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Specialized Siebel Assignment Manager Features

Siebel Assignment Manager provides several specialized features. A brief description of each is provided in the following subtopics; some features are also described in greater detail in other chapters of this guide.

Mobile Assignment

Mobile assignment allows mobile users to make interactive and dynamic assignments. Changes to a Mobile Web Client's local database are queued and are applied to the server the next time the mobile user synchronizes.

Assignment Manager automatically performs interactive assignments made by the mobile user after synchronization. Changes to assignment rules and objects are updated, and affected objects are reassigned dynamically.

NOTE:  Mobile users running Assignment Manager in interactive mode do not make real-time assignments, because interactive assignments made by mobile users are not applied to the server until they resynchronize.

Mobile users may also be assigned records on the server and will retrieve those assignments when they synchronize.

Delegated Assignment

Delegated assignment provides assignment administrators (AAs) the ability to delegate rule administration to other administrators and partners to route leads, activities, accounts (and other assignment objects) to employees or positions. These delegates are known as delegated administrators (DAs). A DA can, in turn, delegate assignment rule administration to others.

This hierarchical assignment feature is well-suited to sales organizations and organizations that work closely with partners.

Assignment Load Splitter Configuration

The assignment load splitter configuration feature provides assignment administrators (AAs) a tool for performing batch assignment for a significant number of objects. It eliminates the need for AAs to plan and implement complex load distribution logic.

You can configure Assignment Manager to automatically split objects for processing into separate batches and submit those batch requests to multiple servers. This type of configuration balances the task load across multiple servers, which in turn improves processing performance.