by: Jake Dickman | February 10th, 2026 | Claims, Risk Management, Loss Prevention/Safety, Workers' Compensation, Trending

🎧 This blog comes alive in our Ai Video Overview —click below for fresh insights.

Gray Rhino - The Dangers We Ignore.mp4

 

At the heart of every safety conversation is a simple human desire: the desire for certainty. We want to believe that if we follow the rules, train our people, and respond when something goes wrong, we can keep harm at bay.

Certainty is the feeling that we understand what is happening and why. Uncertainty is the opposite. It is the uncomfortable awareness that we do not fully know what might happen next, or how exposed we truly are. I, like many others, believe ‘Risk’ lives in the space between those two ideas. It is not simply the chance that something bad will happen. Risk is our attempt to quantify uncertainty so that it feels manageable.

Michelle Wucker, author of The Gray Rhino, puts it plainly when she writes that humans created the concept of risk to heal ourselves of uncertainty. Risk gives us language, numbers, and frameworks that allow us to move forward even when the future is unclear.

I’ve worked in this field long enough now to recognize that not all risks are created equal, and not all uncertainty deserves the same kind of attention.

Gray Rhinos and Black Swans

Wucker introduces the idea of the Gray Rhino to describe risks that are highly probable, high impact, and often visible long before they cause harm. These are the threats that charge straight at us, yet are frequently ignored because they feel familiar, uncomfortable, or inconvenient to address. Gray rhinos are not surprises. They are the things we know about but postpone dealing with.

A Black Swan, by contrast, is rare, unexpected, and difficult to predict. These events sit far outside our normal experience. When they occur, they tend to reshape systems, policies, and priorities overnight. Black swans dominate headlines because of their shock value, but they are not where most organizations experience their greatest cumulative losses.

Workplace safety failures are often framed as black swans after the fact; when many of them were gray rhinos, grazing quietly nearby for years.

The Role of Bias

Our ability to distinguish between gray rhinos and black swans is heavily influenced by bias. Familiar risks can feel less threatening precisely because we see them so often. Think about that slippery walkway at your district that’s gotten just a little slicker every year, or driving on the freeway for any length of time. Rare risks can feel more dangerous because they are dramatic or emotionally charged. Availability bias, confirmation bias, and optimism bias all shape how leaders interpret safety information and decide where to act.

This is where human judgment alone begins to struggle. Experience is valuable, but it is also selective. We remember the incidents that stand out and forget the ones that quietly repeat.

What Data Analytics Really Is

Data analytics is not a replacement for human judgment. It is a corrective lens. At its core, data analytics is the practice of systematically collecting, analyzing, and interpreting data to uncover patterns that are not obvious at the surface. In the context of workplace safety, analytics helps move conversations away from anecdotes and toward evidence. It does not eliminate uncertainty, but it reduces blind spots. Instead of asking, “What feels risky?”, analytics asks, “What is consistently causing harm, cost, and disruption over time?”

What the Data Is Showing Us

At GSRMA, much of the data analyzed comes from workers’ compensation and general liability claims. These claims represent real injuries, real people, and real organizational impact. Within workers’ compensation, slip, trip, and fall incidents consistently rank as the highest category by both claim count and total incurred cost. These are not rare events. They are predictable, repeatable, and deeply embedded in daily operations.

General liability data tells a similar story. Claims related to human resources practices are the highest by both frequency and financial impact. Of the $6.3 million incurred in general liability losses incurred over a span of years, over $3 million is tied directly to HR practices.

General liability data tells a similar story. Claims related to human resources practices are the highest by both frequency and financial impact. Of the $6.3 million incurred in general liability losses incurred over a span of years, over $3 million is tied directly to HR practices.

Redefining Workplace Safety

Workplace safety is often narrowly defined as protection from physical injury. To me, safety encompasses far more. It includes physical and environmental hazards, but also psychological hazards such as stress, harassment, and culture. It includes systems that shape behavior, decision making, and accountability.

Many of the most damaging workplace risks are not sudden catastrophes. They are slow moving conditions that create harm over time. In this sense, most workplace safety challenges are gray rhinos, not black swans.

Data, Bias, and Finding Your Public Entity’s Rhinos.

Data analytics helps organizations confront uncomfortable truths. It challenges assumptions about what is rare versus what is routine. It exposes where attention may be misaligned with actual loss experience. Without data, organizations may treat a gray rhino as if it were a black swan, reacting only after damage has occurred. With data, they can see which risks deserve proactive attention and sustained investment.

If you want help finding your rhinos – that is – someone to help with identifying patterns, pressure points, and shared risks, reach out to riskcontrol@gsrma.org. We can prepare industry-specific breakdowns that illuminate common loss drivers across similar entities or dive into your entity’s experience.

Gray rhinos rarely disappear on their own. The first step toward managing them is choosing to look them squarely in the eye.

(Disclaimer: DO NOT follow this advice for encounters with actual rhinos or any wild animal for that matter)