Ethics and do no harm
Informed consent, voluntary participation, confidentiality, respectful engagement, appropriate referral considerations and risk-sensitive methods.
Quality, ethics and data protection
Quality is designed into the assignment—not added at the end.
GRC integrates methodological rigour, participant protection, data quality and transparent review throughout the evidence cycle. The exact controls are adapted to the risk, population, method and client requirements of each assignment.
Our principle
Collect only what is needed, protect people and information, document decisions, check quality early, and communicate limitations clearly.
Quality pillars
Four safeguards across every stage of work.
These commitments provide a consistent quality logic while allowing project-specific protocols to reflect the context and client requirements.
Data quality and traceability
Tool testing, validation rules, training, supervision, daily review, cleaning logic, version control and documentation of analytical decisions.
Privacy and data minimisation
Collection limited to assignment needs, controlled access, secure handling practices and appropriate treatment of identifying or sensitive information.
Triangulation and review
Use of multiple sources and methods where appropriate, senior review, contradiction checks, limitation analysis and validation of key interpretations.
Across the lifecycle
What quality assurance looks like in practice.
Design
Clarify use, questions, indicators, sample logic, inclusion needs, ethical risks, data flows, analysis requirements and decision points.
Tool preparation
Review wording, translation needs, skip logic, response options, measurement consistency, field usability and digital constraints.
Training and pilot
Build shared interpretation of tools, consent, probing, safeguarding, field procedures and escalation paths; refine instruments before scale-up.
Field supervision
Monitor progress, completeness, duration, patterns, GPS or other permitted checks, qualitative depth and emerging operational risks.
Analysis
Document cleaning, coding and assumptions; test consistency; examine disaggregation; triangulate sources; separate evidence from interpretation.
Reporting
Use clear evidence chains, acknowledge limitations, distinguish findings from recommendations and check alignment with TOR questions and deliverables.
Context-sensitive research
Additional controls are introduced when the assignment carries additional risk.
Research involving children, displaced people, conflict-affected communities, protection concerns or sensitive personal information requires stronger safeguards than routine organisational consultation.
Where relevant, GRC works with the client to clarify required ethical approvals, safeguarding protocols, consent and assent arrangements, referral pathways, data-access restrictions and secure transfer or retention requirements. Requirements that depend on a client, funder or ethics body are agreed before implementation rather than assumed.
Quality requirements in your TOR?
Discuss an Assignment Share the standards, safeguards or data-security expectations that matter for your assignment.
GRC will reflect them in the methodology, field procedures, staffing and quality-assurance plan.