue, gross margin percentage, number of stock-keeping units (SKUs), unit volume, and strategic importance. Weights can be assigned to each of these KPIs to reflect its importance to the organization.
For each KPI, assign a rank to each product-channel group based on how well (or not) that group contributed to the KPI. The highest-ranking supply chain receives a high number, and the lowest-ranking supply chain receives a "1." In this example, food products that were distributed to U.S. government agencies had a revenue rank of 1 (worst), while tech products distributed to U.S retail had a revenue rank of 6 (best).
Finally, complete this exercise for all product-channel and KPI combinations. The end result will be a listing of overall ratings for each of the organization's supply chains. In this example, food products-U.S. retail and tech products-U.S. retail scored the highest ratings, implying that these two supply chains were the most important for this organization.
This exercise can be conducted individually, but subject-matter expertise may be required from different departments. For that reason, it is recommended that it be done in a group composed of key personnel from the different product groups and operations teams. Moreover, since supply chain risks can impact different functions within an organization, it is important to engage cross-functional teams early on to make them aware of the supply chain risk management program and to seek their insight on strategic issues that may need to be considered in developing such a program.
Risk quantification Risk quantification is an operational matter. It consists of quantification of supply chain risks across nine categories, and the creation of functional risk profiles. Its purpose is to identify, segment, and prioritize different external and internal supply chain risks.
Once organizations have segmented and identified their most important, unique supply chains, they can then start to identify risks that are specific to their operations and quantify the risk elements. The following categories form a comprehensive base covering almost all aspects of an organization:
Internal risks: financial, production and inventory, transportation, labor, information technology (IT) External risks: supply, demand, natural hazard, political
Organizations may choose to quantify the risks embedded in each category as listed above, or choose only a subset of categories, depending on what applies to their particular supply chain environment and business strategies.
The basis for quantifying risks starts with the fundamental formula:
Risk = Probability of risk occurring * Impact of that occurrence
To use this formula:
Create a scale. First, create a 1-to-5 scale to measure both probability and impact, with 1 being the lowest and 5 being the highest.
Determine the "risk boundaries." Since the ranges for both P (probability) and I (impact) are from 1 to 5, risk is now measured on a scale of 1 to 25, because Risk=P*I. Hence the lower boundary for risk is 1*1=1 (when P and I both have the minimum value of 1), and the upper boundary is 5*5=25 (where P and I both have the maximum value of 5).
Define risk levels. Given that the risk profile can vary anywhere from 1 to 25, the next step is to define levels of risk using the value ranges. For example, risk levels can be defined as:
Lower boundary
Upper boundary
Low risk
1.00
8.50
Medium risk
8.50
16.50
High risk
16.51
25.00
Once the boundaries of risk levels have been defined, a matrix for easy reference, like the one shown in Figure 5, can be created.
Assign risk levels to categories. As a next step, each risk category, including both internal and external risks, should be assessed individually against the risk boundaries created. Each risk category will score a risk rating in the range of 1 to 25 and should be categorized as high, medium, or low risk based on the risk boundaries created earlier.
Calculate the organizational supply chain risk score. As a final step, assign a weight to each risk category based on its strategic impact on the organization's supply chain. The weights should be in the range of 0 to 100 percent, and the cumulative weight of all risk categories should total 100 percent. A simple dashboard can be created in a program such as Excel listing the risk categories, the weights, and the final risk score, as shown in Figure 6. For this particular example, the weighted average risk calculates out to 9.56, which represents a "medium" risk level based on the risk boundaries created earlier.
Scenario planning Scenario planning is a hypothesis-driven, strategic planning method that involves developing "informed predictions"—that is, "future state" scenarios—and building response strategies for operating under each scenario. Its purpose is to prepare an organization for most plausible eventualities, and to enable it to steer through disruptions in such a way that there will be no substantial impact on its supply chains.
Scenario planning was originally conceived in the 1940s for military applications. But the roots of modern-day scenario planning were developed in the early 1970s by the petroleum company Royal Dutch Shell. Back then, Shell developed a set of possible future scenarios and built response strategies around the price of oil for each scenario. As a result, Shell was better prepared than its competition in reacting to risk and volatility, and consequently made better headway than the rest of the industry.
At a high level, the process of developing scenarios is as follows:
Identify the "focal question." The first step in building scenarios is to identify the focal question—the problem or opportunity—that is to be explored. There are hundreds of scenarios that could be developed about the future, but the objective is to address that one key issue that would have the biggest impact on the organization. The focal question can be broad; for example, "Should we expand into China and open X number of additional distribution centers?" Or it can be very specific; for example, "Should we invest in a multimillion-dollar enterprise resource planning (ERP) system?"
Identify the "driving forces." Driving forces are internal or external factors that will shape future supply chain dynamics and consequently impact the business environment in which the organization operates. Driving forces can include such issues as literacy rate, aging population, gross domestic product (GDP) growth, political stability, government regulations, technological innovations, and so forth.
Develop scenarios. Once a comprehensive list of driving forces has been identified, the next step is to prune the list down to the two sets that are most relevant to the focal question, along axes of uncertainties. By combining the two driving forces along horizontal and vertical axes, we end up with four quadrants, each of which represents a unique future-state scenario that needs to be explored. For example, let's assume that for the focal question "Should we expand into China and open X number of additional distribution centers?" the two driving forces identified are "strength of China's economy" and "government regulations." By assuming the extreme possible outcome of each driving force, and then combining these two driving forces along the X and Y axes, four quadrants are created, each of which houses a unique future-state scenario. Each scenario is identified by a unique name, and the predicted resulting environment is described in as much detail as possible.
For example, for the scenario titled "Accelerated Growth," you might write a short narrative that paints a picture of a booming economy, double-digit business growth, productive labor force, and so forth. The core objective here is to identify the conditions under which your organization would have to operate if the said scenario were to materialize. (See Figure 7 for an example.)
Identify scenario implications. The final step in scenario planning is to capture insights into how the organization would fare and what decisions it should make under each scenario. For each scenario, the potential impact of organizational and decisional behavior can be assessed by setting up simulation models or by simple brainstorming exercises.
The deployment of scenario planning by organizations and its continued use validates the method as a key aspect in strategic planning and in risk assessment. At a recent Council of Supply Chain Management Professionals (CSCMP) conference, a speaker highlighted a video that was shot in the 1960s, in which the narrator predicts how the world will look in the year 1999. It is quite remarkable how accurately future inventions were predicted and future-state scenarios painted. (By the way, this video is available on YouTube by searching for "Year 1999 A.D.")
The benefits of implementing scenario planning are summed up by one of its pioneers, Arie de Geus: "Scenarios are stories. They are works of art, rather than scientific analyses. The reliability of (their content) is less important than the types of conversations and decisions they spark."
Art and science
Accurately predicting disruptions and completely mitigating risks remains improbable, but by implementing the risk management practices described above, practitioners can be better prepared to manage risks and mitigate some of their impact. In addition, the above techniques can help practitioners: segment the supply chain based on product groups and marketing channels and identify risks specific to each segment; identify risk categories and quantify each risk item based on probability and impact; and plan strategically and develop risk mitigation strategies for different future-state scenarios.
Supply chain risk management is both an art and a science. The art aspect comes from years of experience and sometimes reflects "gut feelings," and the science aspect comes from developing and implementing risk management capabilities in the organization. While three risk management practices were highlighted in this article, it is also worth exploring the newer methods that continue to be developed as organizations search for improved ways of managing supply chain risk and developing competitive advantages in increasingly globalized and complex supply chain networks.
Notes: 1.The Chief Supply Chain Officer Report 2012, SCM World (September 2012). 2. Kevin B. Hendricks and Vinod R. Singhal, "An Empirical Analysis of the Effect of Supply Chain Disruptions on Long-Run Stock Price Performance and Equity Risk of the Firm," Production and Operations Management 14.1 (March 2005): 35-52.
Investing in artificial intelligence (AI) is a top priority for supply chain leaders as they develop their organization’s technology roadmap, according to data from research and consulting firm Gartner.
AI—including machine learning—and Generative AI (GenAI) ranked as the top two priorities for digital supply chain investments globally among more than 400 supply chain leaders surveyed earlier this year. But key differences apply regionally and by job responsibility, according to the research.
Twenty percent of the survey’s respondents said they are prioritizing investments in traditional AI—which analyzes data, identifies patterns, and makes predictions. Virtual assistants like Siri and Alexa are common examples. Slightly less (17%) said they are prioritizing investments in GenAI, which takes the process a step further by learning patterns and using them to generate text, images, and so forth. OpenAI’s ChatGPT is the most common example.
Despite that overall focus, AI lagged as a priority in Western Europe, where connected industry objectives remain paramount, according to Gartner. The survey also found that business-led roles are much less enthusiastic than their IT counterparts when it comes to prioritizing the technology.
“While enthusiasm for both traditional AI and GenAI remain high on an absolute level within supply chain, the prioritization varies greatly between different roles, geographies, and industries,” Michael Dominy, VP analyst in Gartner’s Supply Chain practice, said in a statement announcing the survey results. “European respondents were more likely to prioritize technologies that align with Industry 4.0 objectives, such as smart manufacturing. In addition to region differences, certain industries prioritize specific use cases, such as robotics or machine learning, which are currently viewed as more pragmatic investments than GenAI.”
The survey also found that:
Twenty-six percent of North American respondents identified AI, including machine learning, as their top priority, compared to 14% of Western Europeans.
Fourteen percent of Western European respondents identified robots in manufacturing as their top choice compared to just 1% of North American respondents.
Geographical variances generally correlated with industry-specific priorities; regions with a higher proportion of manufacturing respondents were less likely to select AI or GenAI as a top digital priority.
Digging deeper into job responsibilities, just 12% of respondents with business-focused roles indicated GenAI as a top priority, compared to 28% of IT roles. The data may indicate that GenAI use cases are perceived as less tangible and directly tied to core supply chain processes, according to Gartner.
“Business-led roles are traditionally more comfortable with prioritizing established technologies, and the survey data suggests that these business-led roles still question whether GenAI can deliver an adequate return on investment,” said Dominy. “However, multiple industries including retail, industrial manufacturers and high-tech manufacturers have already made GenAI their top investment priority.”
An overwhelming majority (81%) of shoppers do not plan to increase their holiday spend this year over last year, revealing a significant disconnect between retail marketers and shoppers in the weeks before peak season, according to online shopping platform provider Rakuten.
That result flies in the face of high confidence levels from retailers who have been delaying their marketing spend, as 79% of marketers are optimistic they will reach holiday sales objectives, and 65% are timing their spend as late as November.
However, consumers are nervous about supply chain disruptions. Almost half (42%) of shoppers have started their shopping early to avoid shipping delays, while 32% plan to do more shopping in-store to avoid potential delays. The results come from a survey conducted online within the U.S. by The Harris Poll on behalf of Rakuten from Sept. 5 – Sept. 9 , among 2,100 consumers aged 18 and older and 101 retail marketers.
"There's a clear disconnect between marketer perception and consumer realities, but this presents a unique opportunity for retailers to capitalize on the shortcomings of their competition," said Julie Van Ullen, Chief Revenue Officer at Rakuten Rewards. "As shoppers plan to spend less overall, there become fewer opportunities for retailers. This makes it evermore important for retailers to invest in strategies that set them apart throughout the entire holiday season.”
Three reasons behind the diverging views are:
Inflated prices. Even with softening inflation rates, nearly half (46%) of shoppers report that it will have the greatest impact on their holiday shopping strategy. Conversely, only 20% of marketers believe that to be true.
Election nerves. Shoppers anticipate that the upcoming election will have an impact on inflation, with 57% believing it will increase.
Weak brand loyalty. A majority of marketers (98%) believe shoppers will remain loyal to brands, but fully 42% of shoppers indicate they will prioritize finding the lowest prices by trading down to lower-quality brands and products for more affordable alternatives.
"Loyalty is up for grabs this holiday season, and success for retailers will hinge on offering value beyond just reduced prices," Julie Van Ullen, Chief Revenue Officer at Rakuten Rewards, said in a release. "Our research revealed that shopper concern extends beyond just price, and retailers will need to address those concerns with comprehensive deals that include several table-stake incentives. Incentives like free shipping, buy now pay later services, and elevated Cash Back will be important for maintaining a loyal shopper base."
Regardless of the elected administration, the future likely holds significant changes for trade, taxes, and regulatory compliance. As a result, it’s crucial that U.S. businesses avoid making decisions contingent on election outcomes, and instead focus on resilience, agility, and growth, according to California-based Propel, which provides a product value management (PVM) platform for manufacturing, medical device, and consumer electronics industries.
“Now is not the time to wait for the dust to settle,” Ross Meyercord, CEO of Propel, said in a release. “Companies should approach this election cycle as an opportunity to thrive in the face of constant change by proactively investing in technology and talent that keeps them nimble. Businesses always need to be prepared for changing tariffs, taxes, or geopolitical tensions that lead to unexpected interruptions – that’s just the new normal.”
In Propel’s analysis, a Trump administration would bring a continuation of corporate tax cuts intended to bolster American manufacturing. However, Trump’s suggestion for spiraling tariffs may benefit certain industries, but would drive up costs for businesses reliant on global supply chains.
In contrast, a Harris administration would likely continue the current push for regulatory reforms that support sectors like AI, digital assets, and manufacturing while protecting consumer rights. Harris would also likely prioritize strategic investments in new technologies and provide tax incentives to promote growth in underserved areas.
And regardless of the new administration, the real challenge will come from a potentially divided Congress, which could impact everything from trade negotiations to tax policies, Propel said.
“The election outcome is less material for businesses,” Meyercord said. “What is important is quickly adapting to shifting policies or disruptions that address ‘what if’ scenarios and having the ability to pivot your strategy. A responsive manufacturing sector will have a significant impact on the broader economy, driving growth and favorably influencing GDP. One thing is clear: the only certainty is change.”
With that money, qualified ports intend to buy over 1,500 units of cargo handling equipment, 1,000 drayage trucks, 10 locomotives, and 20 vessels, as well as shore power systems, battery-electric and hydrogen vehicle charging and fueling infrastructure, and solar power generation.
For example, funds going to the Port of Los Angeles include a $412 million grant to support its goal of achieving 100% zero-emission (ZE) terminal operations by 2030. And following the award, the Port and its private sector partners will match the EPA grant with an additional $236 million, bringing the total new investment in ZE programs at the Port of Los Angeles to $644 million. According to the Port of Los Angeles, the combined new funding will go toward purchasing nearly 425 pieces of battery electric, human-operated ZE cargo-handling equipment, installing 300 new ZE charging ports and other related infrastructure, and deploying 250 ZE drayage trucks. The grant will also provide for $50 million for a community-led ZE grant program, workforce development, and related engagement activities.
And the Port of Oakland received $322 million through the grant, which will generate a total of nearly $500 million when combined with port and local partner contributions. Altogether, that total will be the largest-ever amount of federal funding for a Bay Area program aimed at cutting emissions from seaport cargo operations. The grant will finance 663 pieces of zero-emissions equipment which includes 475 drayage trucks and 188 pieces of cargo handling equipment.
Likewise, the Port of Virginia said its $380 million in new funding will help to reach its goal of eliminating all greenhouse gas emissions by 2040. The grant money will be used to buy and install electric assets and equipment while retiring legacy equipment powered by engines that burn gasoline or diesel fuel.
According to AAPA, those awards will demonstrate to Congress that the Clean Ports Program should become permanent with annual appropriations. Otherwise, they would soon cease to be funded as backing from the Inflation Reduction Act (IRA) comes to a close, AAPA said. “From the earliest stages of legislative development in Congress, America’s ports have been ecstatic about and committed to the vision of implementing a novel grant program for the port industry that will complement and strengthen existing plans to diversify how we power our ports,” Cary Davis, AAPA’s president and CEO, said in a release. “These grant funding awards will usher in a cleaner and more resilient future for our ports and national transportation system. We thank our champions in Congress and the Biden-Harris Administration for committing to us and we look forward to working closely with our Federal Government partners to get these funds quickly deployed and put to work.”
The majority of American consumers (86%) plan to reduce their holiday shopping budgets this year, with nearly half (47%) expecting to cut spending by more than 50% compared to last year, according to consumer research from Relex Solutions.
The forecast runs against some other studies that predict the upcoming holiday shopping season will be stronger than last year, with higher sales and earlier shopping than 2023.
But Finland-based Relex says its conclusion is based on the shorter holiday shopping period of 27 days in 2024 (five days shorter than 2023), combined with economic volatility and supply chain disruptions. The research includes survey responses from 1,000 U.S. consumers in October 2024.
According to Relex, those results reveal a complex landscape where price sensitivity and decreased brand loyalty are reshaping traditional retail dynamics. That means retailers and manufacturers must carefully balance promotional strategies with profitability while maintaining product availability, since consumers are actively seeking better value and may switch between brands more readily.
"Retailers are facing a highly challenging season, with consumers prioritizing value more than ever. To succeed, retailers must not only offer attractive promotions but also ensure those deals don’t erode their margins. At the same time, manufacturers need to optimize their operations and collaborate with retailers to deliver value without sacrificing profitability," Madhav Durbha, Relex’ group vice president of CPG and Manufacturing, said in a release. The company says it provides a supply chain and retail planning platform that optimizes demand, merchandising, supply chain, operations, and production planning.
"This holiday season represents a critical juncture for the retail industry," Durbha added. "With reduced brand loyalty and a shorter shopping window, there’s no room for error. Retailers and manufacturers need to work together closely, leveraging AI-powered tools to anticipate demand, manage inventory, and run effective promotions," Durbha said.
In additional findings, the survey found:
Brand loyalty is eroding: About 45% of consumers say they're less likely to remain loyal to brands without meaningful discounts, while 41% will switch brands if faced with both poor deals and out-of-stock products.
Digital channels dominate deal-seeking behavior: Store and brand apps (60%) and email promotions (60%) are the primary channels for finding deals, while only 32% of consumers primarily search for deals in physical stores.
Supply chain concerns remain significant: Nearly 85% of shoppers express concern about potential disruptions, with electronics (60%) and clothing/accessories (57%) being the categories of highest concern.
Age significantly impacts shopping behavior: Consumers from age 45-60 show the highest economic sensitivity, with 60% cutting budgets by more than 50%, while shoppers aged 18-29 prioritize product availability over price.