Workplace safety and data-driven analysis go hand-in-hand. So, let’s understand how one complements the other. 

Workplace safety data analysis allows us to understand how occupational health and safety have evolved over the years. In the early 1990s, workplace safety metrics suggest there were more than 23,000 fatal injuries in various industries across the United States.

It’s important to understand that this was before the 38 states had regulated workplace safety—compared to now, when all 50 states partake enthusiastically. In addition, the changes in regulations pertinent to workers’ and workplace safety and security have enhanced a safe and healthy work culture to combat risks and hazards. 

Moreover, to ensure that employees take responsibility for their health and safety and the workplace facility, the Federal OSHA provides safety training through its highly interactive online training courses. The OSHA 10 Hour online courses for entry-level General Industry and Construction Industry workers are highly advised since they provide basic knowledge about site safety hazards and many other safety-related topics. On the other hand, 30 Hour online construction is recommended for Supervisors or Managers employed in the Construction Industry to equip them with advanced level information and skills.

Because the old saying “better safe than sorry” applies to the Big Four industries more than anything else. That’s the reason even when people buy 2000 TikTok followers UK they ensure to make purchases from a safe source.  So, how and where do data-driven safety improvements come into play? Let’s find out. 

What Is Data-Driven Analytics? Its Role In Workplace Safety

Data-Driven analytics is the term used to describe something that’s driven by proven and factual information. Based on the statistics gathered by data technicians, a company or organization can implement new strategies for better results. 

In this case, workplace safety can employ safety analytics software or other tools to understand a few key things, such as:

• The potential risk of injury;
• Data-driven hazard identification;
• Importance of protective gear;
• Cost of workplace injuries;
• Predicting safety measures for potential catastrophes;
• And safety data visualization to teach workers/supervisors to take better measures. 

Data has become quite an essential part of any workplace today because of its ability to predict potential outcomes—including when a strategy is implemented, compared to when it’s not. That’s why the role of data-driven safety culture is increasing every day in workplaces around the globe. 

4 Ways Data-Driven Analytics Can Improve Workplace Safety

Suppose you are wondering how workplace safety can be improved with the help of data-driven analytics. In that case, it’s important to break it into important sections. 

These sections include the role of safety culture, how productivity is improved, and the overall impact of data on safety. So, let’s talk about the four ways it can impact workplace safety: 

1. Promoting Safety Culture

Safety culture is the term used to describe the attitude of employers and the responsibility shown by employees in a potentially hazardous work environment. In a workplace that promotes a safety culture, you would find people with PPE (Personal Protective Gear), common inspections, etc.

A company’s safety culture ensures it complies with local safety rules. Here’s how data-driven analytic fit into this narrative:

• It ensures shared accountability based on employee/employer neglect or mistakes;
• It benchmarks potential cases of hazards and failures of safety equipment, measures, and other safety trends;
• It targets performance efficiency to ensure productivity during work hours;
• And it comprehends and analyzes employee morale in a safe work environment.

Besides that, some employers also report that data-driven safety culture is more cost-effective and time-saving. Therefore, the promotion of a safety culture on the basis of data alone is worth investing in big data for potentially risky workplaces. 

2. Increasing Productivity-Driven Work Days 

Every employer’s dream is to drive productivity and check all boxes during a workday. Yet, when an unfortunate safety hazard happens, the workplace goes into perils, including time wastage over accidents and the potential cost of dealing with it.

Big data analytics are known to improve productivity by providing simpler and better solutions, such as:

• Working smarter, compared to harder in certain areas;
• Using machines or equipment instead of humans in potentially risky areas of a worksite;
• Establishing safety performance metrics for supervisors and workers to abide by.

For instance, consider all the time workplace hazards can hinder productivity, such as they can cause a company to lose important work hours due to work stoppage. Besides that, any potential hazards will cause damage to expensive personal and worksite equipment.

And, if some neglect happens on the employer’s end, it could potentially be a million-dollar lawsuit. Therefore, using data and checking boxes on the safety analytics dashboard also ensures that an employer remains safe and keeps their workers safe while improving productivity. 

3. Predictive Safety Analysis 

Workplaces are always vulnerable to whistleblowing if they aren’t thorough in their safety measures. In 2021, OSHA inspected around 24.5 thousand workplaces—and around 70% of those were filed complaints by workforce or former employees. 

Now, accidents occur in the safest workplaces, but an employee can take preventive measures. That’s when data-driven strategies can implement workplace safety technology as well as practices. 

Depending on the industry and worksite nature, a company can analyze potential accidents in specific areas of a worksite and analyze which workers are more at risk. By providing preventative methods before incidents, a company can safeguard their force a lot more briskly and correctly and ensure all-around safety measures. 

4. Data-Driven Risk Management 

OSHA’s Fata Facts section states many different types of unfortunate incidents in various workplaces. Some of them are related to potential electrocution, getting choked by hazardous air, or accidents caused by crushing (with heavy equipment).

The point of using this data is to ensure data-driven risk management and prevent any incidents in potentially risky situations. For instance, if you look at workplace fatal incidents in the US, you will see that most incidents are caused by:

• Neglect in training/proper measures;
• Usage of heavy machinery in risky situations;
• Employee neglect and is not where they should be, i.e., between a truck and a loading dock;
• Not wearing the right equipment for the job, etc.

To emphasize the last point, a lot of workers who got electrocuted were not using preventive measures such as wearing gloves. On the other hand, employees affected by hazardous chemicals were affected because of the lack of respiratory protective equipment. 

So, a company can implement company-wide policies and strategies that ensure better risk management. This is especially when a company considers all this data and establishes ground rules for safety. That’s when the safety performance metrics convey the importance of data-driven safety. 

Conclusion

These are some of the best pieces of evidence that data-driven safety is the future in workplaces. Using technology for the betterment of lives is nothing new, but implementing the latest technology to ensure workplace safety is the responsibility of every company/organization that falls under specific industries.