Future Date Analysis

Plauti Context Analysis Types

Last published at: June 8th, 2026

Identify records with date values set in the future, to detect potentially incorrect dates.

 

The Future Scans analysis scans date and date-time fields for values that fall after today. The results are grouped by date range, so you can check for dates in the future in general, or dates close-by or far in the future.

Use this analysis to surface data entry errors, broken integrations, and input issues that could affect reporting accuracy, SLA calculations, or automation logic.

This analysis marks future dates as an anomaly by default. If you have date fields where future dates are the norm, and you want to scan for dates that are incorrectly in the past, you can either invert the configured threshold for those fields, or use the Past Date Threshold or Date Range Analysis instead. 
In a future version it will be possible to get notified at certain thresholds, opening up more use cases for this analysis type.

Configuration

Set a threshold for what constitutes a good, warning level, or critical future date rate. For many fields that you apply a Future Date analysis to, such as birth dates or contract dates, you'll want to have as few records with a future date as possible. This would mean for example a good future date rate is 5% or less, warning level would be between 5-20%, and anything over 20% would be critical.

For those cases where having a date in the future is regarded as good, such as renewal dates, you can reverse the threshold signalling by clicking the Reverse button. 

Detailed Job Results

The bar chart shows the percentage of records with a date in the future, per field. Date-time fields with a time later today are not included. Records with an empty value for the field are not taken into account. 

The doughnut chart shows the rate of future dates by time range.

The results table below shows the future date rate per field, with the percentage of future dates labeled green (Good), orange (Warning) or red (Critical) according to the threshold settings.

Key Insights

  • Data plausibility by field: Identify which date fields contain values that logically should not be in the future, such as Birth Date or Contract Signed Date.
  • Data entry errors: Find typos, mis-clicks, or more systematically: broken forms or integrations writing future dates where they don't belong.
  • Process misuse: Dates might have been set in the future on purpose.
  • Impact on reporting and automation: Identify records where future-dated values could distort processes such as SLA calculations or contract reporting.
     
Scenario Actions
Future dates set by accident
  • Add validation rules or flow checks
  • Cross-reference results by field and object to identify the likely source
  • Fix forms, actions and integrations that systematically write future dates
  • Correct or clear future dates, for example with Plauti Manipulate
Future dates set on purpose
  • Find out why this is done and decide if processes need to be adjusted
Protecting reporting and automation
  • Exclude or flag records with invalid future dates in operational reports, dashboards, SLAs, contract logic, etc.