Fionna Smyth, DI’s Director of Growth and External Relations, shares her experiences of how data-driven solutions can support progress towards gender equality.
I have spent the last twenty years working on women's rights, mostly in places where they have few. Despite this lack of gender equality, incredible and dynamic women’s rights organisations operate everywhere that I have worked – even in the most challenging contexts – delivering vital services and influencing decision-makers. For these organisations to achieve the greatest impact with their (often) shoestring budgets, high-quality, disaggregated data is essential.
In the summer of 2019, I visited a camp for internally displaced people in Bria in the northeast of the Central African Republic (CAR). In CAR, gender inequality ranks second highest in the UNDP Gender Inequality Index and it also has one of the lowest levels of human development in the world. Women and girls are disproportionately affected during crises. At the time of my visit, local communities had created women’s protection committees to monitor human rights abuses and sexual and gender-based violence (SGBV). They collected data on SGBV within the camp so that they could identify trends and produce evidence to influence the camp’s management to deliver solutions to keep women safer, such as better lighting in the latrines and designating certain times of day when only women could have access to the water pumps. Development Initiatives (DI) supports these kinds of data-driven solutions at the community level and recently highlighted four key areas for improvement in the prevention, mitigation and response to gender-based violence (GBV) in crisis settings. These include better reporting of where funding is going and whether it meets GBV prevention needs across sector-specific activities.
Progress depends on data: an example from the humanitarian sector
We know that better-funded women’s organisations[1] can deliver more targeted and effective services, but limited access to funding is creating further barriers to women’s organisations’ meaningful participation and decision-making. Clear data, which demonstrates the paucity of funding to women’s organisations and the impact these organisations are uniquely able to deliver, is critical to rectifying this.
DI’s 2022 GHA Report shows that only 1.2% of humanitarian funding goes to local and national actors directly, despite the Grand Bargain Commitment to provide 25%. However, large data gaps, as well as issues with definitions and tracking, make it difficult to get an accurate picture of funding to women’s organisations and, therefore, the extent of the problem that needs addressing. In a more specific country context, DI’s research has shown that less than 0.2% of funding reached women’s organisations in Türkiye.
Lack of support to women’s organisations is also at the heart of a new International Rescue Committee (IRC) report, which includes quantitative analysis from DI: ‘Why Wait? How the Humanitarian System Can Better Fund Women-Led and Women’s Rights Organisations’. It argues that pooled funds are an important instrument in channeling more direct funding to women-led and women’s rights organisations. The report offers concrete recommendations on how to unlock chronic underfunding and meaningfully shift power and decision-making to women’s organisations.
Gender data gaps are limiting progress on gender equality
Progress on gender equality is a mixed picture, and very context-specific. However, it’s difficult to measure progress without improving the production, availability and accessibility of quality gender data. This is indispensable for monitoring and building information systems that can inform policy actions and investments. It's also critical that we understand how people experience discrimination. If we don’t track intersecting vulnerabilities – for example, age, disability and race, as well as gender – the most marginalised in our communities will be left behind.
Community-driven data is an approach to data collection that not only informs decision-making about interventions for women and girls, but can also increase communities’ agency. Without data that represents women’s experiences, policies cannot meet their needs. For example, during the Covid-19 pandemic, women and girls within local communities made a significant contribution to the Covid response, delivering food and finding alternative sources of income, but significant data gaps rendered them 'invisible' and excluded them from humanitarian response plans.
A lack of gender data has real-life consequences for women, girls and non-binary people. It means that:
- Resources will not be allocated to appropriate services;
- The safety of women, girls and LGBTQ persons is at risk;
- WROs can’t access the funds that they desperately need;
- Donors can’t hold themselves to account for their funding choices.
Counting on a better future
In our upcoming Gender Inequality briefing, we outline viable solutions and the best practice for providing flourishing national data ecosystems that see people’s differentiated needs measured and accounted for. We aim to provide technical solutions to effectively fill gender data gaps, which can support the use of more and better-quality data to inform policy and programming and, in turn, target the needs and interests of the people furthest behind.
Good data is a means to attain visibility for gender inequalities. The next stage is using this data to make funding and policy decisions, specifically to tackle barriers to inclusion and to challenge social norms that have different effects based on gender. A lack of data and evidence cannot and should not be used as an excuse by policymakers: the tools and ways to count people do exist for better gender data. They need to be applied consistently and used as evidence so that the findings of that data can start to shift progress on gender equality.
DI’s work in this area is one of the many reasons I am proud to have joined the organisation. I look forward to helping them empower women who fight on the frontline of gender equality. Making progress on reducing gender inequality depends on access to information and DI is doing vital work to get high-quality data to the people who need it most. This data is just one piece of a larger puzzle, but it can contribute to creating a more equal world that's free from discrimination.
NOTES
1The term ‘women's organisations’ used here refers to and includes a diverse group of organisations and movements, from women's rights organisations (WROs) and women-led organisations (WLOs) to feminist groups, among others.