When information monitoring gathers relevant information from data sources, mediation is invoked to aggregate and map data into concepts used by the decision model. This transformed decision-relevant data is sent to a decision maker and to the model. Using the updated data, sensitivity analysis is performed again, yielding a possibly different set of information needs. These are translated to a new set of retrieval requests. In this way, the monitoring process continually provides information relevant to the current decision problem.
Notification takes place via pop-up alerts, email, or alphanumeric pager.
Another key lesson was the existence of a semantic gap between decision model concepts and those typically represented in real world information sources. For example, sensitivity analysis against the decision model might reveal that Loading Facility Status is a critical information item. However, there is probably not a single database item that indicates this. Instead, Loading Facility Status might be a compilation of several data items about numbers and condition of fork lifts, availability of personnel, facilities and supplies to support them, etc. While complete automation is beyond the reach of today's technology, the development of semi-automated tools for bridging the semantic gap is a promising area for future research.