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Comuzzi, Marco
Intelligent Enterprise Lab.
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Assessing and improving measurability of process performance indicators based on quality of logs

Author(s)
Cappiello, CinziaComuzzi, MarcoPlebani, PierluigiFim, Matheus
Issued Date
2022-01
DOI
10.1016/j.is.2021.101874
URI
https://scholarworks.unist.ac.kr/handle/201301/53941
Fulltext
https://www.sciencedirect.com/science/article/pii/S0306437921000995?via%3Dihub
Citation
INFORMATION SYSTEMS, v.103, pp.101874
Abstract
The efficiency and effectiveness of business processes are usually evaluated by Process Performance Indicators (PPIs), which are computed using process event logs. PPIs can be insightful only when they are measurable, i.e., reliable. This paper proposes to define PPI measurability on the basis of the quality of the data in the process logs. Then, based on this definition, a framework for PPI measurability assessment and improvement is presented. For the assessment, we propose novel definitions of PPI accuracy, completeness, consistency, timeliness and volume that contextualise the traditional definitions in the data quality literature to the case of process logs. For the improvement, we define a set of guidelines for improving the measurability of a PPI. These guidelines may concern improving existing event logs, for instance through data imputation, implementation or enhancement of the process monitoring systems, or updating the PPI definitions. A case study in a large-sized institution is discussed to show the feasibility and the practical value of the proposed framework. (C) 2021 Elsevier Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
ISSN
0306-4379
Keyword (Author)
Business processEvent logData quality assessmentData quality improvement
Keyword
MEASUREMENT SYSTEMDESIGNMANAGEMENTPATTERNS

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