Model-driven business performance management

Abstract

In this paper, we present a model-driven approach to business performance management (BPM). BPM is a new frontier in IT-enabled enterprise that supports the monitoring and control of 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. In addition, system support is required for the rapid development of BPM solutions and the adaptation of the solutions to the dynamic business environment. We have adopted a meta-model, dubbed the observation meta-model, for capturing the business requirements for BPM, which frees solution developers from low-level programming concerns. We have also used a hybrid compilation-interpretation approach to map an observation model to the runtime executable. First, we extract and refactor the data aspect of the observation model to facilitate runtime access. Second, we compile the operational aspect of the model, such as logic for metric computation and situation detection, into Java code. Third, we develop a runtime engine that interprets the refactored model and dynamically loads the generated code, according to the meta-model. Our framework further enables the evolution and hot deployment of the observation model and provides the platform for several on-going customer engagement efforts