🌍 Part of our Humanitarian & NGO Industry Training Series — browse all related courses →
About This Course
Accurate, timely data is the foundation of effective humanitarian response. From rapid needs assessments in the immediate aftermath of a crisis to longitudinal monitoring of displaced populations, well-designed surveys allow organisations to allocate resources efficiently, track programme impact, and advocate for affected communities with credible evidence. Yet the humanitarian context presents unique methodological challenges — insecurity, population mobility, language diversity, low literacy, and limited infrastructure all complicate standard survey approaches.
This five-day course, Designing and Implementing Humanitarian Surveys, provides a structured and practical pathway through the entire survey lifecycle. Participants begin with the conceptual foundations of humanitarian data needs, move through questionnaire design and sampling strategy, and progress to field management, data quality assurance, and results communication. Each stage is grounded in real humanitarian scenarios drawn from displacement, food security, health, shelter, and protection contexts.
Delivered by practitioners with direct field experience, the course emphasises methodological rigour without sacrificing operational feasibility. Participants work in small groups to design and critique actual survey instruments, run simulated data collection exercises, and practise analysing and presenting findings for decision-maker audiences. By the end of the programme, each participant will leave with a draft survey instrument and implementation plan tailored to their own organisational context.
TrainingComplex has designed this course for mid-career humanitarian and development professionals who collect or commission data as part of their roles, as well as for M&E officers and programme staff who need to strengthen the quality and credibility of their organisation's evidence base.
Who Should Attend
- Monitoring, Evaluation, Accountability and Learning (MEAL) officers and managers in humanitarian and development organisations
- Field programme officers responsible for needs assessments or baseline and endline surveys
- Humanitarian information management officers working with primary data
- Research and learning officers in NGOs, UN agencies, and government ministries
- Data managers and enumerator supervisors involved in large-scale field data collection
- Grant managers and programme coordinators who commission or interpret survey findings
- Consultants and independent researchers working in humanitarian or fragile contexts
Learning Objectives
- Explain the role of surveys within the broader humanitarian information ecosystem and align survey design with organisational decision-making needs
- Define clear research objectives and translate them into measurable indicators appropriate for crisis-affected settings
- Design a well-structured, context-sensitive questionnaire that minimises bias and respondent burden
- Select and apply appropriate probability and non-probability sampling strategies given field realities and resource constraints
- Develop a field operations plan covering enumerator recruitment, training, logistics, and supervision protocols
- Apply digital data collection tools and configure mobile data collection platforms for offline and low-connectivity environments
- Implement data quality assurance processes including back-checks, logic checks, and real-time monitoring dashboards
- Clean, organise, and perform basic analysis of survey data to produce findings relevant to programme or advocacy decisions
- Present and visualise survey results in formats appropriate for different humanitarian audiences, including cluster coordinators, donors, and community stakeholders
- Identify and mitigate common ethical risks in humanitarian surveys, including informed consent, data protection, and do-no-harm principles
Course Modules
Module 1: Surveys in the Humanitarian Information Ecosystem
- The role of primary data in humanitarian needs assessments and programme cycles
- Differentiating surveys from other data collection methods: KIIs, FGDs, and secondary data review
- Key humanitarian data standards: IASC guidelines, Sphere indicators, and cluster information requirements
- Aligning survey purpose with organisational decision-making and donor reporting needs
- Navigating the humanitarian coordination architecture: how surveys feed into HNOs, HRPs, and cluster reporting cycles
- Managing duplication and data gaps: using the Assessment Registry and coordinating with other actors before commissioning new surveys
Module 2: Defining Research Objectives and Indicators
- Translating programme questions into clear, measurable survey objectives
- Selecting and adapting standard humanitarian indicators (FIES, HDDS, WASH ladders, protection incidence)
- Developing an indicator matrix linking objectives, questions, and analysis plans
- Avoiding indicator overload and scope creep in multi-sector assessments
- Distinguishing output, outcome, and impact-level indicators and matching each to the appropriate survey moment in the programme cycle
- Applying a gender and age disaggregation framework at the indicator design stage to ensure findings support intersectional analysis
Module 3: Questionnaire Design Principles
- Structuring a questionnaire: sections, flow, and respondent journey
- Writing unambiguous, culturally appropriate, and bias-free questions
- Response scale selection: Likert scales, frequency scales, and categorical options
- Piloting and cognitive testing questionnaires in low-literacy and multi-language contexts
- Managing sensitive question placement: sequencing trauma-related, protection, and income questions to minimise respondent distress and dropout
- Designing effective household roster modules to accurately capture demographic composition, displacement status, and vulnerability markers
Module 4: Sampling Strategy and Sample Size Determination
- Probability sampling methods: simple random, systematic, stratified, and cluster sampling
- Non-probability approaches: purposive, snowball, and respondent-driven sampling in hard-to-reach populations
- Calculating sample size using prevalence estimates, confidence intervals, and design effect
- Mapping and listing challenges in displacement settings and adaptive sampling solutions
- Applying EPI-style and SMART survey sampling methodologies for nutrition and health assessments in camp and dispersed population contexts
- Documenting sampling decisions transparently: writing the sampling methodology section to meet peer-review and inter-agency scrutiny standards
Module 5: Ethical Principles and Data Protection in Humanitarian Surveys
- Informed consent processes adapted for vulnerable and crisis-affected populations
- Do-no-harm considerations: sensitive topics, conflict sensitivity, and protection risks
- Data minimisation, anonymisation, and secure data storage in humanitarian contexts
- Respondent fatigue, community engagement, and managing expectations around survey outcomes
- Navigating ethical review and institutional approval processes in humanitarian organisations, including expedited review mechanisms for rapid-onset emergencies
- Handling incidental disclosure: protocols for referral pathways when respondents reveal protection concerns, gender-based violence, or immediate safety risks during interviews
Module 6: Digital Data Collection Tools and Platform Configuration
- Comparing digital data collection platforms: KoboToolbox, ODK, and Survey CTO
- Building forms with skip logic, constraints, and validation rules to reduce enumerator error
- Offline data collection workflows for low-connectivity field environments
- GPS georeferencing, photo capture, and metadata management in mobile surveys
- Configuring user roles, project permissions, and data encryption settings to meet organisational data protection policies
- Designing multilingual forms with dynamic language switching and managing translation version control across iterative form revisions
Module 7: Field Operations Planning and Enumerator Management
- Designing a field work plan: zoning, team composition, daily targets, and logistics
- Recruiting, vetting, and training enumerators for context-sensitive data collection
- Supervisor protocols: daily briefings, spot-checks, and real-time issue escalation
- Managing security, access, and community entry in humanitarian field settings
- Developing a contingency plan for field disruptions: suspension criteria, replacement sampling procedures, and documentation when security incidents or access denials occur
- Building enumerator wellbeing and psychological support provisions into field operations, particularly when surveys cover trauma, loss, or protection incidents
Module 8: Data Quality Assurance and Real-Time Monitoring
- Pre-collection quality controls: form testing, enumerator certification, and pilot review
- Back-check surveys and audio auditing for enumerator performance verification
- Real-time monitoring dashboards in KoboToolbox: tracking submission rates and flagging anomalies
- Data rejection, re-collection, and documentation protocols for quality incidents
- Establishing interview duration benchmarks and using metadata analysis to detect suspiciously short, uniform, or GPS-inconsistent submissions indicative of fabrication
- Designing a data quality incident log and escalation matrix that assigns responsibilities across enumerators, supervisors, and data managers throughout the collection period
Module 9: Data Cleaning, Management, and Basic Analysis
- Systematic data cleaning workflow: identifying duplicates, outliers, and logical inconsistencies
- Data labelling, variable naming conventions, and codebook development
- Basic descriptive analysis: frequencies, cross-tabulations, and disaggregation by sex, age, and location
- Introduction to weighted analysis and adjusting for complex survey design in Excel and SPSS
- Constructing composite indicators and severity scales from raw survey variables, including wealth index proxies and food security phase classification inputs
- Maintaining an auditable analysis trail: version-controlling datasets, logging cleaning decisions, and producing a cleaning report for peer review and donor documentation
Module 10: Communicating and Using Survey Findings
- Structuring a humanitarian survey report: executive summary, methodology, findings, and recommendations
- Data visualisation principles: choosing charts, maps, and infographics for humanitarian audiences
- Producing a one-page evidence brief for cluster coordinators and donor audiences
- Feeding survey findings into programme adaptation, advocacy, and Humanitarian Response Plan updates
- Communicating uncertainty and limitations honestly: presenting confidence intervals, non-response rates, and contextual caveats without undermining the utility of findings
- Conducting a findings dissemination workshop with affected community representatives and programme staff to validate interpretations and build shared ownership of recommendations
Requirements & Prerequisites
Participants should have at least one year of experience working in a humanitarian, development, or research context and some prior exposure to data collection or programme monitoring. Basic familiarity with Excel or a similar spreadsheet application is expected. No advanced statistics background is required, though a comfort with numerical reasoning will support full engagement with the sampling and analysis modules.
Training Methodology
- Humanitarian scenario-based questionnaire design workshops in which small groups develop and peer-critique survey instruments drawn from real food security, protection, and shelter contexts
- Sampling simulation exercises using population datasets from displacement settings to practise calculating sample sizes and selecting households under different constraints
- Hands-on configuration of mobile data collection platforms (KoboToolbox and ODK) through guided lab sessions, including skip logic, validation rules, and offline deployment
- Field role-play and enumerator training simulation where participants alternate between supervisor and enumerator roles to experience data collection dynamics first-hand
- Data quality review practicals using pre-populated datasets with seeded errors for participants to detect and resolve using systematic cleaning protocols
- Case study analysis of real humanitarian survey reports — identifying methodological strengths, limitations, and lessons for practice
- Data visualisation and results communication workshop producing a one-page summary brief and presentation targeted at a cluster coordination audience
- Reflective journalling prompts at the close of each day to consolidate learning and surface questions for the following session
- Coaching clinics where participants present their in-progress survey design and receive structured facilitator and peer feedback
- A capstone planning session in which each participant completes a draft survey design document and implementation plan for their own organisational context
Organisational Benefits
- Improved quality and credibility of primary data used to inform programme design and resource allocation
- Stronger organisational capacity to conduct independent needs assessments and reduce dependence on external consultants
- Reduced risk of data collection errors and biased findings that could lead to misinformed decisions
- Enhanced compliance with donor expectations and cluster-level standards for evidence and accountability
- Better integration of ethical safeguards, including data protection protocols, into standard survey practice
- More effective communication of survey findings to donors, clusters, government partners, and affected communities
- A cohort of staff capable of training and supervising enumerator teams in the field
- Time and cost savings from well-planned survey operations that avoid common fieldwork pitfalls
Where Is Designing and Implementing Humanitarian Surveys Training Offered?
This course runs in-person across: Lagos, Mombasa, Dar es Salaam, Kigali, Dubai, Accra, Kampala, Cape Town, Riyadh, Nakuru, Naivasha, Arusha, Kisumu, Pretoria, Addis Ababa, Johannesburg, Abuja, Zanzibar, Nairobi, plus Live Virtual (online) cohorts. Browse live dates for your city below.
Upcoming Schedules
| Location | Format | Dates | Price |
|---|
| Lagos, Nigeria |
In-Person |
5 Oct 2026 – 9 Oct 2026 |
USD 2,500 |
| Mombasa, Kenya |
In-Person |
5 Oct 2026 – 9 Oct 2026 |
KES 115,000 |
| Dar es Salaam, Tanzania |
In-Person |
12 Oct 2026 – 16 Oct 2026 |
USD 2,300 |
| Kigali, Rwanda |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 1,900 |
| Dubai, United Arab Emirates |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 4,100 |
| Accra, Ghana |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 3,800 |
| Kampala, Uganda |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 1,900 |
| Cape Town, South Africa |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 3,800 |
| Riyadh, Saudi Arabia |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
USD 4,500 |
| Nakuru, Kenya |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
KES 115,000 |
| Naivasha, Kenya |
In-Person |
19 Oct 2026 – 23 Oct 2026 |
KES 120,000 |
| Arusha, Tanzania |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 2,100 |
| Kisumu, Kenya |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
KES 120,000 |
| Pretoria, South Africa |
In-Person |
26 Oct 2026 – 30 Oct 2026 |
USD 3,300 |
| Live Virtual |
Online |
26 Oct 2026 – 30 Oct 2026 |
KES 80,000 |
+233 more dates — view live schedule →
Frequently Asked Questions
Do I need a background in statistics to attend this course?
No advanced statistics background is required. The course covers the quantitative concepts you need — including sample size calculation and basic analysis — in a practical, step-by-step manner. Comfort with basic numeracy and familiarity with spreadsheets is sufficient preparation.
Will I receive a certificate upon completing the course?
Yes. Participants who attend the full five days and complete the capstone survey design exercise will receive a Certificate of Completion from TrainingComplex. The certificate is suitable for inclusion in professional portfolios and donor-facing CVs.
Which digital tools will we use during the course?
The course uses KoboToolbox as its primary platform because it is free, widely adopted in the humanitarian sector, and works offline. Participants are introduced to ODK as an alternative. You will need to bring a laptop; a smartphone or tablet is useful but not essential.
Is this course relevant if my organisation mostly uses secondary data rather than conducting its own surveys?
Yes. Understanding how primary surveys are designed and implemented will make you a more critical consumer of secondary data and third-party survey reports. The course covers how to assess the quality and limitations of survey evidence, a skill that applies equally when reviewing others' data.
Can the course content be adapted for a specific sector, such as health or food security?
The course uses examples drawn from multiple humanitarian sectors — food security, WASH, shelter, and protection — and the capstone exercise allows each participant to develop a survey instrument for their own sector. For teams requiring a fully customised in-house version focused on a single sector, TrainingComplex offers tailored organisational training packages on request.
