People aren’t just data.  But if people aren’t in the data, too often they escape the notice of those who make decisions that affect their lives.

I’m thinking, for example, about a woman I met last year on a visit to Korogocho, one of Nairobi’s sprawling slums.  More than any earlier experience, my conversation with her, in the 8-by-10 corrugated shelter she shares with seven children and a sometime husband, helped me understand the relationship between being counted and being seen.

In an isolated and poor community, virtually unserved by any level of government and sustained by catch-as-catch-can jobs, this woman would be all but invisible to many who make decisions that affect her life. She would be unseen when far off government planners and international donors figure out where to locate health services and schools.  She would be unrecognized as a citizen who needs protection from violence and human rights abuses.  And she would be unknown as a contributor to the Kenyan economy.

She would be, that is, if not for the fact that the African Population and Health Research Center operates a demographic surveillance site in Korogocho.  The site is one of several large communities where data collectors periodically visit selected households – by chance, including hers – and researchers use the information they collect to make visible the basic facts and experiences of people living in Nairobi’s urban slums. Information about this woman, aggregated and analyzed with information about many others, has helped make the policy community understand the needs of the urban poor, and has helped to track progress (or lack of it) over more than a decade.

It’s this connection between being counted and being visible that motivates our work with the United Nations Foundation, the US Department of State and many leading experts in a project called Data 2X. Data 2X, launched by Secretary Hillary Clinton in 2012, starts from a belief that essential features of women’s lives are undercounted or entirely ignored. Consequently, policies – even those that may be intended to improve equity and living conditions – miss the mark.

In phase one of the project, just now coming to a conclusion, the project team led by Mayra Buvinic looked at many aspects of life – freedom from violence, security, livelihoods, health and education – and created an inventory of the main sources of cross-national data through which we understand the conditions women face and the contributions they make. They obtained terrific input along the way from a large number of leading experts on gender data, from academia, UN agencies, government and civil society groups focused on gender-sensitive research and policy.

Sadly, it is an inventory that shows many gaps.  High-quality data that is routinely collected has focused principally on women as mothers. We know more from the Demographic and Health Surveys about women’s childbearing and use of contraception, for instance, than we know from any source about how women make a living.  In contrast, we know more about the work patterns of men than we do about their health or whether they want to father children.  This is not just a reflection of how societies think about gender roles; the availability (and scarcity) of information itself reinforces gender roles and handicaps policymaking.

These data gaps are big.  Despite some important surveys, for instance, we have very little information about the prevalence of domestic and other types of violence against women, or the health and other costs. Without such information, advocates struggle to make the case for better enforcement of the many existing laws, or to monitor progress when more intense efforts are made to protect those who are vulnerable.  

The situation is even more acute in measuring the level and type of economic activity.  Women (and particularly poor women) do work that is rarely captured in official statistics, whether it is tending goats, selling fruit by the side of the road, making and selling food for construction crews or doing cleaning and childcare in the homes of better off families. In most African countries, more than half of all economic activity occurs in the informal sector, and a disproportionate amount of that work is done by women.  But national income estimates, upon which we base so much of our understanding of the world, don’t capture it.  Collectively, women make an enormous economic contribution, but they are systematically excluded from being counted as workers in information that governments and the international organizations that they work with use to shape economic strategies.

Documenting the data gaps is relatively straightforward.  In the next phase of the project, we’ll take on the more challenging task of helping to accelerate progress toward filling those gaps. Fortunately, we are building on many related efforts – we are certainly not the first to recognize the problem or to work hard to help solve it. From UN Women to the UN Statistical Commission to the World Bank and USAID, many organizations are motivated to find better ways to capture data about women and have initiatives to do so. We will be looking for opportunities to provide technical support for those efforts when that is a missing piece, and to bring attention to the importance of work when what’s missing are high-level champions.  And we are starting to think about whether there is a role for non-traditional data to complement standard surveys, censuses and administrative sources, like school records.  (More about that on future Fridays.)

Everyone associated with Data 2X knows that better, more complete data collection will not automatically lead to policies that treat women more fairly.  But we also all believe that having a full and accurate picture of women’s lives around the world will boost the chances that they will be able to be seen from far away, in the ministries, parliaments and donor agencies where many decisions are made that shape the prospects for this generation and the next.