Even in workplaces known for their extremely safe practices, employees may be at risk of getting injured by dangerous equipment, a lack of training or other factors. However, predictive analytics platforms could reduce those hazards.

How Do These Predictive Analytics Tools Work?

The features of predictive analytics platforms vary depending on the kind selected. However, they all work by collecting large quantities of data and analyzing it to spot patterns indicating similarities in past dangerous events. Employers can use that data as guidance when figuring out how to make changes in company policies.

For example, it may become evident that 95 percent of the contractors who got injured during a given year while working for a particular company had fewer than 20 hours of safety training before receiving their assignments. In that case, an employer could conclude more training likely reduces injury rates.

Some Analytics Suites Monitor Driving Habits

If people have jobs that require transporting fleets across state lines or country borders, they could easily risk their safety, as well as that of everyone else on the road. Fortunately, some analytics tools track things like excessive lane departures, hard braking patterns or speeding.

Then, managers could coach at-risk drivers based on what the analytics show. Factors like shift length, years of experience in the long-haul trucking industry and extra stress in a person's home life could make accidents more likely to happen. But intervention from supervisors could prevent catastrophes. Without the help of predictive analytics, those upper managers might not know there is cause for concern.

Numerous Ways to Track Data

One of the convenient things about predictive analytics options for workplaces is they give purchasers plenty of opportunities for collecting data and choosing which information is most important for risk reduction.

For example, a company might attach accelerometers to safety helmets and use those to measure the percentage of time an employee wears a hardhat or does not. Or, other platforms analyze weather data. If it shows most accidents occur on rainy days, an employer might be proactive by alerting teams about upcoming wet weather and reminding them of ways to stay safe.

Moreover, the manufacturers of some platforms believe there is a direct link between human behavior patterns and accidents related to carelessness. Another way to depend on predictive analytics, then, is to have employees take personality tests, and use those as a basis for the data fed into the system.

IT professionals commonly use analytics to avoid network failures. These broader uses of analytics across all kinds of work similarly illuminate problems and provide the early warnings necessary for taking corrective action.

More Safety for Lone Workers and People in Isolated Areas

In many cases, people work in the company of others. Then, if things go wrong and an individual falls, becomes suddenly ill or otherwise has distress while on the job, their co-workers can summon help. However, companies must implement thoughtful strategies to keep lone workers safe, since they often don't work around others.

These employees may wear panic buttons clipped to their clothes or use check-in apps that allow them to report their location and activities. The applications usually give notifications if workers don't provide information at expected intervals. Predictive analytics could shed light on the things that most likely put lone workers in danger, too.

When people work in teams, but are isolated from the public while working on offshore rigs or in mines, predictive analytics could also pick up on things people would otherwise miss.

Researchers in Australia, for instance, engineered a tool that measures the patterns of movement of dirt and other substances around mines, then compares those with signs of a looming issue such as a landslide.

This system senses trouble two weeks in advance. Previous methods only gave hours of notice.

Choosing an Appropriate Predictive Analytics Tool for Your Company

It should be obvious there is a substantial degree of variety in the predictive analytics offerings marketed to companies. As such, when evaluating the possibilities, you have several things to consider.

Ease of use and implementation are both crucial, because if it's difficult to use the platforms each day or integrate them into your company operations, encouraging widespread adoption will be challenging.

You'll also need to find out if it's possible to track data associated with individual employees. It's not a good idea to use predictive analytics platforms to take punitive action, but as discussed earlier, the analytics provided could show which employees could benefit from coaching.

Is it possible to tailor the software to your industry or the type of work employees typically do? If so, you'll likely get data that's more relevant than a generic solution would offer.

Find out about the support offered after purchase, too. Could you get onsite training, as well as technical support when problems arise?

Data Analysis and Responsive Actions Promote Safety

It's not enough to have a robust platform that shows trends and warning signs. That's a good start, of course, but companies must accompany analytics with consistent responsiveness. Then, work environments and employees should be measurably safer.

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