Abstract
Business process management systems (BPMSs) are increasingly gaining momentum as a software platform on which to define, execute, and track enterprise-wide business processes. BPMSs promise to facilitate automation, integration, and optimization of business processes in order to support decision making, increase operational efficiency, and lower the cost of doing business. In spite of the growing popularity, however, realization of the grand vision BPMSs ultimately seek to achieve calls for renewed focus on the holistic approach to continuous process improvement instead of on the process automation alone. In this paper, we present a framework, named xPIA (eXecutable Process Innovation Accelerator), which can effectively facilitate the continuous process improvement through enhancing monitoring capabilities for business data that can significantly affect process performances. In addition to the basic process-related data such as activity start and finish times, the proposed framework allows for monitoring other important business contents as well as events from various sources, including business process definitions, forms and documents, database management systems, enterprise applications, and web services. The presented results outline the key concepts and architectures of xPIA to realize such functionalities on top of contemporary BPMSs while at the same time addressing the implementation issues.
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References
Smith, H., Fingar, P.: Business Process Management: The Third Wave. Meghan-Kiffer Press (2003)
Dumas, M., van der Aalst, W., ter Hofstede, A.H.M.: Process-Aware Information Systems: Bridging People and Software through Process Technology. John Wiley & Sons, Chichester (2005)
Smith, H., Fingar, P.: Digital six sigma: Integrating continuous improvement, with continuous change, with continuous learning. White paper, BPTrends (2003), http://bptrends.com
Jeng, J.J., An, L., Bhaskaran, K., Chang, H., Ettl, M.: Sense-and-respond grids for adaptive enterprises. IT Professional, pp. 33–40 (September/October 2005)
George, M.L.: Lean Six Sigma for Service: How to Use Lean Speed and Six Sigma Quality to Improve Services and Transactions. McGraw-Hill, New York (2003)
Sonnen, D., Morris, H.D.: Businessfactor: Event-driven business performance management. White paper, IDC (2004)
Srinivasan, S., Krishna, V., Holmes, S.: Web-log-driven business activity monitoring. IEEE Computer, 61–68 (March 2005)
Thomas, M., Redmond, R., Yoon, V., Singh, R.: A semantic approach to monitor business process performance. Communications of the ACM 48, 55–59 (2005)
IDS Scheer: ARIS process performance manager. Web site, IDS Scheer (2006), http://www.ids-scheer.com/
FileNet: Filenet process analyzer. Web site, FileNet (2006), http://www.filenet.com
Raisinghani, M.S., Ette, H., Pierce, R., Cannon, G., Daripaly, P.: Six sigma: Concepts, tools, and applications. Industrial Management & Data. Systems 105, 491–505 (2005)
Hammer, M.: Process management and the future of six sigma. MIT Sloan Management Review 43, 26–32 (2002)
ILOG: ILOG JRules. Web site, ILOG (2005), http://www.ilog.com
Neter, J., Kutner, M.H., Nachtsheim, C.J., Wasserman, W.: Applied Linear Statistical Models. 4th edn. IRWIN (1990)
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Park, J. et al. (2007). An Integrated Approach to Process-Driven Business Performance Monitoring and Analysis for Real-Time Enterprises. In: Bussler, C., Castellanos, M., Dayal, U., Navathe, S. (eds) Business Intelligence for the Real-Time Enterprises. BIRTE 2006. Lecture Notes in Computer Science, vol 4365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73950-0_11
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DOI: https://doi.org/10.1007/978-3-540-73950-0_11
Publisher Name: Springer, Berlin, Heidelberg
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