German development cooperation should embrace the potential of digital data to drive development, while being conscious that data is only a means to an end, and acknowledging that the political economy of decision making and the demand for data are as important as the supply of data. When establishing data for development initiatives, German development cooperation should ensure that an enabling environment to incorporate data into decision-making already exists, or that one will be developed alongside the initiative.

Experts interviewed for the study suggested that German development organisations should focus on supporting demand-driven initiatives by building on existing work in a small number of sectors. The decentralised structure of German development cooperation, with staff being placed in or working directly with government agencies, CSOs and business associations of partner countries, gives German development organisations a very granular understanding of context, which is vital for the effective use of data to address complex challenges. Specific recommendations made by the interviewees included demand-driven and sector-specific identification of data gaps in partner countries as well as funding, training and infrastructure for data use projects.

German development organizations will need to invest in internal capacity to build the data literacy needed to leverage data-driven approaches. These may include capacity building on data-driven approaches in designing, managing, and monitoring development projects and programmes, hiring personnel with expertise in digital data to scope and develop data-driven projects, as well as investing in research and experimentation capabilities to investigate and test new and novel approaches in solving persisting problems. Moreover, nurturing creative spaces within the organisations, and promoting experiments to explore and share ways of working with data, could accelerate the diffusion of data knowledge and capacities.

To do this, an assessment of current capacities vis-à-vis the role German development cooperation actors would like to play is necessary to determine how needs for domain and context experts, social scientists, data scientists and technologists can be best met – whether these have to be built from within, outsourced, or cultivated through strategic partnerships.

There is a need to consider reinforcing Germany’s global commitment to the importance of data in achieving the SDGs. While Germany is a signatory to the SDGs and one that explores the use of data for this purpose, it should also consider joining or endorsing the Global Partnership for Sustainable Development Data to liaise with other stakeholders in ensuring that the relevant data is available to establish baselines, monitor progress, and build capacity of various stakeholders in using data to help achieve the SDG commitments. Likewise, while its Digital Strategy specifically mentions its commitment to open data, it may consider adopting the International Open Data Charter to cement its credibility in promoting citizens’ right to data, especially in contexts where it supports partner governments to make government data available.

German development actors should review their engagement strategy with other sectoral partners and key actors, especially the ‘development mutants’, those new and emerging actors that are revolutionising the way development is done. As a starting point, the German development cooperation may need to profile new actors doing work on data and development and assess how each actor’s key capacities can be harnessed to contribute to Germany’s development agenda. This inventory can be used as a basis to explore data collaboratives that may need to be established for key development problems of interest or priority to Germany.

We suggest German development organizations support partner governments in strengthening their data privacy frameworks, work with business and civic organizations to better understand the risks of data collection and use, and champion responsible data approaches in global initiatives.

Likewise, through their existing networks they could help mobilise voices from the global South to contribute to global debates on data privacy issues, especially when it comes to possible ethical issues in the increasing number of data-sharing arrangements, or data collaboratives. In addition, targeted capacity building is required for actors in partner countries to mainstream responsible and secure data practices ranging from data collection to archiving and sharing, especially in sensitive environments.

Apart from regulatory frameworks, capacity and awareness-raising on the potential negative consequences of data for development work, the German government should also consider investing into shaping the debate on the role of artificial intelligence and algorithms in data analysis. Advances in artificial intelligence will make it even less likely to ensure anonymity because of the ability of artificial intelligence systems to cross-reference between vast quantities of data in multiple datasets. Hence, the need to focus on how this emerging technology can potentially jeopardize efforts in ensuring data privacy.

While data can act as a catalyst of change, a too narrow focus on the data, its supply and use rarely lead to achieving the desired impact. German development cooperation, with its strong presence in partner countries, is well placed to combine novel data-driven approaches with a deep, local and context-specific understanding. It can therefore connect data-driven interventions with existing demands to address real pain points as experienced by local communities.

German development cooperation should contribute to realising the potential of data in development by investing in specific sectors instead of cross-cutting data initiatives. This will require engagement with governments and local actors, paying special attention to countries and sectors that expose positive deviance with regard to specific development problems. German development cooperation could combine its strong sectoral expertise and engagement with the opportunities that new types of digital data provide, and help nurture sectoral data ecosystems in countries in sectors like procurement, extractives or health.

German development cooperation should help close the gap in data and information inequalities through targeted research and empowerment of local stakeholders.

There is a scarcity of research that deals with data and power dynamics in societies and communities, an area German development cooperation could invest in by engaging with actors and funding initiatives that seek to build a rich understanding of the complexities that exist at the intersection of data and power. Research on how and to what extent data is actually shaping decision-making on policies and programmes and, more importantly, who benefits as a result is necessary in order to determine strategies to combat and prevent data inequalities.

Greater investments are also needed for the actual empowerment of local players with little resources and capacity to engage with data and to influence the data for development agenda. This capacity building would need to come with financing of the necessary investments into infrastructure required for widespread data access and use that benefits everyone.