Automated data retention policy for document management ensuring compliance

PLM Aras Innovator
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1

I want to share our implementation of an automated data retention policy for document management in Aras 13.0. We were facing a significant challenge: our document repository had grown to over 500,000 documents, many of which were obsolete or past their required retention periods. Manual cleanup was consuming significant IT resources and creating compliance risks because we couldn’t consistently enforce retention policies across different document types.

Our regulatory requirements mandate specific retention periods: quality records must be kept for 10 years, design documents for 7 years, and general correspondence for 3 years. We needed an automated solution that would identify documents eligible for archival or deletion based on their lifecycle state and retention period, while maintaining a complete audit trail for compliance purposes.

The solution we implemented leverages automated retention workflows triggered by lifecycle state transitions, with built-in audit logging to track every retention action. This has dramatically reduced manual cleanup effort while ensuring consistent compliance with our retention policies. I’ll walk through the technical implementation and the business benefits we’ve achieved.

2

Let me provide a comprehensive overview of our automated data retention implementation, addressing all the key focus areas:

Automated Retention Workflows

The foundation of our solution is a set of automated workflows that execute based on lifecycle state transitions and scheduled tasks. Here’s the architecture:

  1. Document Classification and Retention Rules We created a custom ItemType called “Retention_Policy” that defines retention periods for each document classification:
  • Quality Records: 10 years from Obsolete date
  • Design Documents: 7 years from Obsolete date
  • General Correspondence: 3 years from Obsolete date

Each Document item has a relationship to its Retention_Policy, which is set automatically based on the document’s classification property.

  1. Lifecycle State Workflow We enhanced the standard Document lifecycle with additional states:
  • Released (active use)
  • Obsolete (superseded but within retention period)
  • Eligible_for_Archive (retention period expired, ready for archival)
  • Archived (moved to archive vault)
  • Purge_Eligible (ready for permanent deletion, if applicable)

The workflow automation happens through server methods attached to lifecycle transitions:

Pseudocode for retention calculation:


// Executed on transition to Obsolete state
1. Get document's Retention_Policy relationship
2. Calculate expiration_date = obsolete_date + retention_years
3. Create scheduled workflow to check expiration_date
4. When expiration_date reached, auto-transition to Eligible_for_Archive
5. Log all actions to Retention_Audit table
  1. Scheduled Retention Jobs We implemented a nightly scheduled task that runs at 2 AM to process retention actions:
  • Query all documents in Eligible_for_Archive state
  • Verify retention period has elapsed
  • Move document files to archive vault location
  • Update document state to Archived
  • Generate retention action report

Lifecycle State Triggers

The state transition triggers are implemented as server-side methods that execute automatically:

  1. OnBeforePromote Method (Obsolete → Eligible_for_Archive) This method validates that the retention period has truly elapsed and checks for any hold flags:

Pseudocode for state transition validation:


// OnBeforePromote validation logic:
1. Check if current_date >= calculated_expiration_date
2. Verify document has no litigation_hold flag set
3. Confirm no active references from unreleased items
4. If all checks pass, allow transition to Eligible_for_Archive
5. If checks fail, block transition and log reason
// See Aras Server Methods Guide for event implementation
  1. OnAfterPromote Method (Eligible_for_Archive → Archived) This method handles the physical archival process:
  • Moves vault files to archive storage location
  • Updates file references in database
  • Creates archive index entry for retrieval
  • Sends notification to document owner
  1. Exception Handling for Litigation Holds We added a custom property “litigation_hold” (boolean) to the Document ItemType. When this flag is set, the automated retention workflow is bypassed:

Pseudocode for hold flag check:


// Check for retention holds:
1. Query document.litigation_hold property
2. If hold flag = true, skip all retention actions
3. Send alert to compliance team for review
4. Document remains in current state until hold released
5. Log hold status to audit trail

Audit Logging Implementation

Compliance was our primary driver, so we built comprehensive audit logging:

  1. Custom Retention_Audit ItemType We created a dedicated audit table to track all retention actions:
  • document_id (reference to source document)
  • action_type (calculated_expiration, state_transition, archived, purged)
  • action_date (timestamp)
  • performed_by (user or system account)
  • previous_state / new_state
  • retention_policy_applied
  • notes (any exceptions or special handling)

Every retention action creates an entry in this audit table. The audit records are never deleted and have their own 25-year retention policy.

  1. Audit Report Generation We created scheduled reports that generate monthly retention activity summaries:
  • Documents archived in period
  • Documents purged in period
  • Documents on litigation hold
  • Exceptions requiring review

These reports are automatically distributed to our compliance team and stored in the audit vault.

  1. Compliance Proof for Deletion For documents that must be permanently deleted (privacy regulations), we handle it carefully:
  • Before deletion, create detailed audit record including document metadata snapshot
  • Generate deletion certificate with document details, deletion date, authorization
  • Store deletion certificates in permanent audit archive
  • Physically delete vault files and database records
  • Maintain deletion certificate as proof of compliant disposal

Database and Storage Management

We implemented a tiered storage approach to manage database growth:

  1. Active Vault (SSD storage): Released and Obsolete documents
  2. Archive Vault (cheaper disk storage): Archived documents
  3. Purge Process: Permanent deletion for expired privacy-sensitive documents

The archive process doesn’t delete database records - it moves vault files to cheaper storage and updates the file reference. Only documents subject to mandatory purge are physically deleted from the database.

Business Benefits Achieved

After 8 months of operation, we’ve seen significant improvements:

  • Reduced manual cleanup effort by 85% (from 40 hours/month to 6 hours/month)
  • Archived 127,000 documents, reducing active vault storage by 35%
  • Achieved 100% compliance with retention policy in latest audit
  • Reduced storage costs by $18,000 annually through tiered storage
  • Eliminated compliance risks from missed retention deadlines

The initial implementation took about 6 weeks with one developer and a compliance analyst. The ongoing maintenance is minimal - mainly monitoring the scheduled jobs and handling exceptions for litigation holds.

Recommendations for Implementation

If you’re implementing something similar:

  1. Start with a pilot on one document classification to validate the workflow
  2. Build comprehensive audit logging from day one - retrofitting is painful
  3. Include exception handling for litigation holds before going live
  4. Test the archival process thoroughly with vault file movement
  5. Create clear documentation for compliance team on how to apply holds and review exceptions
  6. Schedule regular reviews of archived documents to ensure retrieval process works

The key to success was treating this as a compliance project, not just an IT automation project. We involved our compliance and legal teams from the beginning, which ensured we built the right audit capabilities and exception handling. The automated workflows have transformed our document retention from a manual, error-prone process into a reliable, auditable system that runs with minimal intervention.

3

I’m interested in the database impact of this automation. Are you physically deleting records from the database, or just marking them as deleted? And how are you managing the vault files - are they being purged as well? We’re concerned about database growth and vault storage costs.