In Analytics, Use Cases

A University of California, Davis study calculates that workplace accidents and illnesses cost the United States economy $250 billion annually. That’s more than the direct and indirect costs of cancer. That’s more than diabetes and strokes, combined.

The good news is that workplace accidents and illnesses are easier to prevent than cancer, diabetes and strokes. That’s in part because accidents and illnesses happen at a known place and time: on the job.

That sounds obvious, I realize, and a little trite given the seriousness of the topic. But as we know with situational intelligence, understanding the place and time of an actual or predicted event is powerful.

For example: according to the U.S. Bureau of Labor Statistics, 4,679 workers in the US died from workplace accidents in 2014 (the most recent year for which we have data). That’s an awful number, but also a very general number. It doesn’t tell us who, where or when. Can a situational intelligence approach to safety help detect accidents more quickly and even prevent accidents?

To be more specific, 20 percent of those workplace deaths happened in the construction industry. That tells us a lot more about who, where and when. Furthermore, the BLS reports that the nearly half of all construction deaths are the result of falling or being electrocuted.

Now we have two specific and preventable accident scenarios within a single industry.

Imagine that you’re the safety director for a construction company. Receiving a report every morning of the day’s planned elevated and electrical work gives you insight into where accidents might happen later that day. You’d have time to review safety equipment and procedures with workers before they start their tasks. That’s a good first step towards a safer workplace.

Since we’re now in the Internet of Things era, it’s easy to envision that your workers wear safety vests equipped with GPS and other location technology. Knowing the location of all your workers in real time is another step towards protecting them. The vest tells you when a worker is more than, say, three floors off the ground, or within 10 feet of high-voltage equipment.

Warnings about these potentially dangerous situations are pushed to your laptop and also to your mobile device as you’re out on the site. This information helps you respond faster to accidents, since you know exactly where people are working

Analytics can go further, to help prevent accidents. Knowing that falls and electrocutions are top priorities, you can design new measures to restrict access to dangerous areas. By correlating personnel records with scheduled tasks, you know which workers have the certification and experience to safely work at heights and with electrical systems. If a worker is potentially distracted by daydreams about an upcoming vacation, the personnel records flag that potential hazard for you to address during a safety briefing.

These are just a couple of high-value use cases from the construction industry. Similar use cases exist in nearly any industry where workplace safety can be an issue such as utilities, mining, transportation, agriculture and manufacturing.

Analytics is broadly applicable to reducing the impacts of workplace accidents and illnesses. Those impacts include hard costs associated with insurance premium and claims, litigation, compliance and other expenses that contribute to that $250 billion annual figure. There are also soft costs associated with employee morale, customer dissatisfaction and company reputation.

Improving safety with analytics may be more mundane than curing cancer, but also more achievable.

Image Copyright: hxdbzxy / 123RF Stock Photo

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