Funding Data Quality: The Overlooked Key to African Development

Osapinion's post highlights a persistent but underfunded crisis: data quality in Africa is near-universally poor, especially at sub-national levels. Major global institutions report socio-economic and demographic data, but much of it is unreliable or simply made up. This has real consequences: aid bureaucrats use flawed numbers to allocate billions in foreign assistance, and domestic civil servants cannot even measure the scale of problems like poverty or infant mortality without knowing basic population counts. For example, West African nations like Benin and the Gambia have not conducted a census since 2013, and Nigeria's last census was in 2006. These knowledge gaps compound over time, making any subsequent data collection less trustworthy.

The author proposes a practical solution: fund data quality directly by placing technically skilled personnel inside national statistics bureaus. This could mirror the ODI fellowship model but tailored for data quality improvement. Supporting census rollouts and regular on-the-ground data collection are also essential. While better data won't solve every challenge, it would dramatically improve the capacity of policymakers and aid organizations to make evidence-based decisions. The argument isn't limited to Africa—as political trends in wealthier nations shift, data quality may become an urgent problem there too. Investing in data now is a high-leverage way to lift millions out of poverty and ensure aid dollars have real impact.