Data landscaping: Strengthening national data ecosystems

The issue

Data in all its forms has the potential to inform policies and programmes to better tackle poverty and inequality. This potential can only be fulfilled if data is used. For that to happen, data must be trusted, relevant and accessible. Different data sources and types, from official government statistics to community-generated qualitative insights, have distinct strengths and weaknesses and vary in their suitability for particular contexts and applications. While each can play a role, diverse data from incompatible sources and other weaknesses in the data ecosystem often make it difficult to identify what data to use and with what caveats. For data and evidence to systematically inform longer-term development, the systems and processes that generate, store and share data must be robust and sustainable.

The purpose of our work

Our data landscaping approach uses national and subnational data to inform decisions that aim to reduce poverty and inequality. We have been continuously developing this approach ever since we opened our first office in East Africa more than a decade ago. Data landscaping involves mapping existing primary data sources to identify available data, what that data measures, and the strength of the ecosystems that underpin it. This includes an assessment of the political economy of data within a country; the structures and standards that govern the collection, production and sharing of data; the information systems themselves; and the culture that drives the demand for, and use of, data.

We have applied this versatile methodology to a diverse range of projects around the world, ranging from the joining up of different official district-level datasets in Uganda to assessing the capacity of municipalities to manage data in Nepal.

Our impact

Since 2011, we have continually tested, improved and adapted this methodology to meet the needs of different audiences, from multilateral organisations seeking to invest in data systems to local actors trying to better understand data that can be used to plan, manage and monitor service delivery.

We have explored the added value of data interoperability and championed the benefits of community-based resource tracking and citizen-generated data in Kenya and Uganda. We have promoted the advantages of community information systems and proposed a new methodology for monitoring civil registration and vital statistics. In May 2017 we travelled to Zimbabwe as part of a long-term agreement with UNICEF to review its investment priorities in driving the demand, supply and use of country-level data. We have also conducted data landscaping work in Bangladesh, Malaysia, Nepal, Nigeria, South Sudan, Uganda and the United Arab Emirates, where we have successfully recommended long-term investments in foundational systems such as birth registration, health and education management, developed central data dictionaries and improved systems interoperability.

Data landscaping is a valuable precursor to our work on poverty and inequality data analysis. It ensures that we understand the range of data available that can measure multiple dimensions of poverty for all sections of society. This includes, for example, scoping the available disability data in East Africa. The data landscaping process also supports our understanding of how different data sources can be triangulated to enable a comprehensive and balanced understanding of poverty and inequality in a specific place.

Connecting the local to the global

Drawing on our many years of experience, we are increasingly using findings of our local assessments to contribute to global discussions on data for development. In 2021 we published a discussion paper for the World Data Forum – The data side of leaving no one behind – which highlighted the need to strengthen data ecosystems in low income countries to reduce inequality, prompting Claire Melamed, CEO of the UN’s Global Partnership for Sustainable Development to comment: “If you are at all interested in data, evidence, facts, truth, policy, politics, people, poverty or inequality then you MUST read this report”.

Our subsequent report on the role of international actors in strengthening data ecosystems included implications that resonated with many international agencies, helping to shape their approach, investments and interactions with national governments and data systems. As evolving crises continue to shape the global political and humanitarian landscape, DI’s skills in data landscaping are an increasingly vital tool supporting decision-makers to access and understand data and evidence that can inform policies to reduce poverty and inequality.

The next discussion paper in the series focuses on the 2015–2030 SDG global monitoring system, which was created and agreed by a huge range of actors, from statisticians to diplomats. We consider the issues with the system from a data perspective – some are well known (such as the number of targets to track, with 17 targets featuring 169 indicators) – and some less well known. The paper challenges the existing SDG monitoring system and proposes constructive reform, with the goal of consolidating a discourse that stakeholders can act on, and answering the question: is the SDG monitoring framework broken?