The safety profession has an unhealthy fixation on measurements based purely on negative values. OSHA recordable and lost time injuries are the first such statistics that spring to mind (both lagging and—I would suggest—negative indicators). Once they occur, they cannot be undone. The only value is to learn from the lesson. Basing safety programs on these metrics is flawed in that a lack of injuries or incidents does not necessarily equate to a safe workplace. It could be a simple matter of being lucky. I will offer an example:
Two drivers are tasked with making a delivery. One drives recklessly, regularly exceeds the speed limit, and generally operates with tremendous risk. This driver arrives well ahead of the deadline and is rewarded for increasing productivity and safety (as no incidents occurred). The second driver follows all rules and regulations set by the company and the traffic jurisdiction within the zone of travel. This driver is cautious, drives defensively, and ensures both he and those around him are kept from harm to the extent of controlling those things he can control. He arrives promptly, though well after the first driver. His supervisor, in a passing remark, tells the second driver he should be more like the first driver. Under these conditions, how do you believe the drivers’ behavior will change over time?
Realizing that simply measuring lagging data in the form of incidents and injuries isn’t enough, many companies have begun to adopt leading indicators. Leading indicators are metrics for conditions, behaviors, or activities that reveal how the safety process is operating. The two most common examples of applying leading indicators are found in near miss reports and worksite observations.
Near misses are simply incidents that did not reach their full potential. The following illustration shows the pencil-thin line between an incident and a near miss:
Two workers, both working from a ladder, overextend themselves and fall. One worker breaks several bones and suffers a significant injury that keeps him from work for months. The other worker simply stands up, dusts himself off, and walks away with no injury at all.
The only difference is the unpredictable outcome, yet near misses are applied as an evaluation tool constantly. In this example, the shared elements between the two incidents were the leading indicators before the event that could have been proactively observed and influenced.
Further up the leading chain are the observable inputs such as the behaviors, conditions, and activities expected from a mature and effective safety process. However, many organizations squander and even misuse this data when they rely too heavily on unsafe observations, typically collected through safety inspections or behavior-based systems. Measuring only failures is inherently flawed.
For example, consider the following scenario:
Your observation process only collects unsafe observations. When analyzing data over the previous week, you discover one crew has five unsafe observations in ladder use and another crew has zero unsafe observations in ladder use. Assuming both did similar work, which one was safer?
At first glance—the crew with zero unsafe observations. However, there is a HUGE assumption contained within this circumstance: that no unsafe behaviors went unobserved. The absence of unsafe observations could just as easily be attributed to a lack of documentation. OSHA has a philosophy: “If it is not documented, it didn’t happen.” Safe observations then serve as proof that something did take place. At a ratio of approximately 35:1, we find that there are traditionally many more safe observations than unsafe.
Besides the obvious advantage to recording who was observed, what was observed, and the location where these observations were made, safe observations provide you with several more advantages:
- By using representative sampling, collecting both safe and unsafe observations enables data to be presented in a ratio of safe vs. unsafe.
- By actually counting a representative number of observations (as opposed to just checking a box for the entire project) you can determine the context of your findings. This allows for focus on more severe findings. For example, if you find three unsafe observations for failure to use safety glasses and there were only three workers observed, then this is significant. If 300 other workers were wearing safety glasses, then the gravity of the findings is diminished.
- Safe observations compel the observers to engage in a conversation and share feedback that is positive. The idea is to coach for improvement, moving away from the safety “enforcer” mentality of “busting” workers for safety violations.
- Improvement can only be measured through safe observations. If you found many unsafe observations for a certain hazard and implemented an action plan to address it, yet your safety program did not record safe observations, how would you determine the success of the plan (keeping in mind that an absence of unsafe observations could merely be an indicator that nobody is looking)? An increased ratio of safe vs. unsafe would support a measure of improvement in the targeted, specific safety process.
An absence of injuries does not necessarily equate to a safe work site, as illustrated in the examples above. Documenting more than negative outcomes is the difference in determining whether you got lucky or if your safety programs are actually good. By recording both safe and unsafe observations, you can more effectively measure “what is safe.”
AUTHOR BIO
Cary comes to the SafetyStratus team as the Vice President of Operations with almost 30 years of experience in several different industries. He began his career in the United States Navy’s nuclear power program. From there he transitioned into the public sector as an Environmental, Health & Safety Manager in the utility industry. After almost thirteen years, he transitioned into the construction sector as a Safety Director at a large, international construction company. Most recently he held the position of Manager of Professional Services at a safety software company, overseeing the customer success, implementation, and process consulting aspects of the services team.
At SafetyStratus, he is focused on helping achieve the company’s vision of “Saving lives and the environment by successfully integrating knowledgeable people, sustainable processes, and unparalleled technology”.
