This post, written by Harpinder Collacott, Executive Director Designate, Development Initiatives, is the fifth in our blog series which aims to explore how the Sustainable Development Goals can be drafted to include all social and economic groups.
The success of the last decade has brought with it unprecedented political will to end extreme poverty by 2030 and with it an imperative to ‘leave no one behind’. But leaving no one behind must be complemented with the principle ‘to make people count, we must count them’.
The old method of measurement, which takes country aggregates and averages to monitor success and inform how resources and efforts are targeted, simply cannot work if we want to lift every single person in the world sustainably above US$1.25 a day by 2030 and ensure no one person, no matter where they are, is left behind. A complicated backdrop of exploitation, inequality, and political and environmental insecurity that affects different people in different ways must also be considered. This is very different from the approach to development of the last 50 years, which focused on countries, not people.
Data is central to achieving an end to poverty – data that describes the problems, quantifies the resources available, monitors the performance of existing services and, crucially, puts people at the heart. Without it we cannot identify the most vulnerable, marginalised and poorest people or track their progress. Importantly, data is required at a local level. It needs to be available for use by district officials and community-based organisations so they can make the right decisions about where to spend money for greatest impact. Comprehensive disaggregated subnational data (by quintile and gender) must be collected systematically and sustainably.
This is an ambitious plan. Working in Uganda, a data-rich country that is making big strides to improve national statistical systems, we at Development Initiatives encountered limitations of data at the local level that have provided valuable insights into the challenges faced and therefore the solutions that must be sought. Our project had an initial ambition to collate spending data in education and health sectors in two rural districts and join it up with social impact data, then build an open resource toolkit to empower district officials and community leaders to access this data for their decision making. Working with our partner organisation Development Research and Training, we were soon forced to rethink our ambitions. Aside from the toolkit itself requiring internet, electricity and functional computers, which are not readily available, finding sufficient compatible data was a lot harder than we thought it would be.
Our initial assumption that ‘the data is out there somewhere, we just have to find it’ was simply not the case. We gathered data from noticeboards and paper reports from district offices, and by knocking on the doors of ministries in Kampala, but the data was not complete enough and the disaggregated data that we needed did not exist. For example, data on maternal mortality is collected in a Demographic and Health Survey every five years and the latest was based on interviews with 8,674 women. These small and unrepresentative samples make it impossible to prepare meaningful information at a district level; for example no mortality data existed in the two districts we worked in. Although statistically an accurate approach, this method focuses on averages and overshadows what lies below – the systems and structures that entrench poverty and prevent communities from progressing.
While this work highlighted the absence of the data we needed, it also demonstrated a strong demand and enthusiasm by those who would most benefit from it. An education officer offered to drive 60km just to provide us with data we were looking for, showing there is an existing spirit of cooperation to get things right if we are willing to invest – something we must do to put people at the heart of the agenda for the next 15 years.
None of the solutions are ‘quick-win’. We need to start counting people and recording data consistently across all sectors and districts and publishing it in a way that allows it to be used. Data can’t be trapped in siloed portals and it must consist of common standards so that different datasets can speak to each other and provide meaningful information. Once we have this, we then need the time and money to create a user-friendly interface that caters for the technological and infrastructural limitations we are often faced with. We need to enhance the capacity of national statistics offices and shift the focus of statistics from national aggregation to subnational disaggregation. Furthermore, we need to train staff in every last medical clinic and school and build functional civil registration systems capable of producing consistent, credible data. This is a huge task and will require big, long-term investment.
Although the sustainable development goals (SDGs) come into force in 2016, data will not be available in every country globally to identify the poorest and most vulnerable people. But with sustained momentum and drive, the right data can start to be generated. We must make people count so that we leave no one behind.