Big Data promises to improve government service delivery, complement official statistics and facilitate development in a range of sectors. Countries around the world stand to benefit from ‘Big Data for development’ in health, food security, infrastructure, transportation, humanitarian response and more. Yet, interest until now in capturing and analysing Big Data for public purposes has largely been driven by Northern institutions. A two year-project, Harnessing Big Data to meet the Sustainable Development Goals - Building Capacity in the Global South, funded by the International Development Research Centre (IDRC) and led by the African Institute for Mathematical Sciences (AIMS) and four other institutions from the Global South (CEPEI, LIRNEasia, LDRI and the centre for internet and society), sought to address this challenge by developing capacity among researchers in the global South focusing on the use of Big Data to inform progress in meeting the Sustainable Development Goals.
AIMS is a post-graduate education network and research institute with five centres in South Africa, Senegal, Ghana, Cameroon and Rwanda that served as the regional hub for this project in Africa and aligned the focus of its work to the African Development Bank’s High-5 Priorities. AIMS worked with partners to increase the number of Big Data scientists on the continent, catalyse research on Big Data to address policy, infrastructure, funding and human capital gaps and provide a platform for practitioners to network, learn and coordinate activities.
The impulse for this project came from the realization that voices from the Global South were not sufficiently recognized in discussions around Big Data at the global level. AIMS came together with partner institutions from Colombia, India, Sri Lanka and Kenya to challenge this status quo.
We had many objectives and aspirations at the start of the project—notably in terms of prioritizing gender in research, engagement of the public and private sectors, influencing national, regional and global policy processes and applications of Big Data techniquest to local development problems. One of our main objectives was also to strengthen the capacity of local actors to use Big Data. Each partner could tailor these objectives to the needs of their specific region. For the African Hub of the project, AIMS focused on developing capacity (through training and other capacity-building activities) and on supporting policy and innovation for development and key research initiatives.
We delivered a short training course (Big Data Analytics with Python) and created a Big Data Education executive programme for C-level executives. We ran an innovation programme contest to tackle four development challenges focused on financial inclusion, food security and youth employment. Ten groups of young people and data scientists submitted proposed solutions to these challenges using Big Data. The two winners were included in the Open Innovation Program - Make-IT Africa, sponsored by GIZ Rwanda.
Within and outside of the context of the innovation programme, we built close relationships with private sector agencies that shared their data and engaged in project activities. Our private sector partners included financial institutions, Mobile Network Operators and media companies from several African countries. In many cases, we convinced institutions to share their data for the first time and even to fund the innovation programme. This was the case, for instance, for Orange and the Bank of Kigali. We also published the first Pan-African report on the State of Big Data for Development in Africa.
It is difficult to pick what I am most proud of. Working with young data scientists in the innovation programme and coaching them to develop solutions to key development challenges was exciting and important. The winners were given access to finance, market and skills resources and their solutions are now registered companies in Rwanda and part of the national start-up ecosystem. There was a big sense of excitement in the room when they presented their solutions. The impact of developing the training courses was also rewarding. These trainings were key to filling the needs of and increasing demand from the younger generation.
There are two lessons learned which are unique to Africa. One concerns the importance of training and working with C-level executives to increase up-take of Big Data solutions. Capacity development is not only about technical skills: Leaders can boost demand for technical skills and promote development of new services and products. In other areas of the world such as India or Southeast Asia, leaders seem to have a better understanding of the potential of technology. Africa, in comparison, presents a bigger challenge in converting C-level executives.
We also learned that there is growing demand for courses among African youth that focus on Big Data. However, the average person has very limited access to such courses. Obstacles include the limited number of available trainings, language barriers and infrastructure barriers that limit the reach of online training. That’s why increasing access to this type of education remains a priority.
There are two main categories of barriers: technical and non-technical. Technical barriers include a lack of technical and hard skills as well as insufficient equipment and poor technological infrastructure. Non-technical barriers encompass a broad range of issues such as the lack of data culture and data awareness (especially among leaders), few strategic partnerships to promote Big Data up-take and limited policy frameworks to support data-sharing. Limited funding for research and innovation also remains a key challenge.
The private sector has an important role to play in fostering the use of Big Data in Africa. First, companies must participate in discussions around development priorities and objectives. Development must be seen from all angles, and private sector objectives are not always incompatible with broader socio-economic development. Secondly, the private sector contributes to the demand for skills to process, analyse and use Big Data that can drive efforts to upskill the population. This is why we need to educate C-level executives on the potential of new technologies. Furthermore, private sector stakeholders should participate in the policy debate and help develop data-sharing frameworks that are fit for purpose.
We need to ensure funding is available to replicate some of the good experiences which emerged in the last few years, such as our innovation programme. We also need to spend more time discussing and enabling more data-sharing in the private sector. This requires finding new types of partnerships and frameworks to embed security and privacy concerns. Ultimately, we need to educate people to the language and requirements of Big Data. We are no longer speaking about data as “statistics” anymore. Big Data consists of large quantities of information from different sources, and we must ensure such data can be used within the context of solid policy frameworks and without compromising individual privacy.
- Dr. Charles Lebon Mberi Kimpolo is the Director of the Industry Initiative at the Global Network Secretariat of the African Institute for Mathematical Sciences - Next Einstein Initiative (AIMS-NEI) and a member of the Data Values Project Technical Advisory Group.