Service Delivery Survey Design Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Monitoring and Evaluation Officers, Programme Managers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-ME-128

Before you join: Participants should have basic familiarity with development or humanitarian programmes, service delivery models, and routine monitoring data such as beneficiary counts or indicator 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

Service delivery surveys provide evidence on whether people can access services, receive them when needed, experience respectful treatment, and obtain the intended benefit. Programme managers and public service leaders often have administrative data on outputs but lack credible information from users, non-users and frontline staff. Poorly designed surveys can produce misleading satisfaction scores, exclude hard-to-reach groups, overstate results, or fail to answer decisions about staffing, outreach, referral systems and service standards.

This course prepares participants to design, implement and use service delivery surveys for development and humanitarian programmes. Participants define decision-focused survey questions; map service delivery pathways; select survey designs and samples; develop indicators and questionnaires; apply ethical, safeguarding and data-protection controls; manage enumerators and fieldwork; and analyse findings by sex, age, disability, location and other priority characteristics. The course addresses household, client-exit, facility, phone and mixed-mode surveys, including common challenges such as incomplete sampling frames, recall bias, nonresponse, security constraints and sensitive disclosures.

Teaching combines short technical briefings with realistic cases from health, education, social protection, WASH, livelihoods and local government services. Participants review survey instruments, calculate sample requirements, assess fieldwork risks, interpret disaggregated results and prepare management actions from findings. They leave with a reusable service delivery survey design pack containing a protocol structure, questionnaire blueprint, sampling plan, fieldwork quality controls, analysis plan and reporting framework.

The course suits professionals responsible for monitoring, evaluation, programme quality, research, accountability, public service performance or commissioned surveys. It is particularly relevant where survey findings must withstand management scrutiny and inform practical service improvements.

What you will be able to do

  • Define decision-focused service delivery survey questions using results chains and stakeholder analysis
  • Select suitable cross-sectional, panel or repeated survey designs for service decisions
  • Construct probability samples, calculate sample sizes and document sampling limitations
  • Develop indicators and questionnaire items for access, quality, equity and responsiveness
  • Apply informed consent, safeguarding and data-protection procedures during survey implementation
  • Prepare digital data-collection forms, enumerator instructions and fieldwork supervision plans
  • Analyse disaggregated survey data using weighting, confidence intervals and triangulation
  • Produce findings matrices and management response plans linked to service improvements

Benefits of attending

For you

  • Design survey protocols that answer operational service improvement questions
  • Assess whether a proposed sample can support valid subgroup findings
  • Write clearer client, household and facility survey questionnaires
  • Manage enumerators using documented quality-control and safeguarding procedures
  • Present survey evidence with defensible limitations and practical recommendations

For your organisation

  • Produces survey evidence linked directly to service management decisions
  • Reduces wasted fieldwork caused by weak instruments and unsuitable samples
  • Improves visibility of access barriers affecting excluded population groups
  • Strengthens data quality through documented supervision, back-checks and incident reporting
  • Creates consistent survey protocols for internal teams and external research suppliers

Course modules

10 modules over 5 days

Participants can frame service delivery survey objectives around decisions, stakeholders and measurable service changes.

  • Service delivery pathways mapped from inputs through client outcomes
  • Decision-focused survey questions linked to management actions and accountability
  • OECD DAC criteria adapted for access, quality, equity and responsiveness
  • Stakeholder analysis distinguishes commissioners, providers, users, gatekeepers and affected groups
  • Results chains specify assumptions, risks and measurable service delivery changes
  • Survey scope defined by geography, population, service point and period

Participants can select a survey design and prepare a defensible sampling approach.

  • Cross-sectional, panel and repeated cross-sectional designs matched to decisions
  • Sampling frames assessed for coverage errors, duplicates and excluded populations
  • Probability sampling selects simple random, systematic, stratified or cluster samples
  • Sample-size calculations incorporate precision, design effect, nonresponse and subgroup estimates
  • Multistage cluster selection uses probability proportional to size procedures
  • Nonprobability approaches document purposive selection limits and inference risks

Participants can specify measurable indicators for service access, experience, quality and equity.

  • Indicator reference sheets define numerator, denominator, disaggregation and interpretation
  • Access measures separate availability, affordability, physical reach and eligibility
  • Quality constructs translate timeliness, reliability, safety and courtesy into items
  • Equity analysis specifies sex, age, disability, location and poverty disaggregation
  • Likert scales, indices and composite measures selected against measurement purpose
  • Validity threats include social desirability, recall bias and proxy respondents

Participants can develop clear, testable questionnaires with appropriate response options and routing.

  • Questionnaire flow follows screening, service-use, experience, outcomes and demographics
  • Closed questions use mutually exclusive, collectively exhaustive response categories
  • Recall periods align with event frequency and respondent memory
  • Translation follows TRAPD principles: translate, review, adjudicate, pretest and document
  • Cognitive interviewing identifies comprehension, retrieval, judgement and response problems
  • Skip logic and validation rules prevent impossible or inconsistent entries

Participants can incorporate ethical, safeguarding and privacy safeguards into survey protocols.

  • Ethics protocol addresses voluntary consent, confidentiality, risks, benefits and referrals
  • Do-no-harm assessment identifies distress, retaliation and exclusion risks
  • Safeguarding procedures define disclosure response, referral pathways and staff duties
  • Data protection plans specify minimisation, access controls, retention and deletion
  • Child participation requires assent, caregiver consent and age-appropriate interviewing
  • Accessible methods accommodate language, literacy, disability and communication preferences

Participants can prepare digital instruments, enumerator guidance and workable fieldwork arrangements.

  • KoboToolbox forms configure constraints, skip logic, media and identifiers
  • Enumerator manuals standardise introductions, probing, consent and closing procedures
  • Fieldwork plans sequence listing, appointments, transport, supervision and escalation
  • Recruitment criteria address language, gender, technical skill and local acceptance
  • Pilot testing checks duration, comprehension, workflow and device performance
  • Remote and in-person modes assessed for coverage, privacy and response effects

Participants can manage field teams and detect data-quality problems during collection.

  • Training certification tests enumerator knowledge, role plays and device competence
  • Paradata monitor interview length, timestamps, GPS, edits and synchronisation
  • Back-checks and spot-checks detect fabrication, coaching and protocol deviations
  • Daily quality dashboards flag missingness, outliers, duplicates and unusual patterns
  • Supervision ratios, call-backs and replacement rules protect sample integrity
  • Incident logs document refusals, safeguarding concerns, security events and resolutions

Participants can prepare, analyse and interpret service delivery survey data responsibly.

  • Data cleaning applies range checks, duplicate review, recoding and audit trails
  • Weighting adjusts unequal selection probabilities and documented nonresponse patterns
  • Descriptive statistics report proportions, means, confidence intervals and denominators
  • Cross-tabulations compare service experience by priority population characteristics
  • Disaggregation rules suppress unstable estimates and protect respondent confidentiality
  • Triangulation compares survey findings with administrative records, observation and qualitative evidence

Participants can communicate credible findings and translate them into accountable service actions.

  • Findings matrices connect each survey question, indicator, result and decision
  • Equity-focused interpretation distinguishes aggregate improvement from subgroup exclusion
  • Statistical uncertainty communicated through confidence intervals, base sizes and caveats
  • Service journey maps identify breakdowns between referral, access, receipt and follow-up
  • Recommendation criteria assess feasibility, cost, ownership, urgency and expected effect
  • Management response plans assign actions, owners, milestones and verification evidence

Participants can assemble a practical survey protocol and plan the next implementation decisions.

  • Survey protocols consolidate objectives, methods, governance, ethics and operational procedures
  • Work breakdown structures sequence approvals, programming, training, collection and reporting
  • Budget assumptions estimate staffing, travel, devices, connectivity, translation and contingency
  • Risk registers assign mitigations for access, security, nonresponse and data loss
  • Data dissemination plans define audiences, products, access levels and release dates
  • Application plans schedule the participant's next survey design decisions and stakeholders

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

What you take back to work

  1. Service delivery survey protocol template
  2. Sampling frame assessment checklist
  3. Questionnaire design and testing blueprint
  4. Ethics, safeguarding and data-protection checklist
  5. Fieldwork quality assurance plan
  6. Findings matrix and management response template

Who should attend

  • Monitoring and Evaluation Officers — design credible surveys and turn results into programme decisions
  • Programme Managers — obtain evidence on access, quality and user experience
  • Research and Evaluation Specialists — strengthen sampling, instruments and analysis plans
  • Accountability and Community Engagement Staff — measure client feedback and inclusion barriers
  • Government Service Delivery Managers — assess public services from citizen and user perspectives
  • NGO and Donor Programme Staff — commission, review and use service delivery survey evidence

Skills and tools covered

Survey designProbability samplingQuestionnaire developmentFieldwork quality assuranceDisaggregated data analysisEvidence-to-action planning

Tools and standards

OECD DAC evaluation criteria, TRAPD translation model, KoboToolbox, Probability proportional to size sampling

How the course runs

Training methodology

The course uses short instructor briefings followed by case-based design work, group review and structured simulations. Participants work with service delivery scenarios involving clinics, schools, cash assistance, water points and local government offices. They assess sample frames, refine questionnaire items, plan fieldwork controls, review mock data-quality dashboards and interpret disaggregated findings. Facilitated discussions examine trade-offs between cost, precision, coverage, respondent burden and safeguarding. Each participant prepares an application plan for a current or planned survey.

Requirements and prerequisites

Participants should have basic familiarity with development or humanitarian programmes, service delivery models, and routine monitoring data such as beneficiary counts or indicator reports. Experience supporting surveys, assessments, fieldwork, programme monitoring or commissioned research is helpful. Participants should be comfortable reading tables and percentages and using spreadsheets for basic data review. Prior statistical training, advanced quantitative analysis, programming skills, or experience with KoboToolbox is not required. The course explains sampling and survey quality concepts before applying them to service delivery cases.

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 understand basic programme monitoring concepts and be comfortable working with percentages and tables. Prior survey design, statistics, digital data collection or advanced spreadsheet skills are not required.

Bring a laptop if possible and, ideally, an existing survey, programme logframe, indicator list or service delivery question from your work. Course materials and cases are provided, so participants without a live project can work from supplied examples.

It is designed for M&E staff, programme managers, evaluation specialists, accountability teams, government service managers and professionals who commission surveys. It suits people working in development, humanitarian response, public services and large social programmes.

General M&E courses cover results frameworks, indicators and evaluation approaches across a wide range of methods. This course concentrates on the technical and operational work required to design, implement and use service delivery surveys.

Participants can use the protocol, sampling, questionnaire, fieldwork and reporting templates for a planned survey or to review a consultant's proposed methodology. The methods also support client feedback, facility assessments, household surveys and public service satisfaction studies.

Training runs from 08:30 to 16:30 each day, with approximately 6.5 contact hours daily. The five days cover survey planning, sampling, instruments, ethics, digital collection, field quality assurance, analysis, reporting and application planning.

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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