| Priorities |
Context |
What must we do to bring about change? |
Short-term changes |
Long-term changes and beneficial impacts |
Assumptions and risks |
|
| 1 |
Maintaining High-Level Commitment for Data |
In 2015, the 2030 Agenda for Sustainable Development (“2030 Agenda") was agreed upon, including 17 Sustainable Development Goals (SDGs). The agenda calls for more disaggregated data and data of a greater resolution to support the commitment of leaving no one behind. |
Encourage governments to place data at the heart of decision-making. Create platforms for high-level, international discussion of the data imperative and the agenda to leave no one behind. |
Improvements to data-informed planning and decision-making. Demonstration of value and impact of data (evidence to show investment in data is a smart move). |
More effective policy design, more efficient use of resources and better outcomes. The data and evidence agenda in countries is a valued line of business with clear commitments, accountabilities and senior-level positions such as Chief Data Officers and Chief Statisticians, with an independent NSO in charge, etc. |
Governments and global development initiatives see the benefits of data-based policy and decision-making, and are not more influenced by political dynamics.Governments are a trusted convener and collator of data and will not misuse or distort data for political ends. Governments appoint champions to lead and deliver on the process, notably appointing CDO, etc. |
| 2 |
Closing Persistent Data Gaps and Improving Data Quality |
There are acute data gaps affecting every country in the world (e.g. we have very poor knowledge of gender experiences of poverty). What data is available is often three or more years out of date; alternatively, the data that is available is patchy or irregular. |
In partnership with organizations like the Partnership in Statistics for Development in the 21st Century (PARIS21), advocate for increased investment in statistical systems (including support for human capacity development) and show the return on investment of data.Show the value of innovative interim measures to help fill gaps and stress-test official statistics. |
Increased awareness about the limits to our knowledge and the negative effects upon effective policy and management.There is more evidence on quality issues, data gaps, costs to fill them, and innovative methods to fill gaps or model data.Data is better used, and there is increased adoption of open data principles. |
Well-trained, well-equipped statistical systems are established in all countries worldwide, generating more data of higher quality with greater frequency. |
National governments, bilateral and multi-lateral donors have additional resources to make available for data system development. Money and training can resolve the current shortcomings in statistical systems. The UN and intergovernmental technical data processes are successful in setting standards that are implementable by countries for new data. |
| 3 |
Enabling Collective Efforts Among Data Communities |
Monitoring the sustainable development agenda is complex. No one entity can do it on its own. |
Create spaces to engage a range of data producers and analysts from the private sector, academia and Chief Statisticians in the SDG challenge. Establish principles and standards to ensure data quality and reliability across diverse data producers, and to ensure data privacy. |
Chief Data Officers are appointed to help governments identify new data sources and opportunities.The national statistical office’s (NSO) role evolves from producer of data to part producer and part quality controller over new data sources available.The UN Statistical Commission invites nongovernmental data producers as active participants. |
NSOs work with CDOs, private companies, citizen groups, NGOs and academia to generate data through a more collaborative model that does not impose a strict divide between 'official' and 'non-official' data sources. Open data, data privacy and data interoperability are norms rather than exceptions. |
All partners will respect data sharing and storage best practices, and will uphold data privacy rules. Third parties will produce reliable data over the duration of the SDGs that governments can count on and openly access. |
| 4 |
Harnessing the Data Revolution |
We are in the midst of a “data revolution,” brought about by technological change and the expansion of the internet (both geographically and in terms of content). This brings with it new data collection methodologies and approaches – potentially lowering costs of data collection tools like censuses, improving access and use of data, and enabling low capacity countries to leapfrog in adopting better data and data systems. |
Pilot and make available at-scale new approaches to data collection, storage, management and sharing, drawing upon new technologies and private innovations. Build the capacity of governments and statisticians to use these new methods and to integrate them into the production of official statistics. |
Common standards and replicable methods are established for the use of innovative new approaches to collecting, for example, population data or conducting infrastructure mapping, and use of geospatial data and Earth observations |
Countries are able to access a broad array of innovative interim approaches to data collection to help fill gaps in official statistics (e.g. using satellite imagery, radar or citizen-generated data), and have increased capacity to utilize and analyze these new approaches. |
Countries and communities will welcome new methods and tech-based solutions to their data gaps. Governments are able to raise the necessary resources to build capacity and integrate tech-based solutions to their data gaps. Academia, civil society and private companies will work together to create standards and identify replicable best practices. |
| 5 |
Closing the Digital Divide |
There is a growing digital divide between those with access to the internet and new data technologies and those without, both across and within countries. |
Support governments with money, technology, and training to: create an enabling environment for the expansion of broadband coverage, increase access to modern technologies and promote data literacy through data-oriented curricula in schools. |
More people have access to smartphones, computers and high-speed internet. Governments create e-mechanisms to enable people to report on their personal circumstances or that of their environment using digital tools. More young people are being taught the potential of data, how it can be collected, how it can be used and its associated risks. |
Future generations are empowered to understand, use, and protect data.All citizens in every country are invited to provide feedback on their services and governance using phones and e-based approaches (among other approaches). |
Widespread basic data literacy will help promote its use for sustainable development policy and decision-making - and will help ensure responsive, safe data management. |
