Lean 4.0 as a Socio-Technical System: Mapping the Interaction of Soft Practices and Industry 4.0 in Digital Transformation

This study examines Lean 4.0, defined as the integration of Lean soft practices (LSPs) and Industry 4.0 technologies (I4Ts), from a socio-technical systems perspective. While prior research has mainly linked Lean and I4Ts to operational and cost-based performance indicators, far less is known about how their human and technological elements interact as one socio-technical system during digital transformation. We investigate how LSPs and I4Ts combine to form social and technical subsystems, how their interaction reshapes work systems, and how these configurations relate to organisational performance. An inductive qualitative design was used. Fifteen managers and professionals with direct experience in continuous improvement and digital transformation completed an open-ended online questionnaire. Data were analysed using Braun and Clarke thematic analysis, guided by socio-technical systems theory and complemented by a cross-case synthesis. The findings identify four interrelated subsystems, social, technical, work, and outcomes, that co-evolve in Lean 4.0 initiatives. LSPs such as training, empowerment, and stakeholder involvement constitute a social system that enables the adoption and effective use of I4Ts in the technical system. When both subsystems are strong, their combined operation drives more extensive digital transformation of operational processes and customer facing activities, and in some cases business models, and is associated with broader improvements in efficiency, quality, customer satisfaction, employee engagement, and financial performance than medium or unbalanced configurations. The analysis also highlights recurrent integration challenges, including skill gaps, legacy system constraints, resistance to change, and data security concerns. Overall, the study conceptualises Lean 4.0 as an integrated socio-technical configuration and extends socio-technical systems theory by showing how LSPs mediate and amplify the value created by I4Ts, providing an empirically grounded framework and configuration-based insights for future testing.