A methodology for planning, implementation and evaluation of skills intelligence management - results of a design science project in technology organisations.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Frontiers in Artificial Intelligence Pub Date : 2024-08-07 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1424924
Kadri-Liis Kusmin, Peeter Normak, Tobias Ley
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Abstract

Introduction: The evolving labour market requirements amidst digital transformation necessitate robust skills intelligence for informed decision-making and adaptability. Novel technologies such as Big Data, Machine Learning, and Artificial Intelligence have significant potential for enhancing skills intelligence.

Methods: This study bridges the gap between theory and practice by designing a novel software artefact for skills intelligence management. With its systematic framework for identifying skills intelligence elements, an assessment instrument, and an implementation methodology, the artefact ensures a thorough approach to skills intelligence management.

Results: The artefact was demonstrated in 11 organisations. Feedback collected from interviews, focus group sessions, and observations (N = 19) indicated that the artefact is a feasible starting point for implementing or systematising skills intelligence management. Participants suggested improvements but concurred that the systematic approach enhances skills intelligence data collection and quality.

Discussion: The study shows that the artefact facilitates the application of advanced technologies in skills intelligence management. Additionally, it contributes a set of principles for effective skills intelligence management, fostering a broader conversation on this critical topic. Participants' feedback underscores the artefact's potential and provides a basis for further refinement and application in diverse organisational contexts.

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技能智能管理的规划、实施和评估方法--技术组织设计科学项目的成果。
导言:在数字化转型过程中,劳动力市场的需求不断变化,这就需要强大的技能智能,以便做出明智的决策和提高适应能力。大数据、机器学习和人工智能等新技术在提高技能智能方面具有巨大潜力:本研究通过设计一种用于技能智能管理的新型软件工具,在理论与实践之间架起了一座桥梁。凭借其识别技能智能要素的系统框架、评估工具和实施方法,该工具确保了技能智能管理的彻底性:结果:在 11 个组织中演示了该工具。从访谈、焦点小组会议和观察(N = 19)中收集到的反馈表明,该工具是实施技能智能管理或使其系统化的可行起点。参与者提出了改进建议,但一致认为系统化方法提高了技能情报数据的收集和质量:讨论:研究表明,该工具有助于在技能情报管理中应用先进技术。此外,它还为有效的技能情报管理提供了一套原则,促进了关于这一关键主题的更广泛对话。参与者的反馈意见强调了人工智能的潜力,并为进一步完善和应用于不同的组织环境奠定了基础。
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来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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