The supply chain world is waking up to the fact that operational resilience depends not only on physical buffers and logistics flexibility, but on data and predictive analysis.
The reason? Operations are becoming more volatile. Geopolitics and shifts in demand are contributing to a landscape that’s becoming more dangerous for finance and procurement teams.
That puts a premium on modeling and continually refreshed data. From port traffic and factory output to container tracking and weather forecasts, the real battleground in supply chain resilience lies in the quality, continuity and granularity of its data.
Those underlying data flows, at least around weather-related supply chain disruptions, got a shot in the arm Monday (Nov. 17) with the introduction of Google DeepMind’s WeatherNext 2 AI model. The meteorology system can predict hundreds of possible weather outcomes from a single starting point, generating forecasts 8x faster and with resolution up to 1-hour. Each prediction takes less than a minute on a single Tensor Processing Unit (TPU).
This step-change advance in forecasting ability points to a much broader shift: high-fidelity data feeds once reserved for scientific or energy markets are now becoming accessible, and even foundational, to supply-chain resilience in a turbulent economy.
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Real-Time Data and Supply Chain Resilience
In supply chain operations, the weather does not just matter for deliveries. It matters for every segment: port operations, ocean-route visibility and wave conditions, inland transit, manufacturing disruptions and even risk profile for insurance and finance.
Hourly forecasts, greater detail and scenario generation mean that weather ceases to be a “nice to know” factor and becomes a data feed with near real-time decision relevance for supply chains.
Because global networks are more tightly coupled than ever. Just-in-time inventory, lean supply chains, and multiple outsourced tiers leave little room for error. A weather-induced port closure or inland-freight disruption can cascade quickly.
In the past weather-related supply chain delays were costly but somewhat containable. In 2025’s digital, just-in-time, cash-optimized, omni-node world, the calculus is changing.
“The current trade landscape that we see today is marked by widespread volatility, complete unpredictability,” Dean Bain, SVP supply chain at Coupa, told PYMNTS in an earlier interview. “We’re seeing businesses grappling with rising costs, with margin erosion, with trying to figure out how they deal with this uncertainty and provide greater agility to their business.
“[What is crucial is the] ability for them to identify what alternate sourcing options there are and to use data to make data-driven decisions that ultimately protect the profitability and the market position of that company,” Bain said.
Read also: 5 Ways CFOs Are Shaking Off the Finance Function’s ‘Department of No’ Label
Data Inflection Point
While supply chain resilience has become a function of better data, the underlying challenge is not just having the data but having the analytics and governance to turn those feeds into timely decisions.
The latest findings in the October 2025 edition of the PYMNTS Intelligence 2025 Certainty Project, done in collaboration with HSBC, lay bare a widening resilience gap across the U.S. middle-market, where many businesses find themselves exposed to fragile supply chains.
Companies that lack the analytics, shared data, or decision protocols can struggle to convert predictive information into action. As a result, decision-making may remain slow, fragmented or escalated through cumbersome management, undermining the resilience designed to reduce exposure.
This dynamic illustrates a paradox that has become visible across industries: Companies have evolved technologically faster than they have evolved organizationally. But that’s beginning to shift, with resilience moving away from being a purely logistical challenge and emerging as a test of discipline and readiness.
