Predictive analytics is not a new term in the business world. Many New York companies use this tool in areas such as finance, marketing and sales. However, an increasing number of construction companies are also using predictive analytics to improve workplace safety by reducing work-related accident claims. It works very well when used properly, but there are still struggles for many contractors.
Predictive analytics requires a lot of data in order to be the most useful. Small companies or novice contractors may not have access to this type and amount of information. Data such as audits, inspections, contributing factors, root causes and analyses all need to collected and put into the tool.
This then begs the question: what type of tool should be used? It's no longer enough to rely on Microsoft Excel. The best tools come from machine learning. This is when machines pick up on certain tasks without having to be programmed. Computers are able to find patterns through decision trees, networks and support vectors.
However, the use of technology is still a barrier for many people. Although many workers rely on computers on a daily basis to help them perform job-related tasks, some contractors are still hesitant about trusting in a computer to perform analytical functions. They may believe that human judgment is the best predictor of workplace accidents, but it can be flawed.
When workplace accidents can be avoided, employers save money, employee morale improves and productivity increases. Everyone wins. With construction being one of the most dangerous industries, contractors are encouraged to use the tools available to them to keep employees safe.
Source: Occupational Health & Safety, "Three Reasons Why Construction Companies Fail When Trying to Predict Injuries," Griffin Schultz, Aug. 1, 2014