This can be easily demonstrated with an example. Let us look at a simple dimension hierarchy of Sales Office, Salesperson, and Client. If the exception is a poor average rate to rate-card ratio for a Sales Office, then this may be traced to the Salesperson that is underperforming, and then the Client or Clients that may not be delivering revenues - all by simple drilling on the exception values. The Client or Clients that “caused” the poor Sales Office average rate can then be identified, and become the focus of appropriate corrective “action”.

Careful consideration of the powerful business relationships that govern exception analysis for the Media industry should dictate the Causality Hierarchies offered by your Business Intelligence system. This in turn defines the data relationships implemented by the media data warehouse schema. It is also another example of where the critical analysis expected from the Media Business Intelligence system through the OLAP cube defines the relationships required in the data warehouse Star Schema, and thus the ETL to transform the source data into this required schema.