How To Fix CRM_SERVICE_I303 - Service parts could not be predicted

CRM_SERVICE_I303 - Overview

• Message type: E = Error

• Message class: CRM_SERVICE_I - Service Item - Message Class

• Message number: 303

• Message text: Service parts could not be predicted

What causes this issue?

Service parts could not be predicted for a service item for one of the
following reasons:
You have not entered one or more of the following:
A service product for the item
A reference object for which product master data can be determined
A first-level category
No prediction data is available.
The threshold number of data records required for prediction has not
been reached.
A technical error occurred during the retrieval of prediction data.

System Response

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

How to fix this error?

Enter any missing data in the item or transaction. Otherwise, contact
your system administrator.

Procedure for System Administrators

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message CRM_SERVICE_I303 - Service parts could not be predicted ?

  The SAP error message CRM_SERVICE_I303 indicates that service parts could not be predicted for a particular service order or request. This error typically arises in the context of service management within SAP CRM (Customer Relationship Management) when the system is unable to determine the necessary spare parts for a service activity.
  Causes:
  
  Missing Master Data: The required master data for the service parts, such as material master records or service parts lists, may be incomplete or missing.
  
  Configuration Issues: The configuration settings for service parts prediction may not be set up correctly in the system.
  Incorrect Service Order: The service order may not have the necessary details or may be incorrectly configured, leading to the inability to predict parts.
  Insufficient Forecasting Data: If there is not enough historical data or forecasting information available, the system may struggle to predict the required service parts.
  Authorization Issues: Users may not have the necessary authorizations to access the data