Every sector in Africa is impacted by data gaps. From agriculture to artificial intelligence, financial services to fashion, policy making to purchasing products online, a lack of adequate data or access to reliable and credible data affects the ability to make informed decisions on how to derive and deliver value to stakeholders.
Many things stand out as critical to closing the data gaps challenge that plagues data ecosystems in Sub-Saharan Africa. Here are key take aways distilled from our decades long experience as an insights partner for different clients working in Africa across diverse sectors. These principles have held true over the course of evolving methodologies, expanding client interests, and the existential problems that characterize the challenge of collecting credible data in Africa.
Human Intelligence is Universal
There is no such thing as an Insights monopoly. No research player has ownership over knowledge generation and insights. As research evolves into new and exciting frontiers like AI and the use of synthetic data, we have found that technology is a powerful tool for accelerating access within data ecosystems. But it is also possible for technology to entrench bias and exclusion in many African contexts.
Human Involvement Matters
This is why the human touch or keeping “humans in the loop” is still critical to closing data gaps. Training, skilling and upskilling local teams of data practioners and field support staff in sub-Saharan Africa will continue to be the main force behind acquiring credible data that can be interpretated into authentic and actionable insights. The message here is for African researchers to step up, contribute, collaborate and compete for a share of the global research pie.
Cultural context is Insightful
Culture and contextual understanding are super powers that transform data from abstract information to insightful actions. As is true of many great researchers, the obsession with data ends with finding information, often confirming what we already knew. Occasionally, great researchers may “hit the mother lode” when data mining translates into new insight.
Immersion is Invaluable
Research outcomes must be applicable and relevant to users within the ecosystem. That can only be possible when the interplay of factors and actors influencing the data ecosystem are also considered alongside the data itself. The message here is data is not just about data. It’s also about significant actions and behaviors happening around data sources. Simply put, human action and interactions must be accounted for in the data process. The causal relationships between data, data sources and data ecosystems require immersive experience be part of research design in order gain inclusive perspectives.