How is your company using Predictive Analytics to improve job site safety?
Many think that using compiled data and business trends to predict or improve workplace safety is a relatively new concept. What you may not realize, however, is the use of Predictive Analytics has been in place in your life for a long time, you may just not have labeled it as such. Your DVR studies the TV programs you watch and learns your preferences. Insurance companies study your behavior and its impact on your health to issue you a policy. Banks review your financial history and credit to determine the type of loan you are eligible to receive. Even Starbucks gathers data on your behavior to determine the type of coffee you will buy in the future. These examples can go on and on….
Similarly, companies large and small are using predictive analytics to decrease workplace incidents – by focusing on behavioral trends. Below are some things to think about when considering implementing Predictive Analytics in your Behavioral-based Safety Program:
- Predictive Analytics is becoming increasingly popular and it’s not going anywhere. It should be an important piece of your program — and may even be required in the future.
- The price of things such as increasing fines, the cost of rehabilitation or lost time due to an injury, and more regulation are all strong reasons to invest in a Predictive Analytics platform.
- When evaluating companies that provide various Analytics Workplace Safety Systems, ask these questions (provided by Arbill):
- Does the system look at objective or subjective data?
- Can the system track multiple indicators?
- Is the system easy to use?
- Can the system detect risk down to the employee level?
- Can the system be tailored to your business or industry?
Think Holistically. Focus sharply on the behavior of your workforce. Commit to increasing observations at a micro level. Invest in the safety and wellbeing of your people. Predictive analytics is just another important tool in your toolbox to ensure a healthy safety culture!
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