Demystifying data governance for process mining: Insights from a Delphi study

IF 8.2 2区 管理学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Information & Management Pub Date : 2024-05-07 DOI:10.1016/j.im.2024.103973
Kanika Goel , Niels Martin , Arthur ter Hofstede
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Abstract

Data governance is recognised as a new capability for organisations to maximize the value of data. Process mining is essential for the resilient growth of businesses, making process data a strategic asset for organisations. Even though the availability of reliable process data is vital for obtaining dependable insights into process mining techniques, there exists no framework that explains how to govern process data holistically. We address this gap by presenting the first data governance framework for process mining that was derived from a Delphi study conducted with a panel of academics and practitioners from around the world. The framework provides multiple avenues for future research.

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揭开流程挖掘数据管理的神秘面纱:德尔菲研究的启示
数据管理被认为是企业最大限度地利用数据价值的一种新能力。流程挖掘对企业的恢复性增长至关重要,使流程数据成为企业的战略资产。尽管可靠流程数据的可用性对于获得流程挖掘技术的可靠见解至关重要,但目前还没有一个框架能解释如何全面管理流程数据。为了填补这一空白,我们提出了首个流程挖掘数据管理框架,该框架是由来自世界各地的学者和从业人员组成的小组通过德尔菲研究得出的。该框架为未来研究提供了多种途径。
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来源期刊
Information & Management
Information & Management 工程技术-计算机:信息系统
CiteScore
17.90
自引率
6.10%
发文量
123
审稿时长
1 months
期刊介绍: Information & Management is a publication that caters to researchers in the field of information systems as well as managers, professionals, administrators, and senior executives involved in designing, implementing, and managing Information Systems Applications.
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