{"title":"Demystifying data governance for process mining: Insights from a Delphi study","authors":"Kanika Goel , Niels Martin , Arthur ter Hofstede","doi":"10.1016/j.im.2024.103973","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"61 5","pages":"Article 103973"},"PeriodicalIF":8.2000,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378720624000557/pdfft?md5=91cc6c706f5cfbee767513d9c2592c17&pid=1-s2.0-S0378720624000557-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information & Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378720624000557","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
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.
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.