Data Analysis for Improved Performance
Knowledge is power. High EH&S Consulting has the expertise in data analysis and bio-statistics to provide detailed understanding of your organization's safety performance. So your incident rate has increased? Is the change statistically significant? What about the general trends in performance? Is the age of those having accidents statistically different from those who aren't and by how much? Which departments or business units are having changes in rates that deserve your attention? A small operation may have two accidents in a period and because of their low hour base, this creates a dramatic increase in the incident rate.
Suddenly everyone is concerned. However, this change is likely not significant to the operation. What factors are associated with increased incident rates in your facility and are shown to be statistically significant? What are the quantitative risk levels of these identified factors? What common sources of exposure and injury types are trending upward / downward?
While we can perform a basic review of accidents, we can also provide a much deeper understanding of your data. These analyses can drive decisions about specific loss control efforts to be put in place. A recent analysis at a company identified that employees with less then 1 year of service were accounting for most of the accident events. This is interesting, but without knowing the base-population demographics, we might be driven to institute programs that focus on the "new employee". In reality, the service time for ALL employees was heavily skewed, so the revelation that those being injured had less than one year of service was just a reflection of the worker population. A statistical t-test comparing the accident groups to the non-accident groups demonstrated no difference between the groups. In other words, service time wasn't a factor in increasing risk of accident as had been initially thought. A manager declares that the individuals being hurt are all generation "X-ers". Is this true? While those in most recent memory may have fallen into this category, a more detailed analysis suggests that actually the older population is at greater risk for injury. Basing injury prevention programs on what people think vs. solid data, can waste organizational resources.
Slope trends and comparisons for exposure hours using logistic or possion regression analysis can help pinpoint concerns and issues. Increased data population from accident reports and subsequent analysis can provide very specific recommendations to reduce risk. For example, after a detailed source identification, data entry and analyses, it was determined that a company should establish a trailer bed maintenance program. Prior events, identified that five accidents had occurred in the period assessed resulting in over $300,000 of workers' compensation losses in the period. These details often go unnoticed in a large organization unless specific analyses are performed.
We use excel as well as statistical software packages to analyze your data and provide recommendations for improvement.