A message from CanWaCH
Global health is fluent in the language of metrics: maternal mortality ratios, health facility access percentages, health expenditures per capita and more. Numbers tell a crucial part of the story of our impact, but not all of it. Often, they tell us the what, but not the why; the if, but not the how. Why are girl students leaving school at lunch time and never returning to classes? How has the local hospital secured the highest vaccine coverage rates in the region? Why does a community nutrition program thrive in one setting but not another? Without descriptive data, the lived experiences of women, children and their communities remain largely invisible, limiting our sector’s ability to truly learn from our work and make improvements that result in meaningful change.
CanWaCH has long been on the frontlines of pushing for rigorous, transparent quantitative data analysis in global health programming and research. For example, our Project Explorer has served as a long-standing sector resource, providing comprehensive and current information on humanitarian and development projects around the world. As part of our efforts to ensure that this tool is as useful as possible, we have increased efforts over the last year to include more descriptive information as part of its offerings. You can read some of these enhancements below. Additionally, in our efforts to strengthen collective capacity, we have hosted events such as the Global Health Impact Summit, focused explicitly on learning from qualitative findings harvested across our sector. We have also created opportunities to better understand the changing landscape of information through webinars, resource guides and regular data communiques.
What we hope to convey through this year’s report is that descriptive data is not simply an add-on or embellishment to ‘substantive’ numerical data. Rather, it is a vital component of learning and impact measurement, without which we have only half the story. If we want to truly make a difference for women and children’s health, we need more than metrics. We need to draw meaningful insights from the data we are entrusted with, so that we can learn more and do better, together.
