A process mining-based analysis of business process work-arounds

被引:17
|
作者
Outmazgin, Nesi [1 ]
Soffer, Pnina [1 ]
机构
[1] Univ Haifa, IL-31905 Haifa, Israel
关键词
Business process work-arounds; Process mining; Compliance checking; CONFORMANCE CHECKING;
D O I
10.1007/s10270-014-0420-6
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Business process work-arounds are specific forms of incompliant behavior, where employees intentionally decide to deviate from the required procedures although they are aware of them. Detecting and understanding the work-arounds performed can guide organizations in redesigning and improving their processes and support systems. Existing process mining techniques for compliance checking and diagnosis of incompliant behavior rely on the available information in event logs and emphasize technological capabilities for analyzing this information. They do not distinguish intentional incompliance and do not address the sources of this behavior. In contrast, the paper builds on a list of generic types of work-arounds found in practice and explores whether and how they can be detected by process mining techniques. Results obtained for four work-around types in five real-life processes are reported. The remaining two types are not reflected in events logs and cannot be currently detected by process mining. The detected work-around data are further analyzed for identifying correlations between the frequency of specific work-around types and properties of the processes and of specific activities. The analysis results promote the understanding of work-around situations and sources.
引用
收藏
页码:309 / 323
页数:15
相关论文
共 50 条
  • [31] A policy-based process mining framework: mining business policy texts for discovering process models
    Li, Jiexun
    Wang, Harry Jiannan
    Zhang, Zhu
    Zhao, J. Leon
    INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT, 2010, 8 (02) : 169 - 188
  • [32] A policy-based process mining framework: mining business policy texts for discovering process models
    Jiexun Li
    Harry Jiannan Wang
    Zhu Zhang
    J. Leon Zhao
    Information Systems and e-Business Management, 2010, 8 : 169 - 188
  • [33] Business Process Performance Mining with Staged Process Flows
    Hoang Nguyen
    Dumas, Marlon
    ter Hofstede, Arthur H. M.
    La Rosa, Marcello
    Maggi, Fabrizio Maria
    ADVANCED INFORMATION SYSTEMS ENGINEERING (CAISE 2016), 2016, 9694 : 167 - 185
  • [34] Reinforcement Learning for Process Mining: Business Process Optimization
    Soliman, Ghada
    Mostafa, Kareem
    Younis, Omar
    GOOD PRACTICES AND NEW PERSPECTIVES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 5, WORLDCIST 2024, 2024, 989 : 108 - 125
  • [35] PROCESS MINING IN BUSINESS PROCESS MANAGEMENT: CONCEPTS AND CHALLENGES
    Saylam, Rabia
    Sahingoz, Ozgur Koray
    2013 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTER AND COMPUTATION (ICECCO), 2013, : 131 - 134
  • [36] Towards Simulation- and Mining-based Translation of Resource-aware Process Models
    Ackermann, Lars
    Schonig, Stefan
    Jablonski, Stefan
    BUSINESS PROCESS MANAGEMENT WORKSHOPS, BPM 2016, 2017, 281 : 359 - 371
  • [37] Analysis and Prediction Cost of Manufacturing Process Based on Process Mining
    Thi Bich Hong Tu
    Song, Minseok
    2016 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING, MANAGEMENT SCIENCE AND APPLICATIONS (ICIMSA), 2016,
  • [38] A SYSTEMATIC METHODOLOGY FOR OUTPATIENT PROCESS ANALYSIS BASED ON PROCESS MINING
    Cho, Minsu
    Song, Minseok
    Yoo, Sooyoung
    INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE, 2015, 22 (04): : 480 - 493
  • [39] The Mining of Activity Dependence Relation based on Business Process Models
    Hu, Guangchang
    Wu, Budan
    Chen, Junliang
    2017 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING (SCC), 2017, : 450 - 458
  • [40] Anomaly Detection in Business Process based on Data Stream Mining
    Tavares, Gabriel Marques
    Turrisi da Costa, Victor G.
    Martins, Vinicius Eiji
    Ceravolo, Paolo
    Barbon, Sylvio, Jr.
    PROCEEDINGS OF THE 14TH BRAZILIAN SYMPOSIUM ON INFORMATION SYSTEMS (SBSI2018), 2018, : 120 - 127