03 · What You Need to Know
Logical feasibility and operational feasibility are different
A logically coherent study explains how the research question, design, data, and analysis fit together. An operationally feasible study can actually execute that plan with the people, resources, permissions, expertise, and time available.
Research protocols themselves reflect this broader conception of feasibility. The World Health Organization's recommended protocol structure includes investigators and their responsibilities, participating institutions, methodology, project duration, anticipated problems, project management, budget, support, and collaboration with other scientists or institutions. These elements matter because a method does not implement itself.
Similarly, NIH planning guidance advises researchers to assess whether available resources and the research environment are adequate, identify gaps in expertise, and assemble collaborators who can strengthen and execute the proposed work. In other words, feasibility includes the surrounding research system, not merely the intellectual design.
Verify participant access with the people who control access
Researchers often write phrases such as “participants will be recruited from local schools” long before any school has agreed to participate. The sentence sounds operational. In reality, it may conceal several dependencies.
Who can authorize recruitment? Does the organization permit research solicitation? Can staff distribute invitations? Are enough potentially eligible participants available? Does another project compete for the same population? Are there restricted periods during examinations, clinical peaks, holidays, or organizational events?
A supervisor's belief that access “should be fine” is not equivalent to confirmation from the relevant site or gatekeeper.
Verify data access with the data owner or custodian
Secondary-data projects are especially vulnerable to assumed access. A dataset may exist without being available to you. Even when access is possible, the version you receive may not contain the variables, granularity, identifiers, historical coverage, linkage fields, or documentation your proposed analysis requires.
Before treating the plan as feasible, verify what data actually exist, who controls them, what approval or agreement is required, how long access normally takes, what restrictions apply, and whether the variables needed for the research question are available in usable form.
Where only preliminary confirmation is appropriate at the current stage, distinguish it from formal authorization. The role of informal site, data, or collaborator confirmation is to test whether the assumption is plausible before investing heavily in a design that depends on it.
Verify methodological assumptions with relevant expertise
You do not need to outsource every methodological decision. There are, however, moments when consultation can expose problems that are expensive to discover later.
A statistician or quantitative methodologist may identify that the proposed sample structure cannot support the intended model. A qualitative researcher may question whether the proposed sampling and interviewing strategy fits the methodological approach. A psychometrician may point out that an instrument does not support the interpretation you intend to make. A laboratory specialist may know that the proposed assay cannot reliably detect the quantity of interest under the available conditions.
The important principle is expertise matching. “I asked another researcher” is weak verification when the issue requires specialized knowledge outside that person's competence.
Consult methodological expertise before the irreversible decision, not after it
Consultation is most useful while consequential decisions remain changeable. Statistical advice after all data have been collected can improve analysis, but it cannot add a missing comparison group, correct an inappropriate sampling process, or create measurements that were never taken.
The same timing principle applies elsewhere. Consult the laboratory specialist before ordering specimens, the data custodian before designing an analysis around assumed variables, and the site before constructing a recruitment timeline around access that has not been confirmed.
Verify collaborators' actual availability and role
Someone being interested in a project is not the same as having capacity to perform a substantial role.
Clarify what the collaborator is expected to contribute, when that contribution is needed, what inputs they require, and whether the workload is realistic. If their role is essential to the study, determine what happens if their availability changes.
This becomes particularly important when one person holds unique expertise or controls an essential resource. A project with a single unconfirmed dependency may be more fragile than a project with several modest uncertainties.
Verify equipment and technical resources with the people who manage them
Equipment may exist but be fully booked. Software may require a license the project does not have. Computing infrastructure may prohibit the storage of sensitive data. A laboratory may support a technique but not the throughput required by the planned sample. A platform may export data, but not in the format or detail the analysis requires.
These details are often invisible from equipment inventories or websites. Speak with the people who operate or administer the resource.
Verify ethics and institutional requirements with the responsible authority
Colleagues can explain what usually happens, but they should not be treated as the final authority on institutional requirements.
For human-participant research, ethical review protects the dignity, rights, and welfare of participants. The responsible ethics committee or institutional process determines the requirements applicable to the particular study. WHO's own ethics review process, for example, requires protocols, informed-consent materials, study instruments, and other documentation for projects within its remit.
Other institutions and jurisdictions have their own procedures. If feasibility depends on whether a procedure is permissible, whether particular approval is required, or how long review may take, verify this with the responsible office rather than relying solely on research folklore. Every department has some folklore; not all of it survives contact with the actual form.
Verify the timeline with people whose work sits on the critical path
A timeline is only as credible as its slowest external dependency. Ethics review, contracts, data-use agreements, site authorization, translation, instrument licensing, software procurement, laboratory processing, recruitment, and specialist analysis can all involve lead times outside the researcher's direct control.
Ask the relevant people how long the process normally takes and what prerequisites must be completed before their clock even starts. “Two weeks” may mean two weeks after a complete submission, not two weeks from the day you first send an email.
This is why planning around ethics approval, recruitment, data access, and other dependencies requires more than inserting optimistic durations into a Gantt chart.
Verify costs with the people who know the real price
Budget assumptions deserve similar scrutiny. Participant reimbursement, transcription, translation, laboratory processing, software, equipment, data access, travel, publication, secure storage, research assistance, and institutional charges may have costs that are not obvious from public information.
If the study cannot proceed without a resource, obtain a credible estimate before calling the project affordable. A theoretically available service that costs three times the project budget is not an available service in any useful planning sense.
Verify responsibilities before assuming that “the team” will do something
Collective nouns can hide missing ownership. “The team will recruit participants,” “data will be cleaned,” and “the analysis will be conducted” sound reassuring until everyone assumes someone else is responsible.
For important tasks, identify who owns the work, who provides approval or oversight, who supplies necessary inputs, and who takes over if the primary person is unavailable. WHO protocol guidance explicitly calls for describing team members' roles and responsibilities, reflecting the practical importance of clear project management.
Not every dependency requires the same level of confirmation
Feasibility verification should be proportional. During early planning, an informal conversation may be enough to establish that a collaboration or site is plausible. Before formal submission or expenditure, stronger confirmation may be warranted. Before recruitment or data transfer, actual approval or authorization may be required.
| Dependency |
Useful person or authority to verify with |
What to confirm |
| Participant recruitment |
Site lead, gatekeeper, community partner, recruitment coordinator |
Access, eligible pool, recruitment channel, timing, local constraints |
| Existing data |
Data owner, custodian, database administrator |
Variables, coverage, quality, identifiers, permissions, access timeline |
| Specialized analysis |
Relevant methodologist or specialist |
Design compatibility, data requirements, assumptions, expertise needed |
| Equipment or infrastructure |
Laboratory manager, technical staff, system administrator |
Capability, capacity, booking, cost, compatibility, restrictions |
| Ethics or institutional requirements |
Responsible ethics or research office |
Required review, documentation, sequence, expected process |
| Collaboration |
The collaborator themselves |
Role, availability, deliverables, timing, dependencies |
| Budget |
Service provider, finance office, project administrator |
Actual cost, hidden charges, payment process, lead time |
Watch Out
The person easiest to ask is not necessarily the person able to verify the assumption. Identify who actually controls the resource, permission, process, or expertise on which the study depends.
06 · What This Means for You
Turn assumptions into named verification tasks
Read through the research plan and underline every sentence that depends on another person, institution, resource, permission, or specialist capability. For each one, ask who can actually confirm it.
This turns vague uncertainty into manageable work. “Data access?” becomes “Ask the registry manager whether variables X, Y, and Z are available for 2023–2026 and what approval is required.” “Need statistician” becomes “Confirm whether the planned clustered design supports the proposed analysis and what sample information is needed.”
A simple decision framework
If the assumption concerns scientific or methodological adequacy
Verify it with someone who has the relevant methodological expertise.
If the assumption concerns access or permission
Verify it with the person or body that actually controls access.
If the assumption concerns a collaborator's contribution
Confirm the role, workload, timing, and deliverable directly with that collaborator.
If the assumption concerns institutional or ethics requirements
Check with the responsible authority rather than relying only on precedent or informal advice.
If failure of the assumption would force major redesign
Prioritize verification by consequence. You do not need twenty meetings to confirm minor details. Start with assumptions whose failure would make the study impossible, substantially change the design, threaten validity, create ethical problems, or destroy the timeline.
Once these assumptions have been checked, ask whether the project is realistic rather than merely logically coherent. That is the stronger feasibility test.
