{"title":"An improved FMEA quality risk assessment framework for enterprise data assets","authors":"Jianxin You , Shuqi Lou , Renjie Mao , Tao Xu","doi":"10.1016/j.jdec.2022.12.001","DOIUrl":null,"url":null,"abstract":"<div><p>Analyzing and assessing the quality risks is essential to leverage the value of data assets. In this paper, a framework for proactively assessing the quality risks of data assets based on an improved FMEA is proposed. First, quality risk metrics are identified from a lifecycle perspective through literature research and experts' discussions. Then, Triangular Fuzzy Numbers are adopted to express uncertain and complex information about the expert's assessment. Subsequently, a new risk factor ‘C' is introduced to describe the difficulty of risk controlling and a DEA approach is applied to calculate the weights of risk factors. Finally, a practical case is provided to demonstrate the proposed FMEA framework, and several recommendations are provided to control data asset quality risks.</p></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"1 3","pages":"Pages 141-152"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773067022000292/pdfft?md5=6078ac1a2ee5b9cbcc037a28662f96f3&pid=1-s2.0-S2773067022000292-main.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Digital Economy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2773067022000292","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Analyzing and assessing the quality risks is essential to leverage the value of data assets. In this paper, a framework for proactively assessing the quality risks of data assets based on an improved FMEA is proposed. First, quality risk metrics are identified from a lifecycle perspective through literature research and experts' discussions. Then, Triangular Fuzzy Numbers are adopted to express uncertain and complex information about the expert's assessment. Subsequently, a new risk factor ‘C' is introduced to describe the difficulty of risk controlling and a DEA approach is applied to calculate the weights of risk factors. Finally, a practical case is provided to demonstrate the proposed FMEA framework, and several recommendations are provided to control data asset quality risks.