Food Security Data Analysis for Monitoring and Evaluation Officers Training Course

Course overview

Monitoring and evaluation officers working on food security programmes must turn uneven field data into evidence that programme managers, donors and coordination bodies can act on. This means more than calculating beneficiary totals: officers need to test data quality, select defensible indicators, disaggregate results by sex, age, disability and location, and explain whether changes in food consumption, coping behaviour or market access are plausible programme results. Weak analysis can misdirect targeting, obscure deteriorating conditions and undermine the credibility of donor reports.

This course builds the practical analytical workflow needed to monitor food security interventions. Participants work with food security indicator reference sheets, logframes, baseline and endline datasets, KoboToolbox exports and Excel or Power BI dashboards. They calculate and interpret Food Consumption Score (FCS), Household Dietary Diversity Score (HDDS), Reduced Coping Strategies Index (rCSI) and key market indicators; conduct data-cleaning checks; compare results across population groups; and present findings using tables, charts and concise evidence statements. The course also covers indicator definitions, sampling implications, data protection, triangulation and alignment with IPC evidence and humanitarian reporting requirements.

Teaching combines instructor-led demonstrations with a running case study of a cash, livelihoods and nutrition-sensitive food security programme. Participants clean and analyse a realistic dataset, investigate anomalies, create a monitoring dashboard and draft findings for a management review. They leave with a completed food security M&E analysis pack: an indicator analysis workbook, dashboard prototype, data-quality checklist, disaggregation plan and two-page findings brief that can be adapted for their own programme.

The course is suited to M&E officers, programme staff and information management personnel supporting humanitarian, recovery or resilience projects. It is designed for professionals who need to improve routine monitoring and reporting, not for specialists conducting advanced econometric impact evaluations.

Course objectives

By the end of this course, participants will be able to:

• Construct a food security indicator matrix linking activities, outputs, outcomes, data sources, frequencies and disaggregation requirements
• Calculate Food Consumption Score, Household Dietary Diversity Score and Reduced Coping Strategies Index from household survey data
• Clean KoboToolbox or spreadsheet exports using range checks, duplicate detection, missing-value review and consistency rules
• Assess sampling, recall periods and indicator definitions to identify limits on interpretation of monitoring results
• Disaggregate food security results by sex, age group, disability status, livelihood group and geographic area
• Build an Excel or Power BI dashboard showing targets, achievements, trend lines and indicator alert flags
• Triangulate household survey, market monitoring, distribution and qualitative feedback data into defensible findings
• Produce a two-page food security monitoring brief with charts, evidence statements, limitations and recommended actions

Benefits of attending

Target competencies

Who should attend

• Monitoring and Evaluation Officers — who must convert food security monitoring data into credible programme evidence
• Food Security Programme Officers — who need to use indicator results to adjust targeting, delivery and follow-up
• MEAL Officers — who manage routine monitoring systems and donor reporting across humanitarian projects
• Information Management Officers — who prepare, validate and visualise household and market datasets
• Cash and Voucher Assistance Officers — who monitor purchasing power, market access and household consumption outcomes
• Project Managers — who need to interpret food security findings and defend programme decisions to donors and partners

Requirements and prerequisites

Participants should be comfortable using Microsoft Excel for basic data entry, sorting, filtering and simple formulas, and should understand the purpose of a project logframe and indicators. Experience collecting, reviewing or reporting household survey data is useful but not essential. Bring a laptop with Microsoft Excel installed; access to Power BI Desktop is helpful where organisational policy permits. This is a foundation-to-intermediate course, so complete beginners in food security M&E are welcome and should expect guided practice with core concepts and datasets. Advanced statistics, R, Python, GIS analysis and prior IPC certification are not required.

Training methodology

The instructor uses short technical briefings followed by guided analysis in a realistic food security programme dataset. Participants practise in Excel, review KoboToolbox-style exports, calculate household indicators, inspect data-quality problems and compare results between locations and population groups. Small groups interpret conflicting survey, market and distribution evidence, then defend their conclusions in a simulated management review. Each day adds a component to an individual analysis pack, and the final session converts the completed analysis into a practical action plan for a participant’s own monitoring system.

Course outline

Day 1: Food security M&E architecture and indicator design

• Food security conceptual framework: availability, access, utilisation and stability
• Results chains for cash, food assistance, livelihoods and market-support interventions
• Output, outcome and context indicators in food security programmes
• Indicator reference sheets: definitions, numerators, denominators and recall periods
• Food Consumption Score, HDDS and rCSI indicator purpose and limitations
• Disaggregation requirements for sex, age, disability, livelihood and location
• Data-collection frequency, data-source selection and indicator responsibility matrices

Workshop: Participants develop an indicator matrix for a cash and livelihoods project, specifying measures, sources, frequencies, disaggregation and decision use.

Day 2: Household survey data quality and preparation

• KoboToolbox form structure, variable naming and export formats
• Data dictionaries, codebooks and survey metadata review
• Excel cleaning workflow using filters, conditional formatting and validation rules
• Duplicate household records, respondent identifiers and repeat-interview checks
• Missing values, skip logic failures and out-of-range response detection
• Categorical recoding, labelled values and handling of non-response
• Data protection procedures for household identifiers and sensitive vulnerability data

Workshop: Using a flawed KoboToolbox export, participants produce a cleaned analysis file and a documented data-quality issue log.

Day 3: Calculating and interpreting food security indicators

• Food Consumption Score food-group weighting and threshold calculation
• Household Dietary Diversity Score calculation from 24-hour recall data
• Reduced Coping Strategies Index frequency and severity weighting
• Household Hunger Scale and when it complements routine monitoring
• Descriptive statistics: proportions, means, medians and confidence cautions
• Cross-tabulation by target group, location and assistance modality
• Baseline-to-follow-up comparison and attribution-safe interpretation

Workshop: Participants calculate FCS, HDDS and rCSI for a household sample, disaggregate the results and write three evidence statements with limitations.

Day 4: Market, programme and contextual data triangulation

• Market price monitoring: food basket composition, units and price normalisation
• Terms of trade and purchasing-power analysis for livelihood groups
• Transfer value adequacy against minimum expenditure basket assumptions
• Distribution monitoring, post-distribution monitoring and complaint-feedback data
• IPC Acute Food Insecurity Classification evidence types and analytical boundaries
• Triangulation matrices for reconciling quantitative and qualitative evidence
• Alert thresholds and escalation rules for deteriorating food security conditions

Workshop: In groups, participants reconcile household survey, market-price and feedback datasets to produce an alert assessment and recommended programme response.

Day 5: Dashboards, findings briefs and management use

• Excel pivot tables and pivot charts for routine indicator reporting
• Power BI data model basics and relationship checks
• Dashboard design for target-versus-achievement, trends and disaggregation
• Chart selection for food security indicator distributions and comparisons
• Writing evidence statements that distinguish findings, inference and recommendation
• Donor reporting tables, calculation audit trails and methodological notes
• Monitoring action plans linking findings to programme adaptation and follow-up

Workshop: Participants complete a dashboard and two-page management brief, then present their findings and a 90-day monitoring improvement plan.

Tools & standards covered

Microsoft Excel, Microsoft Power BI, KoboToolbox, IPC Acute Food Insecurity Classification

A typical training day

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

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions