Competence gap analysis of early-career Quality Engineers in the field of Quality 4.0

Purpose The purpose of the paper is to propose a methodology for identification of competence gaps of Quality Engineers in the field of Quality 4.0 and apply it in the selected organisations, which have digital strategies. Based on the results of the Quality 4.0 competencies assessment of early career Quality Engineers, the main weaknesses were identified, which need to be considered and addressed by Higher Education Institutions providing education in the field of Quality Engineering and Management. Design/methodology/approach The structured online questionnaire containing 23 Quality 4.0 competencies was developed based on the literature review and interviews with the representatives of the organisations operating in the automotive industry. The respondents were graduates of the Quality of Production study field who are in their early career path (from 1 to 3 years after graduation) and work in the positions of Quality Engineers. The collected data were evaluated based on the proposed methodology enabling the calculation of Gap Indexes for individual competencies and competence categories. Findings The lowest value of the Gap Index from the four competence categories was calculated for technical competencies (respondents from Tier 1–64% and Tier 2–69%) and subsequently for methodological competencies (Tier 1–75% and Tier 2–74%). Among the most problematic domains that Higher Education Institutions have to address are big data and machine learning knowledge and skills, interdisciplinary knowledge and teamwork, critical thinking, problem-solving, agile project management knowledge and skills and resilience capability. Originality/value The study contributes to the existing body of knowledge in the field of competencies for Quality 4.0. It provides the methodology that enables systematic examination of competence gaps. Subsequently, it shows he practical application of the methodology to define competence gaps of Quality Engineers in the field of Quality 4.0. The findings bring implications for Higher Education Institutions in the context of the development of required competencies and deployment of suitable education methods.

Authors

Publication Details

Journal
The TQM Journal
Published
2025-06-20
DOI
https://doi.org/10.1108/tqm-12-2024-0522
Citations
2
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
2.48
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article

Competence gap analysis of early-career Quality Engineers in the field of Quality 4.0

Róbert Kočiško, David Vykydal, Slavomíra Vargová, Andrea Sütőová et al.
2 citations
The TQM Journal
Digital Transformation in Industry
2.48
article

Competence gap analysis of early-career Quality Engineers in the field of Quality 4.0

Róbert Kočiško, David Vykydal, Slavomíra Vargová, Andrea Sütőová, Radoslav Palacka
article en
2 citations

Abstract

Purpose The purpose of the paper is to propose a methodology for identification of competence gaps of Quality Engineers in the field of Quality 4.0 and apply it in the selected organisations, which have digital strategies. Based on the results of the Quality 4.0 competencies assessment of early career Quality Engineers, the main weaknesses were identified, which need to be considered and addressed by Higher Education Institutions providing education in the field of Quality Engineering and Management. Design/methodology/approach The structured online questionnaire containing 23 Quality 4.0 competencies was developed based on the literature review and interviews with the representatives of the organisations operating in the automotive industry. The respondents were graduates of the Quality of Production study field who are in their early career path (from 1 to 3 years after graduation) and work in the positions of Quality Engineers. The collected data were evaluated based on the proposed methodology enabling the calculation of Gap Indexes for individual competencies and competence categories. Findings The lowest value of the Gap Index from the four competence categories was calculated for technical competencies (respondents from Tier 1–64% and Tier 2–69%) and subsequently for methodological competencies (Tier 1–75% and Tier 2–74%). Among the most problematic domains that Higher Education Institutions have to address are big data and machine learning knowledge and skills, interdisciplinary knowledge and teamwork, critical thinking, problem-solving, agile project management knowledge and skills and resilience capability. Originality/value The study contributes to the existing body of knowledge in the field of competencies for Quality 4.0. It provides the methodology that enables systematic examination of competence gaps. Subsequently, it shows he practical application of the methodology to define competence gaps of Quality Engineers in the field of Quality 4.0. The findings bring implications for Higher Education Institutions in the context of the development of required competencies and deployment of suitable education methods.

The TQM Journal
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Digital Transformation in Industry
2.48
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