perindividual

Perindividual is a term used in data governance and analytics to denote actions, analyses, or measurements performed at the level of a single person rather than for a population. The term highlights granularity and person-centered handling of data, often in contrast to aggregate or cohort-based approaches. Because it is not standardized, perindividual can appear in several spellings, such as per-individual or per individual, depending on the publication.

In practice, perindividual concepts appear in contexts such as personalized services, privacy-preserving analytics, and accountability frameworks. Applications may include perindividual profiling or scoring for recommendations or risk assessment, perindividual consent logs for data processing, and perindividual treatment or intervention planning in healthcare settings. In each case, decisions are intended to reflect the merits or preferences of an individual rather than a group.

Privacy and ethics considerations are central. Treating data at the perindividual level can improve relevance and consent management, but it also raises risks of re-identification, profiling harms, and unequal treatment if data quality varies by person. Effective use typically requires privacy-by-design measures, data minimization, transparent disclosure of criteria for individual-level decisions, and robust access controls.

Limitations and challenges include data quality dependence on single records, scalability and performance costs, potential biases in individual data, and governance overhead. Clarifying the intended use and ensuring alignment with applicable data protection laws are common governance tasks when adopting a perindividual approach.

See also: individual-level data, user-centric analytics, personalized services.