The number one thing all employers in the construction industry should be looking to do is reduce the number of work-related injuries, accidents, and fatalities on their jobsite. This is because, in addition to having a negative effect on employee morale and the reputation of your business, such injuries are accompanied by a snowball effect with respect to costs. This includes the price of replacement training, incident investigation, compliance training, lost productivity, and more. Now more than ever, contractors should be looking for any means available to eliminate safety hazards and reduce lost-time injuries on the jobsite.
The solution is data. Identifying and understanding trends from potential and actual accident data is the first step to identifying the root causes of work-related injuries and taking action to mitigate them. In today’s article, we’ll be discussing how employers can use predictive analytics to collect data on past trends and predict future injuries. If an employee has filed a claim against you for a work-related injury, contact one of our Naples construction attorneys to guard your business against potential liabilities.
What Is Predictive Analytics?
Predictive analytics is a subsection of data analytics aimed at applying mathematical models to large amounts of data to identify trends using patterns of previous behavior and predict future outcomes. With a combination of machine learning, statistical algorithms, and data mining, any organization is able to use their past and current data to reliably forecast trends and behaviors days, weeks, and even years into the future. Essentially, it allows organizations to become proactive and forward-looking by providing them with the ability to anticipate outcomes and behaviors based on real data rather than a hunch or assumption.
What Kind of Data Goes Into Predictive Analytics?
To maximize the effect of predictive analytics on jobsite safety, you need to utilize the appropriate datasets. Ideally, only data that specifically pertains to workplace safety should be collected for inclusion in the algorithm. Examples of valuable data categories include the following:
- Tools in use
- Machines in use
- Level of experience of the worker
- Workers’ compensation details
- Design elements
- Safety training and compliance
- Injury costs
- Accident reports
- Injured-worker demographics
- Timeline of claims
The information gleaned from these datasets is used to create a predictive model of which types of workers are likely to experience which types of injuries; when these injuries are likely to occur; where these injuries are likely to take place; on which equipment or machinery; using which tools; and how much money the injuries could wind up costing your company. Information such as injured-worker demographics as well as claim timelines are, in turn, useful for guiding future outcomes in injury claims. In the future, more datasets are likely to be included in predictive analytics, such as third-party data like weather information, data from connected devices like fatigue monitors, and human capital management data like workforce management. If you need any assistance on how you can collect or manage documentation like this on your jobsite, don’t hesitate to reach out to one of our Naples construction lawyers.
How Effective Is Predictive Analytics At Improving Workplace Safety?
The value of predictive analytics cannot be understated when it comes to reducing the number of workplace injuries. It has statistically been proven time and time again, using 4 years of real-world data, that workplace injuries can be predicted with accuracy rates as high as 97 percent. One Fortune 150 energy company reduced its injury rate by 67 percent within 18 months, while another Fortune 150 manufacturer reduced its lost workday rate by approximately 97 percent within a year. If your company is looking to benefit from similar results and positive ROI on your investment in predictive analytics solutions, it’s time to partner with one of our Naples contractors lawyers.
One of our team members will be glad to sit down with you to determine what you are trying to accomplish with the use of predictive analytics, what questions you’re trying to answer, and how you will measure success through this program. Whether you’re trying to simply predict when injuries will occur or optimize your response to these injury risks will determine what level of predictive analytics you need to be using.
Disclaimer: The information contained in this article is for general educational information only. This information does not constitute legal advice, is not intended to constitute legal advice, nor should it be relied upon as legal advice for your specific factual pattern or situation.