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Experiences and Lessons▶
1. Project Planning and Management2. Geospatial Mapping and EA Database3. Enumeration Instruments and Tools4. Data Capture and Management5. Census Testing and Pilots6. Recruitment and Training7. Deployment and Supervision8. Enumeration and Logistics9. Quality Assurance and Risk Management10. Census Analysis and Products11. Partnerships and Collaboration12. Advocacy and Publicity13. Procurement and Financial Management14. Post-Enumeration Survey15. Alternative Approaches16. Planning Checklist
Case Studies▶
1. Project Planning and Management2. Geospatial Mapping3. Enumeration Instruments4. Data Capture5. Census Testing6. Recruitment and Training7. Deployment and Supervision8. Enumeration and Logistics9. Quality Assurance10. Census Analysis11. Partnerships12. Advocacy13. Procurement14. Post-Enumeration Survey15. Alternative Approaches16. Planning Checklist
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Challenges and Lessons Learnt​

A digital census introduces a unique and complex set of challenges for quality assurance, particularly within the diverse contexts of African nations. Below are some challenges experienced:

  • Kenya used a three-tier supervision structure to support real-time response to issues and ensure data quality. However, concerns were raised about the collection of personal identifiable information and the potential for data misuse. These concerns can also impact participation and data quality.

  • The 2022 digital census of South Africa faced significant criticism regarding data quality, with an undercount and questions about the accuracy of the population estimates. This case underscores that technology alone does not guarantee a quality census.

  • While digital censuses promise faster results, there can be a trade-off between timeliness and quality. Rushing the data processing and analysis to meet deadlines can compromise the thoroughness of quality checks. Uganda disseminated a report with quality concerns and had to withdraw it. This compromises public trust in the results and may affect its use.

  • In Zambia, the census dashboard was not tested due to delay in procuring the server at the time of the final pretest. More human resources to ensure streamlined roles so that data quality staff could focus on working on the census dashboard to provide timely feedback.

Some of the potential risks in digital census undertakings may be difficult to fully mitigate, for instance dependency on foreign technology. Many African countries rely on foreign companies for network equipment and other digital infrastructure. This dependency raises concerns about digital sovereignty and the long-term sustainability of these systems.

Mitigating the risks inherent in a digital census is a complex task globally, but in the African context, these challenges are often compounded by a unique set of deeply rooted issues. The following are significant hurdles to successful risk mitigation in Africa:

  • Systemic problems that can undermine even the best-laid plans. The inadequacy of foundational infrastructure makes risk mitigation a constant struggle. The scarcity of high-quality, secure data centres within many African nations poses a significant challenge to mitigating data security risks. This raises concerns about data sovereignty, as many countries may have to store sensitive census data on less secure local options or store sensitive citizen data with foreign cloud providers or even outside the country if none exists in the country.

  • The capacity of national institutions to manage large-scale, technologically advanced projects is often a limiting factor in terms of insufficient and uncertain funding, limited technical capacity and "brain drain" in crucial areas like cybersecurity, lengthy and bureaucratic procurement processes can delay the acquisition of essential technology and services, impact on timelines and forcing last-minute, often riskier, decisions.

  • Public perception and the political environment can create significant challenges that are difficult to mitigate. In many regions, there is a deep-seated mistrust of government data collection, which is often exacerbated when new technologies are introduced.

  • The legal frameworks needed to support and govern a digital census often lag behind technology. The absence of comprehensive data protection and privacy laws in many countries creates a risky environment for handling sensitive census data.