Safety Reporting Best Practices: Using Actionable Analytics
Predictive analytics allows companies to transform their existing safety data into an effective tool for preventing future injuries and fatalities.

It's an unfortunate reality that we're still not where we should 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, its reputation, and its ability to attract and retain talent.
In an effort to improve their safety performance, many businesses have begun digging into a massive untapped resource. Every organization creates a huge amount of data, but without a concerted effort to gather and analyze that data, much of it goes unrecorded and unused. With advanced analytics, companies can not only collect all of this data but also use it 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 - somewhere in the range 80 to 97 percent. Safety professionals and company leaders who leverage analytics software can, therefore, gain a deeper insight into the root causes of workplace incidents and ensure that they are making optimal use of their resources.
Safety Reporting Best Practices
According to the National Safety Council, recording and reporting incidents (including near misses) can significantly improve workplace health and safety. Conversely, organizations that fail to adopt a proactive reporting culture tend to have higher rates of workplace incidents and near misses, while also losing out on the insights that could be revealed by analyzing those events. Encouraging and engaging in the best safety reporting practices, then, will allow an organization to operate at high safety performance levels.
Some best practices 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 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
(Learn about 10 Critical Steps for Investigating and Reporting Accidents)
What Is Predictive Modelling?
Predictive modelling is an approach to data analysis that uses data mining and various statistical techniques to produce a mathematical model that can effectively predict and segment future events, including work-related injuries.
With predictive modelling, employers can analyze disparate data sets and identify workplace conditions that are indicative of high severity risks.
Using Analytics to Improve Safety Performance
Comprehensive reporting practices will provide you with a wealth of information about your organization's safety performance. Unfortunately, much of the data gathered are lagging indicators, meaning the only provide information on incidents that have already occurred, not those that may occur in the future.
Predictive analytics flips this information on its head. It takes those lagging indicators, analyze them, and can help you identify predictors of incidents before those incidents occur - in other words, leading indicators of safety.
This predictive power allows your organization to implement proactive strategies that focus on preventing injuries, rather than relying on reactive procedures after injuries have already occurred.
To implement predictive methods:
- First, identify factors that influence incident levels and lead to safety issues.
- Second, use those factors to identify high-risk work areas or groups of employees.
- Finally, identify strategies to optimize your injury prevention programs. For instance, using insights gained through data analysis to increase safety training and implement stronger controls for high-risk areas.
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 include but are not limited to:
- The knowledge, skills, and attitudes of employers or workers
- The availability of consistent, quality information
- Access to trained analysts who have the right tools
- The ability to frame questions and identify situations that are likely to benefit from prediction
- 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
While many organizations place a heavy emphasis on workplace safety, many experience a plateau in their safety performance. No matter what measures they put in place, serious safety incidents and fatalities continue to occur.
When this happens, it's time to take a step back. Instead of implementing new safety measures, find a new way to look at the information your organization collects. Instead of using it to paint a picture of your past safety performance, employ statistical modelling methods to predict future events and identify the safety measures that would have the greatest impact.
This effectiveness and efficiency will result in two goals every company strives for: a reduction of both costs and the rate of injury.
But this will only work if your organization collects 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.
Next Steps
To find out how to turn your EHS data into actionable insights and prevent incidents, check out Safety Intelligence.
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Written by Adrian Bartha | Chief Executive Officer

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