How To Fix PG203 - Record valid from &1 to &2 delimited at start

SAP Error Message - Details

• Message type: E = Error

• Message class: PG - Error Messages for Master Data Programs

• Message number: 203

• Message text: Record valid from &1 to &2 delimited at start

What causes this issue?

You have extended the valid to date of an infotype record with time
constraint "1" or "2" or you have created or copied a new infotype
record in such a way that the new period overlaps with another infotype
record.

System Response

The start date of the next record is automatically set to the following
day of the validity period of the current infotype.

How to fix this error?

Ensure that the delimited record is not validated automatically for the
new period.
If necessary, check whether delimiting the existing infotype record has
caused data inconsistencies.

Procedure for System Administrators

The system issues an error message and will not allow you to continue with this transaction until the error is resolved.

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message PG203 - Record valid from &1 to &2 delimited at start ?

  The SAP error message PG203 "Record valid from &1 to &2 delimited at start" typically occurs in the context of managing time-dependent data in SAP, particularly in the area of personnel administration or organizational management. This error indicates that there is an issue with the validity period of a record, where the start date or end date is not properly defined or overlaps with existing records.
  
  Cause:
  
  Invalid Date Ranges: The validity period defined for a record overlaps with another record or is not properly set. For example, if you are trying to create or modify a record with a validity period that starts before the end of an existing record, this error will occur.
  Missing Dates: If either the start date or end date is missing or incorrectly formatted, the system will not be able to process the record.
  Data Consistency Issues: There may be inconsistencies in the data that violate the rules