As we deliberate post-2015 agenda chalking out global development directions after the Millennium Development Goals (MDGs), there’s a renewed interest in the availability, quality and accessibility of data and statistics for guiding policy, monitoring progress, measuring results, and supporting analysis.
The recent report by the High-Level Panel appointed by the United Nations Secretary-General to advise on the global development plans after 2015 stresses that a ‘data revolution’ should support the new set of global development goals to help monitor their progress. It states that “better data and statistics will help governments track progress and make sure their decisions are evidence-based; they can also strengthen accountability. This is not just about governments. International agencies, CSOs and the private sector, should be involved. A true data revolution would draw on existing and new sources of data to fully integrate statistics into decision making, promote open access to, and use of, data and ensure increased support for statistical systems.”
Indeed, this is not the first time that the importance of data and statistics has been expressed in the global development context. In fact, in 2000, when the MDGs were set out, the significant gaps in reliable data required to monitor them came to the forefront. The demand for comparable, good quality statistics relating to MDGs has led to concepts such as Managing for Development Results (MfDR) – a management strategy that focuses on using performance information to improve decision-making and initiatives such as International Conference on Financing for Development (Monterrey, Mexico, 2002) leading to the Monterrey Consensus. One of the concerns in these and subsequent related deliberations, which went beyond the need for financing for development, was to measure results throughout the development process and the need to demonstrate that impacts were made. This required countries to develop strong statistical practices capable of meeting this challenge through a system-wide approach in planning their National Statistical Systems (NSS) – an ensemble of statistical organisations and units within a country that jointly collect, process and disseminate official statistics on behalf of the government.
This, however, has not been the only global push for effective and efficient NSS. Related to the MDG agenda, but further than that, in the context of the use of aid – both for the attainment of internationally agreed goals and the national development priorities, mutual accountability is of crucial concern between donors and recipient countries. This concern has also been echoed in the ‘Paris Declaration on Aid Effectiveness’ endorsed by the 2nd high-level forum on Aid Effectiveness (Paris, 2005). This initiative highlighted the requirement of cost-effective data for results-oriented reporting and assessment frameworks in the context of public accountability. This also called for a comprehensive approach in developing a national strategy for statistics.
National Strategy for the Development of Statistics (NSDS) is the formal framework to strengthen statistical capacity across NSS. Using a strategic plan to provide an overall strategy for improving development statistics has been widely accepted as a best practice. (Marrakech Action Plan for Statistics, 2004 – (PDF), endorsed by the partakers in the 2nd International Roundtable on Managing for Development Results in Marrakech, Morocco in 2004).
Currently, Rwanda is developing its 2nd NSDS for 2014/2015-2018/2019. Still in the initial stages, while drafting this document, came the dawning realisation that much as I would like it to meet the expectations towards the international development agenda, it is the national development context that should drive it.
In Rwanda’s Economic Development and Poverty Reduction Strategy (EDPRS), which is a medium-term strategy towards the attainment of long-term goals – (now in its 2nd leap for the period 2013–2018), data and statistics as evidence, plays an indispensable role in guiding its implementation and subsequent policymaking.
The monitoring and Evaluation (M&E) framework in such strategies provides the context for data as baseline, output and impact indicators. NSS plays a significant role here. It will require concerted efforts by all NSS constituents to meet the objective of providing data for monitoring the EDPRS implementation. This essentially entails obtaining activities/output data from the regular administrative data collection mechanisms of implementing agencies at national and sub-national levels and data for outcome/impact indicators (usually measured at the population level) through population-based surveys and the census.
Hence, a strong NSDS, which ensures that the surveys and censuses are supplemented by administrative data (and vital statistics) from NSS, feeding in learning and discovering what is not working in development or poverty reduction context, is essential.
In the past, though NSS has collectively produced statistics through many population-based surveys and censuses, the administrative records and vital statistics to complement the requirement have fallen short of expectations. It requires rigorous efforts to strengthen the mechanisms to improve the administrative data collection and civil registration system. Also, (and most importantly) data dissemination by NSS constituents has been weak. Some institutions and line ministries don’t have data and statistics on their websites, and in some cases, these are not easily discoverable, useable, or understandable by the public.
It is required that access to data is made easier to allow users to have new insights and help improve the flow of information within and between NSS institutions.
Does the situation call for an open data revolution? (Not just data revolution!), as the recent G8, Open Data Charter states, “open data by default”!
During the 41st session of the United Nations Statistical Commission, held in February 2010, in a seminar titled ‘Emerging Trends in Data Communication’ organised by the United Nations Statistics Division (UNSD), informed its participants about the innovations in the communication of data and on movements towards open data.
Open data implies that data are open to the public, free of charge, machine-readable and follows open standards. In my view, also as a public good, government data and statistics should be freely available for use and reuse by the public.
This may not only reduce the reporting burden on institutions but may as well enhance public accountability and improve decision making.
I’m wondering, though, can NISR as the coordinator of NSS in Rwanda (or similar National Statistics Offices around the world), play a facilitator’s role through NSDS in influencing the line ministries and other government institutions in opening up their data?