Mining Resource Profiles from Event Logs
Author(s) -
Anastasiia Pika,
Michael Leyer,
Moe Thandar Wynn,
Colin Fidge,
Arthur H. M. ter Hofstede,
Wil M. P. van der Aalst
Publication year - 2017
Publication title -
acm transactions on management information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.603
H-Index - 29
eISSN - 2158-6578
pISSN - 2158-656X
DOI - 10.1145/3041218
Subject(s) - resource (disambiguation) , productivity , event (particle physics) , process (computing) , computer science , human resource management system , knowledge management , human resource management , process management , data science , business , computer network , physics , quantum mechanics , economics , macroeconomics , operating system
Human resources are often responsible for the execution of business processes. In order to evaluate resource performance and identify best practices as well\udas opportunities for improvement, managers need objective information about resource behaviours. Companies often use information systems to support their processes and these systems record information about process execution in event\udlogs. We present a framework for analysing and evaluating resource behaviour through mining such event logs. The framework provides a method for extracting descriptive information about resource skills, utilisation, preferences,\udproductivity and collaboration patterns; a method for analysing relationships between different resource behaviours and outcomes; and a method for evaluating\udthe overall resource productivity, tracking its changes over time and comparing it with the productivity of other resources. To demonstrate the applicability of our framework we apply it to analyse behaviours of employees in\udan Australian company and evaluate its usefulness by a survey among managers in industry
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