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Establishment-level occupational safety analytics: Challenges and opportunities
In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the pro...
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Published in: | International journal of industrial ergonomics 2023-03, Vol.94, p.103428, Article 103428 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.
•Advances in analytic methods allow companies to reveal insights from big data that previously would have gone undetected.•Future directions in analytics are categorized into readiness, methods, technology integration, data culture, and impact.•Knowledge gaps remain, and more research and demonstrations of effective analytics in OSH are needed. |
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ISSN: | 0169-8141 1872-8219 |
DOI: | 10.1016/j.ergon.2023.103428 |