Begin with the decision the NGO must make
Good baseline research is designed backwards from programme decisions. For an NGO operating in Malawi, that means defining intended participants, understanding local delivery structures, and choosing indicators that will still make sense at midline and endline. Comparing experiences in Lilongwe and Blantyre can strengthen the initial design because the two settings are not identical: an administrative and consumer-services capital, while Blantyre represents a southern commercial centre.
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 Malawi
Fieldwork should follow the administrative vocabulary used in Malawi: districts, traditional authorities and urban wards. 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
Define the population before choosing sample size. The frame may be households, registered beneficiaries, service users, facilities or another identifiable universe. Decide whether the study needs representative estimates, comparisons between key groups, or exploratory findings; each calls for different selection rules. For probability work, document the frame, selection stages, inclusion probabilities, nonresponse approach, clustering and any planned weights. Quota and purposive samples may be appropriate for some questions, but their descriptive limits should be reported openly rather than hidden by a large number of interviews.
Baseline research in Lilongwe: designing the first city sample
In Lilongwe, where the city functions as an administrative and consumer-services capital, a baseline might start with an inventory of programme catchments and service points. If the intervention concerns water, sanitation and hygiene, the field team should test measures of water source, reliability, access time, costs and household practices. 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 Blantyre: testing a contrasting city context
Blantyre deserves an independent field plan because it is a southern commercial centre. Before importing the Lilongwe 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
A credible baseline rarely depends on a survey alone. Administrative records can describe programme reach, facility reviews can establish service readiness, and qualitative interviews can explain barriers not captured by fixed response options. The survey provides structured measures when the sampling design supports them. Decide which source is authoritative for each construct and how discrepancies will be investigated. A photograph, GPS point or timestamp should be collected only if needed and ethically justified; technology is not a substitute for valid measurement.
Translate and pilot instruments for local respondents
Tools and consent scripts should be tested in Chichewa, English and relevant local languages. 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, traditional authority geography should not be confused with municipal ward sampling. 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
Respondents are more likely to give meaningful answers when they understand who is conducting the study and how information will be used. Consent should distinguish the research team from programme selection decisions and state the limits of confidentiality. Make a documented choice about collecting names, audio and GPS. Use access controls, secure transfer and deletion schedules. If the study covers minors or sensitive health topics, obtain appropriate specialist review and consent or assent procedures before recruitment.
Check quality while fieldwork is still active
The best way to improve data quality is to make failure visible early. Pilot every language version and test skip logic on actual devices. Compare early interview durations, survey routes, subgroup distributions and item nonresponse against expectations. If interviewers struggle with one translated concept, pause and correct the wording through formal version control. Independent back-checks and spot observations can verify authenticity, while clean decision logs show why any interview was excluded or repeated.
Analyse change without overstating causal claims
Before writing the narrative, reconcile sample outcomes, missing data and indicator calculations. Tables should distinguish raw counts, valid percentages and weighted estimates as appropriate. Discuss plausible contextual explanations without attributing causes that were not tested. A useful final discussion links each finding to an operational question, such as targeting, access, implementation capacity or future monitoring. Archive the questionnaire, codebook, cleaning syntax and sampling notes so the next round can reproduce the approach.
Turn baseline evidence into action in Malawi
For a hypothetical NGO programme focused on water, sanitation and hygiene, the useful deliverable is not simply a table showing water source, reliability, access time, costs and household practices. 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 Malawi, what it means specifically for Lilongwe and Blantyre, 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 Malawi 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 Lilongwe, Blantyre or wider coverage in Malawi, 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 Malawi
We run research across African markets. Start with these services for work in Malawi:
- Monitoring, evaluation and learning in Malawi: Baseline, midline, endline and programme evaluation.
- Social and development research in Malawi: 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.
