Home » Could Wearables and Big Data Mitigate Workplace Violence?
One of the most frequently asked question after a workplace violence incident has occurred is how could it have been prevented from occurring? Most experts have relied heavily on the “early warning signs,” which are behaviors and events that historically have preceded incidents of violence. These behaviors and events are based on research that tracked multiple incidents over the years. Some examples of behaviors typically included in the “early warning signs” include acting in an unusually bizarre manner, overly aggressive or angry response to regular situations, paranoia, psychotic episodes (hearing voices, hallucinations or delusions), overly controlling, power obsessions, drastic change in behavior, etc., to name a few.
The general approach is to teach supervisors and employees to know what the signs are and to report them to management or human resources if they observe someone acting is this manner. One of the challenges of this approach is that the observance of the behavior is in “the eye of the beholder,” meaning it is not only subjective, but open to wide interpretations. Most experts will say it’s better to err on the side of caution and if you “think” the behavior fits the model report it. While this is certainly true, the problem is that the vast majority of employees are reluctant to report someone based on what they perceive to be a “guess” or simple conjecture. This is why after an incident occurs we typically learn about many different behaviors that fit into the “early warning signs,” but they were not noticed, taken seriously or reported. The other challenge with the “early warning” approach is that supervisors and employees are taught that it’s not just when you observe one sign, it’s when there is an accumulation of the signs over time. The obvious challenge with this approach is that it requires a vague conclusion about how many signs must be observed over what time period for it to reach the level worthy of reporting?
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