Data can be propagated when creating which types of cases?

Data propagation refers to the transfer of data from one case to another, which can be particularly useful in maintaining consistency across related cases. When creating subcases and spin-off cases, data propagation is a significant feature in Pega.

Subcases are directly related to their parent cases; when a subcase is created, it often inherits data from the root case. This is crucial because subcases usually deal with specific tasks or segments of the overall issue represented by the root case.

Spin-off cases, on the other hand, are created from an existing case but can take a different direction while still retaining relevant data from their source case. This allows for flexibility and adaptability in managing different case workflows while keeping essential information available from the originating case.

Both types of cases are designed to facilitate the efficient sharing and management of data among them, thus making the propagation of data essential for operational coherence in case management.