Save the Children Tanzania use of data to push for an end to child exclusion
Save the Children (SC) is the world’s leading independent organization for child advocacy. They work in more than 120 countries, saving children’s lives, fighting for their rights, and helping them live their potential. SC works to inspire breakthroughs in the way the world treats children and to achieve immediate and lasting change in their lives. In their current global campaign, “Every Last Child,” SC is combatting child exclusion, the social, economic, cultural, and environmental factors that result in some children being left behind while others around them thrive.
To support the global campaign and as part of the Data Revolution more broadly, SC Tanzania is undertaking a children’s exclusion mapping project to demonstrate how existing data can be used to visualize child exclusion in a country. The project aims to use existing national data to develop a diagnostic toolkit to identify children who are excluded and the key drivers behind their exclusion.
Actors across the development sector have become aware that despite the impressive progress achieved by the Millennium Development Goals, there are certain groups of children who have been left behind. Without addressing the systemic barriers that have kept them from benefiting from rising tides around them, these children risk being forgotten again in the implementation of the SDG’s. Using clear, data-derived evidence of the drivers of child exclusion, SC Tanzania hopes to inform decision-makers in the public and private sectors as to how their actions can help bring about an end to child exclusion.
The first critical step in combatting child exclusion is the identification of those who are at highest risk. In Tanzania, gender-based discrimination is the most common form of child exclusion. For example, it has been found that Tanzania has one of the highest child marriage rates in the world, and although these rates have been dropping in recent years, the prevalence of teenage pregnancies remains alarmingly high. A number of organizations have undertaken efforts to map child exclusion and identify the most at-risk populations, including girls who are married or pregnant below the age of 18. Typically organizations use a single indicator, a simplistic approach that fails to take into account the synergistic effects of variables contributing to child exclusion, including economic, education, and health factors. Merging multiple indicators, however, can lead to a more nuanced and realistic picture of where excluded children are located and who they are, but no multi-indicator platform currently exists.
SC Tanzania identified the need for a platform to merge multiple indicators related to child exclusion, and finding that no such platform existed, they set out to create their own. Starting at a local level, SC Tanzania created a diagnostic toolkit that merged few multiple indicators to create regional performance index. Now that the project had been successfully implemented on a pilot scale, SC tanzania is endeavoring to expand their tool by merging all appropriate indicators with national coverage in Tanzania.
Developing a multi-indicator toolkit for child exclusion required first identifying relevant indicators and compiling related data from a variety of sources, including the Tanzanian National Survey, the Health Management Information System (HMIS), the national budget, and others. Critically, SC sought out geographically disaggregated data in order to pin-point areas most in need of intervention. Indicators of child exclusion were identified from a Child Indicators Database and included the prevalence of child marriages, the adolescent child-bearing rate, and school dropout rates.
Upon merging multiple indicators, Shinyanga stood out as a region with an especially large number of factors that are known to contribute to child exclusion.
Figure caption: Data visualization is accessible through the URL ( https://public.tableau.com/profile/data.science2372#!/)
While the toolkit already draws on multiple data sources, the scoring system will only improve as data become more available. SC’s current model can be improved upon with access to more up-to-date data as well as data disaggregated to the district or village level. In spite of current limitations in data availability, however, SC is pushing forward with a plan to expand the project from the pilot level to a comprehensive, national-level map of child exclusion indicators.
Beyond simply creating a tool to help focus internal priorities, SC wanted to use their new multi-indicator toolkit as a resource in advocacy. As such, they have developed a dashboard to monitor changes in child exclusion indicators and have conducted workshops and trainings to demonstrate how they have used data to map child exclusion.
OUTCOMES & IMPACTS
SC’s multi-indicator child exclusion toolkit will become a critical component in their design of advocacy campaign messages to address the issue of child exclusion. Using a solid foundation of data-derived evidence, SC can increase awareness and understanding of the factors contributing to child exclusion and push for policy changes that will reduce child exclusion, early marriage, and teenage pregnancy. This evidence-based approach will combat the resource misallocation and improper interventions that can result from relying on a single variable to make policy decisions. Instead, the toolkit will guide policy-makers on a national level to the contributing factors and geographic areas most in need of attention, while at a regional level, administrators will be able to ascertain which indicators factor most heavily in child exclusion in their own locality.
Save the Children (SC) is the world’s leading independent organization for children. They work in more than 120 countries, saving children’s lives, fighting for their rights, and helping them fulfill their potential. They are both the project’s main implementor and the originator of the successful pilot project. Save the Children can be reached at Tanzania.email@example.com.
The Tanzania Data Lab (dLab) is a national data hub to promote data innovations, literacy, data use and multi-stakeholder data collaborations. They strive to build capacity in data analysis and visualization and offered their expertise to this project.
The National Bureau of Statistics (NBS) is an autonomous public office with a mandate to provide official statistics to the government, business community, and the public at large. The Statistics Act of 2015 assigns NBS as a co-coordinating agency within the National Statistical System (NSS) to ensure the quality of official statistics. NBS provided data and approved the methodology employed in this project.