Capturing Skills Visibility in Your Industry Webinar Series - Episode 2 - Mining - Safety Competence in a Demographic Crisis

In the second webinar of the series 'Capturing Skills Visibility in Your Industry' titled 'Mining  - Safety Competence in a Demographic Crisis', our presenters, Yasmin King and Margo Griffith, demonstrated how to mitigate knowledge transfer crisis by identifying internal technical gaps and verifying safety competence through auditable evidence, moving your operations from paper compliance to a real-time record of field-ready capability.

Liz Horne presented a demo of the SkillsAware platform, where you can see how SkillsAware acts as a foundational infrastructure layer to translate real-world mining capability into auditable data, allowing you to deploy your workforce with precision and confidence.

👉 Watch the full video on https://skillsaware.com/events/webinar-series-capturing-skills-visibility-in-your-industry/

About SkillsAware

SkillsAware is an AI-powered skills recognition engine developed through a collaboration between SkillsIQ, a skills-focused not-for-profit and Edalex, an award-winning EdTech and SkillsTech company, building on decades of technology and skills expertise. Its SkillsTech platform and associated services captures and maintains an evidence-based indicator of the plethora of skills that individuals accumulate progressively.

SkillsAware enables organisations to identify the skills that exist within their workforce and highlight strengths and gaps so they can plan for the future. SkillsAware assists with skills-based hiring and resourcing and supports and contributes to productivity, performance, opportunity and reward goals. SkillsAware has relevance for individuals, small, medium and large enterprises and industries in the recognition of current capability, prior learning and experience.

Learn more on our website - https://skillsaware.com
Connect on LinkedIn - https://www.linkedin.com/company/skillsaware/
Connect on Facebook - https://www.facebook.com/SkillsAware
Follow on YouTube - http://www.youtube.com/@Skills_Aware

Transcript

Yasmin King: Hi, I'm Yasmin King, I'm a director and co-founder of Skills Aware, and joining me today are Margo Griffith, Principal Skills Consultant for Skills Aware, and Liz Horne, also a Senior Skills Consultant for Skills Aware. Thanks to you both for joining us today.

Margo Griffith: Pleasure to be here.

Yasmin King: So, we thought we'd sort of start off by just talking about some of the background, of the mining sector, and why we're focusing on that today. Samaro, do you want to lead off?

Margo Griffith: Well, I think, what I'd love to start with, Yaz, is what the data is telling us. So, how big is this skills issue in the Australian, mining right now, around skills and skills shortages?

Yasmin King: So, look, look, it's significant and it's structural. So skill shortages have increased from around 34% of roles, in shortage. And in the last couple of years, it's increased to over 60%, right? And that makes mining actually one of the most affected industries in the country. And in critical roles, like, for example, mining engineers, the fill rates are sitting around at 42%. So most of these roles simply can't be filled domestically. And if we add the current political climate, regarding migration, importing skills is going to also become incredibly, more challenging as well.

Margo Griffith: So… Yas, realistically, though, is that likely to change?

Yasmin King: Well, I mean, if we just look at what the pipeline is, given that mining engineering completions, for example, have fallen dramatically, in some cases by up to 60… by up to 98%, sorry, the overall number of graduates is so low relative to demand. You have to say, how can this be a short-term gap, right? This has got to be a long-term supply constraint, because you don't just become a graduate mining engineer overnight. So, it's a really… it is a big challenge, and then if you would also then compound the fact that age-wise, there is a significant number of people who are in… going close to retirement. For example, 35% of safety coordinators and lead drillers are now retirement eligible, right now, okay? So, and look, I mean, and we should acknowledge there is work being done to address these challenges. You know, bodies like AUSMASA are trying to say, let's redo the framework, we need a faster way of, you know, having a national framework that enables us to get people, with the right skills faster. But that's something that basically is going to take time, to get agreement on and develop. So it's… and the problem that's being faced is immediate right now. What can we do now to address these shortages?

Margo Griffith: Yeah, so what… I mean, that's slightly terrifying, all of that data that you've just shared. So what is going to drive new entrants? Like, what do you think is going to change, or what needs to change to drive new entrants into this industry?

Yasmin King: I think one of the challenges is there's a real perception problem, right? And, I mean, research shows that half of the young people associate mining primarily with environmental damage, and I mean, look, you know, as somebody who clearly doesn't have a life, I spend some time on job forums for… on Reddit. And it's really interesting seeing how many people will say, for example, when they're thinking about careers in engineering or in other things, will say, there's certain industries I will not consider, right? So they've got a cultural position about what they're prepared to do, which is not driven by, where can I get a job, which is quite interesting. I think the other thing is a lot of people don't understand that the nature of jobs in this industry has changed quite dramatically, that there is so many more technology-driven jobs than exist before. So, you know, it's… it's more about, the automation and the maintenance of very sophisticated, automation equipment, not actually, operating it, because a lot of it is actually robotics. So… so I think… That's… that's a challenge for the sector. And the other is that there is certain cohorts that can't or won't consider a fly-in, fly-out, sort of, job. Scope. You know, so if you think about it, for example, for parents, that becomes more challenging. So I think, you know, there is… The sector has got some… apart from just the structural issues, it's got some perception issues that it's got to overcome for it to be seen as a value proposition for people to enter.

Margo Griffith: Yeah, so then… as well as the nature of the jobs. In that sector changing. They've got some pretty significant environmental, cultural, and social issues that they're fighting as well. So what do you think can be done about that? I mean, some of the things you can't change, but of the things that could be changed, you know, what do you think about these new capability needs, for instance? What does that look like?

Yasmin King: You know, in my recent travels and talking to deployers from different sectors, one of the things that really stands out to me was in advanced… an advanced manufacturing employer, where they, were looking for people to operate automated equipment, and, and they said that the most successful operator that they had was actually a barista. And that… that… and it was because this barista had come constantly and said, I want a job, I want a job, I want a job, and and the employer said, look, you know, I just gave in and said, okay, I'll give you a shot. And he said… and he is now the most valued of his CNC operators. Because he has, incredible attention to detail, he can operate under pressure, he's got great communication skills, right? So it was a case of understanding what his fundamental characteristics were, and then up… and then targetedly training him. In the automation component. So I think what I think this industry, like so many other industries, needs to do is think about how do we identify what skills we actually need? And of the pool of people that are available now, what can we do to target them to basically then upskill them? But you need to have visibility of their skills to be able to do that.

Margo Griffith: Yeah, so true. So, we're talking about skills recognition there.

Yasmin King: Yeah.

Margo Griffith: When people think about… I guess, entry… either pathways into, you know, a certain sector, or transition between sectors. They often think of formal training, I suppose. That doesn't seem to be working. That seems to be broken somewhat. Why do you think training systems are not responding appropriately? What's… what's structurally happening there?

Yasmin King: I mean, I think apart from the fact that speed is an issue, like how long it takes to design a new framework, new process, there's also a fundamental constraint in the fact that the capital equipment that is used in these mines is extraordinarily, specialised and expensive. You know, typically, you know, a piece of equipment costs between $5 and $8 million. And that means that, for example, your traditional training providers, they simply don't have access to that. So, while they might be training on something that might be a few generations behind, or they simply don't have access to the same sorts of environments that are needed in the workplace. And so. There's a bit of a mismatch in that, you know, you might have a trained person, but can they actually be fully job-ready in the workplace when they've probably not been trained on the same level or sophistication of equipment that they're going to face? And so what we're seeing is a lot more employers are trying to deal with this themselves, and they're taking training in-house. And they're, you know. Strategically investing in partnerships with 
universities, for example, and really sort of looking much more at taking on the workforce development self-tasks themselves. But the problem with that is, then, that's recognised in their ecosystem. It's not building the whole ecosystem.

Margo Griffith: Hmm.

Yasmin King: So, it's also expensive to do that as well, right? So, I think that's, you know, some of these challenges of how do we basically think about it, not more from an employer going down to an individual and upskilling, but more about, basically, from an individual point of view, how do we recognise what all of their skills are? So, you're building the whole pool bigger, is what we're going to need to do to really address some of these, because the workforce constraint is going to hold us back from opportunity.

Margo Griffith: Yeah, big time, particularly in an area, you know, such as resources and energy sector. That's a… it's a massive constraint, and I would assume these labour shortages are also, you know, really impacting project deliverables, right? If you don't have the people to deliver on these projects, yeah, your chances of really, you know, being the flywheel of more projects, etc, is huge, and an economic, you know, burden.

Yasmin King: Yeah, and then when you think about how about, you know, the push, for example, to get women in some of the non-traditional sectors, mining being one. And while absolutely, you know, in theory that's a great thing, they only make up about 18% of the workforce. And then you've got the FIFO component, right? Which also makes it much more challenging. So, you know, you've got… Fundamentally, a more narrow talent pool, and it's also a talent pool that's under a lot of pressure, because FIFO, there's a lot of evidence that show that FIFO can really impact people's mental health, and also from a retention point of view. People might do it for a few years, but then find that, you know, they just… it's not sustainable, and they want to do something different. So, it's not just about bringing people in, it's also about how do you effectively keep them as well, right?

Margo Griffith: Good. Yeah, great point. So we've spoken, like, there's multi-pronged challenges here, you know, from… from technological advancements, we've… we've got, perception issues, around talent acquisition, we've got inherent difficulties within the way that, you know, job roles are constructed with FIFO, etc. We collectively on this call, right, are very deep in the weeds around skills recognition, so talk to me a little bit about how that might change, or what… what skills recognition and skills visibility could do for some of these challenges.

Yasmin King: Yeah. So, interesting, look, there is software solutions in this sector, which basically… because, obviously, compliance is a massive thing, particularly in respect to safety, so there's a… there's a lot of, solutions that really address, like, what are the job roles, what… what are the requirements of those job roles from a breast practice point of view? But I suppose where we're coming at it from it is to say, well, okay, that's what's required, okay, but what are the people who are available, what can they actually do? And what can we do to align them to what those best practice needs are? And so you can do targeted upskilling. Because targeted upskilling is going to be far more effective and cheaper, but also enables you to… to maybe look at what you already have access to. And in a shorter time frame, basically get them ready to be operational. And you really need to understand what people's experience is, and map that. In terms of capability. And that's really what we've tried to do in developing Skills Aware. And so, look, I'll probably, at this point, it'd be useful to get Liz to basically give us a, a short demo on, and in particular, relevant to this particular industry.

Margo Griffith: Thanks, Liz!

Liz Horne: Not a problem, thank you. I'm going to share my screen and bring you to the online survey. So, Skills Aware has a capability of, bringing people to an AI-powered, skills recognition framework to find out some information. They interact with, Skills Aware, and it will help them identify and make their… the skills that they have really clear, based on evidence. So they begin their journey by answering just some very basic questions, about their background and experience. So, in this case, I'm going to talk to you a little bit about today about somebody with… who is a heavy vehicle mechanic, with some time in the Australian Armed Forces. In answering the questions, there's different… there's sort of 4 different pages of questions that at any time, I can add some evidence in the bottom here. I'm not going to do that, during the actual presentation. But they will submit that, information, and… That information will be drawn into our system. And that system would then take them to… From the information they've shared in that, overview. It will take them to a series of suggested skills that are related to just the information that they shared in the survey. The individual will then take some time to enter some evidence, so information that they've gathered over the course of their work and life experience, and they'll enter that information into the system by either dragging and dropping it here on the right-hand side. Or, clicking into their… if they click into it, it will take them to their browser, and they can download any piece of evidence. But what you see here is we've got… A USI report, which is the report that they were given when they left the Australian defense Forces, and the qualifications they were provided with there. A couple of references, a position description that they're currently working with, a white card. A reference from the mechanics in the Australian defense Forces, a resume, and then also a training that they've been involved with. So, that's a total, in this case, of 9 pieces of evidence. From that 9 pieces of evidence, the AI has identified 351 skills. From just those 9 pieces of evidence. As an employer, Well, knowing that I want to focus on taking my skills into into the actual mining industry, I would then go and look and see what skills are relevant to the mining industry. So I'm going to move our picture here. And the skills, then, that have come through is… you can see here that, the follow safe work practices in an automotive workplace, that makes sense, he's a qualified mechanic. So… The individual can work on the skills that they think are relevant to that workplace, and in some cases, in the mining industry, they may say, here's your target… here's the target skills that we need. But these here are, are basically the electronics, and also the diagnosing, heavy vehicle, etc. And it goes all the way down to some critical thinking. Participate in work health and safety, which is really important in the mining industry, and then it goes further down to other different, skills. So I've just selected in this, in this demonstration, 20-something skills. Once they've entered that information, they can also have a conversation with the AI, so they can have… they can ask questions in this space. And in the questions here, it will guide them through the types of evidence that they may be able to find that would increase their percentage score here, and I'll get back to that percentage score in a minute. The types of evidence that they can put in, which is showing here, is the certified evidence, organisational evidence, so some information that you've been able to provide from a recent or a current employer. And then also, certified evidence, which might be formal training. So in the case of Walter, our friend here, he had certified training within the armed forces. He's had, references from, his time in the Armed Forces and since he left the Armed Forces. And he's got a series of self-claimed skills that he says, I've done this, this is my resume, this is my, information that I've got on my LinkedIn page, those sorts of different things he's put into the system to actually start to analyze the skills that he has. Once he's done that, he can, look closer at the skills. So, in this case, it's, diagnose and repair heavy vehicle suspension systems. There's two different scores here. One score is experience score, so that says either he's self-claimed or an organization has endorsed his skills, and then in the formal skills, he has some sort of ticket that actually, links to that particular skill. He can actually create a digital skill package, if you like, so it's… it's like a, A… a… a sample, I'm lost for a word here. Certificate that actually shows the skill. So it explains the name of the skill. It explains the different components that are involved in the skill. So, in order to be able to do the overarching diagnose and repair heavy vehicles, it goes down into and breaks the skill down into four sub-skills. At the bottom of that, the evidence that's been used to come up with that score is, is actually, identified at the bottom. The other thing that is here also is what's called our capability report. And this actually goes to explain why, the actual, PCI score has been, in the case of this SR1, prepare and diagnose for heavy vehicles, it's sitting at around about 60%. And so. It will explain why the piece of evidence actually proves that that person has the capability of doing that job. So let's get back to that PCI. The skills indicator for this particular skill is 59%. So that's basically saying the likelihood that the person can do the task in the workforce based on the evidence that's been provided is 59%. It's the probability. It's not the score that we would typically have in a 0% to 100% score, which has that typical bell curve, et cetera, et cetera. It's actually the probability that the person can do the actual job in the workforce. And it provides the reasoning here. Further down, it also identifies the pieces of evidence that have been used to actually come up with that score. So, the onboarding survey is one of them. A white card, makes sense. A reference. And then also the reference from the time in the Army, the transcript from his time in the Army, and again, the onboarding survey. And then self-claimed military experience as well. So you can see all of those different pieces of evidence are there for somebody to look at to validate that the actual person has those skills. So, one of the overarching things that we were just talking about is how do we make our skills trans… how do we see them? And this is a classic way of doing that. Just from the 9 pieces of evidence and a brief conversation between Walter and the AI, it was able to… to… highlight 356 skills, and then we were able to zero in and look at 27 of those. And there's no limit to what the person could look at. But as you can see, they're listed here. The My Skills that I've been working on for Walter are listed here, in really easy-to-read format, and then they can see them all sitting down on the right-hand side. If I've entered new information into the Evidence Hub, and it is relevant to one of the units of competency, or one of the skills here. This update button, will show up, and if I actually click on that, I can actually update it, and we should see the score change, and also all of the information that's attached to it, so if there's more evidence that's attached to it, and the skills package will change accordingly. So that's… that's a very brief overview, of the system. But as you can… with the suggested skills, we can go down in those suggested skills and choose whichever skills we think are relevant to the job that is… that we're looking to fill in our organization. So, for instance, if we were looking for somebody in the risk management space, we would go in here and focus on our work health and safety and our risk management units of competency, or risk management skills. And see how their score went with that. We would then be able to use that information to be able to go, okay, they're scoring at about a 45, and our report Enables us to look at individual sub-skills within that. So you can see one of the sub-skills is 67, one is 52, Another is 67, and one is 50. So we might have a look and see if we want to increase that score, but if one of those came up as 0, you would know you could target your training for that particular person right in on that sub-skill, within that… within that area of interest. So, ways that we can use the information that the Skills Aware provides are really quite broad. But it's a really great way of putting in minimal evidence, that talks to our experience in the workplace. And providing the suggested skills, and being able to dig deeper on those skills to say, yeah, I want to understand those more, or I can see if I can get a better score at that. That would enable me to, apply for a promotion, or alternatively, if I'm using it, to help retain staff, we'd be able to look at those skills and say, if I provide this staff person with this skill. It might actually keep them in the industry a little bit longer and help us promote them through the ranks. Or, in the case of, Walter here. He's a diesel mechanic. He's also done the electrics in a diesel mechanic. He probably would be a good candidate to actually be involved in the remote operation of the heavy vehicles and understanding the information that's coming from those automated machines so that they know when it's time to service them.

Yasmin King: And I think one of the things that's really useful to point out is the granularity of this. Which is, I think, one of the really important aspects, because that enables you to be… that's how you can be targeted. I mean, one of the examples that I often use is, you know, people will say, oh, you know, our HR system will tell us who's a good communicator. Well, a good communicator in what sense, right? There's lots of aspects to communication. In what context? In what way? And I think one of the, advantages of the fact that we've got 71,000, rich skill descriptors that we measure against is that granularity, because I think the fact that this shows that somebody, you know, with just 9 pieces of evidence can say they've got you know, 300-odd skills shows that we all undersell what our actual capabilities are. The visibility of our capabilities is really quite masked. And what we're trying to do is say we need to unlock that, because if we do that, then there's going to be way more opportunities for people in areas that they might not traditionally think of pursuing with some targeted upskilling.

Margo Griffith: Yeah, thanks, Gaz. There's, some international people on the call. One of the things, or one of the questions that have come through is around, we have obviously mapped this system to the Australian, system and the Australian environment. What about if we are, say, you know. dealing with, mining operations in other countries. Do we have the ability to map to other databases, for instance? Liz? Is that… can we do that?

Liz Horne: We can. We're currently working with, a group in Canada, actually mapping their standards, of their training programs into the system, and, it's, it's working quite well. So as long as there's, there's enough information about a standard. It can be bought into the system, and then the AI can map any evidence to that… to that particular standard. And we shouldn't forget that some of the standards that are involved in the training packages in Australia could be helpful to some of those different countries where their standards may not be. Fully developed, to the level of detail that the Australian ones are. So there's that combination of being able to assist with, providing the structure for those as well.

Margo Griffith: Amazing. I see that we're coming up to, to the, almost closing out the half hour, the 30 minutes. Thanks so much, Liz, that was, that was great. Yaz, is there any closing comments?

Yasmin King: No, other than I think we, we, we're very keen to talk to anybody who might be interested in learning more about how we might be able to… to help them, identify, skills. I think one of the things we've… we as a, as a… as a country, and I think this is not only us, it's certainly based on the things we are involved in internationally, is we know there are some real challenges facing industry sectors in getting the right people into the right jobs. And we need to think differently about how we can do that. And particularly in the context of what's happening with AI, we really need to work out what skills people have, and how we can target and upskill them.

Margo Griffith: Awesome. All right, well, thank you so much for today, and, thanks to everyone for joining us, and yes, hopefully we can talk to you some more about skills recognition and skills visibility. We'll say goodbye, have a good afternoon.

Yasmin King: Thanks. Bye. Thank you. Bye.

Margo Griffith: Bye.