The spectacular growth of event data is rapidly changing the Business Process Management (BPM) discipline. It makes no sense to focus on process modeling (including model-based analysis and modelbased process automation) without considering the torrents of factual data in and between today’s organizations. Hence, there is a need to connect BPM technology to the “internet of events” and make it more evidence-based BPM. However, the volume (size of data), velocity (speed of change), variety (multiple heterogeneous data sources), and veracity (uncertainty) of event data complicate matters. Mainstream analytics approaches are unable to turn data in to insights, once things get more involved. Therefore, they tend to focus on isolated decision problems rather than providing a more holistic view on the behavior of actors within and outside the organization. Fortunately, recent developments in process mining make it possible to use process models as the “lens” to look at (low) level event data. Viewing the internet of events through a “process lens” helps to understand and solve compliance and performance related problems. In fact, we envision a new profession —the process scientist— connecting traditional model-driven BPM with datacentric approaches (data mining, statistics, and business intelligence). Process mining provides the process scientist with a powerful set of tools and prepares BPM for a highly connected world where processes are surrounded by devices emitting events.
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