Data Triangulation in Monitoring & Evaluation Training Course

Data Triangulation in Monitoring & Evaluation Training Course

Introduction

In today’s dynamic development landscape, robust Monitoring and Evaluation (M&E) systems are critical for evidence-based decision-making and program success. Data Triangulation ensures that organizations obtain reliable, valid, and actionable insights by integrating multiple data sources, methods, and perspectives. Data Triangulation in Monitoring & Evaluation Training Course equips participants with advanced skills to analyze, cross-verify, and interpret data, enhancing program transparency, accountability, and impact. Participants will gain hands-on expertise in quantitative and qualitative triangulation techniques, bias mitigation, and trend analysis, ensuring high-quality M&E outputs.

This course emphasizes practical application through real-world case studies, interactive exercises, and scenario-based learning. By mastering data triangulation, M&E professionals will improve decision-making, risk management, and program effectiveness. The training also explores emerging digital tools for data integration, visualization techniques, and automated cross-checking, providing participants with a cutting-edge approach to evidence-based program evaluation.

Course Duration

10 days

Course Objectives

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

1. Understand the concepts and principles of data triangulation in M&E.
2. Apply quantitative, qualitative, and mixed-method triangulation techniques.
3. Evaluate data reliability, validity, and credibility.
4. Detect and mitigate data bias and inconsistencies.
5. Integrate multiple data sources for enhanced program insights.
6. Use triangulation for risk assessment and program improvement.
7. Apply digital tools and software for data triangulation.
8. Develop cross-verification strategies for accurate reporting.
9. Enhance data-driven decision-making.
10. Conduct comparative analysis of program outcomes.
11. Utilize visualization techniques for triangulated data.
12. Present evidence-based recommendations to stakeholders.
13. Analyze real-world case studies to strengthen triangulation skills.

Target Audience

• M&E Officers and Managers
• Program Managers and Coordinators
• Data Analysts and Statisticians
• Research Officers and Field Surveyors
• Development Consultants
• Non-Governmental Organizations (NGO) Staff
• Government Monitoring and Evaluation Units
• Academic Researchers

Course Modules

Module 1: Introduction to Data Triangulation

• Definition and types of data triangulation
• Importance in Monitoring and Evaluation
• Principles of reliability, validity, and credibility
• Key challenges in triangulation
• Case study: Triangulation in health program evaluation

Module 2: Quantitative Triangulation Techniques

• Surveys and structured data collection
• Statistical cross-checking methods
• Trend analysis and correlation studies
• Data cleaning for consistency
• Case study: Education program attendance data verification

Module 3: Qualitative Triangulation Techniques

• Focus groups and interviews
• Observation and ethnographic methods
• Thematic analysis and coding
• Validating qualitative findings
• Case study: Community development project assessment

Module 4: Mixed-Method Triangulation

• Integrating qualitative and quantitative data
• Methodological frameworks
• Analyzing mixed-method results
• Avoiding methodological bias
• Case study: Nutrition program outcome triangulation

Module 5: Data Sources and Cross-Verification

• Identifying multiple data sources
• Secondary data integration
• Ensuring data consistency
• Techniques for cross-validation
• Case study: Public health data integration

Module 6: Bias Detection and Mitigation

• Common data biases in M&E
• Techniques for bias detection
• Corrective measures in data analysis
• Ethical considerations in data triangulation
• Case study: Bias correction in survey reporting

Module 7: Data Triangulation Tools & Software

• Excel and advanced spreadsheets
• Statistical software: SPSS, R, and STATA
• Digital dashboards for visualization
• Automated triangulation workflows
• Case study: NGO program data automation

Module 8: Risk Assessment Using Triangulated Data

• Risk identification methods
• Data-informed risk evaluation
• Scenario planning with triangulated data
• Risk communication to stakeholders
• Case study: Early warning systems in agriculture

Module 9: Data Visualization for Triangulation

• Visual storytelling techniques
• Charts, graphs, and dashboards
• Comparative visualization methods
• Interactive data presentation
• Case study: Triangulated M&E dashboard creation

Module 10: Reporting & Evidence-Based Recommendations

• Structuring triangulated data reports
• Presenting actionable insights
• Stakeholder communication strategies
• Ensuring transparency and accountability
• Case study: Evidence-based NGO report

Module 11: Advanced Analysis Techniques

• Multivariate analysis for triangulated data
• Regression and correlation techniques
• Predictive modeling for program outcomes
• Data pattern recognition
• Case study: Program impact prediction using triangulation

Module 12: Ethics & Data Integrity in Triangulation

• Data protection and confidentiality
• Ethical frameworks for triangulation
• Handling sensitive information
• Maintaining data credibility
• Case study: Ethical considerations in health surveys

Module 13: Quality Assurance in Data Triangulation

• QA frameworks and checklists
• Standard Operating Procedures (SOPs)
• Continuous improvement techniques
• Audit trails for data verification
• Case study: QA in government M&E programs

Module 14: Real-World Applications of Triangulation

• International development programs
• Public sector M&E projects
• NGO and private sector applications
• Case-based problem solving
• Case study: Triangulation in water sanitation projects

Module 15: Capstone Project & Practical Exercises

• Design a triangulated M&E plan
• Field data collection simulation
• Cross-verification exercises
• Presentation of findings to peers
• Case study: Comprehensive M&E project simulation

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.