How a Major US Retailer Built Weather Intelligence into Operations

If you live in the United States, there is one big-box retailer that has a store within 10 miles of your home. There’s only a 10 percent chance that isn’t true.

The company operates a mighty supply chain, with more than 100 billion items moving through it each year. Its footprint spans 22 countries and includes grocery distribution centers, e-commerce fulfillment hubs, private fleets, suppliers, and hundreds of thousands of employees.

Their resilience strategy carries double the stakes. The hyperlocal store network, carrying everything from groceries to home goods, functions as a de facto relief organization. The retailer has built a distributed network of partnerships with local chapters of the American Red Cross, the Salvation Army, food banks, and other service nonprofits. Together, they turn parking lots into field sites, using precise maps to position supply depots, service tents, latrines, ingress routes, and egress routes.

During Hurricane Katrina, their truck convoys reaching New Orleans ahead of federal aid defined the moment. Senior leadership leaned into disaster relief and built in-house meteorology to support the capability. The storm validated the distributed logistics approach the company had spent years perfecting. Further refinement became part of the resilience strategy.

Severe weather caused $115 billion in damage in 2025, the third-highest year on record for billion-dollar weather and climate disasters. The economic impacts snowball: When roads and seaways close, materials don’t ship. Work stops.

Places once known for temperate weather are growing more extreme. Trucks travel roadways built 75 to 100 years ago, in many cases along infrastructure designed for a different climate. For the nation’s largest retailer, weather had become a supply chain problem.

When executives approved funding for a new global security operations center, the C-suite set a clear expectation for security operations leaders:

No weather surprises.

At the heart of the investment was a digital twin built with geographic information system (GIS) technology: a living model of the supply chain built for situational awareness, threat monitoring, and incident response. Weather would become part of that picture.

Leadership believed precision forecasting offered the best chance at flawless execution. Advances in meteorology had produced faster data streams and highly localized forecasts capable of tracking storms with block-level precision.

The retailer’s legacy approach to weather monitoring was de rigueur in GIS work: a patchwork of credible open data feeds layered onto a geographic framework showing stores, distribution centers, supplier locations, transportation corridors, and hazards. Analysts could click into sales data and inventory levels. Different teams performed location analysis tailored to their decisions while working from the same operational picture.

After 22 years of refinement, meteorologists and analysts knew where the gaps lived. Blind spots were low-resolution warnings that signaled emergencies where none existed.

Figuratively, if you could sort by weather blind spots, you might call up a folder of inventory orders that missed the conditions entirely. Flood protection staged for a storm that barely arrived. A voicemail from a store manager who started placing sandbags too late, calling to ask where to begin.

Facing an abundant selection of premium weather feeds, security operations leaders could rule out stand-alone solutions. The weather stream needed to fit the workflows their existing systems already served.

That compatibility requirement led them to Esri partner Baron Weather and its ArcGIS Weather Layers.

Baron’s ArcGIS Weather Layers feed into ArcGIS Velocity, a real-time data processing capability that integrates with ArcGIS Enterprise. Meteorologist Dan Gallagher, a GIS solution engineer at Baron Weather, dialed in the layers working with the retailer’s team.

The retailer’s security command center operates under mission-critical requirements. Baron offers 24/7/365 support and a 99.5 percent uptime commitment for GIS weather data.

The larger goal was to bring weather into the same system that already tracked the movement of products.

Through ArcGIS Velocity, real-time weather intelligence joined the stores, distribution centers, transportation corridors, supplier locations, inventory, and other operational data inside ArcGIS Enterprise. Forecasts, observations, radar, storm tracks, and warnings appeared in the same geographic context executives already used to manage the business.

Security operations teams also used ArcGIS Velocity to automate response workflows. As forecast conditions crossed predetermined thresholds, the system generated alerts for the people responsible for acting.

Transportation teams received notice when routes were at risk. Store managers received lightning alerts that halted any work outdoors. Supply chain teams were alerted when conditions called for staging inventory, repositioning resources, or moving goods ahead of the storm.

The messages were not weather reports. They were lists of assets in harm’s way and the actions required before the weather arrived.

The result was a living digital twin of the operation that could forecast weather conditions.

Across a map stretching thousands of miles, weather moved through the same network that moved products. Storm cells approached stores. Ice threatened ferry routes. Flood warnings crept toward distribution centers.

Every forecast arrived with context.

For years, the question had been straightforward: Where is the storm?

Now teams ask: What happens when it gets here?

A hurricane forms in the Gulf. Which stores sit inside the projected path? Which inventories need to move first? Which transportation corridors become vulnerable if the forecast shifts east?

A sudden derecho collapses the roof of a distribution center. What is the least disruptive way to work around the loss? Which trucks do we need to reroute? Which system adjustments do we need to make until it is back online?  

Those questions—and response scenarios—are played out inside the system before conditions deteriorate on the ground. Potentially months ahead of the incident when incorporated into security operations’ incident response planning. 

Now, forecasts, inventories, transportation routes, facilities, suppliers, and demand signals occupy the same geographic space. Security operations teams, planners, and logistics managers can explore possible futures while there is still time to change them.

A weather warning no longer arrives as a stand-alone event. It’s understood within a model of the supply chain.

Every forecast refreshes the picture. Risks emerge sooner. Options stay available longer. Teams gain time to move inventory, adjust transportation plans, and prepare stores before conditions change on the ground.

During a March ice storm, a transportation director in Canada faced a familiar problem: deteriorating conditions for trucks and ferries with little room for error. He needed more lead time.

Using AI-assisted development tools and ArcGIS, he built a routing agent that looked further ahead, evaluating 10-day forecasts alongside highway conditions, ferry schedules, and carrier availability.

That lead time matters in places like Newfoundland, where ferry service is one of only a few transportation links. When sailings are canceled, disruptions ripple through the supply chain and into the communities that depend on it.

Resilience is nonnegotiable in modern supply chains. As weather grows more volatile, the margin for error shrinks. Organizations invest in weather intelligence and location technology because the return is measurable.

Stores stay open. Shipments arrive when expected. Resources are deployed where they matter and nowhere else.

Credit belongs to the supply chain executives, meteorologists, and security operations leaders who reduce uncertainty one decision at a time.