No one left behind – this is the fundamental promise of the 2030 Agenda for Sustainable Development, and one of its most important commitments at all political levels: international, national and local.
To make good on this promise we need data to show us how different groups in society are doing—and not just any data. We need reliable, relevant, timely and detailed data, produced according the Fundamental Principles of Official Statistics. Knowing how different groups are faring and whether they are being included in the development process requires fine granularity, where minority groups, underserved regions and people in vulnerable situations are made visible through data gathered to answer questions not only about ‘what?’ but about ‘who?’ and ‘where?’.
It’s easy to agree with these ideals, but much harder to fulfil them in reality.
National statistical offices face trade-offs to meet the data needs of the Sustainable Development Goals (SDGs) while keeping statistics cost-effective and high quality. Collecting data on small groups, especially if they are also hard-to-reach groups, can necessitate larger sample sizes, longer surveys and increased costs. In some countries, national statistical offices may not be legally allowed to collect data on certain sensitive topics, such as religion. Statistical offices also have a strong commitment to protecting the privacy of their respondents, and this may prohibit them from publishing data on small groups where there is a risk that individual respondents could be identified – as could happen when data are cross-classified by sex, age, ethnicity, disability status and location, for example.
With these challenges in mind, statisticians from 46 countries and international organizations gathered in Geneva this week to discuss how to ensure that ‘leaving no-one behind’ is more than just a memorable motto. The Expert Meeting and Workshop on Statistics for SDGs explored not only the collection and transmission of data, but also how to communicate findings; the best ways for national statistical offices to partner with other data providers beyond the realm of official statistics; and how processes can be modernized to increase efficiency, transparency and quality.
High on the agenda was the incorporation of a geospatial element into statistics for SDGs, enabling policymakers to see the spatial stories behind data. Visualizing statistical indicators on a map can help to highlight the links between the socio-demographic and economic indicators and the daily realities of people in cities, towns and villages that give rise to those statistics, potentially guiding better-targeted approaches to improving people’s lives. Albania, for example, showcased a tool to map SDG indicators such as unemployment and poverty rates. In Portugal, a study combining geographically-identified census data with information on roads and the location of schools allowed researchers to find the time it takes to reach the closest primary school on foot—an indicator for SDG 4 on quality education.
The outcome of the meeting will be reflected in a second edition, currently under development, of the Conference of European Statisticians’ Road Map on statistics for SDGs to guide countries in their measurement of progress towards SDGs. This follows the success of the popular first edition of this publication (issued in 2017) which has been widely used in UNECE region and beyond.