2024 Learning and Optimization Report
This report is CGIAR’s primary learning report for the 2024 Technical Reporting cycle. It consolidates and synthesizes insights from a range of reflection and learning activities to highlight cross-cutting lessons. The 2024 Learning and Optimization (L&O) process was undertaken as part of CGIAR’s ad...
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| Format: | Informe técnico |
| Language: | Inglés |
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CGIAR System Organization
2025
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| Online Access: | https://hdl.handle.net/10568/176799 |
| _version_ | 1855541343474941952 |
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| author | CGIAR System Organization |
| author_browse | CGIAR System Organization |
| author_facet | CGIAR System Organization |
| author_sort | CGIAR System Organization |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This report is CGIAR’s primary learning report for the 2024 Technical Reporting cycle. It consolidates and synthesizes insights from a range of reflection and learning activities to highlight cross-cutting lessons.
The 2024 Learning and Optimization (L&O) process was undertaken as part of CGIAR’s adaptive management methodology for Technical Reporting. Its primary objective is to identify lessons from the 2022-2024 Technical Reporting cycle and generate actionable recommendations to inform the design and delivery of the 2025-2030 Portfolio’s reporting systems, capacity-building efforts, and key products.
The review identified priority recommendations across five L&O pillars to deliver on these priorities:
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Conceptual aspects – Finalize revisions to the Results Framework to ensure coherent, measurable outcomes and impacts aligned with CGIAR’s 2030 targets.
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Processes – Adjust timelines for greater flexibility, improve interoperability between the Performance and Results Management System (PRMS) and Program tools, clarify roles and responsibilities (especially with the integration of Window 3 [W3]/bilateral projects), and integrate quality assurance (QA) earlier in the cycle to strengthen transparency and reliability.
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Systems – Advance PRMS v2 as a cohesive, user-centered platform, scale up artificial intelligence (AI) and automation to reduce reporting effort and enhance QA processes.
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Capacity – Expand training and peer-learning opportunities, strengthen organizational support and engagement with Centers, and build skills for PRMS v2, AI tools, and adaptive management.
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Products/Outputs – Improve report usability and readability, enhance trend analysis and Portfolio comparisons, integrate return on investment (ROI) analyses and impact/results stories, and pilot AI-generated report drafts and summaries to reduce effort and better tailor outputs to decision-makers.
Together, these actions aim to reduce the reporting burden, integrate W3/bilateral results into a coherent evidence base, and reinforce accountability through transparent, verifiable links between planned targets and delivered outcomes. |
| format | Informe técnico |
| id | CGSpace176799 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | CGIAR System Organization |
| publisherStr | CGIAR System Organization |
| record_format | dspace |
| spelling | CGSpace1767992025-10-04T01:09:27Z 2024 Learning and Optimization Report CGIAR System Organization learning CGIAR research This report is CGIAR’s primary learning report for the 2024 Technical Reporting cycle. It consolidates and synthesizes insights from a range of reflection and learning activities to highlight cross-cutting lessons. The 2024 Learning and Optimization (L&O) process was undertaken as part of CGIAR’s adaptive management methodology for Technical Reporting. Its primary objective is to identify lessons from the 2022-2024 Technical Reporting cycle and generate actionable recommendations to inform the design and delivery of the 2025-2030 Portfolio’s reporting systems, capacity-building efforts, and key products. The review identified priority recommendations across five L&O pillars to deliver on these priorities: • Conceptual aspects – Finalize revisions to the Results Framework to ensure coherent, measurable outcomes and impacts aligned with CGIAR’s 2030 targets. • Processes – Adjust timelines for greater flexibility, improve interoperability between the Performance and Results Management System (PRMS) and Program tools, clarify roles and responsibilities (especially with the integration of Window 3 [W3]/bilateral projects), and integrate quality assurance (QA) earlier in the cycle to strengthen transparency and reliability. • Systems – Advance PRMS v2 as a cohesive, user-centered platform, scale up artificial intelligence (AI) and automation to reduce reporting effort and enhance QA processes. • Capacity – Expand training and peer-learning opportunities, strengthen organizational support and engagement with Centers, and build skills for PRMS v2, AI tools, and adaptive management. • Products/Outputs – Improve report usability and readability, enhance trend analysis and Portfolio comparisons, integrate return on investment (ROI) analyses and impact/results stories, and pilot AI-generated report drafts and summaries to reduce effort and better tailor outputs to decision-makers. Together, these actions aim to reduce the reporting burden, integrate W3/bilateral results into a coherent evidence base, and reinforce accountability through transparent, verifiable links between planned targets and delivered outcomes. 2025-09-30 2025-10-03T07:02:16Z 2025-10-03T07:02:16Z Report https://hdl.handle.net/10568/176799 en https://hdl.handle.net/10568/148883 https://hdl.handle.net/10568/131369 Open Access application/pdf CGIAR System Organization CGIAR System Organization. 2025. 2024 Learning and Optimization Report. Montpellier, France: CGIAR System Organization. |
| spellingShingle | learning CGIAR research CGIAR System Organization 2024 Learning and Optimization Report |
| title | 2024 Learning and Optimization Report |
| title_full | 2024 Learning and Optimization Report |
| title_fullStr | 2024 Learning and Optimization Report |
| title_full_unstemmed | 2024 Learning and Optimization Report |
| title_short | 2024 Learning and Optimization Report |
| title_sort | 2024 learning and optimization report |
| topic | learning CGIAR research |
| url | https://hdl.handle.net/10568/176799 |
| work_keys_str_mv | AT cgiarsystemorganization 2024learningandoptimizationreport |