Leveraging Frontline Employees’ Knowledge for Operational Data-Driven Decision-Making: A Multilevel Perspective

Abstract

With the digitalization of manufacturing, firms can now increasingly access and analyze data in real-time, enabling data-driven decision-making (DDM) also at the operational level. Using a multilevel perspective and a mixed-methods research, this article aims to test whether production workers’ involvement (organizational level) and frontline managers’ competency (individual level) are associated with the use of operational DDM. The results of the regression models based on a survey of Italian auto suppliers show that high-involvement lean production practices are associated with a higher probability of DDM adoption when controlling for Team Leaders’ and Supervisors’ competency level, which have a positive moderation effect. Triangulated with qualitative interview data, these findings suggest that firms with skilled frontline managers are more likely to adopt DDM as they can leverage their production workers’ context-dependent knowledge for sense-making, information processing, and knowledge creation. Also, the moderation effect is stronger for Team Leaders, suggesting a central role for them in firms’ digitalization. This study contributes to literature with a socio-technical model that describes operational DDM by integrating organizational and individual dimensions into the data-information-knowledge-decision-making cycle. Organizational and individual implications of this skill-biased technological and organizational change are discussed, and recommendations are offered to managers and education policymakers.