Courtesy image: Amina Mohammed (center) addresses participants in the Post 2015 Data Test and National Implementation of the Post 2015 Agenda workshop in New York, NY on October 14, 2014. UN Foundation
Amina Mohammed recounted seeing sacks of paper - data points on Nigeria’s development progress or lack thereof - left forlornly on the floor with little chance of being seen or used. Ms. Mohammed, speaking at a workshop on the post 2015 data revolution, explained that this experience helped shape her vision as the UN Secretary General’s Special Adviser on Post 2015 Development Planning. Reviewing the UN’s Independent Expert Advisory Group’sdraft data revolution report, I returned to this image of a data graveyard and asked myself whether the report had missed the mark. Even as the data revolution builds a supply of better development data, it must address the broader ecosystem within which it is, or is not, used. In fact, the data revolution discourse should be paying more attention to five critical questions.
1. Who is going to use open development data and how do we design responsively?
Collecting data increases the reporting burden of overstretched officials, requires effort to derive meaningful insights and diverts resources from other activities. But building this supply of better development data could be a catalytic investment to support decision-making and strengthen accountability. We increase our odds that collecting data is indeed worth the cost if we invest more upfront in designing solutions responsively to the questions citizens, scholars and officials are asking and the specific entry points where information can make a difference.
Data that helps us see connections between resource flows, project results and development outcomes is critical to many questions being asked, from maximizing impact to monitoring corruption and identifying under-resourced areas or groups. Researchers and policymakers need quality assured, raw statistical data with which to assess the impact of the development efforts over time. Citizens and policymakers want real-time qualitative and quantitative information with insights they can use to influence key decisions now. With increasing decentralization within countries and rapid regionalization between countries, flexible data that is easily aggregated or disaggregated helps people zero in on what they’re looking for.
2. How do we integrate relevant, high quality data of all types for a complete picture?
The development landscape is changing and the data we capture must similarly evolve.Remittances and south-south cooperation are increasingly prominent funding sources for developing countries, but little is known about how they are used and their effect on the sustainable development goals. Citizens, civil society organizations and private sector companies are no longer merely consumers of information, but have their own data points to share on the quality of public service delivery and the health of their communities. Line ministries, local government offices and parliamentarians are also responsible to create, disseminate and use good data.
A data revolution that narrowly addresses data from national statistical offices and providers of official development assistance will miss out on these other critical pieces of information essential to connecting the dots. If we want to compare insights gleaned from these disparate sources, there are a whole host of interoperability challenges to address.
3. What does an enabling environment for open development data require?
Data must be of high quality if people are to effectively put this to use to further their goals. Beyond quality, data must be accessible - publicly available, relevant, easily visualized and analyzed - to those who want or need to use it. But even high quality, accessible data won’t have impact if prospective users lack the awareness, confidence and desire to use the data. Architecting data systems may be technical, but shaping an ecosystem within which open data is valued and people are empowered to share and use information is inherently political.
Political barriers may be present if government officials are concerned they lack space to accurately report on progress and failure or if citizens and civil society are concerned about retribution for drawing attention to waste and fraud. Socio-cultural barriers may exist that curb the ability of disadvantaged groups to access and use data or if there is limited data literacy and value for evidence-based policy making. Legally, the existence of robust right to information legislation or whole-of-government open data initiatives may increase the likelihood of the data revolution efforts to be sustained in the long-term.
4. How do we lower the barriers to entry for those supplying and using data?
Inertia is difficult to overcome. When faced with the prospect of large costs now in exchange for uncertain future benefits, most people are happy to let someone else do the heavy lifting. This doesn’t bode well for the data revolution, which implies a large upfront investment to build systems to collect, validate and maintain data, as well as putting in time to develop new skills to turn data into meaningful information. Unfortunately, there has been little serious consideration of ways to proactively reduce the costs and increase the rewards to supply and use open development data.
On the supply side, what minimum level of data quality and quantity might be “good enough” as a starting point? How can countries break down the data revolution into smaller building blocks that can sequenced to pick off low-hanging fruit and generate “quick wins”? What can we do to reward progress and nudge laggards?
On the demand side, how do we identify champions within government ministries, civil society and the private sector who are actively using data for evidence-based advocacy, evaluation and planning? How can data literacy be mainstreamed into efforts to improve public service delivery, promote citizen-government dialogue and strengthen civil society and a free media?
5. What can the post 2015 data revolution learn from other similar discussions?
The International Aid Transparency Initiative and the Open Contracting Data Standard seek to increase the transparency of funding for development and provide insights relevant to the post 2015 data revolution. Country ownership of the standard and belief in the value of the data for their own purposes is critical. There is a substantial learning curve in producing data that balances considerations of timeliness, accuracy and comparability. The information you want depends on where you sit - end users need data in different forms for distinct purposes. Benchmarking exercises can contribute to a “race to the top” dynamic that rewards progress and creates pressure for those falling behind.
The post 2015 data revolution will need space to experiment with new approaches, test assumptions and document insights. But the revolution can certainly get a helpful head start by learning from the trials and triumphs faced by these similar initiatives.
