Public Programme Evaluation Methods and Management Training Course

Course Introduction

Public programme evaluation provides government institutions with systematic methods for determining whether policies, programmes, and projects are relevant, effective, efficient, equitable, sustainable, and capable of producing meaningful public results. Evaluation goes beyond routine monitoring by examining why results occurred, whether interventions contributed to observed changes, what worked or did not work, for whom, under what conditions, and what should be changed in future policy and programme decisions.

This course provides a practical and comprehensive framework for planning, managing, designing, conducting, commissioning, interpreting, and using public programme evaluations. Participants will examine evaluation purposes, evaluation questions, theories of change, evaluation criteria, methodologies, evidence sources, research designs, data-collection techniques, analysis, reporting, quality assurance, and evaluation utilization.

Public programmes operate within complex environments where outcomes may be influenced by economic conditions, institutional capacity, other government interventions, stakeholder behavior, external shocks, and broader social and environmental factors. Participants will therefore learn how to select evaluation methods that are proportionate to the evaluation question and context, including quantitative, qualitative, mixed-methods, experimental, quasi-experimental, contribution-focused, process, outcome, impact, economic, and implementation evaluation approaches.

Effective evaluation management is equally important as methodological design. The programme addresses evaluation planning, commissioning, terms of reference, evaluator selection, budgets, timelines, stakeholder engagement, governance, independence, quality assurance, ethical considerations, data management, deliverables, review processes, and management responses. Participants will learn how to ensure that evaluation findings are credible, relevant, practical, and useful for decisions.

The course also examines the growing use of digital technologies in evaluation. Administrative data, surveys, geospatial information, digital service records, dashboards, big-data analytics, remote sensing, artificial intelligence, and machine learning can expand evaluation capabilities. These technologies introduce additional considerations involving data quality, privacy, cybersecurity, interoperability, algorithmic bias, responsible AI, transparency, and human oversight.

By the end of the programme, participants will be able to define evaluation needs, formulate evaluation questions, select appropriate methodologies, develop evaluation designs, manage evaluation assignments, assess evidence quality, interpret findings, prepare evaluation reports, and establish mechanisms for using evaluation results in policy, budgeting, programme redesign, and institutional learning. The training is designed to strengthen a culture of evidence-based government in which evaluations contribute directly to better public decisions and improved development results.

Duration

5 days

Who Should Attend

• Government monitoring and evaluation directors, managers, and officers responsible for programme evaluation, performance assessment, results management, and evidence systems.

• Policy and planning officers involved in policy analysis, programme design, implementation review, evaluation planning, and strategic decision-making.

• Programme and project managers responsible for commissioning, managing, supporting, or using programme evaluations.

• Department and agency heads seeking stronger evidence on programme effectiveness, efficiency, outcomes, sustainability, and public value.

• Evaluation specialists and analysts responsible for evaluation design, methodology, data analysis, findings, reporting, and quality assurance.

• Research officers and policy researchers conducting or managing quantitative, qualitative, or mixed-methods assessments.

• Finance and budget officers interested in assessing public expenditure, value for money, cost effectiveness, and the results of government interventions.

• Development-planning professionals responsible for national, sectoral, institutional, programme, and project results assessment.

• Performance-management officers responsible for indicators, results frameworks, performance reviews, and evidence-based improvement.

• Internal auditors and assurance professionals seeking to understand evaluation approaches and distinguish evaluation from audit and compliance reviews.

• Risk-management professionals assessing programme assumptions, implementation risks, external factors, and sustainability.

• Procurement and contract-management professionals involved in commissioning and administering evaluation services.

• Data and information-management professionals supporting evaluation datasets, administrative data, information systems, data quality, and evidence governance.

• Information-technology and digital-transformation professionals supporting digital evaluation platforms, analytics, dashboards, GIS, and integrated data systems.

• Development partners and programme-support professionals working with public institutions on evaluation, results management, policy learning, and development effectiveness.

• Senior public-sector leaders seeking stronger evidence for policy decisions, programme redesign, resource allocation, accountability, and institutional learning.

Course Objectives

• Develop participants’ advanced understanding of public programme evaluation concepts, purposes, principles, methodologies, management processes, and evidence requirements.

• Strengthen participants’ ability to distinguish evaluation from monitoring, audit, inspection, research, performance review, and routine reporting.

• Equip participants with practical methods for defining evaluation purposes, stakeholders, evaluation questions, criteria, scope, and intended use.

• Develop participants’ competence in selecting appropriate quantitative, qualitative, mixed-methods, experimental, quasi-experimental, process, outcome, impact, and economic evaluation approaches.

• Improve participants’ ability to construct theories of change, results chains, causal pathways, evaluation frameworks, and evaluation matrices.

• Strengthen participants’ ability to plan and manage evaluation assignments, including terms of reference, procurement, evaluator selection, budgets, schedules, deliverables, governance, and quality assurance.

• Enable participants to assess evidence quality, data limitations, causal claims, contribution, implementation fidelity, contextual influences, unintended effects, and uncertainty.

• Build participants’ capacity to use administrative data, surveys, qualitative evidence, geospatial information, digital records, analytics, and emerging technologies responsibly.

• Improve participants’ ability to interpret evaluation findings, communicate conclusions, develop recommendations, and support management responses and implementation.

• Prepare participants to institutionalize evaluation systems that strengthen policy learning, programme improvement, budgeting, resource allocation, accountability, and evidence-based government.

Comprehensive Course Outline

Module 1: Foundations of Public Programme Evaluation

• Understanding programme evaluation, policy evaluation, project evaluation, implementation assessment, outcome evaluation, impact evaluation, economic evaluation, and learning-oriented evaluation.

• Distinguishing evaluation from monitoring, performance management, audit, inspection, research, supervision, and programme review.

• Examining evaluation purposes including accountability, learning, improvement, decision support, resource allocation, effectiveness assessment, and public value.

• Emerging evaluation challenges involving complex interventions, long-term outcomes, multi-agency programmes, changing contexts, limited evidence, and increased demand for credible results.

Module 2: Evaluation Planning, Governance and Management

• Developing evaluation plans covering purpose, scope, questions, criteria, methodology, stakeholders, resources, timelines, deliverables, reporting, and intended use.

• Establishing evaluation governance structures, steering committees, technical teams, management responsibilities, evaluator independence, stakeholder roles, and decision-making arrangements.

• Developing terms of reference, evaluation specifications, budgets, procurement approaches, work plans, milestones, deliverables, and quality-assurance requirements.

• Emerging management approaches involving adaptive evaluation, rapid evaluation, utilization-focused evaluation, portfolio evaluation, digital evaluation management, and continuous learning systems.

Module 3: Evaluation Questions, Criteria and Evaluation Matrices

• Formulating clear evaluation questions that address relevance, coherence, effectiveness, efficiency, impact, sustainability, equity, implementation, and value for money.

• Selecting evaluation criteria and defining standards against which programme performance and results will be assessed.

• Developing evaluation matrices linking questions, indicators, evidence sources, data-collection methods, analysis approaches, and conclusions.

• Emerging approaches involving complexity-aware evaluation, systems evaluation, strategic evaluation questions, AI-assisted question development, and dynamic evaluation frameworks.

Module 4: Theory of Change and Evaluation Design

• Developing and testing theories of change that explain how programme interventions are expected to contribute to outputs, outcomes, impacts, and broader development results.

• Identifying causal pathways, assumptions, dependencies, contextual factors, implementation conditions, and unintended consequences.

• Linking theories of change with evaluation questions, hypotheses, indicators, data sources, and analytical strategies.

• Emerging approaches involving systems mapping, complexity theory, contribution analysis, causal modelling, scenario analysis, and AI-supported theory-of-change development.

Module 5: Quantitative Evaluation Methods

• Understanding quantitative evaluation designs, variables, measurement, sampling, comparison groups, baseline and endline data, and statistical analysis.

• Applying experimental and quasi-experimental approaches such as randomized designs, difference-in-differences, regression-based approaches, matching, interrupted time series, and other appropriate methods.

• Interpreting statistical results, uncertainty, effect sizes, limitations, and the implications of quantitative findings for policy and programme decisions.

• Emerging methods involving machine learning, causal inference, large administrative datasets, predictive modelling, synthetic data, and advanced computational evaluation.

Module 6: Qualitative and Mixed-Methods Evaluation

• Applying interviews, focus groups, observations, document analysis, case studies, process tracing, outcome harvesting, and other qualitative methods.

• Using qualitative evidence to understand implementation processes, stakeholder experiences, mechanisms, context, institutional behavior, and unexpected outcomes.

• Designing mixed-methods evaluations that integrate quantitative evidence with qualitative explanation and contextual understanding.

• Emerging approaches involving digital interviews, online qualitative methods, natural-language processing, AI-assisted coding, social listening, and large-scale qualitative evidence analysis.

Module 7: Data Collection, Evidence Quality and Analysis

• Designing evaluation data-collection plans covering administrative data, surveys, interviews, observations, programme records, financial information, service-delivery information, and secondary evidence.

• Applying sampling, data validation, triangulation, quality assurance, data cleaning, documentation, metadata, and evidence-management techniques.

• Assessing data limitations, measurement error, missing information, selection bias, response bias, inconsistent records, and other threats to evaluation credibility.

• Emerging evidence systems involving mobile data collection, geospatial data, remote sensing, digital administrative records, automated data integration, and AI-assisted evidence analysis.

Module 8: Economic Evaluation, Efficiency and Value for Money

• Assessing programme costs, resource use, efficiency, cost effectiveness, cost-benefit relationships, productivity, and value for money.

• Connecting programme expenditure and resource inputs with outputs, outcomes, benefits, and public value.

• Applying appropriate economic-analysis approaches while recognizing assumptions, uncertainty, distributional effects, non-market benefits, and limitations.

• Emerging approaches involving predictive cost modelling, real-time expenditure analytics, integrated financial-performance systems, AI-supported resource analysis, and dynamic value-for-money assessment.

Module 9: Evaluation Reporting, Recommendations and Utilization

• Preparing evaluation reports covering methodology, evidence, findings, limitations, conclusions, recommendations, management responses, and implementation considerations.

• Communicating complex evaluation findings clearly to executives, policymakers, programme managers, technical specialists, oversight institutions, partners, and the public.

• Developing practical recommendations that are evidence-based, prioritized, feasible, assigned to responsible owners, and linked to implementation timelines.

• Establishing evaluation-use mechanisms including management responses, action plans, policy reviews, programme redesign, budget decisions, dissemination, learning events, and follow-up assessments.

Module 10: Institutionalizing Evaluation and Future Evaluation Systems

• Developing government evaluation policies, evaluation calendars, evaluation portfolios, standards, quality-assurance arrangements, evaluator databases, governance structures, and institutional capabilities.

• Establishing systems for tracking evaluation recommendations, measuring evaluation utilization, sharing lessons, protecting evaluation independence, and strengthening organizational learning.

• Integrating evaluation findings into strategic planning, budgeting, policy formulation, programme design, resource allocation, risk management, and performance management.

• Future trends involving AI-enabled evaluation, real-time evaluation, predictive impact assessment, digital evaluation platforms, integrated government data ecosystems, complexity-aware evaluation, citizen-centered evidence, and adaptive public-sector learning.

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 a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, 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.