- [Mary] Hi there. Welcome to "Safety Labs by Slice." Since its beginnings, the safety industry has worked hard to prevent injuries, mainly through risk assessment and accident investigations. While we've learned a lot by understanding what went wrong, today's guest believes it's time to start learning from everyday work when things usually go right. He co-wrote the white paper, "Learning from Everyday Work," and today we'll discuss the ideas behind this approach to organizational learning.
Brent Sutton works in the commercial, government, and education sectors to address health and safety risks and improve organizational learning. He has over 20 years experience in various OHS roles. Brent is currently the project architect implementing a Learning Teams framework in New Zealand's maritime industry under the Health and Safety at Work Act.
He's well regarded as a safety coach, helping organizations see workers as a solution. Brent guides teams to integrate worker engagement and participation into existing health and safety systems in order to improve operations. He's the co-author of the Practice of Learning Teams and co-hosts a weekly podcast of the same name. Brent joins us from Auckland.
- [Brent] Thank you, Mary. It's great to be with you today.
- So let's talk about the underpinnings of this approach. Why is it important to shift from learning through accidents to learning through normal work?
- I think, once again, it's all about a lens. If we keep focusing on why things keep going wrong, we're actually placing workers in what I call a negative deficit. And, you know, when we think about risk management, risk management says that we should be looking for opportunities. So I think that what's sitting before us at the moment is that great opportunity to look at why things go right.
And the reality is they go far more right more often than they go wrong. And if we keep fixating on why things go wrong, we also see very low frequency of similarity as well. Because in the world that I live in, we're not focusing on people's behaviors, we're not looking at the outcome of these behaviors, we're looking at what conditions existed at that time. What was that worker thinking about how they were having to make do in the system they're trying to work in?
And if we focus on those things at everyday work, it allows us to build a stronger system.
- So there was one quote in the book that caught my eye...sorry, in the white paper that caught my eye, said death hides in normal work. So I wanted to ask, how would you define normal work in terms of failures and successes?
- That's really interesting. So, obviously, that was from Dr. Conklin. And the reality is that when things go wrong, it becomes obvious to us in hindsight why they went wrong. And in the work that I've done, particularly around industrial fatalities, if I look at what the organization believed in terms of the risk that workers were facing, that consequence of death or a life-changing event was always there.
So when the event happened, in actual fact, their risk assessment was correct. So why do organizations get surprised? Well, the issue that's before us is that they weren't looking for those opportunities to try and, you know, do better. And in a lot of what I see at the moment, particularly around what I call critical risks or dynamic risks, organizations are going out to try and get workers to keep conforming to what the system is because the system for some reason is deemed safe.
I can tell you, I don't believe systems are safe when we're dealing with those types of, you know, critical or dynamic risks.
- Yeah. So coming back to something you mentioned just a minute ago, can you explain what you mean by a deficit-based understanding of normal work as opposed to an appreciation-based view?
- Absolutely. It's all that negativity that we think about. The reality is that when we are asking people to do the work on the frontline, we are transferring that risk to them. And when things don't go wrong, we might see those things as being innovation or looking at improving work.
But when those things do go wrong, we basically say that they deviated, it was a violation, was an unsafe act, and we need to punish. And every day workers are having to adapt and to change to be effective and efficient in the work they're trying to do. We don't look at that adaptation, we keep focusing on why things go wrong. And I understand that because it's easier to react than to respond.
And that whole focus of looking at what normal workers requires the organization to be more in a response type phase rather than a react phase.
- So do you think that's why organizations have traditionally shied away from learning through normal work?
- They have from the point of view that they're trying to use an intervention model. And what we put forward was that you can't be everywhere. And in the white paper, we sort of use the iceberg analogy, and organizations can only see the things that sit above the waterline. It's difficult for them to see the things that sit below that, but it's workers, it's that accumulation of workers that can see that.
So, what we put forward was this concept that actually get the workers to lead and get the organization to support them. And we've been doing that for probably about two years now. And even today I'm still staggered about what an organization can learn by treating the frontline as the experts and actually listening - And actually listening.
That's a good point.
- Listening. And that's a real challenge because I don't think organizations know what listening means. They've honed their skills on telling.
- Yeah. And I think organizations are used to coming up...or when approached with new ideas, they're like, that's a great idea. And they don't intend to, but I think very often they just sort of tick the box in terms of, oh, we did the thing, like we asked. But the listening is really what's key.
- Okay. It is because listening leads to better understanding, better understanding leads to reflection, and then reflection leads to improvement. Now, that's not a longer process than the other way, but reflection is the key to change. And that reflective component has been recognized for probably 60, 70, 80 years with the work of people like Deming and the work of Toyota.
So, I understand, you know, you have to create space to learn, but people don't realize how little space you actually need. And, of course, at the moment, we tend to get lost in the noise of everyday work. So, it's really hard. But what we've found is that by integrating that reflective space into normal work is huge gains that can be had by taking that approach.
- Yeah, and I'm going to come back to that when we talk about how we sort of implement this kind of approach. One thing I wanted to ask about though, one of the quotes in the white paper is we ought to learn from everyday work by going out and validating the presence of capacity. So, safety managers have observed work in the field for years, but I'm curious about the idea of validating the presence of capacity.
So talk about that a little bit, please.
- Sure. First of all, when managers are going out into normal work and they're validating something, in most cases, they're actually looking at behaviors. They're not looking at the actual work being performed itself. They're looking at the person doing that. So when we think about capacity, we are thinking about, how is the system supporting a worker to be successful in that work?
And how is a worker having to adapt to be able to do that work in the environment and the conditions that they're having to work in? And it is completely normal for workers to have to make do, because the system can't be perfect. But you can't go out and observe that, you actually have to engage and you actually have to have a conversation.
Whereas an observation, you can actually sit back. And, of course, when we observe, we're actually filtering it through our lens. We're not actually engaging with a worker to try and make sense of how they see the work. We're looking at through our lens. And in many cases, we are comparing it against a system that we call, you know, work as imagined or work as intended that in many cases doesn't resemble reality.
- Let's talk about the reality of normal work. Variability, complexity, and coupling and the role that each of those plays in everyday work. So let's start with variability. The paper discusses this in terms of micro changes, and I believe, correct me if I'm wrong, that that's similar to the concept of drift, correct?
- Yes. In terms of drift in relation to Rob Fisher and Todd Conklin in that really the system is degrading and work is changing and that gap between work as imagined and work as done, or black line/blue line is that adaption or that drift.
But drift sometimes infers, kind of, does drift have a negative connotation to it? That's why we just prefer to say adaption because you're drifting away from something.
- So, that's the making do that you're talking about. And the idea of, yeah, drift, you have to drift away from something, so that's kind of centering the system as ideal [crosstalk 00:09:32] perfect.
- One true thing. Yeah.
- Yeah. What about complexity? How does that show itself?
- Well, that's the interesting thing because, you know, by its nature, the system is complex. And you know it's complex because you can't break that complexity down into steps. And I think that's where Todd talks about difference between something that is complicated versus something that is complex. And with complexity, it's always going to be complex. So, probably the only thing we can do is to try and create that visibility.
And what I observe today, if I was to repeat that observation the next day, I would actually see different conditions. I would see different adaptions or different variations that would exist. And that is because the system is complex.
- So you can't create a rule or for every situation, every condition, every... Yeah. You have to understand and accept the complexity.
- Yes. So, whilst in many cases, the thing we may be engaging with may have some consistency, there are still change happening. The difference here is that change visible to us. And I would say in a lot of cases, we're actually normalizing work through that routineness or that repetitive nature. And that change in work happens in small steps, but, of course, when something goes wrong, what we're now seeing is we're seeing all those changes rolled up into a big change.
And we call that the gap.
- Okay. So, what about coupling now? That's how these different steps, if you want to call them that, affect each other, right? They're interdependent.
- Yes, or co-dependence.
- Yeah. Right.
- Yeah. So really it's two things. So, it's basically saying that, you know...and a good example, we talk about one way to make some of those couplings visible is we use a quadrant that we call step, which basically says we're looking the workers to think about, you know, what is the work I'm performing around the site today? What are the types of tasks and activities that I'm doing? What's the type and, you know, the environment and the equipment I'm using?
And, you know, what sort of do I need from a people and protection perspective? And by looking at those things separately and then standing back, you can start to see where there may be a dependency on one part to another part, or whether they may be separate. And when we use systems in our normal work, those systems are linear.
So those systems can't allow you to see those dependencies or co-dependencies that might exist. And so workers...so we turn up for a job and we expect that the boom lift will turn up at 10:00 because we've got three other things that a sequenced in that job, the boom lift doesn't. What happens?
Do we adapt and make do, or do we stop work, put tools down, and rewrite the entire plan? That's the issue. And the reality is we don't do that.
- No, I think that would be extremely rare. So, I'll ask for more examples about the step framework in a bit. But right now, an important concept in this approach to understand is the difference between weak signals and strong signals. So can you explain what signals are to start with and what makes them weak or strong?
- Sure. And look, signals comes from along of the work with people like Prof. Eric Honnagel. So, basically, what we're saying there is that those weak signals, we might call those adaptions, those changes. We use the word, rubs. So it's that friction between how the system believe work is to be done and how workers are having to do work.
And those signals are always changing, but there's so much of it that it gets lost. Yet when something goes wrong, those weak signals become obvious and they become strong signals. So you might engage with a group of people, something goes wrong, and you ask them about it, and they'll give you a huge amount of stories about every other time that it's gone wrong. So those weak signals are always present.
The difference here is in a lot of the work that we do, we have adapted to that work signal and the work has still been successful, but that one time when something shifted or drifted or whatever language we want to use, all of a sudden that becomes a strong signal. And when we go and we ask questions, we hear all the stories about that signal, yet doing that work every day, you can't sit there and isolate that weak signal because it's just lost in normal work.
- So part of the job of your approach is to find those weak signals?
- Yes. Because it's interesting, they tend to cluster, so they tend to form patterns over time. So it's no different, it's like anything in nature. Those weak signals, I call them like a game of Whack-A-Mole. Those weak signals, they rise up and they drop down, and they rise up and they drop down. But over that time, they start to form patterns.
And the only way to understand weak signals is actually through engagement, through conversation, not through reporting.
- Okay. I was going to say...
- Because, yeah, it's not a thing.
- Sorry. I was going to ask about data. I know that you collect a lot of data. Okay. So you're not seeing the patterns in data, you're finding it through conversations.
- So the conversations allow us to see conditions, the language that the workers use about those conditions tell us about the weak signals. And the language that workers use also tells us about how they're coping in the system. So if they're explaining to us that when they do this job, and a classic one just last week, workers become frustrated because it takes them several hours to do the preparation of all the safety requirements before they start the work, all based off a job card.
They arrive on the site and they find that the job card and actual job aren't the same anymore. And the organization requires them to then complete another risk assessment and have it approved by two people who aren't present on the site.
- So they spend all day trying to get approval and safety and they get actually zero work done.
- Zero work done, or they adapt to that work...
- Which is fine...
- ...and the system is creating a rub, the system is creating a rub - And the adaptation is fine until something goes wrong.
- Yes. And then the organization here's these stories, and then ask questions, why didn't they report it? Why didn't people report it? And there's a good reason why they didn't report it, because every time they have raised it before, nothing ever happened. So they stopped reporting it because as soon as workers realize they're either not involved in the solution, or if they do report it, they get blamed and punished, which is quite normal because we typically respond with more procedures.
You know, I see it all the time, let's double down on procedures, let's not get rid of them. It just encourages workers not to bother, because they realize...because workers take pride in their work. I seldom see it where workers don't care, but they're having to make that decision between, you know, being efficient and being effective in the system they're having to live in.
- What is the 4D approach to weak signals?
- So the four D's is simply a way of getting conversations to show context without needing a high level of facilitation expertise. So the reason the four D's came about was that we're doing a lot of learning teams with organizations and organizations were saying, our people need a lot of skill to do a learning team. And the reality was that when we ran a learning team on learning teams, what we found...I know it's crazy idea, isn't it?
Learning teams and learning teams. What we found is that people had been using systems and processes where they were accessing question banks. And we were asking them like to no longer just use a set of question banks, because question banks by their nature, narrow you into one area. We want them to be a bit more organic. They struggled. So what we explored was, was there a way of using some form of approach that was not a question bank, but something that started conversations?
And with the four D's, with that work with Jeffrey Lyth, what we discovered was by asking workers when they do that job, can they share with us when things don't make sense, being dumb? Can they share things with us when things don't feel right, which is dangerous? Can they share things that shift from what they normally do, which is different, or things that are harder than they should be, which is difficult?
All these stories flowed out.
- Just enough structure to the question.
- Just enough. And we call it a little bit of a thinking frame because if I was to get a group of workers, say team workers together, what you might see as being difficult, another worker might see that as being dumb, or another worker might see that as being dangerous. That's because all of us have a different perception or a different appetite for risk. So, we see risk differently and we perceive risk differently, therefore we have a different appetite for that.
So, the four D's became a powerful tool because it actually reached lots of different types of people. And we've actually done it without changing the four D's. We've done it in multiple languages as well because you don't need to change the four D's as the explanation of what the D means is what creates the conversation.
- Yeah. And then I would think in the end, if, you know, you're talking to 10 workers and like you said, one thing, someone finds it different, someone else finds it dumb or whatever, it doesn't really matter in the end how it's classified because you're not looking to classify these things, you're simply looking to surface them.
- Correct. It's not a box. It's not a box to fill. And once again, the first thing we get asked was, oh, I didn't find any in the difficult category, which was really interesting because, once again, that's not about the person that they have been institutionalized to actually...we call it the fear of incompleteness.
They believe that if they've got this box and they're going out there, they've got to fill those boxes, where in actual fact, that's not the objective. The objective is correct conversations. And the four D conversations show you the conditions, they show you the rubs. So, the rub is the friction between work as imagined and work as done, or...and hot, what we call black line/blue line.
And because it's a narrative, we can take that narrative. And in that narrative, we can see weak signals. So it sounds a little bit unusual because we're capturing the voice of the worker. We're not filtering it down through someone else's lens, which is what happens at an observation.
- As far as implementation, if an organization, or in this case, a listener wants to start to begin to learn or to shift things a little bit towards learning about everyday work, what would you suggest?
- Sure. And we've given a label, we call it a Trojan mouse. So, which is to go in and choose any type of worker activity with the workers and just ask the team, "Hey, guys, can you explain to me, you know, what normal looks like when you do this job?"
So all we're doing is just ask them what normal looks like. Can you explain to me the types of stickies or risks that you might encounter when doing that work? So, sticky means stuff that kills you. So if it's high-risk work... what the sticky is. Can you share with me the stuff that you rely on to do that work well? And can you share with me a story over a period of time, like the last week, the last month, when things didn't make sense, when things didn't feel right, when things were harder, you know, when things were different from what you expected?
And you'll hear those stories. Those stories will come out. They just come out.
- So step one is really to bring them out or to encourage them and to listen. And in your experience, patterns start to show themselves over time.
- Absolutely. Absolutely. And for listeners, if people go to...if they were to Google a large transport logistics company called Linfox. On the Linfox website under health and safety, they have their four D's video where they show stories of workers through the workers' lens of dumb, dangerous, difficult, different, and how these simple conversations have led not so much around safety improvement because it's really hard to measure what a safety improvement is, but what came out of these four D conversations is a whole lot of operational improvements.
So, the example they had and one of them was they were having some issues around condition of containers in one of their logistics warehouses. So the group said, this is dumb, why do we need to travel the furtherest distance with forklifts to get the stuff we need to access the most? Now, for our listeners, they might think, well that is really dumb, but that is the way it's been done for years.
Rather than asking, why has it been done that way for years, which is how we start, let's just accept that the system has allowed that to exist. So workers have told us that's dumb, workers have also shared with us what they think is the solution. You can effect change. And in that type situation, the safety outcome has been that they've reduced the frequency of forklift movements between forklifts and workers by about 60%.
Now, has that reduced risk? Well, the answer is yes, because we've reduced exposure. But the question here is you only need one forklift and one worker to come together for death to happen. So is that 60% reduction really quantifiable?
And that's where death hides in normal work because I would say to you, no, death is still going to be present. As much as we don't want to talk about, you've got a big object, it's got mass, it's got movement, you've got people. But what they could measure was things like the reduction in carbon emissions. What they could measure was the number of reduced hours that the forklifts were operating.
What they could measure was the volume of freight that is now being moved in the same period of time with the same number of people. So all of a sudden, a safety engagement has become focusing now on operational improvement and operational excellence. How do you think the organization responded to that?
- Yeah. I'm sure they were quite happy.
- That's great news.
- Yeah, of course. Yeah. I've noticed there's sort of this blending or blurring of the lines between safety and operations as people I think are realizing that they're so intertwined. There's been more of a focus, at least with the guests I've been speaking to on operations, which has traditionally been seen as very separate.
- Correct. So back in 2019 when we wrote the book, "The Practice of Learning Teams," the title is "Learning Teams for Safety, Quality, and Operational Excellence." So, you know, four years ago, we always said the value in learning is actually more than just safety.
So many of the organizations that we have supported in coaching and mentoring, they used learning teams for information technology, for financial. So they now use a learning team for any type of situation or problem that arises, they use a learning teams approach to do that.
- And I would think too, that by maybe not promising or guaranteeing, but by knowing that learning teams are going to improve operations, it may just be a way to get more budget to get ears to listen in leadership about the resources needed to do that kind of work as opposed to safety.
- Yes. I mean, once again, I think there's two parts to a learning team. Learning teams aren't always about driving improvement. Learning teams can also simply be about better understanding. So once again, we have this issue about fixing organizations once they know something, they believe they have a duty to go and fix it.
There are many risks out there that aren't fixable by their nature. So if I was to touch on psychosocial risks as a really good example, and as something that everyone talks about at the moment, but it's a risk that isn't new. It's just a risk that's come more into focus as a result of, you know, the post-pandemic component of it. But there are many psychosocial risks by their nature that aren't fixable.
So in the absence of fixing, we are left with the alternative, which is simply better understanding. And what we've been able to demonstrate consistently is better understanding actually helps to build resilience with the people that face the work, whereas fixing is trying to actually make the system better.
So there is no doubt. So the example is fatigue. We all know that there is a work design component to fatigue, and we should continue to do our best to improve that work design component. And then there is a component for the frontline around recovery. And I think it's disingenuous for us to expect that if we say that people get a 48-hour break, that they're going to spend that 48 hours resting, that is just, you know, disingenuous.
No, it's not realistic. So the learning opportunity is better understanding those two components of the coin. How can we help to create change in the work design, and how can we build better knowledge and understanding around the purpose of rest breaks rather than the moment, treating it effectively as a rule? And the reason I call it a rule is because if that person turns up tired and tells the organization they're tired, their response is, well, what were you doing on your two-day rest break?
- Yeah, your job was to rest.
- Yeah. So we live in this world of crazy. But the reality was that if we were doing four D engagements with the frontline, getting those frontline insights, it would've become quite apparent about the rubs that the work system creates at the moment around fatigue. And those rubs would've been told as stories and those stories, you know, would've given the context that we needed to see the conditions, Whereas what the organization is focusing on are symptoms and behaviors.
The worker didn't follow the rub, rest break. I wish that rule would work.
- I was just thinking about the system as it's this sort of amorphous, when you say you didn't follow the system, it's a way to sort of blame, but it also abdicates responsibility from those who design the work in a sense. Doesn't it?
- It's transferring the risk to the frontline and saying, you need to make up the stuff we can't do. So if the purpose of risk management...so risk management is supposed to deal with the uncertainty. That's its job. And we try to reduce uncertainty by putting in things like defenses, controls, barriers, and mitigations. And then organization ends up with the end point which they call residual risk.
Effectively, they then transfer that balance of that risk to the frontline and somehow workers magically fix the stuff between residual risk and normal work that the organization can't do. And probably that is the biggest rub for me as a person because when organizations are going out, they're simply going out to validate the things they've put in place.
They're not showing any interest in that gray space that exists between residual risk and normal work. And to me, that's the bit that we are most interested in because whatever is happening in that space where people are having to make do, that is the opportunity that we have to learn from and to improve the system.
And at the same time, by engaging with workers, we're actually creating a learning opportunity at the frontline. And by workers gaining more knowledge, by workers gaining more understanding, so not being trained, not talking about rules by them gaining, that actually helped them build resilience. Or if we use the word capacity, it's helping that human capacity to actually deal with change where at the moment, change is seen as a negative or an evil where in actual fact, all change should be seen as an opportunity.
So, in safety, it's a negative lens because it's a threat. But in our world, we treat it... And I've just spent the last few days with Josh Bryant, who was a guest on one of your previous episodes. So Josh says hello by the way. And he used the watermelon analogy. He says that, you know, organizations are always telling you, you know, the green stuff, you know how good things look.
But if you slice into that watermelon, you see all the red stuff. And the four D's is about actually digging in and seeing the red stuff. Or as the Japanese would say, fear the green, embrace the red because what is happening when nothing is happening?
And I go to tell you, a lot's happening.
- On that note and teaching, not teaching, increasing the capacity of workers to notice what's happening, you talk about the tactic of the pre-start and the post-work learning. Can you explain why that's effective in those terms that we just talked about, like capacity and critical thinking, that sort of thing?
- Absolutely. Because all of us as humans, we plan. We plan every day. And planning is an important part because we do like a bit of structure. So for many of us, you know, the example I always use, many of us, you know, we have different rituals when we get out of bed. Some people, you know, fall out of bed, some people roll out, some people get out. But everyone has a ritual that they follow, and that ritual sets them up for the day.
But how often is that day...does that day ever resemble your plan? And if you sat down and spent a few minutes reflecting on how your day went, this is how you planned, that reflective component or what we call the make do where we have to change or adapt to it, that's the learning opportunity.
So when I look at organizations who heavily rely on pre-start components for their safety, whether it's tool boxes or completing job task analysis, all those types of things, all that's doing is basically looking as work imagined versus work as planned. But throughout that day, work is going to emerge, work is going to change, and workers are having to make do.
So what we've been experimenting with, and these things are experiments and we'll be perfectly honest because that's the whole objective, is to find out what can and can't work. We can shorten the upfront component of the pre-start because we're getting workers to focus on what work looks like for them. And we can spend a very short period of time towards the end of the day where workers actually reflect.
And we've created some visuals for that to happen. And then all workers are doing, because they're seeing it as a visual and they're thinking about that difference between how the work started versus how the work end, all the stories of how they're made to do just come out. So, you know, this machine was late, okay, it held up that job.
Because we're waiting for that job, we then started this other piece of work at the same time. We didn't realize that that piece of work was reliant on this other thing happening at the same time. That's all the stories of what happens. And it's that making do that then feeds into the next day that matters.
Now, reality is it's a form of continuous improvement, but what we're doing is we're providing a thinking frame for that frontline to see variability, to make visible the complexity of the system for them to see where they've got those interdependencies or those co-dependencies.
And those things can't exist in a checklist or in a form or a type of linear system because that system can't support that. But for me, the most important thing that we're doing, Mary, is that we are getting workers to use that curiosity that they have.
And by them using curiosity, we start to build that critical appraisal. Because so much of our systems are based on assessment and evaluative, it's like workers are having to give permission to the system that the work is safe to start. How crazy does that sound? We're giving permission to a piece of paper that I can do this high-risk work. I don't understand that.
- It sounds to me like something that lawyers would make up so that if something does go wrong, it's like, "Well, look, they signed this piece of paper. They took on the risk." I mean, it's the same as waivers in...it doesn't mean that an inherently dangerous thing should have a poor design.
- Absolutely. So, what we've been focused on...all our work focuses on that learning has to happen at three levels. That we need to have learning happening at the worker level, we need to have learning happening at the workgroup level, and we need to have learning happening at the organizational level. But a lot of what we do at the moment is actually focusing on the organization and we are saying that's wrong.
- So I have a question about the post-work reflection. Have you found that it's more successful...have you tried it with people doing it individually, or doing it as a group conversation, or does it make a difference? How has these things...
- Yes, it does make a difference. And we've done both. We've done both. So, obviously, it is most powerful when it's done as a group. And the reason for that is that because all of us see risk differently, because all of us have a different appetite or a different perspective of risk, when workers are hearing other workers talk about how they're making do, that creates a different concept in their head and they're having to resonate with that alternative information.
And that sparks something new for them. And that's just good adult education. It's really good adult education.
- I would think if you were to ask me to reflect on something, I would have something to say. But if someone else was doing it with me, they would almost certainly remind me of something that I had forgotten or a connection I hadn't made or that kind of thing.
- Absolutely. And groups always outperform individuals when it comes to knowledge. So, there's great science and in actual fact, the group needs to be more than three. And about 8 to 12 is optimal, but it's in that space of 3 to 8 is really what we call that sweet spot in that.
It can be more, but the reality is the bigger the group, the more personalities come in. So, we're not saying that...once again, this is not a rule. What we have found is the sweet spot is 8 to 12. We have people working alone. That's a different situation because you're only convincing yourself and you've already convinced yourself. And if you've got multiple voices, there's another issue going on for you.
So what we're doing there is that we're wanting that individual to do that reflection simply around, you know, work as imagined versus work as done. And we take those stories and then we pull together a work team on a regular basis of people that do that work and they look at those stories.
And what they do is we then provide some learning comms back out to everyone else about what were the themes from those stories and what did we learn. Not as good as a group, but as close as you can get better than doing zero, which is what we currently do. And surprisingly, they find stuff that they never thought was present.
And the funny thing that we've been discovering is that reporting dramatically increases as a result. But what we've also seen is that with events that have happened, the severity of harm has dramatically reduced.
- And that's not specifically people who work alone. We're talking all reflection...
- Just in general. Because what's happened is we're not trying to prevent accidents from happening, we're trying to build that greater awareness about how people are present in that system because it's difficult or near impossible to see an error coming, but to be able to learn from that. So in actual fact, errors happen every day.
I mean, you know, we learn through failure. So the reality is that we're trying to build that capacity or build that resilience, whatever name we want to use it. We want to build that both at a worker, at a workgroup, and at an organizational level because that's what we really rely on when things start to move outside normal.
And in the latest work that we're doing at the moment, we are basically visually showing organizations where that drift is happening and we're showing them how weak those controls are because those controls are allowing workers to move outside that safety envelope, and those controls are allowing the presence of the energy or the hazard to also slip into those safety margins as well.
And organizations love visuals. They love a good visual. Numbers have no meaning.
- I was going to ask about the operational learning dashboard. That's what you're talking about, the visuals?
- Yeah. Well, there's two components. The thinking around the operational dashboard was that I don't think we can ask people not to measure stuff. It's just inherent. It's just inherent. So let's give them something they can measure that can create a learning opportunity. So a lot of the data that we present doesn't actually create curiosity.
It doesn't actually create learning. It's simply stating a fact. I did 35-worker engagements, we had 3 harms for this period. I really don't know what that means. But we had three harms this month, but we only had five harms last month. So, does that mean we've done better at not harming people, or has work changed?
I mean, I don't know what it means.
- Yeah. There's too many possible reasons. Yeah.
- Absolutely. It's just a number. And I love it when we add some colors in as well because that just, you know, really emphasizes something. So what we're trying to do is we're trying to say how can we present data in a way that creates curiosity at the leadership level? And then how do we get leaders by being curious to actually drill down into that data to actually see the narrative and the stories?
Because that helps them make sense of the complexity of the system, whereas the number can't. So for me, it might be that we had 35, 40 engagements for the period. Give them a number. But of those 35 engagements, these were the themes that came from those engagements. Here are the learnings that came from those themes.
And here are the system improvements that resulted from those learnings. I don't know, is that evaluative?
- I don't know.
- I don't know if it's evaluative.
- Because we're telling a story. Because we're telling a story. We're basically saying, you know, every time we engage, we should learn. There should be a learning. But the bits that's missing sometime is had that learning come...where was the context of that learning. So hence more, we're trying to explore it through the other lenses and sort of scaffold those leaders to start to move away from looking at symptoms and behaviors and outcomes, which is what our data currently does to shift them back to conditions and work design.
- I tend to think of the difference between data and insight in that the insight is the stories and the context and that kind of thing, whereas data is just cheer information without interpretation.
- Yeah. So, you know, we did high-risk power work. We did 100 jobs. No one got harmed. I don't know, that doesn't tell me about what was the...you know, does that mean there was no variability across those 100 jobs? I doubt it.
Okay. Were there 0 making do across those 100 jobs? I doubt it. If I think old school, was there zero deviation against their rules? I doubt it. So that data that's statistic doesn't give me any assurance or verification around that high-risk work. And that's where Todd talks about death hides in normal work because that data is not telling us anything around that.
There is no context to it. Yeah. We've just tried to explore how to start that journey of looking at data differently. We don't have the answers. We are just saying if you start doing a context-driven element to it, there is an opportunity to learn.
- Yeah. I think that's fascinating and applicable across many industries, both...
- Not just about safety.
- ...having data that engenders curiosity and providing insight and context rather than just raw numbers.
- Yeah. And this notion isn't new. I mean, if we think about Deming's work going to the gemba, was exactly that. Gemba in Japanese means go to the place of actual work. How novel is that? Get a bunch of leaders to go down to the place of actual work.
Now, the challenge here is, what are leaders asking workers? So that's the other thing that we use the four D's for as we talk to leaders and we say that use the four D's to actually create a conversation. And we call that concept is to listen, learn, then lead, which is simply go down to the workforce and say, guys, you know, in this work that they do, you know, what is a thing that worries you the most?
Or in actual fact, if I use the one we're talking yesterday, you go to the workforce and ask the guys, what's the dumbest thing we do around here in terms of the system, not about the people? But, you know, in the work that you're doing, what is the dumbest thing the organizations ask you to do around here?
And you'll find that there'll be a bit of laughter.
- And I'm sure that the answer is it right away.
- Yeah. But there'll be some laughter, we call it a bit of chronic unease, and then the stories flow out. Okay. And that's the power of the four D's. The four D's, anyone can share a story, anyone can gain a story by doing that. Now, the leader, their job is not to respond because they feel that the moment they hear it, they could try and fix it.
And what we're asking them to do is go out, hear those stories, get back together as a group, and now reflect on those stories because that reflection will lead to learning, and then that learning will then turn into leading. And I don't know if you've ever seen...I see some organizations, you know, leaders have to engage so many times a month. And normally, it has to be scheduled to set time because, you know, leaders are busy and that gets communicated.
And shockingly, people always find ways of not being present on the factory floor or in the field at those times. What's the indicator telling us?
- I have a couple of more questions, one of them was actually what's the effect of the learning approach on psychological safety, which I think that's related to, you know, if people are disappearing when they know that the leaders are coming around, what might that indicate?
- Well, I think for me basically they're seeing that interface as a form of compliance, rather as a genuine form of engagement and representation. And I've said over time, I mean, I was just recently in a...you know, I've seen two sides of these things happening.
And I was in a facility recently where workers are provided with an emergency pull cord to pull when things aren't right. And I've seen one example where workers use the pull cord because something's not right, doesn't mean that it's dangerous, it's not right. And the supervisors, the managers will go to them and will apologize why it's not going right and having a conversation with them about it versus other supervisors going down, and saying, "Why'd you pull the cord?"
So if you think about psychological safety, what has that established? So there is this thing that is supposed to be designed for you to support you to be safe, but if you pull it, we're going to blame and punish you because you felt unsafe.
- Okay. One last question for this main part, and then I do have some questions that I ask everyone. I wanted to ask about routine work soak time. So what does routine work soak time mean? I think that's part of the reflection piece, isn't it?
- Yes. So there is many lots of types of work or jobs that are done where change is incredibly slow. So, if I think about manufacturing, where we are producing the same products day in and day out, variability is there, but it's hard to see. So, routine soak time was exactly that.
It was to get workers to reflect back over a period of time to show how variability has come in, even though it's really hard to actually see, versus that when we do high-risk work or work in a dynamic environment, it's changing every day. But in certain sectors that changes a very slow burn.
But the reality is that if there is an impact on quality in that manufacturing process, or if there is an impact on people, that engagement is actually showing that accumulation of those small changes over time. And what then typically happens is that we then put in corrective actions as a big change, and then we are puzzled as to why those big changes didn't stick.
So, what we are trying to do is using that soak time component around routine work is to try and introduce those small changes back in. And if workers lead the small change, I would argue strongly that it's likely to be sustainable.
If the organization implements big change, it's unlikely to be sustainable. And that's a whole notion that our work is trying to get workers and the organization to co-construct the solution, not workers be an output of a corrective action, which is what we currently do in safety. And we do a lot of them.
We love corrective actions. I've got no idea what they do, but we love a good corrective action. And the analogy that I use is that if you had an event and you spent days investigating it, is the amount of time you investigate proportionate to the number of corrective actions? So if you spent three weeks investigating an event and went back to the organization and said there was no corrective action required, how would that go down?
So, I think there's a link between the need of time we spend to the number of corrective actions. Whereas in our work, there doesn't need to be that corrective action because, in many cases, learning is simply an improvement that happens within the work team, not for the system.
But other times, that learning might be a tweak of the system in that way. So it's just a different way of looking at it. But what I've seen is that workers, once they engage, because they love to engage, they've never been given the opportunity, lots of other things happen and the organization doesn't understand it.
I was with a group on the weekend and we've been doing a project and it was around psychosocial risk and there'd been some bullying, harassment, and this one group of workers had been labeled as being the complainers. And we ran a couple of little learning teams sessions with them and we identified, you know, the work design conditions, all those good things. And one of the guys said to me on the weekend, he said, you know, if I went down that area on the RTs, the team would say, look out, the safety guys are coming.
He said, now those guys are coming to us and they're telling us about stuff that doesn't feel right to them. He said, how did that happen in three weeks? And my answer was, we just listened. Because his thing was, what? Did you ask better questions? Well, you know, we used the four D's. I don't know if the four D's are simply better questions because they're not questions, but the fact is workers just shared and through that sharing process.
And the other powerful thing and the thing that I learned from an amazing guy called Rob Fisher, is that I got the workers and the organization that when they looked at these things that we asked this question, are you doing safety to people, are you doing safety for people, or are you doing safety with people?
And the organization thought with, and the worker said to.
- I hope no one bought that - Yeah. And then I felt like a marriage counselor because now I'm dealing with communication as given versus communication as received. And when we got both sides together and we shared those stories, so not facts, the stories, and the workers put those stories into those blocks, the management team, the light bulb came on and they said, "Wow, we didn't know."
Now, they've become curious. Isn't that great? So workers became curious, now the leaders have become curious.
- I could go on for a long time but, unfortunately, I'm going to move into the questions that I ask most guests. And so I think you mentioned you've heard the podcast before, so you may know what's coming. But what do you think is the most important soft skill for tomorrow's safety professionals to master?
- Facilitation. What does good engagement look like? You know, within that, there's the ability to communicate, ability to collaborate. And I think the challenge that we have is that as safety practitioners, and I still follow this trap myself every day, we have got there by relying on strong technical expertise or subject matter expertise.
And it's two different mental models being an expert and being a facilitator. So even when I, you know, hear a story, I can't help feel, but actually try to create context in that conversation. But my job isn't to do that. My job is to be part of that storytelling process, facilitate that process with the workers, and then guide them through that.
And having that faith that they'll actually come up because whatever they come up with will be a much stronger solution than a technical expert could come up with.
- Yeah, there's some power to lack of expertise in some ways. Like, facilitation is a curious place to be, whereas expertise is a certain place to be.
- I get asked what is your expertise if we engage and do this piece of work. And my response is, I'm an idiot. Okay. I have no knowledge of what you do. And the fact is by having zero knowledge, I have no bias.
- Okay. So if you could go back in time to the beginning of your safety career, what's one piece of advice you might give to yourself?
- Systems can support good outcomes. Systems shouldn't be about trying to fix people.
- I'm going to have to go away and think about some of this stuff, which is great.
- But I got trained in systems, system, system, system. System solve everything. Systems keep you safe. Systems do this. Systems do that. Yeah.
- So how can our listeners learn more about the topics in our discussion? Obviously, there's the book.
- Yes. And there's two things. They can download the white paper free from our website at Learning Teams community, or they can support the growth of Amazon on Kindle, or on paperback. But once again, it's free to download, which means that the Kindle version or the paper version is as cheap as we can do it for printing because the whole concept was just to get it out for people to try things.
And, you know, don't be scared of micro-experimenting, you know, take that Trojan mouse effect. We have a new book coming out in June, which actually is like the field guide to doing it because, you know, once again, people want to see, and the book has a whole lot of stories about micro-experimenting and what we found and what were the key lessons.
So we've sort of been following it up because it's been about two years, so a lot of experimenting, but the white paper will give you the ability to go out and start a four D conversation in 10 minutes, 15 minutes, these things don't take long. Try.
- We'll link to those in the show notes as well. If you're listening and you don't have a pen to write it all down. Where can our listeners find you on the web?
- Yeah. So there's obviously LinkedIn, which is always interesting on a good day. But also we have our website called learningteamscommunity.com. And in Learning Teams, there's a section around the four D's and there's actually some different videos there as well, where we show people some of the things that have happened with organizations and some of those learnings at the same time.
And yeah, we are providing some resources for people to sort of download in that space and give it a go. And then there's the podcast series itself around "The Practice of Learning Teams" if people want to sort of get into it. But the podcast series is very much focused around safety. And then there's the work of, you know, other people.
So once again, you know, we've been doing the four D's in collaboration with Jeffrey Lyth as well. But, you know, if organizations look at this language of weak signals and learning from everyday work, it's being spoken about a lot more than what it was when we sort of started our journey. So I think, you know, 2023, 2024, there's going to be a lot of conversation around this.
So that's a bit that excites me because the stuff that we're doing, we're not making them proprietary. So it's not about sort of taking a market or controlling a market. We want organizations to do things differently and to find out whether learning can actually help us to improve.
- Well, I'm sure that those are some good resources. We'll have them linked. That is all the time we have for today. Thanks for tuning in, and thank you for the insightful discussion, Brent.
- Thank you, Mary, for the opportunity, and thank you to Slice as well. So you're doing some great products, so thank you.
- Yeah. And my thanks to the "Safety Labs by Slice" team. It's a joy to do everyday work with you. Bye for now.