Last night I went to sleep with a mental picture of how Fujitsu organizes its new autodiscovery process engine, which was poetically described to me by Hiro Makita and Keith Swenson for Fujitsu, here at the Gartner BPM Summit in Las Vegas.
The images I saw in my briefing drew a unique picture of how processes in most companies are presented to a BPM provider. Most of the time, finding out what a companies processes are can take several months, and the image of what request goes where, and who talks to who, and who orders what, etc., can be depicted by a confusing spaghetti-like diagram.
Instead, Fujitsu offers companies the chance to give them a data dump, and about a week later, an automated process discovery mechanism prepares a report so the company knows exactly what their processes are, both for average situations, and exceptions. It's pretty cool.
The briefing also included a confidential (and extremely impressive list) of customers that Fujitsu is working with to improve their mission-critical processes. They are some of the most important companies in the world.
***If you like this article, you can get all this coverage and more in our weekly ebizQ BPM Update. Sign up to receive it at this link.
It is important to not that ideas implemented in Fujitsu's software have been around for quite some time. There is an active scientific community working on process mining and there are other tools such as ProM and Protos supporting these ideas.
Process mining techniques allow for extracting information from event logs. For example, the audit trails of a workflow management system or the transaction logs of an enterprise resource planning system can be used to discover models describing processes, organizations, and products. Moreover, it is possible to use process mining to monitor deviations (e.g., comparing the observed events with predefined models or business rules in the context of SOX).
Process mining is closely related to BAM (Business Activity Monitoring), BOM (Business Operations Management), BPI (Business Process Intelligence), and data/workflow mining. Unlike classical data mining techniques the focus is on processes and questions that transcend the simple performance-related queries supported by tools such as Business Objects, Cognos BI, and Hyperion.