Titlebook: BPM - Driving Innovation in a Digital World; Jan vom Brocke,Theresa Schmiedel Book 2015 Springer International Publishing Switzerland 2015

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Thinking Tri-laterally About Business Processes, Services and Business Models: An Innovation Perspec process) represents a “value proposition” to the service consumer (client) that enables them to “get their job done.” A service is, in effect, a mini-business or “business within a business” and therefore is implicitly governed by a business model of the process/service owner, the “CEO” of that bus

tolerance

Process Innovation with Disruptive Technology in Auto Insurance: Lessons Learned from a Smartphone-Bovation behaviour. This chapter provokes the critical thinking with regard to the exploration and exploitation of disruptive technology into process innovation. Further, the chapter contributes new knowledge to the research of process innovation with disruptive digital technologies.

acrimony

Extracting Event Data from Databases to Unleash Process Mining(e.g., BPM/WFM systems), most information systems do not record events explicitly. Cases and activities only exist implicitly. However, when creating or using process models “raw data” need to be linked to cases and activities. This paper uses a novel perspective to conceptualize a .. Starting from

蹒跚

Enabling Process Innovation via Deviance Mining and Predictive Monitoringr process performance. Deviance mining deals with the analysis of process execution logs offline in order to identify typical deviant executions and to characterize deviance that leads to better or to worse performance. Predictive monitoring meanwhile aims at predicting—at runtime—the impact of acti

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Sanjaya Mishra,Pradeep K. Misraovation behaviour. This chapter provokes the critical thinking with regard to the exploration and exploitation of disruptive technology into process innovation. Further, the chapter contributes new knowledge to the research of process innovation with disruptive digital technologies.

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Carl Van Dyke,Marc Meketon,Bruce W. Pattyr process performance. Deviance mining deals with the analysis of process execution logs offline in order to identify typical deviant executions and to characterize deviance that leads to better or to worse performance. Predictive monitoring meanwhile aims at predicting—at runtime—the impact of acti