This curriculum reflects the scope typically addressed across a full consulting engagement or multi-phase internal transformation initiative.
Module 1: Foundations of Information Lifecycle Governance under ISO 16175
- Map organizational roles and responsibilities to ISO 16175’s three-part governance framework for accountability and audit readiness.
- Evaluate the alignment of existing records management policies with ISO 16175’s principles of authenticity, reliability, and usability.
- Identify jurisdictional and regulatory dependencies that constrain or extend the application of ISO 16175 in multinational operations.
- Assess trade-offs between centralized control and decentralized implementation in governance model design.
- Define thresholds for metadata completeness required at each lifecycle stage per ISO 16175-2 specifications.
- Establish decision criteria for classifying datasets as “business-critical” under ISO 16175’s risk-based retention model.
- Analyze failure modes in governance structures that result in non-compliant dataset disposal or retention.
Module 2: Dataset Classification and Metadata Architecture
- Design classification schemes that enforce ISO 16175’s mandatory metadata elements (e.g., provenance, context, structure).
- Implement metadata inheritance rules across dataset versions to maintain auditability and chain of custody.
- Balance granularity of classification against operational overhead in high-volume data environments.
- Integrate automated metadata extraction tools with legacy systems while ensuring compliance with ISO 16175-1 requirements.
- Validate metadata integrity during dataset migration or format conversion using checksum and schema validation protocols.
- Define retention triggers based on event-driven (e.g., contract end) versus time-based (e.g., fiscal year) metadata fields.
- Diagnose inconsistencies in metadata application across departments and implement corrective governance workflows.
Module 3: Designing Capture and Ingest Workflows
- Specify technical and procedural requirements for capturing datasets at point of creation to meet ISO 16175’s authenticity criteria.
- Configure ingestion pipelines to enforce mandatory metadata entry without disrupting operational workflows.
- Assess the risk of data loss during manual versus automated capture processes in hybrid work environments.
- Implement validation rules that reject non-compliant datasets at ingest based on schema, format, or metadata gaps.
- Integrate capture workflows with enterprise content management (ECM) and electronic document and records management systems (EDRMS).
- Measure capture latency and success rates to identify systemic bottlenecks in data onboarding.
- Document exceptions and waivers for datasets captured outside standard workflows, including justification and risk assessment.
Module 4: Managing Active Use and Access Control
- Define role-based access policies that align with ISO 16175’s principle of minimal necessary disclosure.
- Implement audit logging for dataset access and modification to support forensic reconstruction and compliance reporting.
- Balance data utility for analytics with access restrictions required for privacy and regulatory compliance.
- Configure version control mechanisms that preserve prior states of datasets without enabling unauthorized restoration.
- Evaluate performance impacts of access controls in distributed or cloud-hosted environments.
- Monitor for anomalous access patterns indicative of policy violations or insider threats.
- Establish procedures for temporary access elevation during incident response or audit support.
Module 5: Ensuring Integrity During Retention and Storage
- Design storage architectures that maintain dataset integrity across technology refresh cycles and media migrations.
- Implement fixity checks and digital signatures at defined intervals to detect unauthorized alterations.
- Specify retention periods based on legal, fiscal, and operational requirements mapped to ISO 16175-3 guidelines.
- Evaluate cost-performance trade-offs between on-premises, cloud, and hybrid storage for long-term retention.
- Plan for format obsolescence by defining migration triggers and validation steps for format normalization.
- Enforce retention holds during legal proceedings or regulatory investigations without disrupting automated disposal.
- Measure storage sprawl and identify datasets eligible for early disposal or archival compression.
Module 6: Disposition Planning and Execution
- Develop disposition schedules that integrate business, legal, and regulatory retention requirements.
- Implement automated disposition workflows with multi-level approval controls to prevent premature deletion.
- Validate that disposal methods (e.g., secure wipe, cryptographic erasure) meet jurisdictional standards.
- Document disposition actions with immutable audit trails for regulatory and internal review.
- Assess risks of data resurrection from backups or caches after formal disposition.
- Manage stakeholder objections to disposition through formal review and escalation procedures.
- Conduct periodic disposition audits to verify compliance and identify policy gaps.
Module 7: Integration with Broader Data Governance and Compliance Frameworks
- Align ISO 16175 practices with enterprise data governance policies, including data quality and stewardship.
- Map ISO 16175 controls to overlapping regulations (e.g., GDPR, FOIA, HIPAA) to reduce duplication and gaps.
- Integrate lifecycle status into data catalogs for visibility across data discovery and usage platforms.
- Coordinate with privacy officers to ensure personal data handling conforms to both ISO 16175 and privacy-by-design principles.
- Assess impact of data minimization requirements on dataset retention and access policies.
- Develop cross-functional escalation paths for conflicts between operational needs and compliance mandates.
- Measure compliance efficiency through metrics such as policy exception rates and audit finding resolution time.
Module 8: Monitoring, Auditing, and Continuous Improvement
- Design audit programs that validate adherence to ISO 16175 across all lifecycle stages.
- Implement continuous monitoring for key control points (e.g., metadata completeness, access logs, fixity checks).
- Define KPIs for lifecycle management, including retention accuracy, disposition timeliness, and capture completeness.
- Conduct root cause analysis of compliance failures and implement corrective action plans.
- Update policies in response to technological changes (e.g., AI-generated records, blockchain) and regulatory shifts.
- Facilitate management reviews of lifecycle performance with decision-ready dashboards and risk summaries.
- Benchmark organizational maturity against ISO 16175 implementation levels and industry peers.