Data revolutionaries around the world (myself included) are using every forum possible to call for more and better data that is disaggregated, produced more frequently, more open, and more useable. Recently, my colleague Alex Ezeh at the African Population and Health Research Centre wrote me: “We cannot address data system challenges in Tanzania or Nigeria by holding high level meetings in New York or London.” He’s right: The path to more, better, timely, and open data starts with strengthening country governments’ core data collection, analysis, and use, whether it’s routine economic statistics or sustainable development goals. Country action should drive the revolution, bottom-up not top-down.
But what exactly might that mean? And how is it different from what we’re already doing? Last month, I attended a meeting that tried to spell out how the data revolution might be realized. My small group was focused on accelerating progress in country systems, and we identified four areas of actions: (1) creating post-2015 quick wins; (2) modernizing National Statistics Development Strategies (NSDS); (3) launching country compacts for better data; and (4) empowering new collaboratives to deal with sticky multi-country issues.
Here’s what we envisioned for each:
SDG quick wins: Some have advocated more, larger, omnibus household surveys to measure SDG baselines. This is unrealistic; it takes at least two years to design and field a household survey and 2015 – the baseline year – is just around the corner. Instead, our group identified several quick ways that could strengthen existing data so that it could be a baseline for the post-2015 goals, such as: supporting documentation of data sets, particularly administrative data; geo-referencing existing survey and administrative data, mapping key indicators and services at relevant political levels, as has started to be done by the World Bank and Paris21; analyzing and visualizing existing data more creatively; creating inter-operable existing data sources, perhaps linking survey and administrative data; enhancing usability, accessibility, and affordability of existing data sources; and developing and deploying analytical techniques such as small area estimation to produce estimates of marginalized or uncounted groups.
Modernizing NSDS: While there are some notable examples, NSDS too often take years to develop and are only weakly linked with users and available budgets. Paris21 has helpfully developed new NSDS guidelines, which is a good start. Here are the group’s ideas: reflect the data revolution and the post-2015 agenda in NSDS; modularize and sequence NSDS preparation and implementation; reform legal frameworks where necessary; develop sector-specific plans that reflect both survey and administrative data; and create opportunities for non-governmental and media tracking and feedback on progress.
Country compacts: Better data requires high-level all-agency commitment. Building on CGD and APHRC’s working group report, our small group recommended a political, financial, and technical compact around NSDS goals. But if the NSDS is intended to mobilize resources and coordinate external funders, on which many developing countries’ statistical systems rely, then it’s time to imagine and support a more flexible pragmatic plan that is directly connected to funding. Compacts could be imagined as a souped-up country-level partnership – led at the Presidential level – that would bring together the government, donors, civil society organizations, and the private sector to contribute intellectually, financially, and technically towards improving national statistics. Compacts could be organized around mutually agreed (modularized) goals on what progress towards good data looks like, disbursing a portion of resources, and creating visibility for progress on coverage, quality/accuracy, timeliness, and openness of prioritized data. A compact could also provide more flexible, longer-term funding to national statistical systems that would be disbursed against progress on mutually agreed goals in the form of challenge grants. This type of agreement could help leverage commitments from donors while also guaranteeing greater sustainability by requiring counterpart financing from the government.
New or ramped-up collaboratives: New or ramped-up collaboratives focused on funding or technical support would help address particularly challenging issues, such as improving statistics in poor and small countries, and addressing the need to rebase GDP in many countries. The group also expressed interested in establishing a civil society funding window for data analysis and use to influence debate and policy (developing “intermediaries” to make data digestible), and with a role in “validating” headline statistics. A final area that requires more effort: a more intensive International Household Survey Network that goes beyond collecting surveys and works towards coordination and harmonization of questionnaires and data collection efforts, always with due consideration of country series.
Together, these actions would go a long way to a data revolution, starting from where it counts – the bottom up.