Business Process Analytics

Doelstelling

In this special workshop on Business Process Analytics, different presenters will detail state-of-the art topics in Business Process Mining and Business Process Management. For a vast majority of organizations, Process Analytics has huge potential. This workshop's first objective is to make the audience familiar with the topic. Furthermore, the presenters will provide insights on how Process Analytics Techniques can actually benefit towards managing and improving business processes in practice.

Programma

1. Process Mining: Understanding and improving Desire Lines in Event Data (Wil van der Aalst)

Process Mining Techniques have matured over the last decade and more and more organizations started to use this new technology. The two most important types of process mining are process discovery (i.e. learning a process model from example behavior recorded in an event log) and conformance checking (i.e. comparing modeled behavior with observed behavior). In his talk Prof. Van der Aalst will introduce the main process mining concepts and illustrate these using various case studies. He will show that organizations can directly profit from these new ideas and start using process mining techniques today !

2. Automatic Derivation of Service Candidates from Business Process Model Repositories (Jan Mendling)

Although several approaches for service identification have been defined in research and practice, there is a notable lack of automatic analysis techniques. Prof. Mendling presents a new automated approach for the identification and detailing of service candidates. Its output is meant to provide a transparent basis for making decisions about which services to implement with which priority. The approach has been implemented and evaluated for an industry collection of process models. 

3. Extremely Visible & Incredibly Hidden: Event Types in Process Analytics (Jan Vanthienen)

Business Process Analytics and Mining aim to discover, analyze and improve business processes based on large logs of events observed in reality. Useful insights about the real business processes can be derived from these event logs. Process Analytics Techniques usually start from real, registered events, but there is more: in this presentation an event existence classification framework is presented, based on business criteria, that deals with various other types of events providing useful insights: invisible, false, unobserved and other types of events. This results in the identification of a number of interesting event types and business process analytics application areas.

4. Getting Tangible Insights into Business Processes by Merging Process Analytics and Conventional Data Mining (Jochen De Weerdt)

The simple application of traditional process analytics tools often fails to provide tangible insights into business processes. Oftentimes, this is caused by the fact that a lot of knowledge about the process is hidden or captured in less structured data. In his talk, a couple of solutions are proposed to leverage process analytics techniques with traditional data and text mining techniques. By combining multiple process information sources and by combining process and data analytics techniques, much more tangible insight can be uncovered so as to steer process improvement efforts.

5. Business Process Analytics and Mining for Governance, Risk & Compliance (Filip Caron)

Process mining techniques allow for an effective and efficient analysis of the audit trails of an information system. Consequently, these techniques can be considered as extremely suitable for supporting the process evaluation activities of stakeholders with a control function (i.e. management, internal auditor, external auditor and audit committee). The framework that will be presented in this talk, structures the relationship between process mining techniques, control functions and control function activities. This detailed analysis results in a clear guidance on the application of process mining in a control function setting, with a focus on enterprise risk management and compliance checking

6. Conclusions (Bart Baesens)