Type of Engagement: Consultancy with anticipated travel
Start and End Dates: 15 July 2026 to 15 January 2026
Level of Effort: 3 days per week (24 hours per week)
Deadline for Applications: 08 July 2026, by 11:59 PM CET
The CGIAR Digital Transformation Accelerator (DT-A) leverages digital technologies, artificial intelligence, data science, and innovation to accelerate transformation of food, land, and water systems. To effectively monitor progress, assess outcomes and impacts, support adaptive management, and generate actionable learning, the DT-A requires technical support to design, develop, operationalize, and strengthen a comprehensive Monitoring, Evaluation and Learning (MEL) system. The MEL system will support performance tracking across DT-A Areas of Work (AoWs), ensure accountability to stakeholders and donors, and facilitate evidence-based decision-making. MEL activities will be conducted at both the Accelerator and AoW levels, with a focus on harmonizing approaches across pooled and bilateral funding streams. The assignment objective is to develop and support the implementation of a best-in-class MEL system that is responsive to the entrepreneurial and adaptive nature of the DT-A, supporting performance management, accountability, learning, and evidence-based decision-making while capturing the emergence, testing, scaling, and adoption of digital innovations across food, land, and water systems.
Key responsibilities:
Activity 1 – Review of the DT-A Design Document and Theory of Change (Weeks 1–4): Working in consultation with the DTA Director, CGIAR partners, and selected stakeholders, the consultant will define MEL objectives; review and refine the Theory of Change (ToC), identifying intermediate outcomes and assumptions; review the key results framework to ensure logical alignment; and identify critical learning priorities and evidence needs.
Activity 2 – Develop the MEL Framework (Weeks 5–12): The consultant will develop a comprehensive MEL framework articulating results pathways, indicators, data sources, responsibilities, and reporting mechanisms; formulate key learning questions; design approaches for capturing planned and emerging outcomes; recommend innovative methods and digital/AI-enabled tools for data collection and reporting; and establish mechanisms for tracking and documenting partner contributions across the results chain.
Activity 3 – Implementation Support and MEL System Operationalization (Week 13 onwards): The consultant will develop templates, guidelines, and SOPs for consistent data collection and reporting; support configuration and deployment of digital MEL platforms, dashboards, and AI-enabled analytics tools; establish data quality assurance and verification mechanisms; facilitate periodic reflection and learning sessions; provide technical advice on approaches for capturing innovation and systems change; and support preparation of periodic performance reports, learning products, and knowledge-sharing materials.
Deliverables (where applicable):
1. Refined Theory of Change and Results Framework.
2. Comprehensive MEL Framework (indicators, data sources, responsibilities, and reporting arrangements).
3. Learning Agenda and Key Learning Questions.
4. Data Collection, Reporting, and Data Quality Assurance Tools.
5. Recommendations for Digital and AI-Enabled MEL Solutions.
6. Partner Contribution Tracking Framework.
7. MEL Dashboard and Reporting Specifications.
8. Periodic Technical Support Reports and Learning Briefs.
9. Final MEL Operationalization and Implementation Guidance Package.
Key competencies:
- Demonstrated expertise in MEL system design and implementation, preferably within CGIAR, international agricultural research, or complex multi-partner programs.
- Strong knowledge of Results-Based Management, Theory of Change development, and results frameworks.
- Proven experience with digital MEL platforms, data visualization/dashboarding tools, and AI-enabled analytics.
- Ability to design adaptive MEL systems suited to innovation-focused and entrepreneurial programs.
- Experience facilitating learning processes and reflection sessions with diverse stakeholders.
- Excellent written communication skills for producing learning products, technical reports, and knowledge-sharing materials.
- Familiarity with food, land, and water systems and/or digital innovation ecosystems is an added advantage.
- Minimum 10 years of relevant experience in MEL roles; advanced degree in a relevant discipline (e.g., development studies, agriculture, data science, evaluation).
All applications must be submitted online by clicking the 'Apply' button below before 11:59 PM CET on 08 July 2026. If you require assistance or face challenges in submitting your application, please email smo-bidding@cgiar.org with the position title in the subject line. Applications submitted through this email will NOT be accepted.
Please ensure your resume and cover letter are in English and does not contain your marital status, age, or photograph. Documents provided in a language other than English will not be considered.
CGIAR is committed to fair, safe, and inclusive workplaces. We believe that diversity powers our innovation, contributes to our excellence, and is critical for our mission. We offer a multi-cultural, multi-color, multi-generational, and multi-disciplinary, collegial working environment. We consciously create an inclusive organization that reflects our global character and commitment to gender equity. We, therefore, encourage applicants from all cultures, races, ethnicities, religions, sexes, national or regional origins, ages, disability status, sexual orientations, and gender identities.
Only shortlisted applicants will be contacted.
We look forward to hearing from you!