Building adaptive Salesforce case management with a metadata-driven framework

The Client, a global automotive services company with operations spanning fleet management, logistics, supply chain solutions, and commercial customer support, needed a more adaptive approach to managing high-volume licensing cases in Salesforce. Changes to the Who-To-License (WTL) value on an Order could leave associated cases with outdated classifications, requiring manual intervention. To address this, Datamatics implemented a metadata-driven framework to automate case reevaluation, maintain accurate classifications, and support scalable case processing.

Business Challenge: Managing changing case classifications

The Client's existing Salesforce licensing case management process lacked the ability to dynamically realign cases when the Who-To-License (WTL) value changed on an Order. Consequently, cases could retain outdated Category, Concern, and Project classifications, requiring manual review to ensure alignment with current business conditions.

The Client needed a scalable solution to automatically identify impacted cases, evaluate existing classifications, and determine whether cases required updates or recreation. The solution also needed to preserve eligible tasks and files, maintain data integrity, and support high-volume operations without disrupting real-time Order transactions or downstream processes.

The Solution: Metadata-driven Salesforce case reevaluation framework

Datamatics implemented a metadata-driven Who-To-License (WTL) Reevaluation Framework in Salesforce to automatically evaluate licensing cases whenever the WTL value changed on an Order. The framework evaluates applicable business conditions and determines whether an existing case should be updated or recreated to maintain accurate case classifications. When recreation is required, eligible tasks and files are transferred to the new Salesforce case, and the previous case is closed.

To support high-volume operations, Datamatics introduced staging, deduplication, and batch processing, enabling controlled case processing without affecting real-time Order transactions. Additionally, processing records capture case mappings, statuses, outcomes, and errors, providing traceability, auditability, and troubleshooting capabilities while supporting controlled Pega reprocessing.