Proactive Management of Business Change
This paper addresses enterprise performance problems that can occur after Business Process Reengineering (BPR) project as consequence of business change. The general idea is to lean a Bayesian network from past BPR projects and use this model for prediction in future restructured processes. The role of Bayesian network will be to measure influence of business process structural changes, quantified by structural change metrics, and the increasing or decreasing of process performance, quantified by operational variation metrics. The paper’s focus is interoperable structural change metrics definition using process ontology, and operational variation metrics definition. Bayesian prediction model learning, application and result interpretation are discussed in (CAMRA, et al., 2007). The method we propose is for use for the validation of enterprise restructuration, more precisely in the validation of business processes restructuration’s.