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Multidisciplinarity of Data: Time to Put Data at the Heart of UN’s 2030 Agenda

Fekitamoeloa Katoa ‘Utoikamanu is the UN High Representative for the Least Developed Countries, Landlocked Developing Countries and Small Island Developing States; El Iza Mohamedou is the Deputy Manager of the Partnership in Statistics for Development in the 21st Century, PARIS21; Koffi Zougbede is an Economist at the Organisation for Economic Co-operation and Development

UNITED NATIONS, Sep 16 2019 (IPS) - The 2030 Agenda for Sustainable Development was adopted in 2015. At its core are 17 Sustainable Development Goals and 169 targets, all meant to guide efforts by all countries towards a more sustainable, prosperous and equal future.

Today, nearly a third of the way towards 2030, progress has been made by several countries in assessing and reporting on whether they are on track to meet those goals. But this stocktaking has uncovered another uncomfortable truth: for many countries, especially the most vulnerable, we simply do not know.

No least-developed country has a complete set of national statistics. The poorer a country is, the spottier its data is. If 22 least-developed countries in Sub-Saharan Africa cannot even measure their own poverty rates, how can we expect them to report on, say, disaggregated indicators such as SDG indicator 11.2.1—proportion of population that has convenient access to public transport, by sex, age and persons with disabilities if they could not generate an aggregated poverty headcount ratio?

Assessments of SDG progress are based on models, or on methodologies and data developed and maintained by dozens of different development agencies working in each country.

Created to support monitoring and evaluation of development interventions, these data are fragmented and limited in scope, painting only enough of the picture to show whether project goals have been met and the spending of donor funds justified.

As a result, there are thousands of different datasets, perhaps overlapping or conflicting, for each country, with no mechanism to collect or process them into an aggregate picture.

Moreover, by focusing on project-based data and working in silos, we compete with national statistical offices for scarce financial resources and other support and therefore limit their ability to develop robust national statistics to advance sustainable development.

This means governments often struggle to use data for the decisions where they are most needed. Poor national epidemiological surveillance systems, instigated in part by the lack of timely and accurate information, is one of the factors that contributed to the spread of Ebola Virus Disease (EVD) in Guinea, Sierra Leone and Liberia as well as its heavy human, social and economic costs.

In May 2018, the Review of Partnerships for Small Island Developing States (SIDS) pointed out that a lack of reliable data baselines, monitoring and documentation is hampering progress towards sustainable development in SIDS.

And, at the most recent High-Level Political Forum in July, African countries called for the creation of a solidarity fund for stronger statistics to strengthen their capacity to design and implement fact-based policies and better monitor their implementation.

Yes, data is central for policymaking and its value for sustainable development goes far beyond its current piecemeal implementation and low priority. It is multidisciplinary in nature, able to tell us many different stories about given economic, social and environment situations.

Take healthcare for example. Without an accurate population count, it is difficult to decide whether a hospital is needed in a given area. But what about transportation data, for instance? How easy is the hospital to access?

Moreover, what effect will seasonal weather have on demand (or illness rates, for that matter)? Then, if a new hospital does get built, the impact on health outcomes needs to be assessed and the investment evaluated. But how will this impact poverty or education rates in the surrounding area, for instance?

None of these questions can be answered with a limited set of project-level data. But by robbing poor countries of the ability to develop strong national statistical capacity and datasets, we deprive them of the tools and resources that they need to gain insights into their own development needs and make informed decisions.

It is not hard to see why national data and statistics have not gained the attention that they deserve. After all, building stable and robust national statistical systems which inform better governance, policymaking and development, is less tangible and visible than, say, physically building a school.

Yet data are an essential prerequisite to ensuring that other development interventions are appropriate. In this example, perhaps high poverty rates will tell us that prospective students are more likely to be working in the fields rather than attending classes and therefore other measures are required.

In 2017, only 0.35% (or USD 689 million) of official development assistance (ODA) went to creating the data required for sustainable development. Although this percentage has been increasing over the years, it is still around USD 200 million short of what is required.

It is time for a change, and the adoption of a global and integrated strategy for data is a good start. The 2017 Cape Town Global Action Plan for Sustainable Development Data focuses on making sure that data production is co-ordinated across a range of disciplines and emphasizes the significant role of official data to policymaking and setting development priorities.

A new global alliance for more and better financing for development data, as has been proposed by the Bern Network on Financing Data for Development, is another welcome measure. Recipient countries, donors and development agencies should come together and make the necessary investments in data.

Data is central precisely because it is multidisciplinary, but that, it seems, makes us forget its centrality.

The opinions expressed and arguments employed herein are solely those of the authors and do not necessarily reflect the official views of the UN, PARIS21 or the OECD.

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