Harnessing the power of data so no child is left behind

First published on World Bank blogs

Data plays a crucial role in the 2030 agenda set out by the Sustainable Development Goals (SDGs). It helps us to focus policies and make better decisions. It is needed to set targets, measure progress towards those targets and to hold governments accountable to their commitments under the SDGs.

Data is also essential for governments to fulfill their pledge to leave no one behind in the SDGs; that the goals should be met for all segments of society and that those furthest behind should be reached first. Despite significant progress over the last few years, we are still far away from being able to systematically identify those at risk of being left behind or to monitor their progress towards the 2030 commitments.

Check out Save the Children's GRID, our Child Inequality Tracker, to identify and track inequalities for child-focused SDG indicators across health, nutrition, education and child protection. It compares group-based inequalities across income, gender, and location. The database brings together more than 400 publicly available household surveys for more than 100 low- and middle-income countries.

The main data sources for GRID are Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), providing population-based data for most low- and middle-income countries. The education data comes from the World Inequality Database on Education (WIDE) by UNESCO and data for malnutrition from the WHO/UNICEF/World Bank Joint Malnutrition Estimates. Using publicly available household surveys as a basis for our GRID dataset provides multiple advantages: the data is nationally representative, widely know and of high standard, and—most importantly for the purpose of our Child Inequality Tracker—it can be disaggregated by household wealth, gender, location, ethnicity and subnational regions. Although these are valuable data sources which can be used to understand inequalities in children’s lives in many countries Save the Children works, there are three challenges that these data sources pose:

• While the various dimensions of disaggregation are important and helpful, they show only part of the picture. DHS and MICS surveys currently lack disaggregation by key dimensions of inequality and marginalization, such as disability, migration status, and for many countries ethnicity. Very little data is disaggregated by age, and surveys rarely capture the challenges faced by different age groups, with 10–14-year-olds often invisible. In this context it is great to see UNICEF and partners including a child functioning module in the latest round of MICS.
• While DHS and MICS are widely available in most low- and middle-income countries in the World, they are absent or out of date in many fragile and conflict affected countries, where Save the Children is working and where child rights are particularly under threat, such as South Sudan, Somalia, Yemen, Syria.
• As useful population-based household surveys are—particularly in providing disaggregated data—they are complex and expansive. Both the gaps between various surveys as well as the time needed for data analysis and publication means that three or four-year-old surveys are still new sources of evidence. This highlights the need for real-time, continuously collected and comparable data.

Among the valuable insights we have gained over recent years since we developed GRID, three stand out:

1. Lottery of Birth: Children face greater risks of mortality, hunger, and diminished opportunities for education because of the wealth of their parents, their gender, or the area they live in. This is goes against the basic precepts of morality, fairness and human rights. The GRID tool highlights examples of these inequalities: children from the poorest households in Nigeria, Angola and Mali are almost three times as likely to die before their fifth birthday than those born into the richest households. Children in rural areas of Burundi are twice as likely to be stunted as those in urban areas. Three out of four girls living in the poorest households are married before their 18th birthday compared to 14% of those from the richest households.
    
   
    
2. Still Left Behind: Those furthest behind must move fastest towards the 2030 goals if the SDGs targets are to be achieved for all segments of society. In other words, countries must achieve convergence between marginalized groups and the rest of the population within countries. The case of under-five mortality in India illustrates this challenge: while the wealthiest 20 per cent have already crossed the SDG target threshold of 25 per 1000 live births and the country is on track to achieve the target ‘on average’, the poorest 20 per cent is well off-track to meet the target by 2030.
    
   
    
3. Every Last Child: Many of the children most at risk of being left behind by progress in health, education or protection are not represented in household surveys despite recent efforts to improve survey sampling and to include more population groups in surveys. Qualitative data collected through dedicated research projects, advocacy work or programmes can offer valuable insights into those groups excluded from household survey data and increase understanding of the barriers they face in accessing programmes and services. Our ‘Mapping Exclusion’ tool brings qualitative and quantitative data together to deepen our understanding of these groups’ experiences. Currently available for Tanzania, the data reveals groups of children (children in poverty, children with disabilities, those from pastoralist communities, orphans) who are excluded from education and highlights the lack of data for many of those groups.
    
   
    

GRID offers valuable insights into which children are at risk of being left behind and is a resource that can be used to monitor their progress towards the SDGs. It also highlights how important it is to track not just national and global averages when looking at progress towards the 2030 goals, but also the pace at which disparities between socioeconomic groups are narrowing. These insights tell us that unequal outcomes and the lack of sufficient progress for the most marginalized and deprived children calls for a much greater alignment of public policy and budget decisions with needs within countries.