I’m having trouble with our workforce planning forecasts in Dayforce cd-2023.1. We import monthly forecast data via CSV using the standard import tool, and while the import process completes successfully with no errors, the dashboard continues to show last month’s data.
The CSV file follows the documented schema with columns for employee_id, forecast_period, planned_hours, and cost_center. Import log shows all 1,247 records processed successfully:
Import Status: Complete
Records Processed: 1247
Records Failed: 0
Timestamp: 2025-05-22 08:30:15
But when I check the Workforce Planning dashboard, all the forecast widgets still display April data instead of the May forecasts I just imported. I’ve tried refreshing the browser, logging out and back in, and even clearing cache, but nothing updates. The backend data sync seems to be failing somewhere between the import completion and the dashboard display. Has anyone encountered this CSV schema validation issue or know what might be blocking the data refresh?
I had this exact problem last quarter and it turned out to be a cache issue at the analytics engine level, not the browser. The workforce planning dashboards cache their data sources separately from the UI cache. You need to go to System Administration > Analytics Configuration > Cache Management and specifically clear the ‘Workforce Planning Data Cache’. This is different from the general dashboard cache and won’t be cleared by browser refresh or user logout.
Another possibility is data validation rules blocking the activation. Even though the import shows successful, there might be business rules that prevent the forecasts from becoming active. For example, if your planned_hours exceed configured thresholds or cost_center codes don’t match active centers, the data stays in a pending state. Check System Logs > Data Validation for any warnings related to your import timestamp.
Check your CSV date format. Workforce planning in cd-2023.1 is very particular about date formats in the forecast_period column. It needs to be YYYY-MM-DD format, not MM/DD/YYYY. Even if the import says successful, incorrect date formats can cause the data to land in a staging table without being promoted to the active forecast tables.