Predictive analytics encompasses techniques for data mining to analyze and predict events based on large amounts of collected information. This information is used for statistical calculations to predict future events. This can be applied in many industries, such as marketing, insurance, healthcare, telecommunications, retail, travel, and many others. For the purposes of this article, we will discuss how predictive analytics could benefit work health and safety routines. Making predictions about potential hazards and risks could be very valuable information used to save money, time, and even lives. With our current technology, we can gather enormous amounts of data, and readily compile it into useful information. This idea commonly referred to as “Big Data,” has allowed companies to grow, reach out to individual needs and interests, and has paved the way for the way businesses interact with their customers. Using the power of predictive analytics can also be an integral part of making your business more efficient, and getting more out of your health and safety routine.
Benefits of Predictive Analytics for Health and Safety
Imagine an assembly line of workers constantly in motion with hazards all around them. Using large machinery, exposure to dangerous chemicals, and working in high places are just a few of the risks involved in many industries. Being able to predict when a machine might require maintenance, or higher risk areas in the workplace is very useful information to have in order to prevent accidents from occurring. If the data is showing that your workers are constantly getting sick in a particular area of the building, you can identify this area as a hazard that needs to be disinfected to prevent future occurrences. Another example could be a machine that tends to breakdown at a particular time of the day. Studying this data and using it to solve problems can make your business run more efficiently and will help the productivity of your workers.
Some of the data that could be helpful to health and safety programs for injured workers may include: past safety experience, age, duration of employment, time of shift, location, ongoing maintenance history and schedules, how your health or safety program is being implemented, or even the types of regulations that apply to that working environment. All of the above-mentioned data will only be useful if it can be applied toward prevention programs and be analyzed in a quick manner. Using algorithms and computing power to do this will enable your health and safety plans to work in real time, crunching data from current situations. The ability to have this real-time data will offer practical solutions to problems that may have occurred during the previous day or week. What is key here is that the data being collected is being used in the right way. Just merely having a bunch of statistics could mean absolutely nothing unless it is being analyzed in the right manner.
When using the process of predictive analytics one must first do two things, decide what type of data to collect, and how to use this data for preventative measures. This will require a sound understanding of the work environment, work flows, and current procedures put into place. Once these things are all known you can start to come up with a health and safety program that is proactive in nature, and one that will save you tons of money as time goes on. The more data that you compile over time, the more accurate your predictions will become. This will keep your employees healthy, uninjured, and productive in the workplace.
Nick Quinlan is a blogger with a focus on health and safety related topics, striving to make sure employers have the latest tools for securing the safety of their workforce. One of the tools is software provided by eCompliance Management Solutions
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