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 sensemaking, 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.

Leveraging Frontline Employees’ Knowledge for Operational Data-Driven Decision-Making: A Multilevel Perspective / Colombari, Ruggero; Neirotti, Paolo. - In: IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT. - ISSN 0018-9391. - ELETTRONICO. - 71:(2024), pp. 13840-13851. [10.1109/TEM.2023.3291272]

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

Ruggero Colombari;Paolo Neirotti
2024

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 sensemaking, 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.
File in questo prodotto:
File Dimensione Formato  
Leveraging_Frontline_Employees_Knowledge_for_Operational_Data-Driven_Decision-Making_A_Multilevel_Perspective.pdf

accesso aperto

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Creative commons
Dimensione 2.1 MB
Formato Adobe PDF
2.1 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2981163