Data Collection, Analysis & Reporting for Monitoring & Evaluation (M&E) Training Workshop

Course overview

The Data Collection, Analysis & Reporting for Monitoring & Evaluation (M&E) Training Workshop equips monitoring and evaluation professionals, programme managers, researchers and development practitioners with practical skills to collect reliable data, analyse programme performance, measure results and produce evidence-based reports that support decision-making and organisational learning. The workshop covers M&E data collection methods, indicator development, questionnaire design, sampling techniques, digital data collection, data quality assurance, quantitative and qualitative analysis, data visualisation, results interpretation and report writing. Participants learn to transform raw data into meaningful evidence that demonstrates project progress, identifies implementation gaps, assesses outcomes and communicates programme impact to stakeholders, management and funding partners.

The course combines monitoring and evaluation frameworks with hands-on exercises using digital data collection platforms, statistical analysis software, spreadsheets and reporting dashboards. Participants will work with realistic programme datasets and develop practical outputs that can be applied to development projects, humanitarian interventions, public programmes, research initiatives and non-profit organisations.

Course objectives

• Design appropriate data collection tools and methodologies aligned with programme objectives, indicators and monitoring frameworks.
• Prepare professional M&E reports that present findings, conclusions, recommendations and evidence-based actions for programme improvement.
• Develop tables, charts, dashboards and indicator tracking systems to interpret programme performance and communicate findings.
• Clean, validate, organise and analyse M&E data using appropriate statistical techniques and software.
• Apply quantitative and qualitative data collection techniques, sampling methods and digital tools to gather reliable, relevant and ethical data.

Who should attend

Course content

• Module 1: Fundamentals of Monitoring, Evaluation and Results Measurement Principles of monitoring and evaluation, differences between monitoring and evaluation, purposes of routine monitoring and periodic evaluations, results-based management, project inp
• Module 2: M&E Frameworks, Indicators and Data Requirements Developing monitoring and evaluation frameworks, results chains and logical frameworks, theory of change and indicator alignment, defining SMART indicators, quantitative and qualitative indicators
• Module 3: Data Collection Methodologies and Research Design Quantitative and qualitative research approaches, mixed-methods data collection, primary and secondary data sources, structured and semi-structured interviews, household and beneficiary surveys,
• Module 4: Questionnaire Design, Survey Instruments and Field Tools Principles of questionnaire design, translating indicators into measurable questions, developing closed-ended and open-ended questions, Likert scales and rating questions, demographic and
• Module 5: Sampling Techniques and Field Data Collection Planning Principles of population and sample selection, target populations and sampling frames, probability and non-probability sampling, simple random and systematic sampling, stratified and cluster
• Module 7: Data Quality Assurance, Cleaning and Validation Dimensions of data quality, accuracy, completeness, consistency, validity and timeliness, identifying missing and duplicate records, detecting outliers and impossible values, checking data types an
• Module 8: Data Management, Organisation and Documentation Developing structured datasets, designing data dictionaries and codebooks, assigning variable names and labels, defining response codes, managing unique participant and record identifiers, organisi
• Module 9: Quantitative Data Analysis Using Excel and Statistical Software Descriptive statistics and frequency distributions, calculating totals and percentages, measures of central tendency including mean, median and mode, measures of dispersion, cross-t
• Module 10: Qualitative Data Analysis and Thematic Interpretation Preparing interview and focus group transcripts, organising qualitative data, developing coding frameworks, open and thematic coding, identifying recurring patterns and emerging themes, anal
• Module 11: Outcome Measurement, Baseline-Endline Analysis and Evaluation Designing baseline and endline assessments, comparing changes in programme indicators, measuring outcome achievement, assessing beneficiary-level changes, interpreting percentage and
• Module 12: Data Visualisation, Dashboards and Performance Monitoring Principles of effective data visualisation, selecting suitable charts and tables, creating frequency charts and trend graphs, visualising indicator achievement, designing beneficiary and
• Module 13: M&E Reporting and Evidence-Based Communication Structure of routine monitoring reports, preparing monthly, quarterly and annual M&E reports, writing executive summaries, presenting objectives and indicator performance, explaining deviations fro
• Module 14: Data Ethics, Protection and Responsible Data Use Informed consent and voluntary participation, confidentiality and privacy, responsible handling of personal and sensitive information, data minimisation, secure data storage and transmission, rol
• Module 15: Integrated M&E Data Collection, Analysis and Reporting Capstone Developing an integrated M&E data workflow, translating programme indicators into data collection tools, configuring a digital questionnaire, conducting simulated data collection,

General notes

• 5. Training Tools and Software The workshop uses practical tools selected according to participants' roles and existing systems. KoboToolbox and ODK support mobile data collection and survey deployment; Microsoft Excel supports data cleaning, descriptive statistics, indicator tracking and reporting; SPSS, R or Python support statistical analysis; Power BI supports interactive dashboards and performance monitoring; and Word and PowerPoint support professional M&E reports and stakeholder presentations. Participants may also use Google Forms or Microsoft Forms for simple questionnaires and qualitative coding spreadsheets for interview analysis. Exercises will emphasise practical workflows, data quality, appropriate analytical choices and responsible handling of participant information.
• Practical Exercises and Expected Outputs Participants will work with a realistic programme monitoring dataset, starting with indicators and a data collection plan and progressing through questionnaire design, digital data capture, data cleaning, statistical analysis, visualisation and report writing. Practical exercises include developing survey questions from programme indicators, building a KoboToolbox form with validation rules, conducting simulated data collection, cleaning incomplete and inconsistent records, calculating indicator achievement rates, comparing baseline and endline results, analysing interview responses, developing a Power BI or Excel dashboard and preparing a concise M&E report with evidence-based recommendations.
• Expected practical outputs include: - M&E data collection plan - Indicator reference sheet and tracking matrix - Questionnaire and survey instrument - KoboToolbox or ODK digital data collection form - Sampling and fieldwork plan - Data quality assurance checklist - Cleaned dataset and data cleaning log - Data dictionary and codebook - Quantitative data analysis tables - Qualitative coding and thematic analysis matrix - Baseline-endline comparison report - Excel or Power BI M&E dashboard - Indicator performance summary - Monthly or quarterly monitoring report - Evaluation findings and recommendations report - Data protection and responsible data management checklist
• The Data Collection, Analysis & Reporting for Monitoring and Evaluation (M&E) Training Workshop equips monitoring and evaluation officers, MEAL professionals, programme managers, researchers and development practitioners with practical skills in survey design, digital data collection, data quality assurance, quantitative and qualitative analysis, indicator tracking, data visualisation and evidence-based reporting. Participants learn to use tools such as KoboToolbox, ODK, Excel, SPSS, R, Python and Power BI to transform programme data into meaningful findings, measure performance against targets, demonstrate outcomes and support effective programme management and organisational learning.
• Data collection and analysis for M&E, monitoring and evaluation training, M&E data analysis course, MEAL training workshop, KoboToolbox training, ODK data collection, M&E reporting course, quantitative and qualitative data analysis, M&E dashboard development, Power BI for monitoring and evaluation, baseline and endline analysis, programme performance measurement, results-based monitoring and evaluation, data quality assurance training, evidence-based programme reporting.

Frequently asked questions

Schedule & fees