Using Safety Data as a Predictive Tool

You track a lot of safety data. So much data you could build a lake and swim in it. You know there are answers somewhere in all those numbers, but you don’t know how to find them.

Sound familiar?

If you’re like many EHS departments, you understand the value of collecting data but aren’t quite sure what to do with it once you have it. We say it’s time to think about your data from a new perspective. You see, data and safety metrics aren't just the details of today – they're the patterns that will stop disasters tomorrow.

How Predictive Analytics Informs Safety

If anything, predictive and safety analytics is the backbone of safety data. If you’re not collecting data to perform predictive analytics, you’re not seeing real results from that data.

However, this isn’t a psychic staring into a crystal ball, nor is it a computer wizard pulled from the annals of the IT basement. To perform predictive modeling (and do so in a timeframe that’s actually efficient), you need to leverage machine learning.

That’s because the human brain can only manage four pieces of information at once, and we’re notoriously bad at multitasking. If you want to see trends in your data, you’ll need to give the humans in the office some help. Some software can handle thousands of data streams at once and use them to identify patterns.

Principles of Successful Predictive Analytics

You need three principles for successful predictive analytics:

1. Accuracy
2. Stability
3. Segregation

The output is only as good as the input, so you want to make sure your safety data is sound. You also want to make sure that your model for measuring the data is consistent across data sets, which is where machine learning comes in.

Finally, there’s risk segregation. The first two principles are used to verify the scientific validity of the model, but risk segregation is more about accepting that no model is perfect, nor can any model predict the future. It’s more about putting data in context and asking the right questions.

How to Use It

With that in mind, let’s talk about how you can use your safety data in predictive analytics.

Let’s say, for example, you collect data on workplace accidents and incidents for a period of months. And let’s say you want to find out whether there’s some sort of pattern in the incidents. You can upload and segment that safety data into predictive software to see if certain incidents are more frequent, or tend to happen at certain times or happen when certain conditions are present.

This will allow you to look at the current conditions and make educated predictions about the likelihood of certain incidents happening in the future. Then you can take steps to mitigate those incidents from happening.

Turn Your Safety Data into Actions

The good news is that you have more safety data than ever before to make accurate predictions. The better news is that EHS software is now equipped to handle big data quickly and effectively.

So, if you could stop accidents before they happen, the real question is why you haven’t invested in safety software yet? If you’re looking for the right software, we’ve got exactly what you’ve been looking for: safety software that makes it easy to manage all your incoming data in one user-friendly interface.

Want to find out how it works? Get in touch today to schedule a demo.

Related: Analytical Skills and the EHS Professional