Courtesy of Petrofac's Jonathan Carpenter, below is a transcript of his speaking session on 'The Digital Plant - using technology to reduce downtime and operating costs' to Build a Thriving Enterprise that took place at BTOES in Oil & Gas Live Virtual Conference.
So let me welcome our first great speaker of the day to day the Jennifer Rogers. Jennifer, very excited to have you with us. Jennifer is an experience learning executive with a demonstrated history of strategic workforce transformation and capability development. She specialized in workforce optimization, and has led large strategic initiatives in several global, high, high risk, high compliance industries, including oil and gas, mining, of aviation, and financial services. Jennifer is passionate about leading cutting-edge innovation in the learning space with particularly rotation to strategies that proactively prepare the workforce for the future of work. Very much looking forward to your presentation, Jennifer, and the thank you for being with us today.
Thank you so much, Josie.
So I'll start today's presentation by, by really just orienting to the mission at hand. This, this presentation is certainly focused on accelerating people potential and the ways in which we really prepare people proactively for the change. That's coming and as Jessie said very eloquently at the top of this intro. We are at a time of quite a bit of change at the moment, so hoping today's presentation will be particularly relevant for you all.
A bit about who I am as we get started. I think it's important to kind of articulate the kinds of work that we do and the passion that drives us. And so, for me, what they are, just, they've already given a bit around who I am and what I do.
for me my passion is really about creating and cultivating those vibrant learning ecosystems that really have to be and called and catapult the work workforce forward. And we'll talk more about what that means throughout the course of this presentation. But essentially, we know what I'm really focused on are our colleagues in the workforce, and the ways in which we can really engage them and set them up for great success and development within our organizations, which we know then, drives quite a bit around Operational Excellence and the continuous organizational strategy that, that organizations have in play.
So we'll start off at the top of this presentation by just talking a little bit about what may be very obvious to us at this moment in time, But the change that is happening to us in the world, in our workforce and in the work itself. So first, talking a little bit around our changing world, and the elements of this slide actually were pulled together by a gentleman called Peter Fiske from some great resources like Blackrock Bloomberg, Deloitte Mackenzie, PWC World, Bank Plots. You see them on the slide.
But basically, we're talking about is megatrend, predicted from 20 20 to 20 30.
And as we look at the fact that we're in 20 20 this year, and it's already been quite a year of change for us all, it's interesting to kind of reflect with regards to the changing world and the mega trends that are predicted.
So we start to see things like shifting economic power, climate change, resource scarcity, technological breakthrough, which I think we've talked quite a bit about this week. In the session's, demographics, social change, rapid urbanization.
These are all mega trends that impact all of us across the world, and really are very relevant to our organizations, because our organizations really need to be positioned in a way in which they can be prepared for the change that's taking place. And as you can see, with these megatrends, there's a heavy people involvement with all of the change that's taking place. And it's very important for us to stay focused on the mega trends as we see them today, and the megatrends as they start to develop over time. Because obviously, this is the fluid situation and continues to change.
But as we start to look a little bit deeper with regards to change that's taking place, there's also change in our work.
This particular graphic comes from a great study that was done by the McKinsey Global Institute in 20 18.
And the reason that I like to show this is because it focuses specifically on energy and mining as an industry. If you, you kinda take a look at what's represented here. It's speaking about sector skill shifts that are predicted by the year 20 30.
It's actually showing which skills we in. We would predict to see fewer of, or less of a need for, I guess, I should say, by 2030, and which ones we actually will need more of. This may not be surprising to any of you, but it does highlight the need to really be prepared as organizations. Just a few things to highlight as we look at this.
And we see a general decrease in skills required in terms of physical and manual labor and basic cognitive skills.
Then increases in skills around or usage of skills around higher cognitive thinking, social and emotional skills, and technological skills. In particular, in energy and mining, we see decreases in the use of skills like general equipment, operation and navigation, inspecting and monitoring, basic data input and processing, and basic literacy, numeracy, and communication.
When we start to think about that, that's a big shift for the workforce. In terms of that decrease, we also see an increase in creativity, complex information, processing and interpretation, entrepreneurship, initiative taking, leadership, managing others, advanced IT skills and programming, and basic digital skills. So, once again, quite a shift with regards to the skill that's required to do the work, as we get to 20 30, which is not that long from now. So, how do we, once again, ensure that our workforce is proactively prepared for what's ahead, and we're not waiting, until the work actually changes to start upskilling people for what's to come?
Then, additionally, on top of our changing world, and are changing work, our workforce is changing as well. This also comes out of that same study from McKinsey. And it talks about our changing workforce. There are mindset shifts that are taking place. We see that already around counselors of lifelong learning and development opportunities are, our colleagues, expect development opportunities at this point. Which is great and emergence of new collar jobs, Which really is speaking about, as those skills shift allocating work in different ways across our organization.
With the creation of new jobs that are kind of middle skill positions, that bridge a gap between one and the other. We'll talk a little bit about that further, as we get through the presentation, workforce composition. So, obviously, the gig economy changes a little bit around the composition of our workforce, organizational structures in terms of how our organization has put together, and the ways in which it can be more dynamic and agile, and adjust to the work that needs to take place, rather than being being fixed hierarchical models.
As well as C Sheets, a C suite, and HR changes that are required to make all of this happen.
Really, the CEO mindset, and then down into the organization, with regards to organizational design and the ways in which we, we empower our people amidst this change, so lots going on here with regards to the change ahead of us. And so, in today's presentation, we'll spend a little bit of time diving and deeply into three different, main, main areas. Because, as we look at operational excellence, and the organizations of today, and tomorrow, we really want to make sure that we focus on a few different things. one, reducing variation in processes and equipment, In all of the things that need to be present to really drive operational excellence.
But, also, at the same time, recognizing the diversity in our workforce, and actually empowering, leveraging that diversity, to really help us, to be agile, and adapt in times of change, Which leads us to re-imagining the workplace, and the ways in which we actually exist as organizations, and work together. So, we'll talk about all three of those things in some detail as we go forward.
We'll start off by talking a little bit about the reduction of variation, and this is really about the ways in which we can make standards, processes, equipment, and parameters, all accessible, And there's a key emphasis on the word accessable. one size does not fit all for our workforce and our colleagues. We have colleagues distributed across the world, in different cultures, with different backgrounds, and different experiences, really different ways that they work.
So, I'll share with you a few concepts to think about, as an organization around that reduction in variation, and, and, more importantly, reduction in variation at scale in an accessible way for the workforce.
So, one of the key points that we start to talk about here is really continuously being able to describe the work, and not the org structure, and this is this is something that needs to happen consistently.
We need to categorize our areas of work, identify risk and measurable operational targets, so that we can start to shift and move as an organization, as these changes occur. It's much easier to do that if we're describing the work versus describing the org structure, which most likely will change. We'll dig into that in a little bit more detail here in a moment. We also want to continuously to find the capabilities for our workforce, once again, by the work, by the discipline. Not by their job title. Because, once again, we know jobs are shifting, skills are shifting. We want to maintain multiple scenarios simultaneously, which we'll also look at from a strategic planning perspective, which is very important to our organizations that are have some rigor around scenario planning.
We want to create re-usable objects that are multimodal and multichannel. I'll explain that to you with regards to what that looks like. And deploy it into the flow of work. So we want to make sure that, once again, that everything is accessible to people in the way in which it needs to be accessible to them. Based on who they are, the language they speak, the culture that they come from, the type of work that they do, their operational area, All of those types of things. And finally, track the behaviors that our workforce exhibit via something called X API, which I'll explain, that is essentially a data standard that exists. It's open source, and allows really a very robust view around our workforce, what they're doing, and how they're developing and growing.
So, we'll start off by talking a little bit about this idea around kind of standardizing capability expectations and being dynamic about this. And the example on the screen is really speaking a little bit around the, the ways in which, a lot of organizations are starting to use artificial intelligence and human validation to do this work, and to continue to make it dynamic. Over time, we know that the capability expectations are going to change.
We can predict what those are, but we may or may not always have it, right, So what this illustrates is, just one example of the ways in which organizations are actually using AI. So, in this particular example, this actually shows the capability to be able to ingest thought paper, thought, thought leadership, white papers, publications, that patent, websites, anything that's out there. that gives us a viewpoint with regards to what's happening in the industry and, in parallel industries, which helps us to continuously maintain a dynamic set of capability expectations for our workforce.
Artificial intelligence is not perfect, it has to be trained. And there is a human validation piece that goes into this. But, once again, the more that we enable AI to help us with this, the more we can proactively start to develop our colleagues in these areas.
The next piece really speaks to capability Matrices and scenario planning, Once again, we want to organize the work by disciplines, so things that, you know, that might come into play, You know, most recently, I've worked with them with mining. So mining, processing, finance, HR, what are the disciplines of where data analytics that might take place? And where the scenarios that, we think can play out, this is, once again, an example of the ways in which organizations are starting to actually incorporate this into scenario planning. So, what are the scenarios that we think could play out in our industry and what are the different set of capabilities that we might need in these different scenarios?
For example, we all just recently saw the successful return of the space-x vessel back back to Earth. I know we were really excited about that in our, in our family. What does the commercialization of that look like? Is that a scenario that we all need to be thinking about? Particularly in this industry? Perfect example of the ways in which we can actually hold multiple scenarios simultaneously and continues to continuously dynamically feed those scenarios with the capability that the workforce may need, which, once again, is, is super important in an era of change.
The next piece to really focus on and think about here is Multimodal multichannel experiences. So, as I was saying before, our colleagues are in different places. They work in different ways, and we want to reach them in the flow of their work.
So, essentially, what we don't want to do, is build different ways to reach them, in isolation from one another. So essentially, you know, building an e-learning course, and I'm putting something up on a webpage, and building a native app. And, and then doing some remote support, all in, isolation from one another, because that's dangerous. We can't version control that. And it's incredibly resource intensive to make that happen. So the organizations that are best positioned at this point, with regards to even the current scenario, are organizations that are already doing something called single sourcing. And what that means is we're creating these assets, regardless of what they are, procedures, online foundations, instructor led courses, augmented reality, virtual reality, ongoing learning support and communities, and contextualized help, and just on equipment support, whether that's remote operations, or even just scary, sharing schematics and fops, and things like that.
Through one common channel. So what we see on the slide here is really an example of actually building these things one time through XML, which allows you that then to just publish them out to all the different places that they need to be in all of the languages and brands and everything else at one time. So we really only create things one time. And then, if we need to make a change, it changes everywhere. Automatically. Organizations that are really well positioned already have this in hand, and particularly with the kogod situation that we're in now, have found it very easy, quite frankly, to shift to different modalities in different ways to reach the workforce. Because, they're not building something new there, always building a core piece that can can be in any mode and channel that their organization's need. So, once again, very important for that that standardization.
There's a piece around single source augmented reality as well. So, I mentioned different modes and channels, one of the ways in which we do this and particularly within the space that we're all in, is through augmented reality. So, the heads-up displays mounted to the hard hats that give them schematics, workflows, SOP steps once again, and even remote operations assistance. And once again, we're not building that in isolation from everything else. We're actually sourcing into that mode and channel for our colleagues to experience, which gives us a robust set of information and data, which we'll talk about in a moment, as well, with regards to how they're engaging with it and how we actually are changing workforce behavior.
one of the key ways that we do this is through the Experience API. This is an open source data standard that exists. And if you're working with vendors and partners and providers right now ask them about and ask them if they use XAPI. What doesn't their data standard look like? Because we're looking for that open source data standards, that we can actually culminate all that data around all these experience experiences back in one place. I mean, if we're using proprietary data formats, it's not so easy to do that. But, just as a primer add to XAPI and you can research this more if you're interested on your own. It's a syntax that gives us really clean data around what's happening in our workforce. There's always a piece of every data statement that has a people part. So, it tells us who, it tells us what they're doing, and what objects they're acting on, which is really, really important. And it also gives us additional parameters, what are the results of their actions.
So, if we're in an operational situation in which there are parameters, we're falling out of limits, and Jennifer is operating a piece of equipment and needs to take a quick decision and and change something, what change did she make, what action did she take, and then what were the results of that action? And furthermore, what was the context? Right, what was the operational parameter that was trending out of limits, And what do we know about the environment in this situation?
This is already a data standard, and it's a huge, huge importance to us because it gives us lots of great information about what we're doing and how our workforce is developing. You can see some of this listed on the screen screen here in terms of a particular example where we're actually looking at a mud gun. Once again, this comes from a mining mining example, but we can actually see an actor, a person, what they're doing that they're basically a close to hatch on a piece of equipment. And, even in virtual reality, these are the kinds of things that we're expecting to see, not just someone completed it and they got a score and they answer certain questions, right, But what did they actually do in the operational environment that we placed them in?
We see this with simulators as well so this is another great example of XAPI statements coming from a physical simulator. This one happens to be operations of equipment. So you can see that they're applying the service brake and the accelerator simultaneously, right. So it gives a good idea of what exactly we're seeing from a behavioral perspective.
This one is fine as well. This is an example of facilitated reality. So, this is a virtual environment, but real people, so a facilitator on the other end of this virtual environment, kind of driving this person that I'm speaking to, and having to react to the things that I do. We see this a lot with building skills around leadership, problem solving, how to collaborate with colleagues in a safe space. And once again, pulling out that data that helps us to see what behaviors are decisions our colleagues take.
In those experiences, We can personalize virtual reality as, as we, we start to get more advanced around this and actually take the decisions that people have taken previously in different environments. and actually start to adapt the environment. to give them different challenges based upon the skills that they already have, and the decisions they've taken before.
So that's very nice as well. Then, another piece that's really interesting is there's a lot of things emerging on the market, with regards to actually taking different VR experiences that are built by different vendors, and putting them all together in one place. Once again, that we can actually deploy this out to the workforce at scale, and get those data points back, that we want to see, what are the behaviors that we're expecting to see? Are we changing those behaviors? What does that look like? and how is that data coming then back into our or our organization in what's called a learning record store. So that's where those XAPI statements are stored that show us what people actually do. It's really important that that data is all defined, because, once again, it plays into your scenarios, it plays into your operational parameters, and all of the things that you're looking to see from an organizational perspective.
But all that said, We can standardize all we want at scale, and unless we recognize diversity, we will not see the, the real strategic value of our organizational strategies come to life.
So, when we recognize diversity, it's really important to understand that people are the strategy of a sustainable organization.
We want to make them visible, and often, we're talking about changing skills. And how are we going to give people the skills and everything else? But at the end of the day, what's really important actually is for us to be able to see the skills we have. How can we engage in workforce and capability curation across an organization? Link continuous feedback to performance. Make capability expectations evergreen and fully transparent, so that anyone in the organization can see what capabilities are skills are required for, for any role.
We also want to measure real-time capability development and look at how it correlates to the different experiences that our colleagues are having so that we can actually increase or accelerate that development. Which is nice. And then, obviously, lots around strategic planning. And the ways in which we decide, do we recruit people? Or do we actually have people in our own organizations that are actually well positioned to do some of the things that we need, regardless of what their job is today?
So, this is just an example, but over the last hundred years, a lot of us and organizations have have not had the benefit of a lot of technology to do this. So, we may have had some kind of CV from a person that gave us some basic information, if we were really sophisticated. We were looking for keywords in that, and pulling that out, and those kinds of things. But, but Time has changed, and technology has changed. And so I'd like to share a few pieces with you around what we may have been missing by just pulling out those keywords out of CVs. Alright.
What we see on the screen is, is actually taken from an oral kind of video, storytelling object from the same. Same kind of scenario as the person TV that we just saw, and we start to see a whole different piece come come alive. In terms of the person, their skillset, what they do in and out of their daily work for the organization in their community and everything else. Where they may be using skills that we haven't thought to ask them about, and they haven't thought to tell us about, because it's not their job description. And so, how do we do that, and do it at scale?
Once again, AI has proven incredibly helpful with this, With regards to learning about people through the information that they provide. And actually recommending skills to them. That they may have, based on skills that they've already said that they have. Or different pieces of information that we have about, whether that's than telling a story, which I think is really significant for some of our frontline workers, or typing out a CV, which is also important, as well. There's a whole way to do this, and create human validation around this, as well, whereby the AI makes a recommendation to the person of a skill that they might have. And they either accept or reject it. And once they do that, the work teams that they work with, have the opportunity just to give a viewpoint on a daily basis, or weekly basis, or whatever, how they're applying that skill, and at what level, and which really gives us that step change around actually seeing, for the first time ever, capability development happen in real time.
And it's really important to actually incorporate this into continuous feedback.
So, for organizations that are really taking that next step, in terms of moving into a continuous feedback performance, performance management system, instead of maybe an appraisal system. Or things like that, or maybe even just complementing it.
We imply this as well. So what are the core skills or the target skills that that individuals working on? And how do we surface those to the people that they work with? So as they give that continuous feedback, they know what skills that person is working on, and can give them a viewpoint as to how they're actually developing in real time.
This also plays out well, particularly with the AR headsets, because as we have remote operations and support and play, they can do the same thing as they're observing someone, do the work on site.
This is important to us, because it gives us an individual view linked to experiences of how someone's skill profile is moving morphing, and changing and then dynamically. And we can provide different experiences to them, based upon how they're developing. And the ways in which they want to develop. We can also infer potential skills. So, the AI is great, about saying, because you have this skill in this skill, you might also have the skill, which once again, sometimes gives people an opportunity to reflect, and say, I actually do have that skill. I'd never would have thought to tell you about it, because it's not my job right now.
And I didn't think, I didn't even think about it, quite honestly. And, so, lots of different opportunities there. And then, once again, and this is just an example on the screen, It's not any real data from any real organization, because that's definitely intellectual property, and, and very valuable strategic information. But it gives us an organizational view of current and future state against those different scenarios. What skills do I have? How strong are those skills?
And am I really prepared for scenarios as they play out?
We can then start to really do amazing things around predicting and doing comparative analytics. So once again, what skills were acquired? What capability was acquired? How much of it and what did it correlate to? So in this particular example, you know, you're slicing and dicing around assessment of potential and how are these different populations evolving over time.
You can drill down to any specific demographic. But once again, having that data is the way in which we do that. Which really gets us to a different place. It positions us in a way in which we can truly get to capability based organizational development, where everything is tied together. Recruitment, accelerate onboarding, I can onboard someone faster if I've already learned from them in the recruiting process a bit around their capability and their profile, So that I can actually accelerate their onboarding from the time that they're hiring, or even pre fire, which reduces time to competence and increases development. And we've also got the performance in real-time capability development that's also very, very important. And then, of course, the true, strategic workforce planning and global mobility aspects that come from all of this data.
So, finally, just a small piece with regards to how this all comes together, How do we start to re-invent the workplace with this reduction in variation, in equipment and processes, and really a full realization of the diversity within our organization?
So, as we start to do this, we're looking at evolving equipment, evolving processes, and evolving people. And there are great pieces of technology that are in place right now to actually do just this. If you are measuring and tracking those key operational parameters in your workforce, you can actually use that to then trigger interactions for people where we give them process information, and information connection to other colleagues, Remote operations Assistance. All this particular piece is based on what's actually happening in their, their operational environment at that time. Which gives personalized intervention points for that person that help them to make better decisions, work on those complex decision making skills, and continue to build and develop their skill set.
We can also correlate the capability development that comes from that, with continuous process improvement.
So, really quickly, there's a couple of pieces to look at as we kinda start to round this out. In terms of how all this works.
As we look at the slide ad that's present here, there's a lot going on. And we won't go into great detail about this, but the key highlights are kind of the teal parts at the top. So, if we know about a persons capability profile and we have IOT inputs around the environments, then we take that capability information. And the content or processes are schematics.
We can actually personalize an experience for someone that leads to them getting a particular intervention at a particular time. Then actually, if you skip down to the next teal bar, resolve the operational contacts through IOT. Which then gives us a great view as to how we've actually done dynamic, real-time, continuous improvement in the flow of work and simultaneously developed capabilities.
In. so, doing, IOT is greater on this, and there's a lot of emerging work in this space, I'm quite passionate about this, currently, around using IOT data as anticipatory learning. So, how do we actually take the data that we have? In this particular example, we've got information about the environment and back information around people, information around processes, and actually bring all that together and personalize an experience, someone for someone right then and there at the time in which they need it. That is going to give them the tools that they need to be successful and to really continuously improve our operations. So, as we look at this, there's a great opportunity to use that operational data plus a personal capability profile to really personalize an intervention or an experience that results in those great XAPI statements that say in this context.
Jennifer did this to this piece of equipment and we saw a resolution in the sense that the operational parameters resolved.
So, lots of great work in this space and lots of opportunity that really do put our people ahead of the change and position them quite well for the future. And in closing, I wanted to just share a quote that I think is really relevant to all of this work, from Jim Rohn. It says, the big challenge is to become all that you have, the possibility of becoming, you cannot believe what it does to the human spirit to maximize your human potential and stretch yourself to the limit. And I know that's what we're all after, in this great quest to continue to evolve as organizations. And it's just such a pleasure and honor to share this with you all today. I do, thank you and I look forward to hearing what some of the rest of you are doing around some of these aspects as well. You can always reach out to me if you have any additional questions or, you know, there's collaboration that you want to do around some of the innovation that you're doing in your own organization.
Terrific. Terrific, Jennifer. I'm gonna ask you to stop sharing their ego. And the, I'm going to come on here. And as you're speaking, though, there are a number of questions that came up, so share those with you. Thank you, first, of all for that. For that coverage. A very.
Super interesting topic, because there are some commentary that was going on as you're presenting, and then some people talking about their own organizations. And it's like, this is not what my my Learning and Development Department looks like. And, and I think that's an experience that's that a lot of people can relate to, that learning development has been slow to adapt certain technologies. A lot of technologists.
We still, I think that in certain organizations are still in the mode of digitizing some paper forms type of thing and they call it knowledge advanced.
So, so terrific.
There is so much that we can go deeper on here.
So, let me try to, one of the questions was, and trying to simplify this, this whole universe is, tell us about someone who's beginning on this journey. You know, you have clearly done quite a bit. How would you start something like what you have there, while you haven't laid out for us?
Yeah, you know, regardless of how much technology you have access to, there's some really practical things that you can do right now to start to move in this direction. And some of you may have already done some of these things, but it's worth looking at, right, how are you describing work in your organization? Are you describing it by your org structure, or are you describing it by disciplines, broad disciplines, that that will always be those disciplines, regardless of how your org structure may change? That's definitely something to think about. And how is that accessible to people? Can it be used? And that leads into things around taxonomies and classifications. Do you have a taxonomy within your organization?
Do you have a way to classify these things, so that you can once again, connect people to the work that's meaningful within the organization? It doesn't take necessarily, really fancy tech and AI and all those kinds of things to do some of that work. It's, it's great foundation to start to think about. Another practical thing is, is really, do you have clear behavioral targets that are set up for your workforce in your high risk areas?
That's a place to definitely start, right? If we look at the areas in which they're the highest degrees of risk, it's, it's pretty, it's pretty powerful to compare that to your risk matrix. And by the way, if you don't have a miss risk matrix, another point to look at. But how does that combined with your SLPs, right? Do you actually know which parts of your SLPs correlate to Your Risk Matrix?
Where are the places where it might be helpful to, to, to connect somebody with a person, with, an experience, to measure their behavior, and what behavior we actually looking for, those are, those are driven pieces that are really important, and, I think, regardless of the amount of text that you have, you can do you know, which parts of your operation have the most risk, have you clearly define what behaviors you're expecting from people in those risk scenarios. And then, do you have a way to measure or track those? I think those are all really good first steps in terms of preparing yourself to really do this at mass scale.
That's, that, that really is very helpful.
To just lay out, like you have, the, the, the approach using the structure, may be that you have to think about before you really start thinking about bringing some of the technologists that you talked about.
So, assuming that, those tech, not those, that structure has been laid out, as you described, what would be the first, maybe, technological piece that you may want to bring in, or maybe a sequence of technologists that you bring into that structure now?
So, one of the most important pieces, where you, you have the opportunity to realize a great amount of value, very quickly, is through technology, like, like the learning content management system piece that I spoke about, which, once again, allows you to create things in XML so that they can be augmented reality. Virtual reality, web based, paper based, Whatever they need to be all at once. Right. And that you can deploy them out to people in different ways. And typically with that, with that learning content management piece there, there is a repository piece that involves a Learning Record Store. And that Learning Record Store is also very important because that's that actually stores all of these XAPI statements around what people are doing in their real work and in some of these virtual scenarios as well.
And also very, very important, this deviates a little bit from the traditional view, around learning systems and things, whereby we, you know, what we started with with technology in this space long ago were words, only learning management, systems, which are different. Right. They basically say you must take this course, and then you take it, and then it says, yes, thank you, very good, you did that, and here is your score. That's not really what we're looking for here. That can be important as well, and we're still measuring all of that. But what we're looking to see is, did we actually shift the workforce behavior and develop capability in our workforce? So, that Learning Record Store is though it stores all of those XAPI statements and that's something I'm really important to consider.
The final piece I'll talk about is for those of you that are deploying augmented reality on headsets or VR, virtual reality, which seem to be very popular at this point. The one thing I would urge you, if you've got different providers that are working on those, think about getting a portal to bring all those things together so that you can standardize what the data is that you want out of those. And actually, you know, get the good, rich information that you need from them. They're very virtual reality, in particular, is very expensive. And so without actually seeing your return on investment there, it's difficult to decide what to do next with it. So there, there's lots of great technology around that, too, if you already have a bunch of those experiences where you can pull them all together in one place to be able to see them and action them and actually know if they're, if they're effective and changing behavior or not.
Very good. Very helpful. Laura Pascal has a bit of a challenging question here for you.
And I really like this question, because it goes deeper into the strategic so, and her question is, when it becomes strategic, to change the workforce, rather than investing in developing the workforce. So that's, that's, you know, that's a tough situation sometimes. That, you know, we, we can think altruistically that we can redirect labor, and we can retrain people to do different tasks. And that sounds very good. But there are certain limitations, and there's on doing that. And just your, your experience on the, on settings, where it may be difficult to upskill, do workforce and you may need to replace. So, if you could talk a little bit about the dynamic of developing versus replacing.
Absolutely, and I spoke about that a little bit when I talked about that, that capability driven org or structure, right? Because recruitment is important, as well. one of the things that I found the most amazing around some of this work, which I think I just want to share as an anecdote for you, is when we started to apply AI, to actually look at the concept of related skills.
And what I mean by that is, Jennifer doesn't have this skill, right? And this is a skill we need.
But, what a cluster of other skills that would indicate that that person could potentially accelerate into the skill We need faster.
Fascinating, From an AI perspective. Because, it started, it, actually, starts to give you a different view and say, OK, if I look at this as binary, right, it's either we have it, or we don't, that's one picture. But, how do I look at this and say, wow, here's this, this group? Or, they may even be in a group? These people that are scattered across my organization that are developing at a very rapid rate because, once again, we're getting real-time reads on them all the time, right? And have this cluster of related skills. That would infer that we could, if we wanted to accelerate their development very quickly into the skill that they don't have that, we need that changes a lot from a strategic perspective. Because we know it's very expensive to recruit new Talent, To bring new talent in. And it's very necessary at times, but. where are areas of opportunity in our organization already today? Can we see them?
And my challenge to everyone who can't see them, Can you, Can you look at the scenario I'm talking about and say, OK. We don't have the skill, but all of these people that data's telling us, if we invested, you know, the next month or two in these people, they could already do it.
That gives us a different mix in our recruiting profile, than we would currently see today. We're still to recruit. We absolutely need to. But it may be changes the mix of what we're doing internally, versus how our recruiting, because that organizational knowledge is also very important. Right. And when we bring people in that new, they don't have that organizational context, particularly.
And are more strategic roles, to be able to get up and running quickly. So, just all kinds of things to think about. It's not one or the other, it's the mix, and do you have the right data to inform your strategy with regards to what that mix should be?
And that's my challenge, is, I am not sure that all organizations currently do.
That's, that's awesome. Thank you so much, Jennifer, for sharing your passion, your incredible insights, and knowledge about them, in this area, and we're very grateful for you to, to take the time to share that with us.
Thanks to say, it's been a great pleasure, I can't wait to hear what others are doing, it's, it's really an exciting time to be in an innovation institute and strategic space.
Very much so, thank you, Jennifer.
All right. Ladies and gentlemen, this concludes this segment of oil and gas live. We're gonna see you back at the top at the top of the hour where Rick Highland, the Executive Vice President of our LG International, he's going to discuss capital Project transformation. What do we need to do to change the performance of capital projects? And in a time of great disruption and dislocation and capital, project performance especially mega-projects has been an issue for decades. And could this be an opportunity to significantly change the performance of this projects? And how can we do that? What are some of the approaches that the great, Enduring organizations are, are thinking, strategically about, the most important executing on?
So, I will see you at the top of the hour, and I hope that you have continued to have these great questions for Rick, later on in that segment. Thank you, And I'll see you soon.
Group Head of Strategy & Transformation,
Experienced Strategy & Corporate Development Executive with a track record of delivery across strategy development, business performance improvement, BD and M&A, with a passion for the application of digital technology to enable business performance and for driving renewable technology projects to support the Energy Transition
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