The document discusses the role of the electronic Biennial Review (eBR) platform in improving data quality and management for the CAADP Biennial Review process. It provides background on how countries previously reported data manually through Word documents, which were difficult to consolidate. The eBR allows online reporting through a centralized web-based system, improving efficiency. It describes the front-end interface where countries report data and the back-end database. The eBR aims to reduce errors, improve user experience for reporting, and ensure high quality BR datasets. In conclusion, it notes the eBR has helped streamline the reporting process since 2019 and facilitates decision-making.

1. Manager Data-Centric Web Applications,
AKADEMIYA2063
The role of the eBR in improving BR
data quality and management
Babacar Ceesay

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Outline
1. Background
2. Front-end and back-end duality
3. Critical analysis
4. Conclusion

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Background
• During the first BR, countries manually reported and submitted (by email) their
reports to Regional Economic Communities (RECs) via MS Word document (e.g.,
the Country Reporting Template)
• RECs had the responsibility to manually transfer country reports from MS Word
to a MS Excel database and submit to AUC
• Difficulty to integrate the various submissions into one single Excel database.
• Prone to human error, data from various files, hard to consolidate, weak
collaboration, not user-friendly

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Background (Cont’d)
• The eBR was introduced during the 2019 cycle to facilitate BR data reporting and
management at the country, regional, and continental levels.
• It improves the efficiency of countries’ BR data reporting through a web-based
platform.
• Can be accessed through various devices, only a web browser is needed, same
version, more manageable, 24/7 accessibility
• Allows RECs and AUC to instantaneously review, validate, and provide feedback
on the data.

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Front-end and
back-end duality

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Front-end
Data reporting at
parameter level
 Various access levels
 User friendly interface

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Front-end
Scores computations
based on the technical
guidelines
 Scores generated in a
click

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Front-end
Scorecards and country
profiles generation
 Scorecards and country
profiles generated in a
click
 In 5 AU languages

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Front-end
Profile 1 – Member States (MS)
• Data reporting (parameter
level)
• Report submission to RECs
• Receive feedbacks from
RECs
• Address feedbacks from
RECs and re-submit report
• Respond to questionnaires
Profile 2 – Regional Economic
Communities (RECs)
• Account creation for member
states
• Member states report access
and review
• Send feedbacks to member
states
• Submit the final report to AUC
• Receive feedbacks from AUC
Profile 3 – African Union
Commission (AUC)
• Account creation for regional
economic communities
• Receive and review country
reports from RECs
• Send feedbacks to RECs
• Compute scores, generate
scorecards and country
profiles in 5 languages.

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Back-end
• Developed from scratch for flexibility. Millions of lines of code and a database
with over 100 tables.
• Replicated database to ensure that an accurate backup exists at all times in case
of a catastrophe
• 24/7 availability
• Security is managed via a dedicated server (full control)

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Critical analysis
Learning and improving is important in the CAADP process. New features and
improvements are continuously been added to the eBR.
The objectives of the e-BR critical analysis are mainly driven by the desire to:
1. Reduce avoidable data discrepancies in the BR datasets
2. Improve the user experience when they report data.
3. Improve the BR datasets quality insurance.
Example of how we are trying to overcome the challenges :
• Data cells restrictions
• Mandatory data source
• BR data access

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Conclusion
• The eBR has been very instrumental in the biennial review process since the
second cycle
• The role of A2063 is to facilitate the process as technical partner. Reporting done
by countries under the supervision of RECs, and report submitted to AUC
• Put in one location, make the process of data gathering easier, avoid inherent
errors in the reporting itself and in the computations of scores
• Good reporting will improve decision-making

13. THANK YOU