Investigating safety incidents after they occur can be an effective practice to prevent future incidents. Root cause analyses of incidents identifies gaps in an organization’s safety systems so that they can be fixed.
However, there are three significant flaws in only focusing on reactive incident analysis: First, it’s costly; second, it sends a negative message to your employees; and third, as your incident rate improves, you have fewer and fewer data points to analyze.
There is a better way. Stop just reacting to safety incidents and other lagging indicator data, and start predicting and preventing safety incidents through the use of leading indicator safety data analytics. Research conducted by a team from Carnegie Mellon University (CMU) in Pittsburgh has resulted in leading indicator safety analytics programs that can predict safety incidents with accuracy rates from 80-97 percent. If analytics engines can predict incidents, safety professionals like you can prevent them.
Let’s start by reviewing the three flaws in relying solely on lagging indicators, then we’ll discuss the benefits of leading indicators.
The Three Flaws With Lagging Indicators
The first flaw in relying on lagging indicators to prevent new incidents is that it is expensive. OSHA estimates that the direct cost of a recordable incident is $7,000 and a workplace fatality is $910,000. Other industry experts put the indirect costs at three times those amounts. Can companies really afford to rely on such costly occurrences just to get access to data that can help reduce their risk in the future?
The second major flaw is that waiting for incidents to occur before preventing new ones sends a very chilling message to employees about the company’s safety culture. To put it bluntly, leaders are essentially saying, “Chris, I am going to wait until you are severely injured in our production process before I figure out how to ensure Joan doesn’t suffer the same fate. In the meantime, stay safe, and keep that assembly line moving … we have profit goals to hit!” If leaders are trying to drive both a strong safety culture as well as productivity, this is not an acceptable option.
Finally, and most relevant to those who are experiencing measurable improvements in their injury-prevention programs, companies simply run out of incident data points to analyze and learn from. If a company succeeds in driving their incidents down to just a few, or even zero, are they truly safe? How do they know their rates will stay low? The devastating incident with the Deepwater Horizon oil rig, where 11 workers lost their lives in April 2010, unfortunately helps make this point. According to reports, “The very day of the blast on the rig, executives were aboard celebrating its seven straight years free of serious accidents.” I don’t know what data that group was using to manage their risk levels, but if they were using incidents, then they had no data.
I recently spoke with a director of safety for a medium-sized construction company in Pittsburgh. Currently, they rely almost exclusively on incident analysis to prevent future incidents. He expressed his concern by saying, “I had no injuries yesterday, or last week, or even last month, but I could have five tomorrow – how would I know?”
Once a company reduces its incident rate to a low level, similar to the Deepwater Horizon, they run out of lagging data to analyze and have to turn to other data points, like leading indicators, to ensure continued low incident rates. For example, one company studied as part of the research conducted at CMU lowered its total incidents by 95.3 percent from 2009 to 2010, resulting in just 20 lagging indicator (incident) data points to analyze. At the same time in 2010, it recorded 8,215 leading indicator data points to analyze. As they became safer, the lagging data just wasn’t sufficient to provide relevant and continuous learning opportunities. This company now has transformed the basis of its injury prevention program from reactive – using lagging indicators such as incidents – to proactive – using leading indicators derived from predictive analytics fueled by a job safety analysis (JSA) inspection checklist program.
While reducing incident rates always is good, it does not mean that the work of injury prevention is over. We simply have to address it from a different perspective.
Use Leading Indicators
One of the best ways to arrive at predictive leading indicators of safety outcomes is to do regular safety inspections, otherwise referred to as “audits” or “observations,” of your worksite. This is the methodology employed by the companies that were researched. By analyzing their workplace safety inspection data, these companies were able to predict incidents with accuracy rates as high as 80-97 percent. Armed with this information, they are able to direct their scarce safety resources at those locations and work teams that are at highest risk of having safety incidents.
This research resulted in four main leading indicators that have been referred to as “The Four Safety Truths”:
Safety Truth #1: More inspections predict a safer worksite. Worksites that did more inspections generally had fewer incidents.
Safety Truth #2: More inspectors, specifically more inspectors outside the safety function, predict a safer worksite. Worksites that had everyone involved in safety management generally had fewer incidents.
Safety Truth #3: Too many “100 percent safe” inspections predicts an unsafe worksite. Worksites that encouraged their employees to find “unsafes,” or areas of improvement,generally had fewer incidents.
Safety Truth #4: Too many unsafe observations within an inspection predicts an unsafe worksite. Just as no unsafe observations are associated with the worksites with the highest incidents, so were sites that found too many unsafes. The sites with the lowest incident rates continually found a medium level of unsafe observations, and then fixed them quickly.
While many additional leading indicators can be developed by analyzing safety inspection data, these four truths confirm what many safety professionals have been preaching for years. We now have the data to back them up.
It is unconscionable to many of us that advanced analytics are employed to produce leading indicators that can predict outcomes in many industries and business functions including product recommendations, wine production and even casino loyalty programs, yet not pervasively in safety. We need to change that. Leading indicators can predict where incidents will occur, so that we can prevent them. Why would we not employ them?
Griffin Schultz, general manager, Predictive Solutions Corp., is responsible for all aspects of the Predictive Solutions business, a wholly owned subsidiary of Industrial Scientific Corp. In addition to his experience in safety, Griffin earned an MBA from the Wharton School at the University of Pennsylvania and has extensive expertise in leveraging technology and software across business functions to drive game-changing results. He can be reached at [email protected]or 412-490-1996.