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24/06/2026 6:57 pm
TL;DR: ALCOA remains the core data integrity model for life sciences because compliance failures usually begin with weak process discipline, not bad intent, according to Collibra. The governance lesson is that traceability, auditability, and contemporaneous control matter as much as the system storing the record.
NHIMG editorial — based on content published by Collibra: Clinical and operational data is as trustworthy as the processes behind it
Questions worth separating out
A: They should define a single authoritative source for each record, then test every transfer, correction, and migration step against that source.
Q: Why do audit trails fail to prevent compliance findings even when they exist?
A: Audit trails fail when they are present but not operationally reviewed.
Q: What breaks when contemporaneous recordkeeping is replaced by later reconstruction?
A: The chain of evidence breaks because the record can no longer prove it was created at the time the event occurred.
Practitioner guidance
- Preserve contemporaneous change evidence Require timestamped updates, actor attribution, and source-state retention for every regulated record change.
- Validate handoffs between paper and electronic systems Map every conversion point where source records move between mediums or platforms, then test whether the authoritative version remains unambiguous after each transfer.
- Review audit trails as an operating control Schedule routine inspection of audit trails, exception logs, and correction workflows so data integrity evidence is actually used, not merely retained.
What's in the full article
Collibra's full blog post covers the operational detail this post intentionally leaves for the source:
- The article's GxP framework breakdown across GMP, GLP, GCP, GDP, and GDocP for regulated operating environments.
- The regulatory explanation of ALCOA and ALCOA+ in the context of FDA and EMA inspection expectations.
- The specific compliance failure patterns the author says keep reappearing in life sciences data programmes.
- The discussion of how remote audits and AI-assisted inspection are changing the visibility of poor data practices.
👉 Read Collibra's analysis of ALCOA, GxP, and data integrity governance →
ALCOA and GxP data integrity: what IAM teams need to watch?
Explore further
25/06/2026 3:59 am
ALCOA is a trust model, not a documentation slogan: the article correctly frames data integrity as a chain of evidence, not a filing exercise. Attributable, contemporaneous, and accurate records are only meaningful when the process around them preserves actor identity, timing, and source state. The practitioner conclusion is that record trust has to be engineered into workflow, not inspected into existence later.
A few things that frame the scale:
- Only 44% of developers are reported to follow security best practices for secrets management, exposing a significant developer behaviour gap, according to The State of Secrets in AppSec.
- The average estimated time to remediate a leaked secret is 27 days, even though 75% of organisations express strong confidence in their secrets management capabilities.
A question worth separating out:
Q: Who should own data provenance in a GxP programme?
A: A named control owner should own provenance for each critical dataset, with responsibility for change approval, audit trail review, and lifecycle validation. Provenance cannot be everyone’s job in practice, because shared responsibility often becomes no responsibility. Clear ownership is what turns governance policy into accountable operations.
👉 Read our full editorial: ALCOA data integrity exposes the governance gap in clinical records
