The use of big data analytics in enhancing operational efficiency in manufacturing
Year: 2024
Type: article
Abstract: This study seeks to offer significant insights into the actual implementation of Big Data Analytics into manufacturing organizations by conducting a comprehensive analysis of existing literature, case studies, and data-driven research. A mixed-methods methodology was used, integrating quantitative and qualitative research methodologies to facilitate a holistic comprehension of the multidimensional effects of Big Data Analytics on operational efficiency within the industrial sector. Findings suggest that the use of Big Data Analytics has a favorable impact on operational efficiency. This highlights the capacity of industrial organizations to leverage data analytics in order to attain operational excellence. Additionally, some of the factors that need to be considered in this context are concerns related to data privacy and security, the resistance to cultural change, the complexity of data, the costs associated with investment, and the obstacles associated with data integration. Furthermore, exemplary methodologies and instances of triumph from manufacturing enterprises that have successfully included Big Data Analytics into their operational frameworks have been identified in this study. In addition, the usage of Big Data Analytics in these areas can yield substantial improvements, resulting in heightened levels of operational efficiency.
Author: Jinyoung Hwang
Institution: University of Edinburgh
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6912036673
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