Trolling for rule-breaking behavior
But are you missing root causes beneath the surface?
Sometimes when managers see injuries occurring, but lack valid or accurate measurement systems capable of revealing root causes, they may begin throwing safety’s version of “chum.” They walk around trolling to catch the smallest violations.
It’s an illusion to believe this “trolling” prevents injuries. The reality is each of your employees has good moments and bad moments. All have moments of good safety performance, making an effort to keep themselves and others safe. At other times they may have moments when they take risks, intentionally or not. Most of the time employees vary around an average set of behaviors that, for the most part, keep them safe and productive.
If you fail to pay attention to variance in behavior, you tend to overlook the average set of behaviors generally responsible for keeping employees safe. What you notice on your “fishing expeditions” are outliers in performance.
You notice when a particular employee promotes safety in an exceptional way. Perhaps, tired of waiting for an engineered fix, the employee built a guard on a piece of machinery that had worn down and presented a hazard. You note that behavior and praise the employee, perhaps even recognizing that effort in front of the work team.
But you didn’t understand variations in behavior. You praised a single data point. This exceptional performance was an outlier; not what that employee always did. So the employee’s safety performance regressed back to the employee’s average set of behaviors. You saw the employee’s safety performance drop and didn’t recognize this as a natural occurrence. Perhaps the next day you see the employee take a shortcut by walking over some pipes. You think to yourself, “I just praised him and now he’s doing something risky.” You are less likely to use praise in the future because you’ve just been punished for being positive. But your interpretation is an illusion. It was not your praise that caused the drop. It happened naturally.
When you troll for violations you search far and wide for risk, ignoring the average safe practices going on all around; or worse, think that if you praise safety, you’ll promote injuries. Then you catch an employee who does something obviously risky. Perhaps he had his safety glasses around his neck — he had taken them off to clean and forgot to put them back on. So you yanked “the line” and caught him. You were upset and disappointed in him and let him know it.
In the past, this employee probably always wore his personal protective equipment (PPE). This lapse was a rarity. After this incident, this employee wore his PPE consistently like he always had. You may have perceived, “I just scolded him and his safety performance increased.” So you are more likely to scold in the future. But it’s an illusion because your scolding did not produce the improvement; it happened naturally.
Eventually your management behavior becomes like a fishing expedition — looking for opportunities to use unpleasant consequences — under the illusion that they work. Sometimes this can shape you into quite the grumpy dude. Even worse, you’re not stopping injuries.
Fishing expeditions based on faulty illusions frighten employees. This damages a safety culture. Think about it from the employees’ perspective. When they see you coming, they anticipate punishment.
Folks get nervous and distracted. They hide their behaviors. Peers teach one another how to avoid getting caught. (I’d do that if I were a fish who could talk.) The culture deteriorates. Injuries increase.
Don’t go fishing. Instead, use a good measurement system that accounts for variation, then discover its source and manage the variance. A good measurement system scans your operations objectively, looking for pockets of variation that may reflect hazards and risks. When you find this variance, use your problem-solving tools to cast your net over the potential problem and solve it… before harm results.
But you can only grasp variation and its sources if employees participate in the measurement. Outcome data such as injury rates are not sufficiently sensitive. Additionally, your walk-arounds probably reflect your personal biases and are confounded, thereby, by your presence. Instead, turn to your employees, who should be able to provide the insights into the risky behaviors and conditions that set the stage for them. They know the sources of variance; they can collect those data in a no-name/no-blame system of the type found to be successful in behavioral safety systems; and they can play a part in reducing that variance.
It’s a fisherman’s dream: the fish just jump in your boat.