Despite the proliferation of data, the volume and quality is unequally distributed. Data deserts exist in areas, both geographic and demographic, where data is not regularly collected. As a result, many communities in global majority contexts are unable to benefit from the increase in focus, policies, and investments that data informs.
While artificial intelligence can address some data gaps, it can also exacerbate data inequalities by flattening contexts and introducing bias. Furthermore, high quality qualitative insights that provide interpretive analysis of the drivers, influences, values, and beliefs behind observed phenomena is even more scarce.
In this session, we will share our experience implementing the Gender Equality Design Labs in Ethiopia, Nigeria, and Pakistan. The Labs are taking a design-centric approach, where our research is focused on developing insights around the most vulnerable women in these countries to inform the design of strategic investments and the next generation of women’s health innovations. By relying on Pathways vulnerability segmentation (https://www.projectpathways.org/home), we’ve assembled panels of women representing the most vulnerable households. We’re engaging these women long-term as a core part of our design team to continuously test and reframe investment hypotheses, and move from validated hypotheses to opportunity areas for product, service, and policy innovation. We’re capturing data, findings, and insights from these panels in a queryable database across segments, geographies, and markets to identify women’s most salient priorities. In addition to developing a rich dataset, we’re experimenting with how we share insights in formats, such as audio insights and podcasts, that are timely, digestible, and actionable.
During this session, we will reflect on lessons learned from implementing the Gender Equality Design Labs to-date, and offer recommendations on how different funders, implementers, and innovators can adapt this model in their own contexts.
