Development of Digital Competency Framework for Vaccine Manufacturing Industry
DOI:
https://doi.org/10.59261/jequi.v8i3.392Keywords:
Design Science Research Methodology, Digital Competency, Pharma 4.0, Proficiency Level, Vaccine ManufacturingAbstract
Background: Digital transformation in vaccine manufacturing requires advanced technologies and competent personnel capable of operating within highly regulated environments. Existing digital competency frameworks remain broad and insufficiently address critical areas, including data integrity, computerized system validation, electronic quality management processes, operational technology, and regulatory compliance.
Objective: This study developed a Digital Competency Framework and defined proficiency levels for vaccine manufacturing personnel using PT XYZ as a single organizational case study.
Methods: The Design Science Research Methodology and a qualitative descriptive approach were employed. Data were obtained from literature reviews, regulatory and organizational documents, observations, semi-structured interviews with six purposively selected informants, and validation conducted by two domain experts.
Results: The study identified 18 digital competencies organized into five proficiency levels, ranging from digital awareness to digital initiative and transformation. These competencies were categorized into three pillars: data, system governance, and compliance; digital manufacturing and quality systems; and operational technology and advanced digital capabilities. Expert validation confirmed adequate coverage, logical progression, and observable competency descriptions. The framework supports role-based competency mapping, targeted training programs, and workforce planning.
Conclusion: The framework provides a context-sensitive and proficiency-based reference for competency mapping, gap analysis, and workforce development. It contributes to advancing Pharma 4.0 while maintaining GxP compliance. However, the findings are analytically transferable rather than statistically generalizable, reflecting the limitations of a single organizational case study.
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