When disaster strikes, the instinct is to respond. Emergency services are mobilised, communities are evacuated, damaged infrastructure is assessed and relief efforts begin. These actions are essential, but they happen after risk has already materialised.
For cities and organisations facing increasing exposure to flooding, extreme heat, drought and other hazards, resilience requires a different question: what can we understand and act on before a disaster happens?
This is where risk intelligence becomes important. Instead of relying primarily on what has happened in the past, risk intelligence combines data, analysis and forward-looking information to help decision-makers understand where risk exists, who or what is exposed, how vulnerability is changing and where action could reduce future losses. UNDRR increasingly emphasises this shift from hindsight to foresight, noting that forward-looking risk analytics can help cities identify future hotspots and target resilience investments before losses occur.
Response is necessary, but it cannot be the whole strategy
Disaster response will always matter. When a flood displaces communities or extreme weather disrupts essential services, people need immediate assistance. But repeatedly responding to the same impacts without understanding why those impacts keep occurring can leave communities caught in a cycle of damage and recovery.
Consider flooding in a rapidly growing city. Heavy rainfall may be the immediate hazard, but the scale of the resulting disaster can depend on much more: where people have settled, how land use has changed, the capacity and condition of drainage systems, the location of critical infrastructure and the number of people and businesses exposed.
These conditions do not appear overnight. They develop over time, and many can be observed through data.
This creates an opportunity to move beyond asking, “What happened during the last flood?” and begin asking, “Where is flood risk increasing, what is driving it, and what can be done before the next event?”
Risk intelligence connects the pieces
Understanding disaster risk requires more than a record of past events. It requires different types of information to be brought together.
Geospatial and satellite data can show how cities are expanding and how land cover is changing. Environmental and climate data can help identify changing hazard conditions. Population and demographic information can indicate where more people may be exposed. Infrastructure data can reveal critical assets and potential points of vulnerability, while historical disaster and loss data can show where previous events have caused damage.
Individually, these datasets tell us something. Together, they can reveal relationships that are much harder to see otherwise.
A flood-risk map, for example, becomes more useful when it can also show the communities, roads, hospitals, businesses and other critical assets located within exposed areas. That information can help decision-makers determine where drainage improvements, land-use controls, early-warning systems or other interventions may have the greatest value.
This is the difference between simply having data and being able to use data as intelligence.
From hindsight to foresight
Traditional disaster planning often looks backwards. Historical events are analysed to understand what happened and where losses occurred. That information remains important, but it is not enough on its own.
Cities are changing. Populations are moving. Infrastructure is expanding. Land use is changing, and climate conditions are evolving. A location that was relatively low-risk in the past may not have the same risk profile in the future.
Newer approaches to risk analytics therefore combine historical information with projections, hazard modelling, exposure data and vulnerability analysis to identify where risk could grow. UNDRR describes this as a shift from hindsight to foresight: using data and modelling to identify potential future hotspots even where severe losses have not yet occurred.
For African cities, this shift is particularly important. Rapid urban growth means that decisions being made today about land, infrastructure and services can shape tomorrow’s exposure to risk. Identifying emerging vulnerabilities early gives governments and organisations more options than waiting until those vulnerabilities become disasters.
Better risk intelligence leads to better decisions
Risk intelligence is not about predicting every disaster with certainty. It is about improving the quality of decisions made under uncertainty.
Where should new infrastructure be located? Which existing assets require additional protection? Which communities need stronger early-warning systems? Where is development increasing exposure? Which areas should be prioritised for resilience investment? These are practical decisions, and they require practical information.
UNDRR’s current work on risk and resilience analytics reflects this approach: risk information is intended to help decision-makers understand current and future exposure, assess potential impacts and identify investments that can reduce future losses.
The same principle applies beyond government. Businesses depend on roads, electricity, water, telecommunications, supply chains and physical facilities that can all be disrupted by hazards. Understanding where those dependencies intersect with environmental and disaster risks can help organisations plan for continuity rather than simply react to disruption.
The goal is not to eliminate risk. It is to see it earlier.
Disasters cannot always be prevented. But the consequences of hazards are not entirely predetermined.
Better data can help reveal where risk is concentrated, how it is changing and which factors are making communities, infrastructure and economies more vulnerable. Better analysis can turn that information into insights. And better insights can give decision-makers a stronger basis for prevention, preparedness and investment.
That is the shift from disaster response to risk intelligence: moving from asking what we will do when something happens to understanding what we can do before it does.
For African cities and organisations facing increasingly complex environmental risks, that shift is no longer simply about having more data. It is about making data usable; turning information about hazards, exposure and vulnerability into decisions that can reduce risk and build resilience.
