Volume 15, Issue 1 (3-2025)
J Health Saf Work 2025, 15(1): 105-124 |
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Ahmadabadi A, Khaloo S, Saeedi R, Gholamnia R. Presenting a Business Intelligence Dashboard to Analyze the State of Safety Risks by the Predictive Risk Index (PRI) in a Pharmaceutical Company. J Health Saf Work 2025; 15 (1) :105-124
URL: http://jhsw.tums.ac.ir/article-1-7128-en.html
URL: http://jhsw.tums.ac.ir/article-1-7128-en.html
1- Department of Health, Safety and Environmental Management, School of Public Health and Safety Workplace Health Promotion Research Center Shahid Beheshti University of Medical Sciences
2- Department of Health, Safety and Environmental Management, School of Public Health and Safety Workplace Health Promotion Research Center Shahid Beheshti University of Medical Sciences ,gholamnia@sbmu.ac.ir
2- Department of Health, Safety and Environmental Management, School of Public Health and Safety Workplace Health Promotion Research Center Shahid Beheshti University of Medical Sciences ,
Abstract: (1287 Views)
Introduction: One of the most critical factors supporting industry managers and decision-makers in adapting to changes is the Business Intelligence (BI) dashboard. Dashboards, enriched with indicators, reports, and charts, enable managers to monitor industry performance at any given time.
Material and Methods: To evaluate safety status and prevent future accidents, risk factors within the industry were assessed using the RI risk index. In this study, the index was calculated through a geometric averaging relationship. Additionally, the ARIMA (2,0,0) time series model was applied, converting the average daily Risk Index into the Predicted Risk Index.
Results: Based on the occurrence of accidents, when the trend of the Risk Predictor Index is below 3, it is considered a safe zone in that industry. When the index trend is between 3 and 4, it represents a warning zone. If the index exceeds 4, there is a high probability of accidents, categorizing it as an action zone. According to the presented dashboard and zoning, the industry manager can conclude that 33% of risks are in the action area, 24% of the risks are in the warning area and 43% of the identified risks are in the safe area.
Conclusion: The results of this study demonstrated that leveraging business intelligence for prioritization can enhance decision-making and analytical processes for senior organizational managers.
Material and Methods: To evaluate safety status and prevent future accidents, risk factors within the industry were assessed using the RI risk index. In this study, the index was calculated through a geometric averaging relationship. Additionally, the ARIMA (2,0,0) time series model was applied, converting the average daily Risk Index into the Predicted Risk Index.
Results: Based on the occurrence of accidents, when the trend of the Risk Predictor Index is below 3, it is considered a safe zone in that industry. When the index trend is between 3 and 4, it represents a warning zone. If the index exceeds 4, there is a high probability of accidents, categorizing it as an action zone. According to the presented dashboard and zoning, the industry manager can conclude that 33% of risks are in the action area, 24% of the risks are in the warning area and 43% of the identified risks are in the safe area.
Conclusion: The results of this study demonstrated that leveraging business intelligence for prioritization can enhance decision-making and analytical processes for senior organizational managers.
Type of Study: Research |
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