Monitoring and Evaluation for Donor-Funded Projects Training Course

Duration 10 days 20 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Project Managers, Monitoring and Evaluation Officers and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-ME-082

Before you join: Participants should have experience working on development, humanitarian, public-sector or social-impact projects and be familiar with basic project documents such as proposals, workplans, budgets or progress reports.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Donor-funded projects are judged not only by activities delivered but by credible evidence of results, responsible use of funds and timely management decisions. Project teams must translate proposal commitments into measurable indicators, workable monitoring systems, data-quality controls and evaluation plans that satisfy donor requirements without creating unnecessary reporting burdens. Weak baselines, vague indicators, unreliable partner data and late reporting can undermine funding relationships and obscure whether intended change is occurring.

This course develops the practical monitoring and evaluation skills needed to design, manage and improve donor-funded development and humanitarian projects. Participants work through results chains, logframes, theories of change, SMART indicators, baseline studies, monitoring plans, sampling, data collection, data-quality assessment, evaluation design and donor reporting. The course addresses common requirements associated with bilateral donors, multilateral agencies, foundations and humanitarian funding, while showing how to adapt M&E arrangements to project scale, risk, operating context and implementing-partner capacity.

Teaching combines focused instructor briefings with case work drawn from health, education, livelihoods, protection, governance and emergency-response programmes. Participants analyse project documentation, develop M&E components, assess sample datasets, review indicator performance and make evidence-based management recommendations. Each participant leaves with a practical M&E package: a results framework, indicator reference sheet, monitoring plan, data-quality checklist and evaluation outline that can be adapted to an active or planned donor-funded project.

The course suits programme staff, project managers, M&E personnel, grants teams, partner organisations and technical advisers who already work with project plans, donor proposals or results reports. It is particularly useful for staff moving from activity management into accountability for results measurement and learning.

What you will be able to do

  • Develop a donor-aligned theory of change, results chain and logical framework
  • Define SMART indicators with indicator reference sheets and disaggregation requirements
  • Prepare a costed monitoring and evaluation plan linked to reporting deadlines
  • Design baseline, monitoring and endline data-collection approaches using appropriate sampling
  • Apply data-quality assessment procedures to verify accuracy, reliability, timeliness and integrity
  • Interpret quantitative and qualitative findings for adaptive project management decisions
  • Develop an evaluation terms of reference using OECD DAC evaluation criteria
  • Present a complete donor-funded project M&E package for technical review

Benefits of attending

For you

  • Produce credible M&E sections for donor proposals and project inception documents
  • Diagnose weak indicators before they create reporting and accountability problems
  • Manage partner monitoring data with clearer quality checks and follow-up actions
  • Contribute confidently to baseline, midterm and final evaluation processes
  • Use evidence to justify project adaptations in donor and management meetings

For your organisation

  • Improves consistency between proposal commitments, implementation plans and donor reports
  • Reduces unsupported results claims through defined indicator and data-quality controls
  • Strengthens implementing-partner accountability for monitoring data and reporting deadlines
  • Provides earlier evidence for corrective action when delivery or outcomes fall behind
  • Produces clearer evaluation scopes and more useful learning for future funding bids

Course modules

20 modules over 10 days

Participants can explain how monitoring, evaluation, accountability and learning support donor-funded project decisions.

  • Monitoring, evaluation, accountability and learning distinguished through practical project decisions
  • Donor funding cycle mapped from concept note to final report
  • Results-based management principles linked to planning, implementation and reporting
  • Accountability relationships between donors, recipients, partners and affected communities
  • Common M&E failures identified from donor-funded project case evidence
  • Evidence needs aligned with management, compliance, learning and communication purposes

Participants can interpret donor requirements and translate them into an M&E architecture.

  • Proposal commitments traced into implementation plans, indicators and reporting schedules
  • Bilateral, multilateral and foundation reporting expectations compared systematically
  • Compliance matrix built from grant agreement clauses and deliverables
  • Results architecture connects strategic objectives, outcomes, outputs and activities
  • Assumptions and risks recorded alongside expected project results
  • Reporting calendars reconcile donor deadlines with internal review cycles

Participants can construct and test a theory of change for a donor-funded intervention.

  • Problem tree analysis separates causes, effects and stakeholder concerns
  • Theory of change maps pathways from interventions to intended change
  • Preconditions identify what must occur before outcomes become plausible
  • Causal assumptions tested against evidence, context and implementation capacity
  • External influences distinguished from project-controlled intervention elements
  • Outcome pathways refined using stakeholder perspectives and available evidence

Participants can develop a logical framework with coherent results, assumptions and measurement logic.

  • Logframe vertical logic links goal, outcome, output and activity levels
  • Narrative statements written as measurable changes rather than planned actions
  • Means of verification matched to each result statement
  • Assumptions assessed for likelihood, consequence and management response
  • Horizontal logic connects results, indicators, baselines, targets and evidence
  • Logframe quality checked for duplication, gaps and implausible causal links

Participants can select relevant indicators and document their precise measurement specifications.

  • SMART criteria applied to outcome, output and activity indicators
  • Indicator reference sheets define purpose, formula, source and frequency
  • Numerator and denominator specified for percentage and ratio indicators
  • Proxy indicators selected when direct measurement is impractical
  • Disaggregation requirements set by sex, age, disability and location
  • Indicator pitfalls include double counting, attribution claims and ambiguous terms

Participants can establish defensible baselines and targets for project performance measurement.

  • Baseline purposes distinguished from needs assessments and routine monitoring
  • Target-setting methods use historical trends, service capacity and planned reach
  • Benchmarks selected from policy standards, norms and comparable programmes
  • Baseline protocols define population, timing, tools and responsible staff
  • Target trajectories show expected progress across project reporting periods
  • Zero baselines handled where new services or behaviours are measured

Participants can prepare a practical, costed M&E plan for project delivery.

  • M&E plan schedules indicators, methods, responsibilities and reporting products
  • Data flow diagrams show collection, verification, aggregation and approval steps
  • RACI matrix assigns accountable, responsible, consulted and informed roles
  • M&E budgets cost personnel, tools, travel, training and evaluations
  • Partner capacity assessments identify support needs and control measures
  • Risk registers address access constraints, data protection and staff turnover

Participants can select and plan suitable quantitative data-collection methods for project indicators.

  • Survey designs match indicator definitions, populations and decision requirements
  • Questionnaire wording reduces recall bias, leading questions and respondent burden
  • Sampling frames identify eligible units and coverage limitations
  • Probability sampling methods include simple random, systematic and cluster samples
  • Sample-size assumptions balance precision, budget, timeframe and operational feasibility
  • Enumerator protocols cover consent, neutrality, safeguarding and field supervision

Participants can use qualitative methods to investigate experiences, mechanisms and unintended effects.

  • Key informant interviews explore implementation processes and contextual influences
  • Focus group discussions capture shared perceptions and group differences
  • Semi-structured guides link questions directly to evaluation and learning needs
  • Purposive sampling selects participants with relevant knowledge and experience
  • Participatory methods include community mapping, ranking and seasonal calendars
  • Qualitative coding identifies themes, exceptions, patterns and explanatory evidence

Participants can establish secure data-management processes for field monitoring information.

  • KoboToolbox forms configured with skip logic, validation and required fields
  • Unique identifiers prevent duplicate records across repeated monitoring rounds
  • Data dictionaries document variables, codes, labels and permitted values
  • Version control protects approved datasets, tools and reporting calculations
  • Access permissions separate collection, editing, approval and analysis responsibilities
  • Data retention schedules reflect donor obligations and safeguarding requirements

Participants can assess and improve the quality of monitoring data and reported results.

  • Data-quality dimensions assess validity, reliability, precision, integrity and timeliness
  • Source document verification compares reported values with underlying records
  • Data-quality assessment protocols select indicators, sites, samples and reviewers
  • Spot checks test completeness, consistency and adherence to collection procedures
  • Discrepancy logs record errors, root causes, corrections and follow-up actions
  • Partner data reviews establish evidence standards before report consolidation

Participants can operate a routine monitoring system that produces timely management information.

  • Routine monitoring cycles connect field data, review meetings and action tracking
  • Output tracking tools compare planned reach, actual reach and variance
  • Beneficiary feedback mechanisms capture complaints, suggestions and satisfaction evidence
  • Community accountability channels establish response standards and escalation routes
  • Field supervision checklists verify service quality and protocol adherence
  • Monitoring dashboards prioritise exceptions requiring management attention and decisions

Participants can analyse project data and communicate findings accurately for decisions.

  • Descriptive statistics calculate frequencies, percentages, averages and disaggregated results
  • Cross-tabulations reveal differences by location, sex, age and participant group
  • Trend analysis compares performance against baselines, targets and prior periods
  • Data triangulation combines monitoring records, surveys and qualitative evidence
  • Charts selected according to comparison, distribution, trend and composition questions
  • Interpretation distinguishes observed change, plausible contribution and unsupported attribution

Participants can convert monitoring evidence into documented project adaptations and learning actions.

  • Pause-and-reflect reviews examine evidence, assumptions, risks and delivery constraints
  • Decision logs document evidence considered, choices made and accountable owners
  • After-action reviews capture lessons following implementation milestones and disruptions
  • Adaptive management triggers define thresholds requiring corrective action
  • Learning questions focus inquiry on uncertainty, performance and programme design
  • Change-control processes preserve donor approval requirements for material amendments

Participants can select an evaluation approach and frame questions using OECD DAC criteria.

  • OECD DAC criteria frame relevance, coherence, effectiveness, efficiency, impact and sustainability
  • Evaluation questions distinguish accountability questions from learning-focused inquiry
  • Process evaluations investigate implementation quality, fidelity and operational barriers
  • Outcome evaluations assess changes associated with project interventions
  • Mixed-method designs combine quantitative estimates with explanatory qualitative findings
  • Evaluation timing considers baseline availability, project maturity and decision windows

Participants can prepare an evaluation terms of reference with a feasible methodological approach.

  • Terms of reference specify purpose, users, scope, questions and deliverables
  • Evaluation matrices connect questions, indicators, sources, methods and analysis
  • Comparison approaches consider counterfactuals, contribution analysis and process tracing
  • Evaluator selection criteria assess independence, technical expertise and sector knowledge
  • Inception reports confirm methodology, workplan, risks and quality assurance
  • Management responses assign actions, owners, deadlines and follow-up arrangements

Participants can apply ethical, safeguarding and data-protection controls to M&E activities.

  • Informed consent procedures explain purpose, risks, rights and withdrawal options
  • Do-no-harm assessment identifies risks created by data collection activities
  • Safeguarding referral pathways protect children and adults at risk
  • Confidentiality protocols govern identifiers, recordings, quotations and report access
  • Data minimisation limits collection to information required for stated purposes
  • Incident reporting procedures address breaches, disclosures and field safety concerns

Participants can prepare evidence-based donor reports that explain progress, variance and action.

  • Narrative reports connect activities, outputs, outcomes, evidence and expenditure
  • Indicator tables show actuals, targets, variance explanations and corrective actions
  • Results stories combine participant perspectives with verified project evidence
  • Variance analysis explains underperformance without concealing implementation challenges
  • Evidence annexes organise datasets, tools, source records and methodological notes
  • Donor report reviews check consistency across narrative, finance and indicator data

Participants can establish proportionate M&E arrangements with implementing partners.

  • Partner due diligence assesses M&E systems, staffing, tools and records
  • Subgrant reporting templates align partner data with prime recipient indicators
  • Capacity development plans prioritise skills gaps, systems and supervision needs
  • Joint monitoring visits clarify evidence expectations and resolve data discrepancies
  • Performance review meetings examine commitments, risks, findings and agreed actions
  • Proportionate controls match partner risk, budget, geography and delivery role

Participants can build, review and present a complete M&E package for a donor-funded project.

  • Project results chain refined from problem analysis and intervention logic
  • Logframe completed with indicators, baselines, targets and verification sources
  • Indicator reference sheets specify formulas, disaggregation, frequency and responsibilities
  • Costed M&E plan integrates collection methods, quality controls and reporting dates
  • Evaluation outline frames OECD DAC questions, methods and intended users
  • Peer review tests coherence, feasibility, ethics and donor reporting readiness

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Donor-aligned theory of change template
  2. Logical framework and indicator reference sheet
  3. Costed monitoring and evaluation plan
  4. Data-quality assessment checklist
  5. Evaluation terms of reference template
  6. Donor results-reporting checklist

Who should attend

  • Project Managers — responsible for delivery, results reporting and corrective action
  • Monitoring and Evaluation Officers — designing indicators, systems and evidence products
  • Programme Coordinators — translating donor commitments into operational project plans
  • Grants Managers — assuring proposal, reporting and compliance requirements are met
  • Technical Advisers — defining credible measures of sector-specific project results
  • Implementing Partner Staff — managing monitoring data and reporting obligations

Skills and tools covered

Results framework designIndicator developmentData quality assuranceEvaluation planningDonor reportingAdaptive management

Tools and standards

Logical Framework Approach, OECD DAC Evaluation Criteria, KoboToolbox, Data Quality Assessment

How the course runs

Training methodology

The course uses short technical briefings followed by structured case work, group analysis, simulations and individual application planning. Participants examine realistic donor-funded project documents, identify measurement weaknesses and build M&E components using supplied templates. Small groups test indicators, select data-collection methods, conduct data-quality reviews and interpret findings for management decisions. Facilitators provide technical feedback against recognised M&E standards and donor expectations. Participants progressively adapt course tools to a project relevant to their own role, culminating in a reviewed M&E package.

Requirements and prerequisites

Participants should have experience working on development, humanitarian, public-sector or social-impact projects and be familiar with basic project documents such as proposals, workplans, budgets or progress reports. They should understand the difference between activities and project objectives. Previous exposure to logframes, donor reporting or spreadsheet-based data management is helpful but not essential. This is an intermediate course, so it does not teach basic project management from first principles. Advanced statistical analysis, specialist evaluation software, coding and prior donor accreditation are not required.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should have experience with projects, programmes, grants or development operations and understand basic project documentation. You do not need advanced statistics, evaluation credentials or prior experience with a particular donor.

Bring a laptop if possible and, where permitted, a non-confidential proposal, logframe, workplan or report from a project you support. Course templates and case materials are provided.

It is suited to project managers, M&E officers, programme coordinators, grants staff, technical advisers and implementing-partner personnel. It is designed for professionals who need to turn donor commitments into credible evidence systems.

General project management courses focus on scope, schedules, budgets, risks and delivery controls. This course concentrates on results measurement, data quality, evaluation, learning and donor-facing evidence requirements.

Participants build reusable M&E documents throughout the course and can adapt them to active grants or proposals. The methods support inception planning, routine reporting, partner reviews, baseline preparation and evaluation commissioning.

The first week establishes results frameworks, indicators, baselines, plans and data-collection methods. The second week focuses on data quality, analysis, evaluation, reporting, partner management and a final M&E package presentation.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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