‘Insight Unlocked’: Applying a Collective Intelligence approach to engage employers in informing Local Skills Improvement Planning

Autor: Rae, David, Cartwright, Edward, Gongora, Mario, Hobson, Chris, Shah, Harsh
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Popis: The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. The project for which the paper provides a case study was a Knowledge Transfer Partnership between De Montfort University and East Midlands Chamber, funded by UKRI. This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills 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.
Databáze: OpenAIRE