[Cite as http://purl.org/au-research/grants/arc/DP180102839]
Researchers Prof Marcello La Rosa; Dr Artem Polyvyanyy; Prof Arthur ter Hofstede; Prof Dr Wil van der Aalst; Prof Marlon Dumas-Menjivar
Brief description This project aims to develop an innovative approach based on process execution semantics, to analyse event data logged by IT systems in order to diagnose and predict business process deviance. Anticipated outcomes include novel business intelligence algorithms producing deviance diagnostics, predictions and recommendations and exposing results via interactive visual analytics. The outcomes are expected to aid process workers in steering business operations towards consistent and compliant outcomes and higher performance, and assist analysts and auditors to explain deviant operations. This should significantly benefit industries such as healthcare, insurance, retail and the government where compliance and integrity management are imperative.
Funding Amount $377,784
Funding Scheme Discovery Projects