Network Analysis for Evaluation Training Course

Network Analysis for Evaluation Training Course

Introduction

In today’s data-driven evaluation landscape, understanding relationships, influence, and connectivity within social, organizational, and project networks is critical for achieving impactful results. Network Analysis for Evaluation Training Course equips professionals with advanced techniques to map, measure, and analyze complex networks using cutting-edge tools and methodologies. Participants will gain actionable insights into stakeholder dynamics, knowledge flows, and collaboration patterns, enabling evidence-based decision-making and strategic interventions. This course integrates practical applications, real-world case studies, and interactive exercises to ensure participants can translate network insights into tangible program improvements.

Through this training, evaluators, program managers, and analysts will master key concepts such as social network analysis (SNA), network metrics, visualization techniques, and predictive modeling for evaluation outcomes. Leveraging modern software platforms and data sources, participants will learn how to identify central actors, detect structural gaps, and optimize influence pathways within programs. By the end of the course, learners will be able to design, implement, and report network evaluations that drive organizational learning, enhance program efficiency, and maximize social impact. This course is ideal for professionals seeking to elevate their evaluation practice with sophisticated analytical approaches that reveal hidden patterns and strengthen evidence-based strategies.

Course Duration

10 days

Course Objectives

1. Understand foundational concepts and principles of Network Analysis in evaluation.
2. Identify key network actors and relationships using social network mapping.
3. Apply network metrics to measure connectivity, centrality, and influence.
4. Visualize complex networks using advanced graph visualization tools.
5. Analyze communication and knowledge flow patterns for program efficiency.
6. Detect structural gaps and bottlenecks in organizational networks.
7. Apply predictive network modeling to anticipate program outcomes.
8. Integrate network insights into impact evaluation frameworks.
9. Enhance stakeholder engagement through network-informed strategies.
10. Interpret network data to inform evidence-based decision-making.
11. Conduct comparative network analysis across programs and regions.
12. Develop actionable reports with interactive network dashboards.
13. Use real-world case studies and simulations to strengthen practical skills.

Target Audience

1. Monitoring and Evaluation (M&E) professionals
2. Program managers and coordinators
3. Data analysts and research specialists
4. Social scientists and policy researchers
5. Organizational development practitioners
6. Impact assessment consultants
7. NGO and non-profit program evaluators
8. Academics and graduate students in evaluation or social network studies

Course Modules

Module 1: Introduction to Network Analysis

• Core concepts of nodes, edges, and network structures
• Types of networks: social, organizational, and project networks
• Role of network analysis in evaluation
• Case Study: Evaluating NGO collaboration networks
• Mapping a small organizational network

Module 2: Data Collection for Networks

• Identifying relevant actors and relationships
• Survey and observational techniques for network data
• Ethical considerations and privacy in network data
• Case Study: Collecting network data in a community health program
• Designing a network survey

Module 3: Network Metrics and Analysis

• Degree, betweenness, closeness, and eigenvector centrality
• Network density and clustering measures
• Identifying key influencers and connectors
• Case Study: Mapping leadership influence in corporate networks
• Calculating centrality metrics

Module 4: Network Visualization Techniques

• Tools for network visualization 
• Layout algorithms and aesthetic mapping
• Interpreting network diagrams effectively
• Case Study: Visualizing inter-agency collaboration networks
• Creating visual network maps

Module 5: Social Network Analysis (SNA) in Programs

• Role of SNA in monitoring and evaluation
• Measuring collaboration, communication, and knowledge flows
• Network intervention strategies
• Case Study: SNA in education program networks
• Analyzing real-world SNA data

Module 6: Advanced Network Modeling

• Predictive and statistical network models
• Simulating network changes and outcomes
• Using models for program planning
• Case Study: Modeling diffusion of innovation in health programs
• Building a predictive network model

Module 7: Identifying Gaps and Bottlenecks

• Detecting structural holes in networks
• Analyzing weak links and isolated nodes
• Strategies to strengthen network resilience
• Case Study: Organizational network gap analysis
• Gap identification exercise

Module 8: Network Dynamics Over Time

• Longitudinal network analysis
• Tracking network evolution and trends
• Measuring impact of interventions on network change
• Case Study: Evolution of a donor coordination network
• Visualizing temporal network changes

Module 9: Stakeholder Mapping and Analysis

• Identifying critical stakeholders and their influence
• Using networks for stakeholder engagement
• Case Study: Stakeholder network in a public health program
• Practical: Developing a stakeholder network map
• Prioritizing stakeholder engagement

Module 10: Collaboration and Knowledge Flow Analysis

• Measuring knowledge diffusion in networks
• Identifying bottlenecks in communication
• Promoting effective collaboration strategies
• Case Study: Knowledge network in academic institutions
• Analyzing communication flows

Module 11: Network-Driven Program Improvement

• Integrating network insights into program design
• Enhancing performance through network interventions
• Evaluating program outcomes with network metrics
• Case Study: Using networks to improve youth empowerment programs
• Designing a network-informed intervention

Module 12: Reporting and Dashboards

• Network visualization in reports and dashboards
• Storytelling with network data
• Best practices for communicating complex networks
• Case Study: Interactive network dashboards for NGOs
• Building a sample dashboard

Module 13: Comparative Network Evaluation

• Comparing networks across regions or programs
• Identifying common patterns and unique structures
• Benchmarking network performance
• Case Study: Comparative evaluation of health sector networks
• Cross-network comparison exercise

Module 14: Tools and Software for Network Analysis

• Introduction to Gephi, NodeXL, UCINET, Pajek
• Importing and cleaning network data
• Automation and reporting with network software
• Case Study: Software-assisted evaluation of program networks
• Hands-on tool training

Module 15: Capstone Project and Simulation

• Designing a full network evaluation
• Implementing analysis and visualization
• Presenting actionable recommendations
• Case Study: End-to-end evaluation of NGO collaboration
• Group simulation and report presentation

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.