Evidence-Informed Decision Making in M&E Training Course

Evidence-Informed Decision Making in M&E Training Course

Introduction

Evidence-informed decision-making (EIDM) in Monitoring and Evaluation (M&E) is a critical competency for professionals striving to enhance program effectiveness, accountability, and impact. Evidence-Informed Decision Making in M&E Training Course equips participants with advanced skills to systematically collect, analyze, interpret, and apply high-quality evidence to guide strategic decisions. Emphasizing data integrity, evidence synthesis, and rigorous evaluation frameworks, the training ensures that M&E practitioners can transform raw data into actionable insights, optimize resource allocation, and strengthen organizational learning. Key themes include data-driven planning, real-time monitoring, evaluation ethics, and predictive analytics for proactive interventions.

In an era of complex programmatic landscapes and increasing donor expectations, EIDM is central to achieving measurable results and sustainable outcomes. Participants will gain practical expertise in integrating quantitative and qualitative evidence, designing evidence-based policies, and using innovative tools to support decision-making processes. Through interactive case studies, simulations, and scenario-based exercises, this course fosters critical thinking, problem-solving, and evidence application in real-world contexts. By the end of the training, participants will be prepared to enhance program effectiveness, demonstrate accountability, and drive impact through informed decisions.

Course Duration

10 days

Course Objectives

1. Develop proficiency in evidence-informed decision-making frameworks.
2. Apply data synthesis techniques for actionable M&E insights.
3. Enhance skills in quantitative and qualitative data integration.
4. Strengthen capacity for real-time monitoring and adaptive management.
5. Implement predictive analytics for evidence-based forecasting.
6. Interpret evaluation results to guide strategic program decisions.
7. Utilize data visualization and reporting for stakeholder engagement.
8. Apply ethical considerations in evidence collection and usage.
9. Build institutional capacity for evidence-driven decision-making.
10. Identify trends, patterns, and anomalies for informed interventions.
11. Develop policy briefs and evidence summaries for decision-makers.
12. Integrate technology and digital tools for evidence management.
13. Promote a culture of learning and accountability within M&E systems.

Target Audience

1. M&E Officers and Specialists
2. Program Managers and Coordinators
3. Data Analysts and Research Officers
4. Policy Makers and Decision-Makers
5. Donor and Funding Agency Representatives
6. NGO and Development Practitioners
7. Health and Education Program Evaluators
8. Government and Public Sector Monitoring Staff

Course Modules

Module 1: Introduction to Evidence-Informed Decision Making

• Definition and principles of EIDM
• Importance in M&E practice
• Global and local case studies
• Evidence vs. intuition in decision-making
• Case study: Interactive exercises on evidence use

Module 2: Evidence Sources and Data Types

• Quantitative and qualitative evidence
• Administrative data and surveys
• Secondary data review and meta-analysis
• Case study: Use of national health data for program planning
• Data sourcing and quality check

Module 3: Evidence Synthesis and Integration

• Data triangulation techniques
• Combining multiple evidence sources
• Systematic review methods
• Case study: Integrating household and service delivery data
• Practical exercise on evidence synthesis

Module 4: Designing Evidence-Based Policies

• Policy design principles
• Linking evidence to program goals
• Cost-effectiveness and feasibility analysis
• Case study: Evidence-led nutrition program policy
• Drafting a policy brief

Module 5: Data Analysis for Decision Making

• Descriptive and inferential statistics
• Trend analysis and forecasting
• Identifying patterns and outliers
• Case study: Predictive modeling in education programs
• Interpreting analysis for decisions

Module 6: Real-Time Monitoring and Adaptive Management

• Continuous data collection and feedback loops
• Adaptive program design
• Case study: COVID-19 response monitoring system
• Decision-making under uncertainty
• Tools for real-time monitoring

Module 7: Evidence Visualization and Communication

• Dashboards and visual storytelling
• Infographics for decision-makers
• Case study: Data visualization improving policy uptake
• Creating visual summaries
• Tips for clear reporting

Module 8: Evaluation Design and Evidence Use

• Formative and summative evaluations
• Linking evaluation to strategic decisions
• Case study: Evaluation-driven program scaling
• Designing evaluation questions
• Ethical and practical considerations

Module 9: Ethical Considerations in Evidence Use

• Data protection and privacy
• Avoiding bias and misinterpretation
• Stakeholder consent and participation
• Case study: Ethical dilemmas in health M&E
• Ethical decision-making

Module 10: Technology Tools for Evidence Management

• Data management systems
• Digital dashboards and analytics tools
• Case study: DHIS2 for decision-making
• Tool selection and usage
• Future tech trends in M&E

Module 11: Predictive Analytics and Forecasting

• Basics of predictive modeling
• Risk assessment and scenario planning
• Case study: Forecasting malaria outbreaks
• Building simple predictive models
• Integrating forecasts into decision-making

Module 12: Institutionalizing Evidence-Based Practices

• Capacity building and training programs
• Organizational learning and culture
• Case study: Evidence-driven NGO transformation
• Developing capacity plans
• Policy integration for sustainability

Module 13: Data Quality Assurance and Validation

• Data accuracy, completeness, and timeliness
• QA frameworks and audits
• Case study: Improving reporting systems in health
• Conducting a data quality audit
• Techniques for continuous improvement

Module 14: Stakeholder Engagement and Evidence Uptake

• Identifying key stakeholders
• Evidence translation for decision-makers
• Case study: Multi-sectoral collaboration using data
• Engaging decision-makers
• Feedback mechanisms for uptake

Module 15: Advanced Case Studies in Evidence-Informed Decision Making

• Real-world M&E challenges and solutions
• Case Study: Sector-specific applications
• Lessons learned from global and local programs
• Applying full course learnings
• Group presentations and peer review

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.