Begin with the decision the NGO must make
Good baseline research is designed backwards from programme decisions. For an NGO operating in Eswatini, that means defining intended participants, understanding local delivery structures, and choosing indicators that will still make sense at midline and endline. Comparing experiences in Mbabane and Manzini can strengthen the initial design because the two settings are not identical: an administrative and service-sector centre, while Manzini represents a commercial centre with retail and commuting flows.
Hold a short inception exercise before building the sample. Programme staff should explain what the intervention will deliver, when exposure begins, and which target groups could be affected first. The research team then turns vague ambitions into a limited set of testable questions. For instance, a health programme may need to distinguish awareness of a service from physical access and actual use. Keeping these constructs separate makes later comparisons more credible and ensures that resources are spent collecting evidence that can inform management.
Understand how research geography works in Eswatini
Fieldwork should follow the administrative vocabulary used in Eswatini: regions, tinkhundla and chiefdom structures. These structures help researchers identify the correct boundaries, local gatekeepers and likely sources of population lists, but they do not automatically supply a complete probability sampling frame. First establish which boundaries apply to the actual programme area, then verify maps and household or facility counts. Administrative labels should be used only after checking their exact local meaning and relationship to the study population.
Define the target population and sampling frame
The sample plan must say what the estimates will represent. An NGO might need one estimate across programme communities, separate estimates for women and men, or a comparison of exposed and unexposed participants. These are different sample-design problems. Selection should not be delegated to interviewer convenience. Build a frame, test its completeness, document clustering and calculate practical design effects. Where populations are mobile or records outdated, conduct listing or frame verification before drawing respondents.
Baseline research in Mbabane: designing the first city sample
In Mbabane, where the city functions as an administrative and service-sector centre, a baseline might start with an inventory of programme catchments and service points. If the intervention concerns food security and cash assistance, the field team should test measures of food consumption patterns, payment experience, market access and coping strategies. Interviewer routes should deliberately cover selected neighbourhoods rather than concentrating around accessible offices and major roads. Compare the register of intended participants with people who actually use services; discrepancies may expose targeting or access problems. Whether the unit is a household, young person, facility or beneficiary must remain consistent through analysis.
Baseline research in Manzini: testing a contrasting city context
Manzini deserves an independent field plan because it is a commercial centre with retail and commuting flows. Before importing the Mbabane questionnaire unchanged, conduct a short cognitive pilot and verify where the target population resides, travels and receives services. The sample allocation should reflect the stated comparison question, not an arbitrary equal split made for convenience. If the NGO needs a comparison between the two cities, agree the minimum precision and subgroup coverage needed. Findings should describe the observed difference without attributing it automatically to geography or programme performance.
Build indicators that can be measured again
Create an indicator reference sheet before programming the tool. Each measure needs an unambiguous numerator, denominator, unit of analysis, reference period and method of calculation. Distinguish access from use, knowledge from behaviour, and service availability from service quality. Plan disaggregation only for groups that the sample is actually large enough to analyse responsibly. Keep core wording stable for follow-up rounds and version-control every change. Without these safeguards, a later percentage may look comparable even though it measures a different reality.
Choose appropriate survey and qualitative methods
Build a mixed-method design around the research questions. Structured interviews may estimate the prevalence of a condition in a defined population; in-depth discussions can uncover how respondents interpret the issue. Site observation can test whether reported services exist and are usable. A phone-only design may miss participants with limited ownership or connectivity, so consider whether targeted in-person coverage is essential. Before fieldwork, reconcile questionnaires, consent language, qualitative guides and indicator definitions so the evidence fits together.
Translate and pilot instruments for local respondents
Tools and consent scripts should be tested in siSwati and English. A language that works for a formal meeting may not be the clearest language for a household interview, and bilingual respondents may switch vocabulary when describing sensitive experiences. Prepare a glossary for core constructs, reconcile translations with the source questionnaire and role-play difficult questions. Recruit interviewers for language competence and cultural familiarity, not only device skills. Translation changes need recorded approval so that future midline and endline rounds can preserve conceptual equivalence.
Design field operations around actual access conditions
Operationally, urban samples should be interpreted separately from chiefdom and rural catchments. Plan interviewer assignments, transport, safe operating hours, supervision and escalation around this reality. An initial reconnaissance visit can check listing feasibility, accessibility, the actual duration of an interview and any mismatch between administrative maps and lived settlement boundaries. A rigorous pilot should include sample-selection rehearsal, consent practice, skip-logic tests and mock data submission. Budget for replacements that comply with the original selection procedure rather than allowing opportunistic substitution when a respondent is absent.
Protect consent, privacy and vulnerable participants
Plan for ethical interviewing as carefully as for sample selection. Recruitment scripts should not pressure participants through local authorities or service providers. Interviewers need a safe way to handle distress, complaints, safeguarding concerns and requests to withdraw. Consent for recordings must be explicit, and remote client observation must be disclosed when used. The research team should maintain a data-management plan describing storage, restricted access, de-identification and retention, with site-specific requirements verified.
Check quality while fieldwork is still active
Quality assurance should begin with the sampling frame and tool. Train enumerators on eligibility, consent, neutrality, translation, route procedures and escalation. Use role plays and certification interviews before deployment. During collection, dashboards can flag unusual duration, repeated coordinates, inconsistent answers and incomplete quotas; none of these signals proves misconduct by itself. Supervisors should investigate patterns using observations, call-backs and documented checks. Predefine interview rejection rules to prevent convenient decisions after fieldwork.
Analyse change without overstating causal claims
Analysis should move from data validation to clearly labelled findings. Report weighted estimates only when design and weights justify them. Examine subgroup differences with attention to sample sizes and uncertainty, and separate observed conditions from assumptions about programme causality. Triangulate conflicting findings: a facility may report stock availability while households describe barriers to access. The final product should include baseline values, limitations, an indicator annex or calculation dictionary, and a short decision brief for programme managers.
Turn baseline evidence into action in Eswatini
For a hypothetical NGO programme focused on food security and cash assistance, the useful deliverable is not simply a table showing food consumption patterns, payment experience, market access and coping strategies. It is an explanation of which barriers can be addressed through the intervention and which reflect factors outside programme control. If participants know a service exists but rarely use it, explore cost, location, opening time, quality, trust and social norms. Recommend a response only when the evidence distinguishes among those explanations. The baseline should also register external shocks and programme exposure dates to protect later interpretation.
At the end of the exercise, the NGO should be able to say what the baseline means for Eswatini, what it means specifically for Mbabane and Manzini, and what it does not mean. Set a schedule for repeating core indicators, preferably at comparable seasonal periods. Keep the sample frame, contact protocol, questionnaire versions, interview-date records and calculation syntax. Use a short management session to decide whether targeting, staffing, communication or referral practices should change. Record those decisions so the endline can examine both outcomes and the adaptation process.
What a useful baseline report should deliver
A strong Eswatini baseline report should provide a clearly defined study population, an honest sampling account, accepted-interview totals, response outcomes, reproducible indicators and accessible recommendations. City comparisons should carry their own denominators and limitations. The report can be supported by a clean dataset, fieldwork memo, codebook and monitoring matrix, for internal analysis and subsequent measurement rounds. Any gaps in coverage should be visible so implementers can decide whether further listing or targeted qualitative inquiry is needed before expanding activities.
How Surveysphere Africa can support
Surveysphere Africa helps NGOs and development organisations design baseline studies, define indicators, plan samples, manage fieldwork, verify data quality and turn findings into actionable programme decisions. For work involving Mbabane, Manzini or wider coverage in Eswatini, the research design should begin with the intended decision and the population it needs to represent, then adapt responsibly to the local context.
Related guidance
For the continent-wide view, read our guide to baseline, midline and endline studies.
Our services for research in Eswatini
We run research across African markets. Start with these services for work in Eswatini:
- Monitoring, evaluation and learning in Eswatini: Baseline, midline, endline and programme evaluation.
- Social and development research in Eswatini: Qualitative and quantitative studies for social and development programmes.
We also offer: Outsourced fieldwork, Market and consumer research, Public health research, Policy, economic and institutional research, Data analytics and insights visualisation.
