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'Insight Unlocked': Applying a Collective Intelligence Approach to Engage Employers in Informing Local Skills Improvement Planning
- Source :
-
Industry and Higher Education . 2024 38(2):164-176. - Publication Year :
- 2024
-
Abstract
- This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills Improvement Planning information for employers, education and skills training organisations and regional economic policy organisations. This took place within a Knowledge Transfer Partnership between a Chamber of Commerce and a University. This aimed to develop and deploy regional business intelligence for enhanced policy and decision-making in enterprise and economic development. The project converged knowledge from several research centres including economics, entrepreneurship and innovation, data science, and Artificial Intelligence. The paper presents a project case study which provides two contributions to applied knowledge. Firstly, it demonstrates how a Collective Intelligence (CI) approach can be applied to achieve rapid results in resolving the real-world problem of local skills information availability. Useful real-time data was gathered from employers in three sectors on skills requirements, supply and training. This was analysed using Artificial Intelligence tools, then shared publicly via an automated Internet portal, providing a scalable model for wider use. Secondly, it explores and evaluates how the knowledge exchange (KE) process can function effectively and quickly in applying CI-based innovation in practical ways which create new value, within a Knowledge Transfer Partnership between a University and Chamber of Commerce.environment.
Details
- Language :
- English
- ISSN :
- 0950-4222 and 2043-6858
- Volume :
- 38
- Issue :
- 2
- Database :
- ERIC
- Journal :
- Industry and Higher Education
- Publication Type :
- Academic Journal
- Accession number :
- EJ1417707
- Document Type :
- Journal Articles<br />Reports - Evaluative
- Full Text :
- https://doi.org/10.1177/09504222231186376