Written by Johannes Jütting, Manager of the Paris21 Secretariat.
“We don’t need your data revolution,” were the words of a frustrated statistician in Maputo, Mozambique. He had sat through yet another workshop presentation about the importance of statistics for the post-2015 development agenda, something he understood probably better than the presenters. “It’s just more talk from New York, what we need is support for what we’re doing here.” There is no doubt that support is needed. Despite great effort by country statisticians and international organizations, development statistics are often out-dated, unavailable or of questionable quality.
This is a serious problem. Based on the recently published new PPP numbers, researchers from Brookings are estimating that there are half as many poor people in the world as we thought – not 1.2 billion but rather some 600 million. If these estimations are reliable this would be great news, but are they? One thing is clear: more nationally produced poverty numbers of high quality are badly needed as the basis for an aggregated global poverty number and for making effective policy change toward leaving no one behind at the national and local levels. Similarly, announcements that infant mortality has fallen over the past decade could be reason to celebrate. However can we celebrate the fact that only a quarter of South Asian countries have a complete civil registration system, meaning that most of those data are estimates? Despite such uncertainties, donors and international agencies give aid here and there, and start up multimillion dollar projects, while countries craft national policies with long term development and economic implications. In much of the developing world, decisions over which district will get a new school, or which province requires investment in sanitation infrastructure, or how to get money to those most in need are made without really knowing whether it’s the right choice – some call this “flying blind”. Timely and high quality data produced at the country level are needed. What’s preventing that from happening?
Those country statisticians who are actually in a position to measure accurately what’s happening in their home countries struggle to get by on limited and inconsistent funding, on an ever increasing demand for data for international monitoring needs, aid agencies’ hunger for monitoring and evaluation data for their specific projects, and the increasing perception by “data techies” that national statisticians are expendable mainly due to innovations in big data, satellite imaging and the use of mobile devices such as mobile phones for data collection. The reality of today is though, that international aid to statistics remains at less than $500 million USD per year, a shameful fraction of a percent of official development assistance.
In the face of such challenges, some are saying we should just get rid of the statisticians entirely. After all, with big data on the way, why do we need official statistics? There are over 2.5 quintillion bytes of data being created daily, and over 6 billion active mobile phones in use today. The amount of data is staggering. Surely we can use this to fix all of our measurement issues? This is a dangerous assumption. Ultimately there must be someone to analyse that data, disaggregate them to the local level, put them into forms that are useable by policy makers, and ensure that they can be sustainably produced at a reasonable cost and with a recognized quality. All this requires the establishment of a functioning national statistical system that produces statistics that matter to people and that are useful for decision-making purposes.
There is hope, and we have been granted an opportunity. With the Millennium Development Goals coming to an end in 2015, the world is set to agree on a new set of goals and targets. This time, statistics are taking a front seat, with the High Level Panel of Eminent Persons calling for a data revolution. There is recognition that without quality data produced at the country level, along with serious coordination between international players, regional institutions, and countries themselves, we will once again be left with assumptions, estimates and guesses.
This is not an impossible challenge – but it will involve several steps. First, it requires an inventory of the current state of development data and statistics, and a rigorous assessment of the strengths and weakness of the international and national data production system. This should be followed by an investment plan detailing what a data revolution at the country level would actually cost, what data are needed from countries and how they can be supported in providing those data, and what kind of institutional framework would be best suited to monitoring an international agreement. Everyone from the private, public, and non-profit sectors will have a role to play. Promoting institutional and technological innovations, strengthening national capacities, increasing funding and improving co-ordination at different levels should be the cornerstones of a development data revolution that promises to provide the right data to the right people at the right time.
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