It's an unfortunate reality that we're still not where we want to be when it comes to workplace safety. Safety continues to be a rising concern for both safety professionals and executive teams across all industries. And they have good reason to worry: an organization’s health and safety management strategies can directly affect its profitability and reputation, as well as its ability to attract and retain talent. Not surprisingly, many businesses are now taking advantage of their big data—obtained through advanced analytics—to make predictions regarding the occurrence and prevention of workplace injuries.
According to numerous researchers, advanced analytics tools can predict workplace incidents with high levels of accuracy, ranging from 80 to 97 percent. As such, leveraging analytics software allows safety professionals and company leaders to not only gain a deeper insight into the root causes of workplace incidents, but also how to use their resources in the most optimal way.
Safety Reporting Best Practices
According to the National Safety Council (NSC), recognizing and reporting workplace incidents and near misses can significantly improve workplace health and safety. Organizations that fail to adopt a proactive reporting culture not only tend to have higher rates of workplace incidents and near misses, but are also losing opportunities to prevent incidents based on the gaps that these incidents and near misses can reveal. Encouraging and engaging in the best safety reporting practices, then, will allow an organization to operate at high safety performance levels.
Some best practices to consider when reporting workplace incidents and near-misses include:
- Establishing a reporting culture by company leaders, which encourages employees to act on every opportunity to identify and control hazards, reduce risk, and prevent harmful incidents
- Ensuring that the reporting system is non-punitive and, if the person reporting wishes, anonymous.
- Investigating all incidents and near misses to identify root causes, as well as any weaknesses in the company’s existing health and safety management system.
- Using the results obtained to improve safety systems, control hazards, and reduce risks.
What Is Predictive Modelling?
Predictive modelling involves the application of data mining and various statistical techniques to produce a mathematical model that can effectively predict and segment future events—in this instance, work related injuries. Using predictive modelling to improve safety performance is an approach that holistically analyzes disparate data sets and identifies certain workplace conditions that are indicative of high severity incident risks.
Using Analytics to Improve Safety Performance
Comprehensive reporting practices provide a wealth of information about an organization’s level of safety performance. While safety reporting provides information on what has already occurred, predictive modeling techniques can use this data to help identify high-risk predictors of incidents before those incidents occur. This predictive ability allows safety professionals and company leaders to put in place strategies that focus on workplace injury prevention.
The first step to implementing predictive methods involves identifying factors that influence incident levels, such as independent, quantitative risk predictors and lead indicators of safety issues. Second, the insights from the risk predictors and lead indicators are used to identify high-risk work areas or groups of employees. Finally, these insights help organizations identify strategies to optimize their injury prevention programs and ensure the health, safety, and well-being of their employees. Strategies to improve safety practices based on insights gained from the analysis can, for example, include the implementation of increased safety training and measures for high risk areas, or targeting areas for wellness or safety awareness programs (for practical advice on implementing that last strategy, see How Can I Raise the Safety Awareness of My Workers?).
Barriers to Implementing Predictive Analytics in the Workplace
According to the National Institute for Occupational Safety and Health (NIOSH), there are many barriers to using predictive analytics to improve workplace safety and health. These may include but are not limited to:
- The knowledge, skills, and attitudes of employers or workers (see Safety and Overconfidence for a related discussion)
- The availability of information of adequate quality and consistency
- Access to trained analysts who have the tools to do their work
- The ability to frame questions and identify situations that are likely to benefit from prediction
- The lack of motivation to apply analytics beyond sales and marketing
- Privacy concerns that may limit access to relevant data
A New Way to View Safety
Despite the fact that many organizations place a heavy emphasis on workplace safety, many are still experiencing a plateau in their safety performance statistics. No matter what measures they put in place, serious safety incidents and fatalities continue to occur. What these organizations may need is a new way to look at the information they collect.
Automated analytics tools can revolutionize the way companies use their safety reporting data. Instead of using that data to paint a picture of the organization's past safety performance, advanced statistical modelling transforms that data into a tool for predicting and preventing future incidents. By plugging in the data collected over the company's entire history, these models can reveal previously unnoticed hazardous locations, dangers associated with tasks, and unsafe patterns in employee behavior. These revelations allow companies to allocate its safety resources with extreme effectiveness and efficiency, reducing both costs and rates of injury.
But this will only work if companies collect enough safety data to get a comprehensive picture of statistical trends in the first place. This means that following safety reporting best practices such as The Guide to Advanced Safety Analytics and Reporting, including recording as much information as possible about even the smallest safety incident, is more important than ever. Collecting that data is no longer simply a matter of compliance; it could be the key to dramatically improving your future safety performance.
When applied to workplace safety, actionable analytics brings employers one step closer to the vision many organizations share: sending every employee home safe at the end of each day. After all, if workplace injuries can be predicted, they can be prevented.
To find out how to turn your EHS data into actionable insights and prevent incidents, check out Safety Intelligence.