05-12-26 | BY FAST COMPANY CUSTOM STUDIO
For decades, supply-chain management has been an exercise in precision—shave a day off transit, squeeze a cent out of packaging, trim the inventory. The discipline’s guiding star was efficiency. Over the next five years, it will be joined by a constellation of more volatile forces: geopolitical rivalries, tariffs, climate-driven disruption, energy shocks, and a surge of AI and robotics investment that promises transformation but demands scale.
That interconnection may be the defining feature of the new environment. “There are several factors that can be isolated individually, but the real challenge is the connectivity,” says Geoff Dabelko, a professor at Ohio University’s Voinovich School of Leadership and Public Service. “International tensions, natural disasters—these are not in isolation from rapid environmental change and climate change impacts that are also not incremental.”
Dabelko points to recent history for precedent. In 2010, wildfires and drought in Russia triggered a wheat export ban that sent global prices soaring, and fertilizer and energy markets lurched—a cascade of weather, policy, and market reactions that rewrote food security almost overnight. A similar torrent is building today: AI data centers are driving electricity demand that the International Energy Agency (IEA) projects will more than double globally by 2030, even as the U.S. pulls back federal support for renewable energy. Companies navigating this environment, Dabelko says, are doing it “with one hand tied behind [their] back.”
— Geoff Dabelko, Ohio University’s Voinovich School of Leadership and Public Service
“Robotics is not one-size-fits-all. It depends on your product profile. Leaders have to be patient.”
Some large operators are already moving in that direction, blending human judgment with sharper technology. Scotts Miracle-Gro, the 156-year-old lawn and garden company with more than 80 manufacturing facilities, leaned on AI to solve an inventory problem its people couldn’t untangle on their own. “Coming out of COVID, we had a ton of challenges with inventory buildup, and frankly, the math equation was not something a human could solve,” David Huskisson, Scotts’ head of enterprise transformation, recalled during the same Manifest panel. “We were able to reduce our year-ending average inventory by $600 million by being more predictive through the data that we had.”
Huskisson is candid about automation’s limits. A pilot of autonomous forklifts looked dazzling to visiting executives—“the sexy, glamorous thing,” he calls it—yet the ROI wasn’t there. Drones that map soil-pile inventory at Scotts’ outdoor facilities, meanwhile, paid off almost immediately. “Robotics is not one-size-fits-all. It depends on your product profile. Leaders have to be patient.”
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Rocked by tariffs, geopolitical rivalries, and more, industry leaders are learning to reckon with a volatile landscape. Here’s how some are absorbing the shocks.
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DHL Supply Chain’s Insight 2030 study, which surveyed 350 North American business leaders, captures the scope of their concern: 70% of executives expect cybersecurity threats to disrupt operations by 2030, while large majorities of others worry about labor costs (69%), labor shortages (66%), natural disasters (63%), and geopolitical tensions (62%). (To read more about DHL Supply Chain’s Insight 2030 findings, click here.)
None of these risks travels alone, which is why businesses are reshaping their networks around that principle. Speaking at the recent Manifest conference, DHL Supply Chain’s chief commercial officer, Will Heywood, put it this way: “Leaders anticipate bigger and more complex networks, more facilities, more capacity, while also contending with higher transportation costs, higher labor costs, and a risk environment that’s not easing up. That’s why nearshoring is on the rise.” Sixty-five percent of Insight 2030 respondents expect to expand nearshoring—outsourcing work to neighboring states—to manage trade uncertainty.
What worries leaders
FIGS, the medical-apparel brand known for its scrubs, is on a steeper curve. CEO John Tam has overseen the rollout of a fully automated warehouse and now views technology selection as a management problem as much as a capital one. “It comes down to confidence,” Tam remarked on the DHL Manifest panel. “There are so many options out there. You need to build that confidence to understand what’s the right solution for your business—not only as your business is today but how it’s going to grow.”
FIGS also relies on its logistics partners to spot patterns its own scale can’t yet reveal. Embroidered scrubs—customized with doctors’ names, titles, and institutions—once looked like an operational exception. Working with DHL, Tam learned that peer brands faced the same “exception,” and together they represented enough volume to standardize the process. That’s the quieter half of what a major logistics operator does over a five-year horizon: piloting AI and robotics, hardening cybersecurity, and pointing out redundancies workers can’t easily identify.
Neither executive pretends that technology alone is the answer. AI, Dabelko cautions, excels at recognizing patterns in stable environments—and today’s is not stable. “A lot of this analysis is predicated on the rational, predictable actor,” he says. “And that is going to prove challenging.” China can withhold critical minerals over an unrelated dispute, extreme weather is trending upward, and populist trade policies don’t optimize for efficiency. A pivot like re-onshoring rare-earth processing, he notes, is “a 10-, 25-year enterprise”—not a near-term fix.
The lesson for the next five years is straightforward. Efficiency buys you the everyday. Redundancy buys you a bad day. The supply chains that come out ahead will invest in both.
Predicting behavior in an unstable environment
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