Orphaned Record Detection

Orphaned Record Detection checks lookup (relationship) fields on your records for empty values: records that should reference a parent but don't. The percentage of records with an empty lookup value for a given field is called the orphan rate.

Use this analysis to maintain referential integrity, and spot incomplete records before they cause problems downstream in reporting, automation, or AI.

Orphaned Record Detection or Fill Rate?

The Fill Rate analysis measures empty values across any field type. Orphaned Record Detection is specific to lookup fields, and frames the result as a relationship-integrity metric (the orphan rate) rather than a general completeness score. Use Orphaned Record Detection when you specifically care about broken or missing parent references; use Fill Rate for general field completeness.

Configuration

Set a threshold for what constitutes a good, warning level, or critical orphan rate. For most fields that you apply an Orphaned Record Detection analysis to you'll want to have as few lookup fields empty as possible. This would mean for example a good orphan rate is 5% or less, warning level would be between 5-15%, and anything over 15% empty would be critical.

Detailed Job Results

The Orphaned Records per Field bar chart shows the percentage of records with an empty lookup value for each anayzed field.
Below, the Field Details table displayes for each field the total number of analyzed records ( # Records Analyzed), the number of records with an empty value for that field ( # Orphaned Records), and the percentage of orphaned records labeled in red/amber/green based on your configured threshold.

Key Insights

• Relationship completeness: find out which lookup fields are consistently populated and which are frequently left empty.
• Trust level for automation and AI: a low orphan rate indicates a field is reliable enough to use in reports, flows, or AI models without unexpected results.
• Reality check on relationships: confirms whether a lookup field is actually being used as intended across your records, not just configured.
• Cleanup candidates: a high orphan rate on a field that should always be filled points to a data entry, integration, or automation gap worth investigating.

Recommended Actions

Scenario	Actions
Critical lookup field has a high orphan rate	- Make the field required on page layouts and flows. - Add validation rules so that all entry points (UI, API, imports) enforce it. - Check integrations that create or update these records. - Re-run the analysis after fixes to confirm improvement.
Non-essential lookup field has a very high orphan rate	- Decide whether to fix or retire the field. - If retiring, remove it from page layouts and mark it deprecated in the field description.
Required lookup field isn't close to a 0% orphan rate	- Analyze the empty fields to see whether this is a legacy problem or a recent issue.- If it still occurred recently, audit all entry points (forms, API, flows, imports) for ways the field can be bypassed. - Monitor the orphan rate trend until it stabilizes near 0%.
Preparing a lookup field for AI or reporting use	- Define a maximum acceptable orphan rate for that use case. - Only include fields below that threshold in AI models or core dashboards/KPIs.