Evidence-Based M&E for Sustainable Development Goals (SDGs) Training Course

Introduction

Evidence-Based M&E for Sustainable Development Goals (SDGs) Training Course is designed to strengthen participants’ capacity to generate, interpret, and use data and evidence for tracking progress toward the 2030 Agenda. The SDGs demand rigorous monitoring and evaluation systems that not only measure outcomes but also drive strategic policy decisions for sustainable development. This course equips professionals with the advanced analytical, methodological, and strategic tools needed to achieve that.

The training provides a comprehensive understanding of how evidence-based M&E frameworks can guide planning, implementation, and reporting of SDG-related programs. It focuses on integrating data-driven approaches into decision-making, ensuring that national and institutional priorities align with global targets for inclusive and sustainable growth.

Participants will learn how to design M&E systems that capture the interlinkages between economic, social, and environmental dimensions of development. Through practical case studies and hands-on exercises, they will gain skills in collecting, managing, and interpreting data from multiple sources, including administrative records, surveys, and big data analytics.

The course also emphasizes strengthening institutional capacity to link M&E systems with policy frameworks. It explores how evidence informs resource allocation, policy coherence, and accountability mechanisms at national and subnational levels. Special attention is given to promoting partnerships and cross-sector collaboration for SDG monitoring.

In addressing emerging global trends, the training delves into data innovation, digital monitoring platforms, and the use of AI and geospatial technologies for real-time SDG tracking. Participants will explore how these tools enhance data quality, transparency, and inclusivity in M&E practices.

Ultimately, this course empowers professionals to build robust evidence ecosystems for sustainable development supporting data-informed governance, impactful policy reforms, and measurable progress toward the SDGs.

Who Should Attend:

• Monitoring and Evaluation (M&E) professionals and officers
• SDG focal points and national statistics officers
• Policy planners and government program managers
• Development partners and donor agency representatives
• Data analysts and research specialists
• NGO and civil society program coordinators
• Sustainable development practitioners
• Academics and researchers in development policy
• Project managers in international and national organizations
• Consultants working in governance, M&E, or development effectiveness

Duration

5 Days

Course Objectives:

By the end of the course, participants will be able to:

• Understand the principles and frameworks of evidence-based M&E for the SDGs.
• Strengthen capacity to design and implement SDG-aligned M&E systems.
• Integrate data-driven decision-making into development planning.
• Enhance the use of statistical, administrative, and geospatial data for SDG tracking.
• Build competencies in analyzing and interpreting multidimensional SDG data.
• Improve institutional collaboration for evidence generation and policy alignment.
• Promote transparency and accountability through evidence-informed reporting.
• Address data gaps and quality challenges in SDG measurement.
• Apply innovative technologies for real-time monitoring and evaluation.
• Foster sustainable data ecosystems and long-term evaluation culture for SDGs.

Comprehensive Course Outline

Module 1: Foundations of Evidence-Based M&E for SDGs

• Understanding the SDGs framework and global indicator architecture
• Linking national priorities to SDG targets and indicators
• Principles of evidence-based monitoring and evaluation
• Challenges and opportunities in SDG M&E integration

Module 2: Designing SDG-Aligned M&E Frameworks

• Theory of Change and Results Frameworks for SDGs
• Selecting indicators and setting baselines and targets
• Data mapping and alignment across sectors
• Integrating SDG indicators into national M&E systems

Module 3: Data Collection and Management for SDGs

• Tools and methods for collecting SDG-relevant data
• Administrative data systems and interoperability
• Citizen-generated data and participatory approaches
• Ensuring data quality, consistency, and disaggregation

Module 4: Quantitative and Qualitative Analysis for SDG Evidence

• Advanced statistical tools for analyzing SDG data
• Integrating qualitative insights for inclusive development
• Evaluating multidimensional poverty and sustainability outcomes
• Using mixed methods for evidence synthesis

Module 5: Digital Technologies and Innovation in SDG M&E

• Leveraging AI, big data, and remote sensing for monitoring
• Geospatial and GIS-based approaches for SDG indicators
• Digital dashboards and real-time data visualization
• Ethical considerations in data innovation and governance

Module 6: Linking Evidence to Policy and Planning

• Translating evidence into actionable policy recommendations
• Strengthening policy coherence through M&E results
• Institutional coordination for evidence use
• Case studies on SDG-driven policy reforms

Module 7: Partnerships, Coordination, and Capacity Development

• Multi-stakeholder collaboration for SDG data ecosystems
• Role of development partners in national M&E systems
• Capacity-building strategies for sustainable M&E institutions
• Strengthening national statistical systems for SDG monitoring

Module 8: Communication and Use of SDG Evidence

• Communicating evaluation results to policymakers and the public
• Data storytelling and visualization for advocacy
• Designing SDG progress reports and policy briefs
• Building trust in data and fostering evidence culture

Module 9: Evaluating SDG Programs and Interventions

• Approaches to evaluating complex SDG interventions
• Evaluating interlinkages across SDGs
• Measuring outcomes, impact, and sustainability
• Emerging global practices in SDG evaluation

Module 10: Future Directions in Evidence-Based SDG M&E

• Strengthening resilience of data systems post-2030
• Integrating climate and sustainability metrics
• Innovations in financing for SDG data systems
• Institutionalizing learning and adaptation for future development goals

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808 

Terms of Payment

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.