The value of loss and damage data, from early warning to recovery
Disaster loss and damage data is often associated with post-disaster assessments and reporting. When systematically collected and analysed, loss and damage information can serve a broader purpose, supporting anticipatory action, and informing recovery planning.
These four case studies illustrate how disaster impact data is being used across different contexts and stages of the disaster management cycle. From drought preparedness in Madagascar and Southern Africa to institutional strengthening in Kyrgyzstan and post-conflict recovery planning in the agricultural sector in Lebanon, these examples show that loss and damage data is being used as a resource for decision-making.
Madagascar: Using historical impacts to anticipate future crises
A promising application of loss and damage data is in anticipatory action. Rather than waiting for disasters to unfold, governments and organisations are increasingly using historical data to identify when early action should be triggered, to reduce humanitarian impacts.
In southern Madagascar, the Food and Agriculture Organization (FAO) joined forces with government and humanitarian partners to calibrate drought trigger systems by linking meteorological indicators with observed impacts on agriculture, food security and livelihoods. Traditional early warning systems often rely on climate indicators alone, which may not fully capture the consequences of a drought on vulnerable communities.
By incorporating historical loss and damage data, decision-makers were able to identify thresholds that correspond more closely to real-world impacts, so that anticipatory actions can be activated before conditions deteriorate into a humanitarian crisis. The experience shows the value of grounding early warning systems in evidence of past losses and impacts, rather than relying only on hazard forecasts.
Southern Africa: Learning from past El Niño events
Similar lessons resulted from FAO-led efforts to analyse the potential impacts of El Niño across Southern Africa. The region is prone to droughts associated with El Niño events, affecting agricultural production, water availability and food security. Anticipating these impacts requires an understanding of how previous events translated into losses and damages for communities and economic sectors.
Working with national governments and regional partners, FAO combined climate information with historical impact data, to better understand potential risks to agriculture and food security. The analysis informed policy discussions, preparedness planning and anticipatory action efforts, helping decision-makers allocate resources and prioritise interventions before the worst impacts materialised.
Kyrgyzstan: Building the systems that make data usable
The benefits of loss and damage data depend on the existence of reliable systems for collecting, managing and analysing information. Without standardised methodologies and institutional arrangements, data can remain fragmented, inconsistent or inaccessible.
Kyrgyzstan's experience illustrates the importance of investing in national disaster damage and loss assessment systems. Recognising the need for more consistent information on disaster impacts, the country undertook efforts to establish methodologies, institutional processes and digital tools for collecting and managing damage and loss data.
By developing a standardized assessment system, Kyrgyzstan strengthened its ability to document disaster impacts in a systematic manner. The process brought together government institutions responsible for disaster risk management, agriculture, and statistics, helping clarify institutional responsibilities and improve coordination among stakeholders involved in data collection and reporting.
The case demonstrates that effective use of loss and damage data depends on governance arrangements, institutional ownership and clear procedures that ensure data is collected consistently and used effectively. Reliable information systems form the foundation upon which risk analysis, planning and decision-making can be built.
As countries seek to strengthen disaster risk governance, investments in data systems are becoming increasingly important. Accurate and accessible information not only supports reporting needs but also enables evidence-based policymaking and resource allocation.
Lebanon: Informing recovery and reconstruction
Loss and damage data also plays a crucial role in the aftermath of disasters. Impact assessments provide the evidence needed to identify recovery priorities, estimate needs and guide investments.
This is particularly important in contexts where multiple shocks interact, such as in conflict-affected regions, to restore livelihoods and support long-term recovery.
In Lebanon, FAO's work on agricultural loss and damage assessments demonstrates how impact data can inform post-conflict recovery planning. By documenting losses across agricultural sectors, assessments provide a clear understanding of how crises affect production systems, rural livelihoods and food security.
Such information helps governments and development partners identify priority interventions and target resources more effectively. It can inform decisions on rehabilitation of infrastructure, restoration of productive assets and support to affected communities. In doing so, loss and damage data becomes an important bridge between assessment and action.
The Lebanon case also highlights the broader value of sector-specific data. While national-level estimates provide an overview of impacts, detailed information at the sectoral level enables more targeted and effective recovery measures. Understanding where losses occurred, who was affected and what resources are needed can help ensure that recovery efforts address the most pressing needs.
From data collection to decision-making
Taken together, these case studies demonstrate that the value of loss and damage data extends beyond documenting the impacts of disasters.
In Madagascar and Southern Africa, historical impact information helped strengthen anticipatory action and preparedness by connecting forecasts with likely consequences. In Kyrgyzstan, investments in assessment systems improved the quality and accessibility of disaster impact data. In Lebanon and post-conflict recovery contexts, agricultural loss and damage assessments provided evidence for recovery planning and resource allocation. Although the contexts differ, the four case studies demonstrate that loss and damage data is most effective when it is integrated into decision-making processes.
As climate change intensifies disaster risks and places growing pressure on communities and institutions, the demand for timely and reliable impact information will continue to increase.
Strengthening national capacities to collect, manage and use loss and damage data can help countries move from reactive responses toward more proactive and risk-informed approaches.