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Begin with the decision the NGO must make

The first question for an NGO in Mali is not how many interviews it can finish, but what evidence it needs before intervention activities change local conditions. Baseline findings should inform targeting, resource allocation and later outcome tracking. Research in Bamako and Sikasso can help test the assumptions behind the programme, provided the study clearly separates those city-level findings from conclusions about the wider country.

Begin by questioning the programme assumptions rather than accepting the logframe uncritically. If an NGO expects improved uptake, the baseline must examine existing service access, trust, cost and behaviour, not only awareness. If the intended result concerns income, collection should account for seasonal variation and multiple earning sources. Make the key decisions explicit: what finding would require redesign, what subgroup requires additional support, and when the team must receive results for them to matter.

Understand how research geography works in Mali

Fieldwork should follow the administrative vocabulary used in Mali: regions, cercles and communes. 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. Before committing to a location, review current security, displacement patterns and partner access. Do not pressure enumerators or respondents to travel to unsafe sites simply to fill geographic quotas. A smaller ethically feasible study with stated limits is preferable to a nominally broad but unsafe design.

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 Bamako: designing the first city sample

In Bamako, where the city functions as a capital with concentrated urban livelihoods, a baseline might start with an inventory of programme catchments and service points. If the intervention concerns livelihoods and local employment, the field team should test measures of income sources, employment quality, seasonality and access to productive assets. 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 Sikasso: testing a contrasting city context

Sikasso deserves an independent field plan because it is a southern trading and agricultural centre. Before importing the Bamako 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 Bambara and other national languages, alongside French where appropriate. 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, field access and conflict sensitivity need review before enumerator deployment. 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 Mali

For a hypothetical NGO programme focused on livelihoods and local employment, the useful deliverable is not simply a table showing income sources, employment quality, seasonality and access to productive assets. 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 Mali, what it means specifically for Bamako and Sikasso, 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 Mali 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 Bamako, Sikasso or wider coverage in Mali, 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.

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