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 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.

Establishment-level safety analytics: a scoping review.

The use of data analytics has seen widespread application in fields such as medicine and supply chain management, but their application in occupational safety has only recently become more common. The purpose of this scoping review was to summarize studies that employed analytics within establishments to reveal insights about work-related injuries or fatalities. Over 300 articles were reviewed to survey the objectives, scope and methods used in this emerging field. We conclude that the promise of analytics for providing actionable insights to address occupational safety concerns is still in its infancy. Our review shows that most articles were focused on method development and validation, including studies that tested novel methods or compared the utility of multiple methods. Many of the studies cited various challenges in overcoming barriers caused by inadequate or inefficient technical infrastructures and unsupportive data cultures that threaten the accuracy and quality of insights revealed by the analytics.

Advancing safety analytics: A diagnostic framework for assessing system readiness within occupational safety and health.

Big data and analytics have shown promise in predicting safety incidents and identifying preventative measures directed towards specific risk variables. However, the safety industry is lagging in big data utilization due to various obstacles, which may include lack of data readiness (e.g., disparate databases, missing data, low validity) and personnel competencies. This paper provides a primer on the application of big data to safety. We then describe a safety analytics readiness assessment framework that highlights system requirements and the challenges that safety professionals may encounter in meeting these requirements. The proposed framework suggests that safety analytics readiness depends on (a) the quality of the data available, (b) organizational norms around data collection, scaling, and nomenclature, (c) foundational infrastructure, including technological platforms and skills required for data collection, storage, and analysis of health and safety metrics, and (d) measurement culture, or the emergent social patterns between employees, data acquisition, and analytic processes. A safety-analytics readiness assessment can assist organizations with understanding current capabilities so measurement systems can be matured to accommodate more advanced analytics for the ultimate purpose of improving decisions that mitigate injury and incidents.

The fatiguing effects of camera use in virtual meetings: A within-person field experiment.

The COVID-19 pandemic propelled many employees into remote work arrangements, and face-to-face meetings were quickly replaced with virtual meetings. This rapid uptick in the use of virtual meetings led to much popular press discussion of virtual meeting fatigue (i.e., "Zoom fatigue"), described as a feeling of being drained and lacking energy following a day of virtual meetings. In this study, we aimed to better understand how one salient feature of virtual meetings-the camera-impacts fatigue, which may affect outcomes during meetings (e.g., participant voice and engagement). We did so through the use of a 4-week within-person experience sampling field experiment where camera use was manipulated. Drawing from theory related to self-presentation, we propose and test a model where study condition (camera on versus off) was linked to daily feelings of fatigue; daily fatigue, in turn, was presumed to relate negatively to voice and engagement during virtual meetings. We further predict that gender and organizational tenure will moderate this relationship such that using a camera during virtual meetings will be more fatiguing for women and newer members of the organization. Results of 1,408 daily observations from 103 employees supported our proposed model, with supplemental analyses suggesting that fatigue affects same-day and next-day meeting performance. Given the anticipated prevalence of remote work even after the pandemic subsides, our study offers key insights for ongoing organizational best practices surrounding virtual meetings. (PsycInfo Database Record (c) 2021 APA, all rights reserved).