| Issue |
BIO Web Conf.
Volume 86, 2024
International Conference on Recent Trends in Biomedical Sciences (RTBS-2023)
|
|
|---|---|---|
| Article Number | 01061 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/bioconf/20248601061 | |
| Published online | 12 January 2024 | |
Data-Driven Decision Making: Real-world Effectiveness in Industry 5.0 – An Experimental Approach
1 Department of management and innovation, National Research University Moscow State University of Civil Engineering, 129337 Yaroslavskoe shosse, 26, Moscow, Russia
2 Uttaranchal Institute of Technology, Uttaranchal University, Dehradun, 248007
3 Lovely Professional University, Phagwara, Punjab, India
4 Assistant Professor, GRIET, Bachupally, Hyderabad, Telangana
5 K R Mangalam University, Gurgaon, India
* Corresponding author: hus1@list.ru
This empirical study on Industry 5.0 offers verifiable proof of the transformational potential of data-driven decision making. The validation of data-driven choices as a key component of Industry 5.0's performance is shown by a noteworthy 46.15% increase in decision outcomes. The fact that choice criteria are in line with pertinent data sources emphasizes how important data is in forming well-informed decision-making processes. Moreover, the methodical execution and oversight of choices showcase the pragmatic significance of data-driven methodologies. This empirical evidence positions data-driven decision making as a cornerstone for improving operational efficiency, customer happiness, and market share, solidifying its essential role as the industrial environment changes. These results herald in an age when data's revolutionary potential drives industrial progress by providing a compass for companies trying to navigate the complexity of Industry 5.0.
Key words: Industry 5.0 / decision outcomes / decision factors / decision implementation / data-driven decision making
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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