AU-IBAR is a specialized technical office of the African Union Commission (AUC), headed by the Director who reports directly to the AUC through the Department of Rural Economy and Agriculture (DREA). Founded in 1951 to study the epidemiological situation and fight rinderpest in Africa, AU-IBAR9;s mandate covers all aspects of animal resources, including livestock, fisheries and wildlife, across the entire African continent.

Objectives of the Consultancy

The Data Management Consultant will collaborate closely with the National Assessment Coordinator to carry out Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs) as components of the consultancy project within the specified country. The consultant will be responsible for ensuring precise data collection, recording, documentation, and maintaining data integrity. Furthermore, the consultant will collaborate with the assessment team to provide clarity on questions and topics related to data management in feed and fodder.

Scope of the Consultancy

The Data Management Consultant shall:

• Attend interviews and focus group discussions (FGDs) as an observer and data recorder.
• Record detailed notes during interviews and FGDs, capturing key points, responses, and discussions.
• Ensure that notes are clear, organized, and accurately reflect the content of the sessions.
• Collaborate with the Interviewer and FGD Facilitator to capture all relevant information through notes, audio/video recordings.
• Compile and organize data from recorded notes, audio, transcripts, and other sources into a structured format.
• Ensure that data is categorized and labeled appropriately for easy reference.
• Collaborate with the Data Analysis Specialist to prepare data for analysis.
• Maintain data integrity and accuracy during the compilation process.
• Compile and organize data from recorded notes, transcripts, and other sources into a structured format.
• Safeguard collected data, ensuring confidentiality and compliance with data protection and research ethics.
• Assist in preparing sections of the assessment report related to data compilation and summaries.
• Provide input for report sections that rely on the compiled data.
• Collaborate with the Data Analysis and Reporting Specialist to ensure that data-related sections of the report are accurate and coherent.

Deliverables

• Detailed and organized session notes for all interviews and FGDs.
• Comprehensive records of key points and discussions.
• Structured and organized data compilation.
• Categorized and labeled data sets ready for analysis.
• Contributed content for data-related sections of the assessment report.
• Collaborative efforts to maintain assessment report accuracy.

Duration

• The Data Management Consultant will work for a period of 12 working days to be completed over a three (3) calendar week period. All the proposed activities and outputs should be completed within his period.
• The assignment will start immediately after signature of the contract by both parties

Confidentiality

• All documents and data acquired from the records and during the interviews and meetings are confidential and will be used solely for the project.
• The deliverables and all material linked to the assessment (produced by the consultant or AU-IBAR itself) shall be confidential and proprietary in nature and may not be shared with 3rd parties without the written consent of AU-IBAR and/or the relevant national authorities.

Remuneration and Terms of Payment

• The total amount for the consultation will be $3,600 to be paid upon the successful completion of the assignment, submission of the satisfactory final report, and fulfillment of the terms outlined in the terms of reference. Other costs related to the activities such e.g cost of meeting venues, ground transportation, materials and tools for data collection will be covered by AU-IBAR.

Supervision and Coordination

• The Data Management Consultant will be under the overall supervision of the National Assessment Coordinator to identify and coordinate teams for the assessment. AU-IBAR will hold a training session with the country assessment team on the assessment tools and approach to the assessment.

Requirements: Qualifications, Experience & Skills

• University degree in Data Sciences, Information Management, Computer Science, Statistics, and any other related field of expertise.
• Demonstrated experience in qualitative data collection, techniques and methodologies including conducting KIIs and FGDs, ideally in similar assessment contexts.
• Proficient in data collection tools such as ODK, Kobo Toolbox, Google Forms, with the ability to troubleshoot technical issues during data capture.
• Strong communication and collaboration skills to work effectively with diverse stakeholders, Interviewers, Discussion Facilitators, and other team members to maintain data accuracy.
• Knowledge of and commitment to ethical research practices, including confidentiality and informed consent, when handling sensitive data during assessments.
• Awareness of and sensitivity to cultural diversity, especially in the context of the assessment’s location.
• Capacity to work collaboratively as part of a team, including coordinating with other Assessment Consultants and RAFFs Project Staff.
• All reports and consultancy outputs will be in English. In the course of execution of the assignment, proficiency in local languages will be required for engagement with relevant to the assessment country or stakeholders.

Selection Criteria

• Criteria Scores (%)
• Qualifications 25
• General Experience of the Consultant 25
• Specific Professional Experience 35
• Other skills and competencies 10
• Working language(s) 5

Application Procedures

• Interested individuals should submit their applications which should include the following:
  • A brief technical proposal indicating the approach to the assignment, objectives, activities to be carried out, expected outputs and a clear work-plan with timelines for carrying out the assignment.
  • A recent Curriculum Vitae (CV).
  • Copies of identification documents
  • Signed declaration on exclusion criteria