We’re experiencing inconsistent profitability data in our project accounting reports. Our SuiteAnalytics dashboards show revenue and cost figures that don’t match the actual project records when we drill down. The issue seems related to custom fields we created for tracking client-specific billing rates and resource allocations - these fields appear in some reports but are missing from others.
We’ve built several custom project profitability fields using SuiteBuilder to capture margin calculations and utilization metrics. However, when we try to expose these fields in our executive dashboard, only some of them appear in the field picker. The missing fields are critical for our monthly financial reviews, and we’re struggling to validate which data sources are reliable.
Has anyone dealt with custom field visibility issues in SuiteAnalytics workbooks? We need to ensure our dashboard validation process catches these gaps before reports go to leadership.
Building on everyone’s excellent troubleshooting, let me provide a comprehensive approach to resolve your custom field exposure and dashboard validation issues.
Custom Field Configuration in SuiteBuilder:
First, systematically audit all custom fields used in profitability calculations. In Customization > Lists, Records, & Fields, verify each field has:
- ‘Store Value’ enabled (critical for SuiteAnalytics indexing)
- ‘Show in List’ checked (makes fields available in dataset field pickers)
- Appropriate ‘Search Level’ set to ‘Run’ or ‘Report’ for performance
For your billing rate and resource allocation fields specifically, ensure they’re defined on the correct record type (Project vs Transaction vs Custom Record) because SuiteAnalytics dataset joins depend on proper record relationships.
Dashboard Validation Process:
Implement a three-tier validation:
- Field-level validation: Create a saved search listing all custom fields with their analytics settings. Filter for fields where ‘Store Value’ = false or ‘Analytics Enabled’ = false. This becomes your audit checklist.
- Data-level validation: Build reconciliation workbooks that compare SuiteAnalytics aggregations against native saved search totals. Any variance indicates indexing or formula issues.
- Role-level validation: Test dashboards with each executive role to verify field visibility. Use ‘View As’ functionality to simulate their permissions.
SuiteBuilder Configuration Best Practices:
For complex profitability metrics, consider creating a custom record type specifically for project analytics. This gives you complete control over:
- Field indexing and analytics exposure
- Scheduled workflows to populate calculated fields
- Independent permission management separate from transaction access
Link this custom record to projects via a custom relationship field, then build your SuiteAnalytics datasets from this analytics-optimized structure.
Historical Data Handling:
As mentioned, you’ll need to re-process historical records. For your project accounting data, I recommend:
- Create a saved search identifying all projects needing re-indexing
- Build a Map/Reduce script that processes projects in batches of 100
- In the map stage, load each project and perform a minimal update (like setting a ‘Last Analytics Sync’ custom field)
- This triggers NetSuite’s analytics indexing without changing business data
Schedule this script during off-peak hours and monitor governance usage. Most importantly, validate a small batch first to ensure your profitability calculations populate correctly before processing your entire project history.
Ongoing Monitoring:
Set up a scheduled saved search that alerts you when new custom fields are created without analytics enablement. This prevents future visibility gaps in your executive dashboards.
Yes, historical data won’t automatically populate. NetSuite’s analytics engine only indexes data going forward from when you enable the ‘Store Value’ option. For historical records, you have two options: either run a mass update to touch those records (which triggers re-indexing), or use a SuiteScript scheduled script to systematically update the records in batches. The mass update is faster for smaller datasets, but for thousands of project records, the scripted approach gives you better control and avoids governance limits.
Also verify your SuiteAnalytics dataset permissions. Even if fields are configured correctly in SuiteBuilder, users need explicit access through role permissions. Navigate to Setup > Users/Roles > Manage Roles and check the ‘Analytics’ tab. Make sure the roles accessing your dashboards have ‘View’ permissions on the custom record types and fields. I’ve troubleshot situations where executives couldn’t see margin data because their role lacked analytics permissions on custom project fields, even though they had full transaction access.
Thanks both - I checked the Store Value settings and found three fields that weren’t configured for analytics indexing. However, I’m still seeing inconsistencies in historical data. Do we need to trigger a re-index of past transactions after enabling these settings?