Employee safety is not exactly a hot topic, nor is it a particularly interesting one.
Naturally, it involves a lot of procedures and processes. It’s usually somewhat tedious for all parties involved, until a safety issue actually arises.
At this point, all the old procedures will be given a good once-over.
Enter predictive analytics, and the entire challenge becomes a bit less bothersome and a whole lot more intelligent.
Let’s talk about its impact.
What Kind of Data is Needed?
Predictive analytics is, essentially, using the past to predict the future. And unlike the crystal ball, it requires a whole lot of data to make the most accurate, actionable, and timely predictions.
The more data you feed into your analytics dashboard, the better results you can expect.
Here are the main areas to focus your data collection processes on:
- Previous safety incidents: as much information about each incident as possible, including relevant details that have preceded it, how it has unfolded, and the consequences that ensued
- Incident rate: will be useful as a means of tracking improvements
- Employee safety training and certification: will help you pinpoint the individuals who require additional training or additional areas you need to focus on
- Tools in use at the time of the incident
- Worker experience levels
- Any injury costs and details about their severity
- Any compensation details
Naturally, you also want to ensure all of this data is accurate and that it has been gathered from reliable sources.
Injury Prevention
Predictive analytics is one of the most efficient ways to prevent construction fatalities as it will identify tasks that are particularly high-risk. This allows everyone involved to raise their focus levels and employ added care around these specific tasks.
This also allows factories, construction sites, and manufacturing companies to rethink the way they deploy their employees on the ground. They can ensure the most experienced and well-rested person is in charge of the most delicate tasks.
It will pinpoint the underlying causes of injuries, whether it’s employee fatigue, the use of wrong materials, or a fault in the planning process. This is achieved by – you guessed it – the analysis of worker injury data. This data is crossmatched with future and ongoing scenarios, raising an alert in time for managers to react.
Analytics is not a silver bullet for injury prevention, of course. There are situations where it won’t be able to react on time, and these mostly involve clear-cut cases of human error. These kinds of situations often cannot be predicted even with the use of the cleverest of AI.
Unique Insight into Different Sites
Predictive analytics allows for the development and application of procedures that are specific to each individual site a company may have.
Each factory and construction site will come with a unique set of challenges based on the people, tasks, and materials involved. This means that developing one overarching safety plan is not just impossible, but even unnecessary. Creating site-specific plans is much more efficient, and predictive analytics makes this very possible.
Creating a specific and custom list of safety procedures for each location would cost a lot of time and resources if it were to be done manually. Data analytics, on the other hand, is much more cost-effective and has no expiration date. It can be used over and over, making it the ideal solution.
Alerts in Real Time
One of the more obvious advantages of predictive analytics is that it enables managers to make real-time decisions based on real data. This prevents accidents and injuries before they can occur.
Old safety procedures were largely based on data that is essentially static. This data is usually not updated regularly and can very quickly become outdated. Contrary to that, safety procedures that are based on predictive analysis will always be current. That’s especially if your software is continuously fed with new sets of data.
We don’t even need to get into the impact making a decision based on outdated data can have on an unfolding situation. With sensors placed throughout a factory floor or at strategic points on a construction site, you can literally keep an eye on facts and figures as they are being gathered. The system itself can alert you when the confluence of data is pointing toward disaster or danger.
Add to that, the fact that employees can be equipped with wearables that will also sound the alarm when someone is feeling unwell or might just need to slow down, and you can improve employee wellbeing significantly. This, in turn, will also reduce the risk of injury, bearing in mind the number of incidents and injuries that occur due to fatigue and inattention.
Modeling Future Scenarios
Predictive analytics can also help you come up with procedures for scenarios that have never happened on your site yet, but can potentially occur in the future. This is especially important when it comes to natural disasters and global occurrences such as the recent pandemic. Disaster planning can save not only lives. but property and resources too.
With the help of your analytics software, you can determine what the best
solutions would be for different scenarios and their severity. You can then
educate employees on the best course of action if a certain scenario should
ever unfold.
When something unpredictable happens, it’s often up to the individual to find the most appropriate solution and reaction. But as humans, we are liable to lose our heads and cool. With the help of predictive analytics, employees never have to find themselves at a loss for the next step.
Final Thoughts
Predictive analytics can help reduce the risk of injury and allow floor and site managers to react in real time, relying on reliable and accurate data sets that have already taken into account the most likely outcome.
Of course, human input will still be required to monitor the real-life situation as it unfolds. No matter how sophisticated software solutions become, they will never be present in the three-dimensional world.
