research-article

Mining Resource Profiles from Event Logs

Authors:

Anastasiia Pika,

Colin J. Fidge,

Arthur H. M. Ter Hofstede,

Wil M. P. Van Der AalstAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 8, Issue 1

Article No.: 1, Pages 1 - 30

https://doi.org/10.1145/3041218

Published: 23 March 2017 Publication History

Abstract

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 employee behavior in an Australian company and evaluate its usefulness by a survey among industry managers.

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Index Terms

Mining Resource Profiles from Event Logs
1. Information systems
  1. Information systems applications
    1. Decision support systems

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cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 8, Issue 1

March 2017

80 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3068852

Editor:
Alexander Tuzhilin
New York University, USA

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Copyright © 2017 ACM.

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Publication History

Published: 23 March 2017

Accepted: 01 December 2016

Revised: 01 September 2016

Received: 01 April 2016

Published in TMIS Volume 8, Issue 1

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ethical clearance for conducting the survey
National Statement on Ethical Conduct in Human Research
“Risk-Aware Business Process Management” project (ARC DP110100091)

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Aalikhani RFathian MRasouli M(2025)Enhancing remaining time prediction in business processes by considering system-level and resource-level inter-case featuresSoftware and Systems Modeling10.1007/s10270-025-01267-4Online publication date: 31-Jan-2025
https://doi.org/10.1007/s10270-025-01267-4
Rubensson CPufahl LMendling J(2025)A Conceptual Framework for Resource Analysis in Process MiningEnterprise Design, Operations, and Computing. EDOC 2024 Workshops10.1007/978-3-031-79059-1_12(183-202)Online publication date: 9-Feb-2025
https://doi.org/10.1007/978-3-031-79059-1_12
Mahala GSindhgatta RDam HGhose A(2024)Multi-Objective Evolutionary Search for Optimal Robotic Process Automation ArchitecturesIEEE Transactions on Services Computing10.1109/TSC.2024.339632917:5(2654-2671)Online publication date: Sep-2024
https://doi.org/10.1109/TSC.2024.3396329
Wang JYu DLiu C(2024)Task allocation for maximum cooperation in complex structured business processesKnowledge-Based Systems10.1016/j.knosys.2024.111989299:COnline publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1016/j.knosys.2024.111989
Diamantini CPisacane OPotena DStorti E(2024)Combining an LNS-based approach and organizational mining for the Resource Replacement ProblemComputers and Operations Research10.1016/j.cor.2023.106446161:COnline publication date: 1-Jan-2024
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Martin NBeerepoot I(2024)Unveiling Use Cases for Human Resource MiningBusiness & Information Systems Engineering10.1007/s12599-024-00894-3Online publication date: 29-Aug-2024
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Padella AMannhardt FVinci Fde Leoni MVanderfeesten I(2024)Experience-Based Resource Allocation for Remaining Time OptimizationBusiness Process Management10.1007/978-3-031-70396-6_20(345-362)Online publication date: 1-Sep-2024
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Ter Hofstede AKoschmider AMarrella AAndrews RFischer DSadeghianasl SWynn MComuzzi MDe Weerdt JGoel KMartin NSoffer P(2023)Process-Data Quality: The True Frontier of Process MiningJournal of Data and Information Quality10.1145/361324715:3(1-21)Online publication date: 28-Sep-2023
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