Brazilian Journal of Operations and Production Management | 2026
Authors: Lorenzini I.P.; Yamaguchi C.K.; de Mattos M.C.
DOI: 10.14488/BJOPM.2682.2026
Journal: Brazilian Journal of Operations and Production Management
Year: 2026
Publisher: Associacao Brasileira de Engenharia de Producao
Document Type: Article
Open Access: All Open Access; Gold Open Access
Cited by: 0
Objective: To analyze the implementation of data capture in a medium-sized metal-mechanic industry, considering factors related to Digital Transformation (DT) under the human-centered approach of Industry 5.0 (15.0). Methodology: Quali-quantitative study developed through action research in five phases (Oct/2023-Jul/2024), and a survey with its instrument based on the UTAUT and MD3M models. Findings: Six forms were identified, containing 108 fields involving 51 unique attributes, with high redundancy in the entry of general descriptions. The digital data collection, integrated with the company's ERP system, concluded with 10 forms and 35 unique variables, reducing redundant fields by 72%. Employees were involved throughout the process, with the most interaction occurring during training sessions and analysis meetings. The survey results show over 87% acceptance across the four main constructs of the UTAUT model, and the correlations between variables and participation levels indicate a reduction in users1 insecurities regarding the adoption of new technology, reinforcing that the human-centered approach was essential for the acceptance of the new data collection format. Research limitations: Technology implementation time, absence of Industry 5.0 maturity models and inability to measure data-management maturity using the MD3M model. Practical implications: Identification of challenges in IT-operations coordination; highlighting the need for an empathetic and collaborative approach in DT, as revealed by the reduction of resistance through employee participation in the process. Originality: Practical demonstration that the challenges of DT can be overcome through the active participation of employees, highlighting — through the correlations found — the impact of a human-centered approach on technology implementation. © 2026, Associacao Brasileira de Engenharia de Producao. All rights reserved.
Data capture; Data-driven organization; Human-centered approach; Industry 5.0