Authors:
Ruopeng Lu
and
Shazia Sadiq
Affiliation:
School of Information Technology and Electrical Engineering, The University of Queensland, Australia
Keyword(s):
Business process management, flexible workflows, process evolution, business process analysis.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Process Management
;
Databases and Information Systems Integration
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Enterprise Resource Planning
;
Enterprise Software Technologies
;
Information Engineering Methodologies
;
Information Systems Analysis and Specification
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Software Engineering
;
Symbolic Systems
Abstract:
Business process management systems (BPMS) have been prevalent in business information systems, yet still striving to cope with emerging demands from current business environments. It is particularly challenging in managing knowledge intensive business processes, which has partially led to the demand for more complex BPMS functionality such as instance adaptation and streamlined process evolution. On the other hand, various process analysis and discovery techniques have been developed as an important component in BPMS. In this paper, we present a technology framework that supports process discovery from preferred work practices in a flexible process management system. The framework supports instance adaptation and a systematic approach towards process evolution/improvement.