An Intelligent Learning Management System for Identifying Skill Gaps and Supporting Workforce Reskilling in SMEs

Angelo Leogrande (), Mauro Di Molfetta (), Valeria Notarnicola, Maria Giovanna Trotta () and Nicola Magaletti ()
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Angelo Leogrande: LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro
Valeria Notarnicola: LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro
Nicola Magaletti: LUM - Università LUM Giuseppe Degennaro = University Giuseppe Degennaro

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Abstract: In addition, digital transformation has created a new organizational landscape that requires different workforce structures. This has led to a growing need for new digital skills. Despite these challenges, organizations, especially SMEs, face major challenges in identifying gaps in skills and developing reskilling strategies. This study proposes a data-driven framework that helps identify performance gaps for organizations and competency gaps for the workforce. The proposed methodological framework for identifying gaps in skills for the workforce involves a two-level analytical method. In the macro level, a Composite Performance Gap Index is proposed for measuring the performance of organizations in different economic and organizational dimensions. This index helps classify different industries or geographical locations based on the performance of organizations in a given sector. This index helps identify organizations that are performing poorly in different sectors and requires support for digital transformation. In the micro level, the proposed framework helps identify gaps in skills for the workforce by using CV-based skill extraction techniques involving Natural Language Processing (NLP) methods. This helps identify gaps in digital skills for the workforce. It also helps calculate a Skill Gap Indicator that measures the difference between existing skills and skills that are mandated by a digital skills framework for different industries. Based on these gaps in skills for the workforce, the proposed framework helps generate intelligent learning management systems for organizations that are relevant for digital transformation. In order to propose a data-driven framework for identifying gaps in skills for the workforce, a prototype for an Intelligent Learning Management System (LMS) for organizations is proposed. This LMS has different dashboards for firm benchmarking, employee skill gap analysis, and a catalog for training programs that are relevant for digital transformation. The proposed framework has shown significant gaps in skills for the workforce for SMEs based on the proposed methodological framework. This study has also shown that organizations face major challenges in developing skills for the workforce based on different competency gaps that are relevant for digital transformation. The proposed framework helps organizations identify gaps in skills for the workforce that are relevant for digital transformation.

Keywords: Digital Transformation Skill Gap Analysis Learning Management Systems (LMS) Workforce Reskilling Data-Driven Decision Support; Digital Transformation; Skill Gap Analysis; Learning Management Systems (LMS); Workforce Reskilling; Data-Driven Decision Support (search for similar items in EconPapers)
Date: 2026-03-13
Note: View the original document on HAL open archive server: https://hal.science/hal-05552200v1
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