To achieve process intelligence, the system typically requires a mechanism (i.e., process intelligence engine) capable of providing information about how the data points were derived. This usually involves a second-order, multivariate analysis after the data points have been collected and correlated.
In software development, process intelligence is in contrast to development management and reporting systems that output data to static reports and dashboards. Even if agents can interact with the data in dashboard-oriented systems (sort, visualize in custom forms, export, etc.), they are usually unable to apply a development policy that analyzes the data points based on specific organizational goals. As a result, resources must be dedicated to consuming and interpreting the data in order to make decisions. This is opposed to gaining insight about the process through automated, prioritized findings via a process intelligence engine.
Logistics: When a PO is generated in a modern logistics system, several data points are collected about the delivery of a shipment from a PO to final acceptance, which my include:
There are several more data points that could potentially be collected. A process intelligence engine would be able to collect and process all this data to ensure that the PO was fulfilled quickly and without incident, and that the process for fulfilling POs is continuously improved.