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  • 标题:A Proposal for a Software Tool to Perform Business Process Smart Assessment in Enterprises
  • 本地全文:下载
  • 作者:Marcelo Romero ; Wided Guédria ; Hervé Panetto
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:1
  • 页码:900-905
  • DOI:10.1016/j.ifacol.2021.08.107
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe challenges faced by enterprises on a daily basis such as regulatory compliance, novel technology adoption, or cost optimisation, foster them to implement improvement initiatives. As a first step towards the implementation of those initiatives, there is a need to perform assessments to understand the As-Is state of the enterprise considering different aspects such as maturity, agility, performance, or readiness towards digitisation. However, assessments are expensive in terms of time and resources. Specifically when considering qualitative appraisals, such as maturity or capability assessments, since they often demand the participation of one or more human assessors to review documents, perform interviews, etc. Therefore, means to automate or semi-automate the assessment process are essential, since they could reduce the effort to perform it. In this sense, this work introduces a software tool to support assessments in enterprises using text data as assessment evidence. The tool is developed following a conceptual framework named Smart Assessment Framework, which introduces a metamodel with abstract components to be instantiated for the development of systems dedicated to organisational assessments. The elements defined by the framework are grounded on the capabilities of smart systems. The application domain of the tool is focused on Process Capability assessment, in compliance with the ISO/IEC 33020:2015 international standard. The tool uses a Natural Language Processing method to process the assessment evidence and an Ontology as Knowledge Base to support the calculation of capability levels and to provide improvement recommendations.
  • 关键词:KeywordsComputer softwareArtificial intelligenceMachine learningKnowledge-based systemsEfficient evaluationAssessment
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