Nick Herbert serves as the Executive Director, Global Public Sector, at ServiceNow, enabling a trusted digital society.
The problem isn’t access to information—it’s identifying the handful of signals that truly matter.
In November 2024, I was two weeks into a new role focused on the public sector, working with governments. I was in Barcelona for the Smart City Expo World Congress. It brought together global government, policy and technology leaders to discuss everything from cleaner air and improved citizen services to safer urban environments. But the wider Spanish region was already facing its own safety crisis. Six days earlier, flash floods had devastated Valencia and the communities around it, and by the time I landed, at least 217 people were confirmed dead.
The day I arrived, Barcelona also flooded. November 4, 2024, the skies opened, and torrential rain hit the city. Catalan rail services were suspended (paywall), and at Barcelona-El Prat Airport, 18 flights were diverted, and 153 more were cancelled. The contrast stuck with me: Thousands of us had flown in to talk about making cities smarter and more resilient, while the country around us was under real pressure.
Crises—whether in the form of natural disasters, catastrophic errors or violence—present themselves as a flow of information that spans across public safety, foreign affairs, borders and transport systems. The more IOT sensors, social media platforms and CCTV streams that arise, the more we can tap into these to get a sense of what’s happening. So, an event rarely emerges as an emergency call feeding up through a chain of command. It’s more complex than that.
Incidents Aren’t Reported In Order
Historically, governments built systems and processes around trusted information moving through defined channels. This was for good reason—decisions made by police, border agencies, foreign ministers and emergency services carry real consequences. However, the world doesn’t organize itself around a predefined process—it operates organically with individuals making decisions based on the information and signals that they have access to. A single event can now generate information almost simultaneously across official reporting, local media, sensors and people simply describing what they’re seeing.
So, the problem isn’t access to information—it’s identifying the handful of signals that truly matter. It’s working out which signals are related to the same event and knitting together a picture of what’s happened, what’s happening and what’s likely to happen and staying current as the situation unfolds.
Faster Isn’t Always Better
Los Angeles saw a different version of the same problem during the January 2025 wildfires. An after-action review commissioned by Los Angeles County found outdated policies and communication gaps across the systems used to alert and evacuate residents. During one of the fires that month, a warning meant for a single area was sent, by mistake, to nearly 10 million people across Los Angeles County. The problem wasn’t a lack of speed. If anything, the information moved too fast.
This matters in our design and consideration of these systems, especially as agencies are moving into AI-assisted operations. Used well, AI can help people act swiftly with access to more information than ever before, improving accuracy and productivity and ultimately saving more lives and property. But speed without accuracy undermines public trust in the information being given and can jeopardize more lives. We need to be sure of what’s happening, corroborate it, understand what’s changed and identify who needs to know.
Cross-Border Challenges
The same pattern exists outside of emergency management. In March 2026, the fast-moving crisis in the Middle East left thousands of Australians trying to get home across borders and through airspace that could close without warning. By month’s end, more than 10,000 had made it back on direct commercial flights, with thousands more out through other routes.
A foreign ministry responsible for coordinating a response has to bring together information and data from multiple sources, such as other governments, transportation agencies, social media and direct reporting. The challenge comes from finding what matters and turning scattered information into something a decision maker can use.
What We Should Be Designing For
Design for continuous discovery, not just collection. Government agencies have access to huge amounts of data. The critical edge comes from recognizing an event early, when it’s first signals appear—even if they come from outside of an official government system altogether.
Design for explainability. The earliest report is often wrong, misleading or missing information. Two accounts may trace back to the same source, so decision makers need to see not just what the system believes is happening, but why.
Design the decision path alongside the systems that sense an event, and enforce it. The flooding in Spain highlights this point. The weather agency issued warnings, the river basin authority had the sensor data, but the regional government was the one with authority to issue population-wide alerts. Thresholds and escalation paths need to be set before an event, not invented during one. Japan does this well: They can detect P-waves threatening an earthquake or tsunami and seconds later, trains are automatically slowing, lifts are stopping and factory equipment is shutting down before the stronger shaking arrives.
Conclusion
The next crisis might first show up as a sensor reading, a camera image, an airport closure, a local report or a video from someone already there. Governments can’t control where that signal appears, but they can control how fast it’s found, how carefully it’s checked into and whether someone already has the authority to act on it.
The gap isn’t in whether the information exists but whether anyone can turn it into a decision before the moment that mattered has passed.
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