This document explores leveraging social assistance data and information systems for improved shock preparedness and response. It investigates the role of these systems in identifying beneficiaries and delivering aid effectively after a crisis. The document builds upon existing research and offers insights valuable for policymakers, program designers, and practitioners in humanitarian and social protection sectors. It is intended to help governments and organizations make informed decisions about whether and how to use existing data and systems to build more adaptive social protection systems.
Key Insights
Completeness of Coverage
Completeness refers to the level of data coverage and the number of records compared to what is perceived as a full set of records. Social assistance registries may be useful for emergency response if the data covers all those affected by the shock or a high enough proportion. Important distinctions need to be made between data on beneficiaries and registered non-beneficiaries.
Relevance of Data
Data is relevant if it contains the variables required for the intended purpose. Data collected for long-term social assistance may not always be relevant for shock response if it does not comprehensively identify households in affected areas, assess household needs, and enable an immediate response.
Currency of Data
Data currency is the degree to which data are current (up to date) and thus represent households’ real circumstances at the required point in time. Post-disaster revalidation is always required. The relevant factor is how up-to-date existing data are overall.
Accessibility of Data
Accessibility refers to the ease with which potential users (national or local government agencies and departments or their partners) can obtain the data. Accessibility can vary widely depending on who the users are, what processes and authorization levels are in place for data sharing, the underlying policy and legislation, etc.
Accuracy of Data
Data are considered to be accurate if they are free from errors and omission. Accuracy means that a high level of confidence can be placed in the data, affecting their wider credibility and ultimately their usability.
Data Protection
Data are secure when they are protected against unauthorized access, misuse, or corruption. Data privacy is guaranteed where data are utilized while protecting an individual’s privacy preferences and their personally identifiable information.
Key Statistics & Data
- In Ecuador, only 15% of households within the “Registro de Damnificados” (the registry of affected households collected in the aftermath of the 2016 earthquake) were recipients of the country’s flagship social assistance programme, the Bono de Desarrollo Humano (Beazley, 2017a).
- In Mozambique, government estimates of the median population affected by the 2016 droughts was 15% across the 71 affected districts. The median coverage of the country’s largest social assistance programme in these districts was only 9%, suggesting that even if the recipients of the PSSB were indeed the population most affected by the drought, there was still a large population in need of support (Kardan et al., 2017).
- A similar analysis in Lesotho at the time of the 2016 droughts showed that the proportion of people living in CGP households as a percentage of those estimated to be facing survival deficit using the Lesotho Vulnerability Assessment Committee (LVAC) data on food security was on average 28% across the affected districts, with high regional variations (Kardan et al., 2017).
Methodology
The research presented in the document draws on recent international experiences in using social assistance data systems for shock response. It builds on an earlier briefing note on the “Factors affecting the usefulness of existing social protection databases in disaster preparedness and response.” It involves literature review and case study analysis.
Implications and Conclusions
Depending on their set-up, existing social assistance data systems can offer a range of potential uses for shock response. The varied nature and quality of social assistance registries and broader information systems means that their role and use in emergencies can only be identified with reference to the particularities of the registries in the country and context under review. The core conclusion is that - before using existing data and information systems at any cost - it will be essential for every country to make a careful assessment of existing data and systems based on the criteria discussed in the document, the benefits, risks and trade-offs of using existing data versus starting from scratch.
Key Points
- Existing social assistance data systems can offer potential uses for shock response, such as providing household-level data and comprehensive socioeconomic information.
- The effectiveness of social assistance registries and broader information systems in emergencies depends on their particularities in each country and context.
- Six dimensions, including completeness, relevance, currency, accessibility, accuracy, and data protection, are used to assess the potential utility of social assistance registries in response to shocks.
- Social assistance data can inform decision-making before, during, and after a shock, as a complement to other data sources and data collection efforts.
- Vertical expansions and piggybacking on beneficiary data can enable timely responses but may have drawbacks in terms of the coverage of affected populations.
- Leveraging shared data can improve coordination amongst social protection, DRM, and humanitarian actors, leading to improved knowledge/learning and reduced duplication of efforts.
- The extent to which the benefits of building on existing data can be reaped depends on factors beyond data and information management, including lack of funding and swift decision-making.