Dynamic Evolution of Business Performance Management

  • Authors:
  • Liangzhao Zeng;Hui Lei;Michael Dikun;Henry Chang;Chang Shu

  • Affiliations:
  • IBM T.J. Watson Research Center;IBM T.J. Watson Research Center;IBM T.J. Watson Research Center;IBM T.J. Watson Research Center;IBM China Software Development Laboratory

  • Venue:
  • ICEBE '06 Proceedings of the IEEE International Conference on e-Business Engineering
  • Year:
  • 2006

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Abstract

Business PerformanceManagement(BPM) is a new frontier in IT-enabled enterprise that supports the monitoring business operations. BPM solutions must be able to efficiently process business events, compute business metrics, detect business situations, and provide the real-time visibility of key performance indicators (KPIs) in dynamic environments, wherein sources of dynamicity are plentiful, including new strategies, operations, KPIs, etc. Therefore, BPM solutions need to adapt these changes by dynamic evolution. We propose a policy-driven approach, where evolution policies capture the evolution mechanism of BPM solutions. This frees solution developers from low-level programming concerns. We implemented a hybrid compilationinterpretation framework that enables execution of wide spectrums of evolution policies. Further, our framework enables execution of evolution policies in parallel with on going event processing and guarantees the integrity on both of them.