24 - 28 Feb 2025
London (UK)
Hotel : Landmark Office Space - Oxford Street
Cost : 5250 € Euro
Monitoring and Evaluation are increasingly identified as the cornerstone for efficacious program management and are essential for organizational sustainability. A continuously increasing need for suitably skilled monitoring and evaluation project managers has been identified as a priority area by various stakeholders active in different sectors and industries, as an example; globally-funded sponsorships often require evidence of effective monitoring and evaluation systems before awarding funds.
The Advanced Monitoring and Evaluation training course aims to provide managers and M&E officers across different sectors with advanced skills and knowledge to successfully design and implement monitoring and evaluation systems from program/project initiation to close-out.
This program is structured in such a way that it guides learners to apply monitoring and evaluation principles within the context of their unique work environment.
After completion of this qualification, participants will be able to:
Master key principles of monitoring and evaluation relevant to implementing projects and programs
Apply results-based management principles
Explain and apply the value of a Theory of Change and Logical Framework in monitoring and evaluation
Learn how to undertake a stakeholder mapping and analysis for monitoring and evaluation purposes
Design monitoring frameworks
Manage data quality
Conduct routine data quality assessments
Identify indicators for projects and programs
Demonstrate the ability to use and report on monitoring data
Plan and conduct an evaluation
Study practical considerations in selecting appropriate evaluation designs and methods for data collection
Construct an organizational learning agenda and identify evaluation priorities and questions
Apply evaluation ethics
Acquire skills in developing practical sampling and data analysis strategies
Plan for resources needed for an evaluation
Develop a Terms of Reference for evaluations
Learn key steps in ensuring effective communication and utilization of evaluation findings
Any individual that is presently operating in a monitoring and evaluation role who has identified a need to further develop their monitoring and evaluation knowledge and skills, in addition to their current vocational focus, e.g. a manager whose performance agreement demands the effective design and management of monitoring and evaluation system for a program or organization.
Day 1
Introduction to monitoring and evaluation principles and concepts
Programme Logic Models and Theory of Change
Analysing and reporting monitoring data for decision making
M&E in the context of the 2030 National Plan
Results-Based Management – history, meaning, context.
Day 2
Problem analysis tools and techniques
The theory of change
Developing a results chain
Linking and testing the relationship between the theory of change and the results chain
Linking the log frame and budget
The meaning and types of result
Defining results and indicators
Day 3
Structure and types of indicators
Design an M&E framework
Monitoring the M&E framework
Communicating the M&E framework
Understanding the roles of key practitioners in the maintenance of the framework
Facilitate team performance improvements using assessment findings;
Establish performance standards and monitoring systems – linking individual and organizational processes
Day 4
Understand methods and tools for basic data collection;
Understand methods and tools for basic data analysis;
Understand the key uses of monitoring data: project management, evaluation, and reporting;
Understand the difference between process and outcome evaluation practices; and
Develop project evaluation reports.
The outcomes-based approach and strategic planning
Problem analysis -understanding the context, assumptions, and challenges
Day 5
Designing evaluations
Planning and managing evaluations
Disseminating and using evaluation results
Designing monitoring systems for programs
Implementing program monitoring systems
Managing data quality