Mining the Organisational Perspective in Agile Business Processes

Agile processes depend on human resources, decisions and expert knowledge, and they are especially versatile and comprise rather complex scenarios. Declarative, i.e., rule-based, process models are well-suited for modelling these processes. Although there are several mining techniques to discover such declarative process models from event logs, they put less emphasis on the organisational perspective, which specifies how resources are involved in the activities. As a consequence, the resulting models do not specify who should execute which task and with which constraint (like separation of duties) in mind. In this paper, we propose a process mining approach to discover resource-aware, declarative process models. Our specific contribution is the extraction of complex rules for resource assignment that integrate the control-flow and organisational perspectives. Our experiments demonstrate the expressiveness of the mined rules with a reference to the Workflow Resource Patterns and a real-world use case.

[1]  Wil M. P. van der Aalst,et al.  Analyzing Resource Behavior Using Process Mining , 2009, Business Process Management Workshops.

[2]  Hajo A. Reijers,et al.  UnconstrainedMiner: Efficient Discovery of Generalized Declarative Process Models , 2013 .

[3]  Manfred Reichert,et al.  RALph: A Graphical Notation for Resource Assignments in Business Processes , 2015, CAiSE.

[4]  Jan Mendling,et al.  Discovering Target-Branched Declare Constraints , 2014, BPM.

[5]  A. Sperduti,et al.  User-guided discovery of declarative process models , 2011 .

[6]  Fabrizio Maria Maggi.  Declarative Process Mining with the Declare Component of ProM , 2013, BPM.

[7]  Christoph Bussler,et al.  Organisationsverwaltung in Workflow-Management-Systemen , 1998 .

[8]  Weidong Zhao,et al.  Process Mining from the Organizational Perspective , 2014 .

[9]  Jan Mendling,et al.  Imperative versus Declarative Process Modeling Languages: An Empirical Investigation , 2011, Business Process Management Workshops.

[10]  Stefan Jablonski,et al.  Towards a common platform for the support of routine and agile business processes , 2014, 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing.

[11]  Wil M. P. van der Aalst,et al.  Towards comprehensive support for organizational mining , 2008, Decis. Support Syst..

[12]  Wil M. P. van der Aalst,et al.  Declarative workflows: Balancing between flexibility and support , 2009, Computer Science - Research and Development.

[13]  Boudewijn F. van Dongen,et al.  XES, XESame, and ProM 6 , 2010, CAiSE Forum.

[14]  Stefan Jablonski,et al.  Supporting Rule-Based Process Mining by User-Guided Discovery of Resource-Aware Frequent Patterns , 2014, ICSOC Workshops.

[15]  Mark Strembeck,et al.  Bridging the gap between role mining and role engineering via migration guides , 2013, Inf. Secur. Tech. Rep..

[16]  Marco Montali,et al.  Discovering Data-Aware Declarative Process Models from Event Logs , 2013, BPM.

[17]  Stefan Jablonski,et al.  MOBILE: A Modular Workflow Model and Architecture , 1994 .

[18]  Wil M. P. van der Aalst,et al.  Analysis of Patient Treatment Procedures , 2011, Business Process Management Workshops.

[19]  Charles L. Forgy,et al.  Rete: a fast algorithm for the many pattern/many object pattern match problem , 1991 .

[20]  Mark Strembeck,et al.  A Case Study on the Suitability of Process Mining to Produce Current-State RBAC Models , 2012, Business Process Management Workshops.

[21]  Wil M. P. van der Aalst,et al.  Workflow Resource Patterns: Identification, Representation and Tool Support , 2005, CAiSE.

[22]  Richard Hull,et al.  Declarative business artifact centric modeling of decision and knowledge intensive business processes , 2011, 2011 IEEE 15th International Enterprise Distributed Object Computing Conference.

[23]  Hajo A. Reijers,et al.  Discovering Social Networks from Event Logs , 2005, Computer Supported Cooperative Work (CSCW).

[24]  Massimo Mecella,et al.  A two-step fast algorithm for the automated discovery of declarative workflows , 2013, 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

[25]  Wil M. P. van der Aalst,et al.  Efficient Discovery of Understandable Declarative Process Models from Event Logs , 2012, CAiSE.

[26]  Wil M. P. van der Aalst,et al.  Enhancing Declare Maps Based on Event Correlations , 2013, BPM.

[27]  Raghava Rao Mukkamala,et al.  Contracts for cross-organizational workflows as timed Dynamic Condition Response Graphs , 2013, J. Log. Algebraic Methods Program..

[28]  Richard Hull,et al.  Data Centric BPM and the Emerging Case Management Standard: A Short Survey , 2012, Business Process Management Workshops.

[29]  Wil M. P. van der Aalst,et al.  Process Mining - Discovery, Conformance and Enhancement of Business Processes , 2011 .

[30]  Wil M. P. van der Aalst,et al.  A Knowledge-Based Integrated Approach for Discovering and Repairing Declare Maps , 2013, CAiSE.