Reframing Serious Injury and Fatality (SIF) Prevention

Today we’re digging into a bit of a puzzle in workplace safety. You see, the US has made these incredible leaps forward in reducing recordable workplace safety incidents. The total recordable incident rate or TRIR since 1993, it’s dropped dramatically.

[00:00:31]
Yeah, massively. From around 8.5 incidents per 200,000 working hours down to less than 3.

And so that’s huge progress, right? But here’s a catch. This does not account for some of the more serious stuff. So these are life altering injuries, fatalities, SIFs, we call them: serious injury and fatality. And they haven’t followed the same steep decline, and in some cases stats are flat or even increasing, which is a bit worrying.

[00:01:07]
So it creates a real challenge for safety managers, doesn’t it? If the overall number of incidence is low, how are you able to predict, let alone prevent those really bad ones?

[00:01:13]
It really is a critical turning point for safety professionals. It isn’t just some statistical quirk. It signals a pretty fundamental shift needed in how we approach safety.

And so that’s what we want to unpack on the show today. Our evolving understanding of SIFs and explore proactive strategies, the things that are actually working that organizations and specifically safety managers are using to get closer to zero SIFS.

[00:01:37]
Okay. So let’s dive into the data then. What does this new landscape really mean, when success in preventing the small injuries makes the big injuries harder to see coming? Well, for years, the bedrock of this was the Heinrich’s Safety Triangle. It’s like a pyramid. For one major injury, you’d expect to see 29 minor ones leading up to it, and 300 near misses or unsafe acts. Before, that kind of acted as the rule book the measure that you’d use.

[00:02:05]
And so the idea was to tackle the base of the pyramid, those 300 non-injury things. And the idea, I think, is that the serious stuff at the top would just take care of itself.

[00:02:16]
That makes sense to me.

[00:02:17]
It does. But what we’re realizing now, and this is fascinating, is that not all of those non-injury incidents are the same. Only a specific subset of near misses actually contain the precursors that could lead to a SIF.

[00:02:33]
Okay. So focusing on all minor incidents might actually be distracting from the real problem.

[00:02:39]
Exactly. You could end up diluting your efforts. Say, spending resources on things that frankly, were never going to cause a fatality. And so the new SIF prevention model is all about isolating and really focusing hard on that specific subset with SIF potential.

So these are events that have different root causes and context, and hence they need a different strategy. And this ties into what safety professionals like Todd Conklin and Rob Fisher have been saying organizations aren’t going to reach zero SIFs just by trying to fix the worker.

[00:03:15]
Yeah, because people make mistakes. Humans are fallible. And the real leverage comes from designing work processes to minimize or even eliminate the opportunity for error and crucially addressing the gaps in the systems, procedures and in the organization itself.

Fisher talks about these gaps: Error traps like poor lighting, confusing instructions, error-like situations where circumstances just make a mistake more probable and organizational weaknesses like flaws and procedures or culture that can lead to these things happening.

So, boiling it down, Heinrich’s Triangle is useful. But not really the whole picture for SIFs, because these SIF potential events are just fundamentally different beasts than looking at those 300 near misses. And the big opportunity for safety managers is shifting that focus from fixing people to fixing the safety management systems and processes.

[00:04:08]
Right. And to do that effectively, we need some clear definitions. So let’s start with what we are calling serious injury. It’s generally defined as a life-threatening or life-altering, work-related injury or illness. So think like permanent impairment or something like that. For example if you didn’t immediately get help, it could likely lead to mortality or long-term disability.

So then to define SIF potential events. These are events that could have been a serious injury but was not. So maybe due to, I don’t know, luck, or a single control that happened to work, or just where someone was standing, for example, like a dropped tool that misses someone. That’s a classic SIF potential event. It had the potential but did not result in harm, that time.

[00:04:57]
So it’s basically almost a SIF. And in contrast with that I think it’s good to also define a SIF precursor because that is a little bit different. A precursor is a high risk scenario where the necessary controls are already absent or ineffective, or are being ignored.

If that situation continues a SIF isn’t just possible, it’s likely and actively dangerous. Think about working on energized power lines, inherently high risk, right? It becomes a SIF precursor if the worker isn’t using the right insulated gloves, or maybe their specific training for that task has expired. Kristen Bell over at Kraus Bell talks about this combination: A high risk task plus risk amplifiers. Things like bad weather interruptions, poor communication. That mix creates a precursor.

[00:05:50]
Yeah, and that distinction feels really important for safety managers to consider. The potential versus precursor: one is like a close call and the other is like an accident waiting to happen.

So how do safety managers actually spot these precursors, these situations that are ripe for something terrible happening?

[00:06:12]
Well, we have some more data. Don Martin points to three critical indicators that safety managers should be looking for. The first one is normalization of deviation: when unsafe practices, shortcuts, or workarounds become accepted in the culture of your workplace. They become just the way we do things around here, and maybe workers improvise because they haven’t been trained properly, or they bypass a safety step to save time and nobody stops them. These small deviations can mask really serious risks, right?

I know we’ve talked about this. Can you tell us about the second indicator?

[00:06:51]
Sure. So the second is uncalibrated risk perception or tolerance. So this is when different people within an organization may have very different ideas about how risky something is or perhaps they don’t have the right information to judge the risk accurately.

So one person thinks a task is routine and another sees a major hazard. And so if you’re doing a pre-job risk assessment, you need everyone on the same page. You need alignment on that risk matrix. What constitutes high probability? What’s high severity? If the team isn’t calibrated, then the pre-job risk assessment loses its value.

[00:07:33]
That makes sense. The third indicator is when data collection and analysis isn’t mindful or targeted. You can collect lots of data, but if it’s giving you no actionable information. What’s the point? You’re just looking at data for data’s sake.

We need to be aware of cognitive biases too, like it’s never happened before. That mindset can lead to people drastically underestimating the potential severity of an event. Safety decisions need to be based on real data. What are workers actually exposed to? Are corrective actions truly working? We can’t just go off of gut feelings.

[00:08:10]
So we have some clear warning signs. Normalization of deviation, uncalibrated risk perception, untargeted data. So moving from identifying the problem to taking action, what specific things can safety managers do?

[00:08:24]
The DCRA or the Department of Consumer and Regulatory Affairs suggests a practical three step approach for intervention here. First, educate everyone. This includes senior leaders. Make sure that they understand SIF exposure. This new way of thinking beyond the traditional safety triangle is really important because sometimes when non-fatal injuries go down, people can start to feel a bit complacent about the bigger risks. So step one is awareness and education, especially at the top.

[00:08:54]
Step two is to provide visibility to SIF exposure. So this means actively focusing your efforts on finding and importantly eliminating SIF potential. When you do this, you start generating leading indicator data. Which you need to be proactive to actually stop these events before they happen. So you are looking to find the potential SIFs in order to prevent the real ones.

[00:09:20]
Precisely. And the third step is to systematically identify the precursors. This involves doing gap analysis, looking closely at your procedures, your controls, and your employee’s behavior. Using tools like SIF decision flow charts can help pinpoint error traps, error-likely situations, and any underlying organizational weaknesses that we talked about earlier.

[00:09:43]
So this sounds like a lot of this connects back to, I don’t know, like core safety practices, but maybe we’re viewing it through a sharper SIF lens.

[00:09:54]
Yeah, I’d say you’re exactly right. Think about things like job hazard analysis or JHA or pre-task risk assessments. These aren’t new, but we can make them much more powerful for SIF prevention by making them more rigorous, frequent, and part of the process of setting up a job. Asking key questions like, is the JHS really a collaborative effort involving the crew? Is there a field level risk assessment happening the night before a job starts?

And then is risk being reassessed during the work, especially if conditions changed? Have we clearly defined the triggers so that anyone could have the ability to stop or pause work if they feel unsafe or see someone doing something unsafe.

[00:10:42]
Yes, right. And again, echoing Todd Conklin, the solutions shouldn’t just be about telling the worker to “Be more careful.” Instead, the corrective actions need to move up the hierarchy of controls. So, hierarchy of controls is this sequence for controlling hazards. Top of the list is elimination: getting rid of the hazard completely. Then substitution: so replacing it with something less hazardous. Then there’s engineering controls: this is physically isolating people from the hazard. And the next are administrative controls: procedures and training. And then lastly, personal protective equipment. And so the goal is to use the controls higher up the list.

[00:11:24]
So you want controls that engineer out the risk and don’t rely solely on someone following a rule or remembering to wear their PPE perfectly every time. PPE is essentially the last line of defense, not the first.

[00:11:38]
Yeah, that’s right. So let’s talk real examples, how are leading companies actually putting these SIF prevention ideas into practice? What are they doing?

[00:11:50]
So it usually begins with developing a roadmap, defining what a SIF and SIF potential means for their organization specifically. Then comes the data piece, mining their past incident data for hidden SIF potential, setting up systems to collect better quality data. Really importantly, getting out there and gathering observational data. You want to be having conversations with frontline workers, talking to your people.

Some companies are considering using AI and machine learning in the long term, and others are putting a huge emphasis on safety culture from the outset.

[00:12:23]
Got it. Any tips for understanding one’s own company’s specific risks?

[00:12:28]
It’s really fundamental, and it’s where everything diverges here and where you have to do a little bit of your own groundwork. So you’re going to have to look at what parts of your organization are the high risk areas, what unique risks come with your line of work, and what sort of guidance that you want to create around these these pieces of high risk activities in your company.

[00:12:51]
Got it. So other than incident reports, where are safety managers getting this data and information to build these guidelines?

[00:12:59]
Sometimes you have to look at the broader picture. You can look at your accident reports, your near misses, your workers’ comp data, your lagging indicators.

What are you seeing during walkarounds of a job site? What are workers telling you when it comes to, informal conversations about the job site safety? That’s often where the real precursors will surface.

[00:13:28]
So then how do we find those situations, for example, where controls are broken or missing?

[00:13:35]
It can be really challenging. So examples can vary. Some companies that have found issues linked to project management or others that have seen risks in newly acquired businesses. There can also be patterns related to nightshifts or even, very experienced workers who maybe become complacent. There’s a lot of things that have to do with worker fatigue as a significant factor.

So there’s many different things that can come into play, and it’s about pattern recognition. A simplified way to think about it is this equation: risk plus critical controls being absent, failing or ignored, plus a situation not being mitigated.

Once you can identify those combinations, that’s where you’ll see your SIF precursors.

[00:14:21]
Right. So are there tools and technologies that are being adopted to help with SIF prevention?

[00:14:27]
Oh, yes. A whole range. So education tailored to different audiences is key. Things like robust stop work authority programs, which gives your workforce the authority to stop work at any time if they see something unsafe or feel unsafe. That’s going to be a huge way to prevent a lot of SIFs.

There’s also things like machine risk assessment tools. Or conditions based risk assessments with checklists and heat maps that can tell you where people are, what they’re doing, and maybe what was happening around when a near miss or a SIF occurred.

[00:15:03]
Yeah, and there’s a lot happening in tech too: Predictive analytics using data from incident reporting portals, camera technology, proximity detectors, AI powered video, and robotics and drones are increasingly being used for dangerous tasks like confined space inspections.

[00:15:22]
So it sounds like there’s lots of things that we can do and implement to set up our toolbox to stop these things from happening. But I’m curious how coaching and communication fit into this.

[00:15:34]
Yeah. It’s central. So global safety training programs, hazard recognition skills, better drop briefings, incident investigation teams that actually share their lessons learned effectively. And then ensuring visibility at the top: sharing formal, apparent cause evaluations with all of your teams. You can use predictive messaging or real time alerts. And then there’s just also changing the focus of safety meetings, asking your workers, “have we had any near misses with SIF exposure potential?” So like talking about it instead of just analyzing recordables. Lleaders asking better questions.

[00:16:11]
Okay. Yeah. Making sure that they’re getting their safety messaging into more personal questions like “how are you protecting yourself from specific exposure?” Or “have you ever used our stop work authority? Tell me about how that went.”

I know that I’ve seen examples of one page documents and sharing apps among these safety teams that help them to reach frontline workers a little more easily.

[00:16:35]
Right.

[00:16:35]
So we’ve talked a lot about the things that you can do to prevent this and what data that you need to start trying to make these changes, but what about measuring successes once you’ve implemented them? How can we track progress with these SIFs?

[00:16:48]
Well, of course, measuring SIF actuals themselves, but also many organizations are tracking SIF potentials now too. And an aspect of that is raising awareness and building a culture where reporting SIF potentials is encouraged and seen as positive.

Other metrics might include how quickly SIF events get reported up the chain, or how often critical control verifications are actually done in the field.

That said, there are barriers for implementing SIF potential documentation. Things like getting everyone calibrated on reporting thresholds or dealing with, as we mentioned, different risk perceptions. There can be lack of standardization and sometimes it’s challenging to ensure communication actually reaches the front lines.

[00:17:37]
So it sounds like there’s a lot of struggles, but there can also be successes. Significant ones like streamlined reporting processes, big increases in near miss and SIF potential reporting, which often correlates with a decrease in actual SIFs down the line. Better ways to measure the effectiveness of their safety defenses, and ultimately measurable reductions in SIFs and potential SIFs.

Plus, many report seeing improvements in business outcomes and production quality, suggesting that strong SIF prevention is just good for business. Which I think ties into one of our earlier safety lab episodes where we talked about the psychological safety climate. Because I think if you’re in a job where there’s low potential for serious injuries and fatalities, you’re going to be doing better work.

[00:18:23]
Yeah. It really shows the interconnectedness of all of these strategies. So, for a safety manager wanting to implement these ideas, this might feel overwhelming. Is there a structured way to approach this?

[00:18:35]
Yes, absolutely. You can integrate these strategies using a familiar model, PDCA: Plan, Do, Check, Act. Can you walk us through PDCA for SIF prevention? What’s in the plan stage?

[00:18:50]
Plan is simply secure the leadership support that we just talked about and then you develop your roadmap. Assess your specific organizational risk profile, clearly define SIFs and related terms for your context, and create a solid communication plan for rolling it out.

[00:19:07]
Then it’s time to Do. This is the point where you implement, roll out the education, the training tailored for SIF prevention. Clearly outline the program’s expectations and goals. Identify your data sources. Where will you get these meaningful metrics? Actively work to identify specific SIF precursors in your company and consider what tools and technologies might help you.

[00:19:31]
Okay, so. We’ve planned, we’re doing. Now, Check. Check is about monitoring and analysis. Are you tracking trends in your SIF metrics? Are your controls actually effective in the real world? So you need to assess your numbers and solicit feedback. Talk to your workers, talk to your leaders. What’s working, what isn’t?

[00:19:54]
Once you’ve done that check, it’s time to act. Take action based on what you’ve learned in the check phase, implement improvements, and address the feedback. Maybe you need to reevaluate your metrics or find new data sources. Perhaps your understanding of the precursors has evolved based on new information.

It’s a continuous improvement cycle.

[00:20:13]
Yeah. The PDCA cycle provides a practical framework for safety managers to implement and refine their SIF strategy.

[00:20:22]
Okay. We’ve covered a lot today. We’ve journeyed through an understanding of the SIF paradox to exploring new models of thinking, identifying precursors, and diving into the concrete strategies and advanced concepts being used by lots of organizations.

It’s clear that a major shift is happening.

[00:20:40]
Yeah. The idea is that we’re moving beyond just counting incidents. It’s about fundamentally understanding and controlling potential. Leveraging data smartly and recognizing the critical role that leadership plays in building a proactive safety culture.

[00:20:57]
And moving from being reactive to truly proactive.

And maybe that’s what leads to a final thought here for everyone listening, thinking about your own workplace and your own team: what’s a single small change that you can make in how safety is discussed among your team or in the culture of your company?

Perhaps shifting the focus in toolbox talks slightly towards SIF potential instead of just past incidents. Or maybe you could try asking different kinds of questions during your safety observations. What is a small step that could be the beginning of uncovering hidden SIF precursors where you work?

[00:21:36]
Yeah, that’s a powerful question. So hopefully our deep dive today has armed you with a robust framework and real world examples to consider SIFs and SIF potential.