Resources for Data: Transformative Opportunities?

Event Recap:

Resources for Data:

Transformative Opportunities?

by Deirdre Appel, Open Data Watch

On the sidelines of the World Bank and International Monetary Fund Spring Meetings, stakeholders, national statistical offices, UN agencies, bilateral donors and development data experts came together to discuss an issue underpinning all other development issues discussed last week in Washington – data and statistics. Implementing the Sustainable Development Goals (SDGs) and meeting government aspirations to provide a better life for their people will require more and better data. However, critical data gaps limit the world’s ability to achieve the SDGs, and low levels of financing slow progress.

“Resources for Data & Statistics: Transformative Opportunities,” a side event hosted by the Global Partnership for Sustainable Development Data, Open Data Watch, Development Gateway, World Bank, Swiss Statistics, PARIS21, and the UN Statistics Division on April 12, was organized with the aim to catalyze a broad partnership behind more and better funding for development data and statistics ahead of the United Nations World Data Forum 2020 in Bern, Switzerland. It is part of a continued effort by advocates to make the case for more and better funding for data and statistics and discuss possible solutions to narrowing the SDG data gap.

Here are some key takeaways from the event:

Create a business case for investing in data

There are compelling reasons to invest in data: evidence-based policy making, monitoring results and progress and improving outcomes. Despite the benefits, national and international statistical systems remain underfunded. To convince donors to invest, well-documented stories of impact are needed. As Homi Kharas, the Interim Vice President and Director of the Global Economy and Development program from Brookings Institution stated: “You are not actually funding data. You are funding saving lives because that is what the data is going to do. ” To galvanize support for data revolution, we need compelling stories and advocacy with a clear demonstration of how data drives actions and improves live.  

Country-driven demand for data is needed

The Rwandan Minister of Finance, Uzziel Ndagijimana, explained that the reconstruction process of Rwanda’s Vision 2020 strategy emphasized the importance of data as a pillar of a capable state and for strong governance. While certainly an accomplishment, this positive recognition of data was not always the case, said Ndagijimana. Through the reconstruction process, the government developed the National Institute of Statistics for Rwanda (NISR) in 2005. As a country with a history of civil war and conflict, data have been used as a tool to leave nobody behind. As Rwanda works to reconstruct public services, they are using data as a critical component for evidence-based decision making. Ndagijimana also highlighted the importance of disaggregating data to target areas with high levels of malnutrition maternal deaths.

Learn from previous global financing facilities

As conversations on potential mechanisms for financing more and better statistics continue to develop, previous efforts to pool funds should be reviewed for lessons learned. Current inadequacies must be addressed to create a comprehensive funding strategy. Mariam Claeson, the Director of the Global Financing Facility for Every Woman Every Child at the World Bank (GFF), who has set up financing facilities for a multitude of development initiatives on maternal health and civil registration and vital statistics (CRVS), among other issues, emphasized looking to previous efforts when planning new ones.

Donors should not coordinate each other;

the country should coordinate donors

Everyone loves coordination but no one wants to be coordinated. The sentiment is true for donors funding statistical activities within a country as previous efforts to finance statistics have received criticism for lack of coordination. So, what is the solution? One way is to place efforts in coordinating the donors and ensure they work together to reduce duplication. Another–perhaps more promising–way, as brought up in the discussions, is to put countries in the driver seat, having them derive a set of national priorities for statistics and coordinate the activity within their own country.

Strengthen systems and be patient;

building statistical capacity is a long-term process

Closing data gaps is a priority, and while new innovations can offer compelling solutions, they can also prove to be disruptive. Many developing countries are still struggling to deliver basic statistics and civil registration services due to weak statistical foundations. Short-term or one-off investments in new technologies may fail to support the building of national statistical systems that will live long beyond a grant cycle. Mariam Claeson reinforced this point and reminded us of the one thing we all need – the denominator. While new data sources are important, we still need traditional data systems like CRVS to get all of the information we need. Efforts to do so should be underpinned by the recognition that building statistical capacity and investing in data systems takes time.

Leave no donor behind

On January 24, 2019, a group of bilateral and multilateral donors, as well as data technicians, came together to discuss the funding-for-data landscape at the Bern High-level Dialogue on Funding for Data for the SDGs. The result of that meeting was the formulation of the Bern Network on Financing Data for Development (Bern Network). It aims to develop a new robust funding framework to be launched at the World Data Forum 2020 in Bern. The Bern Network aims to make communication and advocacy more impactful, improve coordination, and work towards an improved funding mechanism.

Emphasizing the need to translate words into action beyond the Spring Meetings, Shaida Badiee encouraged all (including donors) in her closing remarks to join the ongoing efforts in the Bern Network.

– see also published version of this blog on  TRENDS –