One of the consistent findings in my research across Nigerian public institutions is that disaggregated data by gender is either not collected or not used. Service providers often do not know whether men and women are accessing their services at different rates, experiencing different outcomes, or facing different barriers. They are therefore unable to design responses to disparities that, from the aggregate data, are simply invisible.
This is not primarily a question of political will. Many of the institutions I have worked with genuinely want to serve women and men equitably. The problem is upstream: the data systems do not capture what is needed to understand inequality, and the people responsible for reporting have no mechanism or mandate to surface it.
Making inequality visible
Consider a public service that tracks the number of complaints received. If the complaint data is not disaggregated by gender, the institution cannot know whether women are underreporting, whether they face different types of problems, or whether they are being served less effectively. The aggregate number looks fine. The experience on the ground may be very different.
Part of what the 1864 Institute does in the gender area is work with institutions to build data collection practices that surface what was previously hidden. Not by adding complexity, but by asking, systematically, the questions that make inequality visible. Once you can see a problem in the data, responding to it becomes possible.