This focus on data makes sense – particularly as the current quality, timeliness and accuracy of data is dire – and the new development agenda, regardless of its details, will rely on accurate data to assess progress.
So what does a Data Revolution actually mean and how can it happen? Some development practitioners will advocate for more data — a lot more. Others will argue there is already plenty of data collection occurring, but not the right kind. Some experts will suggest that we rely primarily on internationally comparable development statistics, and encourage more development partner involvement. Others will suggest country-developed statistics should be used as the gold standard, and countries should lead their own data priority-setting and production. Meanwhile, Open Data evangelists will say open access to all kinds of data, whatever its quality, is the key. Finally, there are lots of “old” global data initiatives still around – Paris21, trust funds at the World Bank, DHS and others.
No doubt it will be hard to make sense of this complex landscape and balance these viewpoints within a new global initiative, let alone a region or a single country.
So our Data for African Development Working Group (DFAD)—co-chaired with Alex Ezeh from theAfrican Population and Health Research Center (APHRC)–is grappling with these issues in the context of sub-Saharan Africa. While the diverse group of Working Group experts–which include national statistics producers, donors and international institutions—have varying opinions on every issue debated, the group has discussed barriers to the improvement of data usability and statistical capacity (as well as mechanisms to overcome them).
We would argue that a successful data revolution will require the following:
- Building data quality checks and balances: There has been increased attention in recent years on the low quality of measures to evaluate economic growth — like GDP. But less attention has been paid to the quality and timeliness of other social and economic measures in spite of their relevance to policy makers and substantial investments by donors. Working group research shows that there are systematic discrepancies between survey and administrative data. This may be caused by perverse incentives that inadvertently manipulate the reporting of administrative data, limiting the accuracy and usefulness of the data for policy making. (read more on this in a recent blog from our colleague Justin Sandefur).
- Enhancing functional independence and budget stability of National Statistics Offices (NSOs): NSO’s need to be autonomous and independent in order to ensure freedom from political interference, allow for professional independence of NSO staff and management (including aspects such as salary scale, retention), and to support NSO capacity building. Greater autonomy doesn’t necessarily mean that an NSO would be entirely independent of the national government. But parastatal or société privée status (reporting to the President or home ministry) would allow the NSO staff to operate more independently and effectively.
- Nurturing open data: Limitations to the access and use of data in Africa are closely tied to many political economy issues. While more data are being collected and analyzed, there are still major gaps in the accessibility and quality of this information. Use of open data platforms would increase data sharing and use across agencies and institutions, ensure greater accountability and use of nationally produced data, and could help promote innovation.
No matter what targets are chosen for the post-2015 development agenda, accurate measurement through timely and quality data will be integral to determining their success. Stay tuned for the final recommendations from the Data for African Development Working Group, which are expected to be released later this year. We hope they will provide tangible next steps for the development community to achieve the much-needed Data Revolution in Africa.
This blog was originally posted on the Center for Global Development Website
Associate Research Scientist