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Mining Resource Profiles from Event Logs

Mining Resource Profiles from Event Logs Mining Resource Profiles from Event Logs ANASTASIIA PIKA, Queensland University of Technology MICHAEL LEYER, University of Rostock MOE T. WYNN and COLIN J. FIDGE, Queensland University of Technology ARTHUR H. M. TER HOFSTEDE, Queensland University of Technology and Eindhoven University of Technology WIL M. P. VAN DER AALST, Eindhoven University of Technology and Queensland University of Technology In most business processes, several activities need to be executed by human resources and cannot be fully automated. To evaluate resource performance and identify best practices as well as opportunities for improvement, managers need objective information about resource behaviors. Companies often use information systems to support their processes, and these systems record information about process execution in event logs. We present a framework for analyzing and evaluating resource behavior through mining such event logs. The framework provides (1) a method for extracting descriptive information about resource skills, utilization, preferences, productivity, and collaboration patterns; (2) a method for analyzing relationships between different resource behaviors and outcomes; and (3) a method for evaluating the overall resource productivity, tracking its changes over time, and comparing it to the productivity of other resources. To demonstrate the applicability of our framework, we apply it to analyze http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Management Information Systems (TMIS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2017 by ACM Inc.
ISSN
2158-656X
DOI
10.1145/3041218
Publisher site
See Article on Publisher Site

Abstract

Mining Resource Profiles from Event Logs ANASTASIIA PIKA, Queensland University of Technology MICHAEL LEYER, University of Rostock MOE T. WYNN and COLIN J. FIDGE, Queensland University of Technology ARTHUR H. M. TER HOFSTEDE, Queensland University of Technology and Eindhoven University of Technology WIL M. P. VAN DER AALST, Eindhoven University of Technology and Queensland University of Technology In most business processes, several activities need to be executed by human resources and cannot be fully automated. To evaluate resource performance and identify best practices as well as opportunities for improvement, managers need objective information about resource behaviors. Companies often use information systems to support their processes, and these systems record information about process execution in event logs. We present a framework for analyzing and evaluating resource behavior through mining such event logs. The framework provides (1) a method for extracting descriptive information about resource skills, utilization, preferences, productivity, and collaboration patterns; (2) a method for analyzing relationships between different resource behaviors and outcomes; and (3) a method for evaluating the overall resource productivity, tracking its changes over time, and comparing it to the productivity of other resources. To demonstrate the applicability of our framework, we apply it to analyze

Journal

ACM Transactions on Management Information Systems (TMIS)Association for Computing Machinery

Published: Mar 23, 2017

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