Episode 211: Building a Skills-Based Organisation: Lessons from a 30-Year Journey (Interview with Sandra Loughlin)
What can we learn from an organisation that has been a skills-based pioneer for over 30 years? At EPAM Systems, building a future-ready, skills-based workforce has been a foundational strategy, positioning the company as one of the most mature examples in the field.
In this episode of the Digital HR Leaders podcast, David Green is joined by Sandra Loughlin, Chief Learning Scientist at EPAM Systems, to discuss the lessons EPAM has learned over its decades-long journey and how organisations can apply these insights to their own skills transformations. Together, they dive into:
The structure and strategy behind EPAM’s skills-based evolution, shaped by 30 years of experience in skills management.
Common myths around skills-based organisation.
The importance of defining the work itself before pinpointing necessary skills.
Practical guidance on selecting the right technology to support skills-based practices.
Approaches to validating skills data, moving beyond self or manager assessments to more reliable data sources.
Insights on tailoring a skills strategy to different industries and functions, and determining when high-quality skills data is a must.
This episode, sponsored by TechWolf, is essential for HR leaders seeking to drive business impact through robust skills data and build a truly future-ready workforce.
TechWolf is an AI-powered solution focused on one mission: delivering reliable skills data for every role and every employee in your organisation.
With TechWolf, companies like HSBC, GSK, IQVIA, Workday, and United Airlines have accelerated time-to-hire by 32%, boosted internal mobility by 42%, and saved around $1,000 per employee annually on talent management.
Visit techwolf.com for more information.
Learn More:
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[0:00:00] David Green: In our 2024 research on Building the People Analytics Ecosystem at Insight222, we found that the skills-based organisation was one of the key factors driving the continued growth in people analytics. Indeed, we found that 50% of people analytics teams are supporting their company in their efforts to become a skills-based organisation. This perhaps isn't surprising given that skills data, and to be more precise, the quality of skills data, is a foundational element of the value proposition for the skills-based organisation, and arguably the most difficult component of a successful skills transformation. On the Digital HR Leaders podcast, we've had multiple organisations discussing their journeys and how they're currently navigating their way through it. But today, I'm extremely excited to bring you an organisation that has been a skills-based company for over 30 years.
My guest today is Sandra Loughlin, Chief Learning Scientist at EPAM Systems, and she will be discussing what a mature skills-based organisation actually looks like in practice. In our conversation, Sandra and I will debunk some common myths about skills-based organisations and explore the foundational steps companies should take when starting on their own skills journey. And of course, it wouldn't be the Digital HR Leaders podcast without discussing practical considerations, like technology selection, skills validation, and how to tailor a skills strategy across various functions and industries. So, whether you're just beginning your journey towards a skills-based model or looking to refine an existing strategy, this episode is packed with actionable insights to help you build a future-ready workforce. So, without further ado, let's dive into the conversation with Sandra Loughlin.
Sandra, thank you for joining me today. To start the conversation, please can you share a little bit about your career journey and your role at EPAM Systems?
[0:02:07] Sandra Loughlin: So, prior to coming to EPAM, I was a professor actually at the University of Maryland here in the US. My background is in learning science, so the psychology of learning, motivation, cognition and so on, as well as organisational psychology. So, prior to coming to EPAM, I actually taught courses and did research and was looking at the future of bridging the gap between university and work. As part of that, I actually got to know EPAM. I started out as a consultant to EPAM on the side, looking at their learning and talent approach because for years, clients had been telling EPAM leadership that their people were somehow very special and different. And clients kept saying like, "What's your magic? Do you have anything that you can share?" And EPAM, I mean they built everything themselves, and they didn't quite know. So, they said, "Hey, can you come and look". And so, amongst other things, I discovered this amazing organisation that does skills and data exceptionally well, and learning programmes as well. And so, I left my wonderful, lovely career in academia to join EPAM to do two things.
So, one is to actually continuously improve all of the different people-related approaches, tools, processes that we have in the organisation; and the second is to take the best of the best and turn those into solutions for clients. So, I'm internally- and externally-facing. Depending on the year, I'm more or less of one, but I have this very unusual very exciting job at a company that is, I think, breaking a lot of ground in this space.
[0:03:51] David Green: What I love about the story at EPAM, and you kind of put hints of it there, is it's probably one of the longest examples I've come across of a skills-based organisation. Correct me if I'm wrong, but EPAM has been on the skills journey for around 30 years. So I'd be interested, obviously coming into EPAM systems now, what does the skills-based organisation look like at EPAM?
[0:04:16] Sandra Loughlin: It's how we do business. So, at the foundation of everything in our organisation are data around skills and work. And again, we've been organised that way, collecting those data for 30 years, but we use those data to make decisions across the board in pretty much every facet of what we do. So, we use skills and work data to hire, to staff, to manage performance; we use that to optimise our operations in the organisation; we use it to design effective learning programmes; we use it to incentivise people to learn through skills-based performance management. It is the nature of how work gets done. And I mean that not just in the people organisation, but in the business. It is just the foundation for decision-making, for forecasting, for everything. It's funny because it's so built into the culture here that when I first came and was trying to explain to EPAM leadership, "This is very unusual, very exciting", they just didn't believe me, because they said, "It's not possible that we're different. How does any other organisation make decisions?" And I'm like, "Well, I don't know, but they do, without all of the incredible data that you have".
[0:05:34] David Green: There are a lot of opinions around skills-based organisations. A lot of consultants obviously have got wonderful processes and methodologies on how organisations could do this. There's a lot of technology in the space now as well. And certainly when I go to conferences, the two topics I hear about are skills and AI, and I suspect that will be the case next year as well. So, I'd love to hear from you, as someone that's actually working in an organisation that's doing this, what are the most common myths that you hear about what people think a skills-based organisation actually is, and maybe you could tell us about some of the stuff that it isn't as well.
[0:06:15] Sandra Loughlin: Yeah, so I mean there's a few. So, yeah, the one that always first comes to mind is the idea that if you're a skills-based organisation, you no longer have jobs, like it is a future without jobs. And that is, at least in our experience, very much not the case. There are a lot of reasons for jobs to continue to exist. The difference in how we approach jobs and what is traditionally done, is that jobs are traditionally defined top-down and they're very rigid. So, you build a box, you name the box, you put skills and tasks in the box, then you put people in the box and assume that anybody in the box has those skills and can do those tasks. But of course that's not actually true. And then it creates a host of assumptions, built on assumptions, creates a lot of error and confusion in the space.
The difference is that we take a bottom-up approach, a data-driven approach, to job definition. So, we have jobs, but we identify those jobs by finding naturally occurring clusters of tasks, work that gets done, and that from a data perspective, they do cluster. And very happily, people that have the skills to do those clusters of work also tend to cluster. And so you have, if you just opened up your crayon box, you threw the crayons on the ground, you could actually find nice, clean patterns of colours that we would consider jobs. So, we find the naturally occurring things, we build a box, we name the box, and we are able to then evaluate, and on an ongoing basis, the degree to which that box, that job is still relevant. Are those tasks still clustering? Are the people that can do those tasks still clustering? And so, it's a different way of thinking about jobs, but we still have to have them. So, that's one of the, I think, biggest myths that I hear.
The other ones that I'm not sure they're myths, but I think they're misconceptions. So, the biggest one is that people don't often think about skills and tasks in terms of data, but these are just data constructs. They're nested, you have different levels of granularity, data quality becomes a huge issue. So, thinking about this whole construct from the perspective of data I think is extremely clarifying, but it's not what a lot of, at least in my experience, the conversation is focused on. And it needs to be because it is data, and it's very important to get the data right and understand that it is using data to inform business decisions across the board. That's really what skills are and tasks are the same.
Another, I guess, misconception is that this is an HR problem, and it's not, right? Skills, if you think about a workforce, right, that is the engine of any business, human capital. And the degree to which the human capital is aligned to the business strategy from a skills perspective, from a structural perspective, from a mindset perspective, that's a business problem, because if you don't have that, then you're not able to fulfil your business objectives. And so, something that I talk about a lot and really try to emphasise is the fact that in, well, at least at EPAM, right, in our skills-based organisation, the business is the driver and the owner of the alignment of skills to the business strategy. HR and the people organisation are a critical mechanism by which all of that happens, but they don't own it, it's not their sole problem.
[0:09:42] David Green: This episode of the Digital HR Leaders podcast is sponsored by TechWolf. TechWolf is an AI-powered solution focused on one mission, delivering reliable skills data for every role and every employee in your organisation. While companies often spend over 18 months identifying skills, surveying employees, and mapping them to jobs, TechWolf provides all that in a matter of weeks, without disrupting the business. As skills constantly evolve, TechWolf also provides the tools to help you continuously manage the change, and enable you to apply that data to real-life use cases. With TechWolf, companies like HSBC, GSK, IQVIA, Workday and United Airlines have accelerated time to hire by 32%, boosted internal mobility by 42%, and saved around $1,000 per employee annually on talent management. Ready for tomorrow? Talk to TechWolf, visit techwolf.com.
Certainly a lot of the organisations I speak with, big global organisations in the work that we're doing at Insight222, they get the why of a skills-based approach. Where they struggle a little bit is with the how. What would be your guidance to those organisations that are maybe starting on their skills journey to set themselves up for success?
[0:11:26] Sandra Loughlin: I'll actually have to ask them, do they really know the why? Because a lot of the times I hear, "Well, we're trying to optimise internal mobility [or] we're trying to optimise hiring", and those are all fantastic things, but that, to me at least, is not the why. The why is business agility play. Again, if people are the engine of business, people have to be tuned to your strategy. And as your strategy changes, as technology evolves, as your competitive landscape evolves, you need to continually understand who you have in the organisation relative to the work that needs to get done. So, I would start by figuring that out, because a lot of companies, I think, still think about skills from the perspective of optimising HR, as opposed to optimising business. And so, I would love to actually sit down and say, "Okay, well, what are your big reasons?" because it's probably going to have something to do with AI-enablement, or digital transformation, or moving into a new sector of industry. And being able to articulate the value of skills for agility, no matter what you're doing, but then very specifically for whatever that strategy is, that to me is the starting point.
Then from there, you really want to understand, what is your operating model as a skills-based organisation? Who does what? What is the role of the business? What is the role of the people organisation and the sub-functions underneath that? What is the architecture, from a data and technology perspective, that's required to actually allow this stuff to happen at scale? What are the roles that you're going to focus on? Because at least from our point of view, being a skills-based organisation is not an all or nothing proposition. It's expensive. It's expensive to collect and validate skills data and constantly keep that up, from a governance perspective and from a data perspective. It's not worth it to do that for every role. So, being able to think about the roles in the organisation that are most valuable to focus on, not just initially, but in the long term, what are the roles that are closest to P&L? What are the roles where, if people don't have the skills, you're actually exposed from a business perspective, either from a risk perspective or a cost or revenue perspective? Then, at least everybody has an idea of, in theory, what is it going to take to get here? And then you can sit as a business and say, is it worth it, or which parts of it are worth it? Where should we start? Where does this make most sense?
[0:14:01] David Green: I mean, let's talk a little bit about, let's do the data and technology piece then. What are some of the data sources that a company is going to need to do this effectively, because they're not all sitting in our HR systems, are they?
[0:14:16] Sandra Loughlin: No, and that's a big problem, right? So, you know when you start thinking about not just defining what the skills are, but defining what is the work to be done and verifying when someone has skills, that really starts to require data from systems of work. So actually understanding, you know, your ticketing systems or GitHub or all the different places where work really happens, those are places where signals around skills and tasks need to be supported. And that means that that needs to be integrated with your foundational data in your HCM and your ATS and your learning system. Really, it's everything. Because if you think about all the systems that people touch or touch people, that's the full set of data sources that need to be integrated. And so this is why I think of this as like, this is not a small problem.
What's super, I like about this space though, is that this is a problem that every business has and every business has been trying to solve. Data silos is a huge issue for not just people, for everything. And so, being able to tie the people use cases to an already awareness of a problem that needs to be solved, like essentially adding more fuel to the fire of, "We need to solve this thing", really helps to get that investment to drive forward the data integration and coordination orchestration activities that are, I'm sure, underway in every organisation today.
[0:15:51] David Green: You've mentioned a couple of times now, start with defining the work that needs to be done. Could you share a little bit more about this approach and why it's a critical first step in building that data-driven skill strategy?
[0:16:07] Sandra Loughlin: Yes. So, at EPAM, we have this tool that has been sitting at the foundation of our skills ontology, and it's a task intelligence tool. So, basically what it does, it used to be done by hand, now it's done largely by AI, is look at a role or a position, or whatever, and break that down into what are the major tasks, so what are the activities, what are the deliverables, right? You can do this at different levels of granularity, like let's take a role and say, what are the top 30 tasks, right? Each one of those tasks, in theory, you could make 30 steps underneath each one, but at the highest level, you're thinking about what are those things that need to get done, what is the work to be done? This is very, very important for a lot of reasons. One is because when you're thinking about what skills the company needs, it really should be connected to the skills required to do those tasks. So, that starts with the foundation of your denominator, if you will, of a skills-based organisation. The denominator is the skills the company needs; that comes from tasks. The numerator is skills the company has; that comes from any individual. So, that lays a foundation.
But it's also very valuable in a world of AI and automation. Because when you think about, what is the impact going to be of AI and automation on the workforce, AI is not impacting skills, it's actually doing tasks. And so, if you have this task intelligence foundation and understanding the work to be done, you're actually able to have a much better idea of where you're going to expect to see AI and automation having an impact, so that's really helpful for the business. But it's also very helpful, because if you have five or six roles, some subset of each one of those roles is going to be taken away, the tasks will be done now by technology. Now you have a bunch of incomplete roles. But having that task intelligence in the organisation is a game changer for understanding the needs of the organisation and setting the foundation for agile job and organisational structure design.
[0:18:19] David Green: We hope you're enjoying this episode of the Digital HR Leaders podcast. If you are looking to continue your learning journey, head over to myHRfuture.com and take a look at the myHRfuture Academy. It is a learning experience platform supporting HR professionals to become more data-driven, more business-focused, and more experience-led. By taking our short assessment, you will see how you stack up against the HR skills of the future. Then, our recommended learning journeys guide you every step of the way, helping you to close your skills gap, deepen your knowledge, and press play on your career.
Rather than naming any names, what's the sort of technology that companies should look to either build or buy to support their skills-based work?
[0:19:23] Sandra Loughlin: Well, this is a big challenge, because there's a shift that I think is going to be happening in the HR tech space. So, in every other tech stack, you have these things called monoliths, like these big, big, big, huge, massive technology infrastructures, and those have been the standard for a very long time. In every other area, there's a movement, it's called strangling the monolith, but you're trying to actually break out this one massive tool into smaller tools, because it's cheaper, it's faster, they can innovate better. It's very, very different. And when you do that, the tools actually, you sort of think of them less as tools that you interact with, and more as data sources that talk to each other and give you insights, and then you can make actions around those. This, I think, is what's going to be happening relatively soon in the HR space.
So, right now, in any organisation, you have your HCM as a foundation. And increasingly, you have all these other tools that are skills-based to do very better point solutions. As I said earlier, the problem is that all of these things don't talk to each other. The data are structured differently, your ontologies are very different. And so, what you're getting is a system that, again, is maybe, maybe, optimising decision-making around skills, but only in verticals, and there's no coordinated effort around that.
If I were investing in technology on the HR tech side, I would be putting a pause on finding new point solutions and I would be -- oh, and by the way, this space is about to change really fast, so there's going to be a lot of acquisitions and a lot of dynamism in this space for the next couple of years. If I were a buyer, I would stop buying stuff for a little bit and I would look for data-only solutions. So, this would be investing in data layers, like analytics layers, investing in cleaning up the data, like getting it coordinated, putting it in the same systems. I would be investing in using existing sources, but building an ontology of tasks and skills that is specific to my organisation. There's going to be like 80%, 90% even, something from the market, but taking the energy and time to work with the business, with your SMEs to tailor all of those to make them specific to your organisation. I would be investing in middleware players that are just pulling signals from different systems of record and work, and coordinating all of those.
That's where I would be spending money today, as well as if I had the budget, actually buying systems that help me validate skills at scale, while I wait for this space to calm down. Because what I suspect is going to be happening is there's going to be a tremendous movement and a new set of tools coming out over the next couple of years that are going to actually just make all of this data sing. And instead of trying to optimise more in the point solutions, laying the foundation, getting the business on board, building the business case, and waiting for that future to come, because then you can actually hit the ground running and start getting a lot of those insights and actions that are not really possible to do today at scale very quickly, which will then help accelerate the transformation for your business.
[0:22:52] David Green: And then that leads on quite nicely to this question, you mentioned the technology function in companies particularly wanting to do this because they need to, basically. So, I'd like to expand that a little bit. How does the way that an organisation approach skills vary from industry to industry, and then functions within those industries as well?
[0:23:18] Sandra Loughlin: So, this goes back to the idea that there's differential ROI for investments in skills, intelligence and infrastructure. There are, in every company, I believe, there are roles where -- so let me step back. I think that every company is going to ultimately become skills-based, but not every role in every company will be. So, for any organisation, again, thinking about what are the roles that are closest to P&L, focusing on those. In a company like EPAM, we're professional services, the majority of the work that we do is done by software engineers, data scientists, AI experts. Those are the people, those are the roles where we need to have very high-quality skills data, because if we are mismatching people to work, if we don't have the right people in the right roles, it's a problem; we're going to lose revenue, we're going to lose clients, our business will suffer. Other organisations are going to have those same, exact importance of roles, but in different locations. It could be customer service, it actually could be product design. It just depends on the different industry. So, thinking about where you're going to get the most value from this investment, it needs to happen.
Then across industries, that's going to be a mega trend. Professional services, one of the reasons that everybody in professional services is on this skills train is because they sell people, that is the nature of the job. And so for a company like EPAM, we're going to have the vast majority of our employees we need to have super-high-quality skills data on. If I am in a different industry, I'm still going to have certain roles, but those roles are likely to take up less of the total population of the organisation. It's just the nature of business should dictate where you're spending your energy and money around skills and task infrastructure.
[0:25:23] David Green: So, to listeners that are thinking, "Okay, I definitely want to invest more in this. I'm listening to Sandra, I'm really fired up now, I've thought about a couple of areas in my business where I can maybe apply this", what are some of the benefits or some of the value that you get at EPAM from being a skills-based organisation?
[0:25:41] Sandra Loughlin: This is such an easy and hard question to answer. So, let's start with the hard part. The hard part is that unlike every other organisation, we don't have a transformation story. It isn't as though I can say, "Prior to skills, here was our time to hire. Prior to skills, here was our attrition rate. Prior to skills, here whatever", because we just evolved. I mean, for 30 years, we've been just doing this and getting better and better and better at it. So, I don't have that super-clean use case to say, "Here are the benefits". I can tell you what we are confident are the benefits without having the data to back it up. The most important one is that it's a business agility issue. Again, for us certainly, we're a technology organisation, we've transformed our core business four or five times. We're doing it again right now with AI.
The reason that we've been able to do this as well as we have, and continue to grow like wildfire at the same time, is because we do skills-based performance management, meaning that skills data -- if you can do the skill or if you can't do the skill, that actually impacts the degree to which you can keep your job or grow in your career. This builds this massive incentive structure and motivation for people to continually upskill. That is the secret to being agile as a business. Being able to say, "Okay, as a business, we need to move in this new area. Here are the tasks that need to be done differently, here are the skills to do them, here are the gaps that any one individual has. Okay, go close those gaps". Being able to do that on the fly in a relatively quick fashion, that is what, in addition to all the other things, being skills-based has given us. Plus, of course, then you have people at EPAM, I think we're like double -- our retention rate is double average, our tenure is more than double the average in our industry, our employee engagement scores are through the roof.
In addition to all of that, we believe that people come to EPAM, stay at EPAM, thrive at EPAM, in large part because of our skills-based approach. But we don't have a perfect AB case to share with the market. But if you ask our CEO, who is the biggest champion for all of this, that's what he would say. It's the ability to be agile as a business, and attract, develop and retain some of the best technology talent in the world in a highly competitive market.
[0:28:21] David Green: Two final questions before we get to the question of the series. One is around data. You wrote a great article, actually, which I'd definitely recommend listeners check out on your LinkedIn profile, around data quality, because you've actually said that this is a data problem that needs to be solved in order to help you get the outcomes that you want. Can you talk to that a little bit, about some of the -- what are the elements of skills data that are important for an organisation to focus on?
[0:28:49] Sandra Loughlin: I'll give a few examples, right. So, when you're when you're thinking about what skills you need for any job, there's always a question of like, "Well, how many should we define? Should it be 10 or 100?" To me this is a variance-explained issue. In any role, a certain set of skills or tasks is going to explain a certain percent of the ability to get that job done. And so, let's say you can hit, I've explained 85% variance with ten skills. You can add 100 more skills, and you can only get yourself up to, I don't know, 92%. Diminishing returns exist. So, being able to really think about what are we trying to accomplish? How much information do we need? What is the most valuable, yet parsimonious data model, from a skills perspective, that's going to help get us the insights that we need to get the work done?
Another one goes to, again, how do you know if somebody actually has that skill, right? This is where you're talking about the longer-term play around having validation around skills data. But at EPAM, we use skills data to inform very high-stakes decisions, but we also have very good quality skills data. And so, we get that by having lots of different data sources, lots of different data from different points in time, in different contexts, really thinking about every sort of -- we are trying to measure latent constructs. It's very difficult to do. You need to have lots and lots of data sources to get strong signal from noise. And so thinking about the longer term, having a bunch of those data sources so you're collecting a lot of data in a lower-cost way, and then actually thinking about how you're weighting the data sources so that you can prioritise the most high-quality ones.
Other data elements to think about are the timeliness of the data. Just because I had a skill five years ago, I haven't used it, is that skill relevant? Probably not. So, thinking about that, thinking about skills in terms of clusters of data, understanding distance between skills, that you can actually recommend certain skills based on others. There are so many, many data elements to think about when considering skills. I don't say this to turn people off to the concept, just to say that there are experts, there are data experts who can help with this. People leaders, analytics leaders, need to understand the complexity of the data around this, not to scare people off, but to really underscore the importance of thinking about data from a quality perspective, because you need to have good quality to make high, important, and critical business decisions.
[0:31:46] David Green: As a clear leader in the field, what are some of the most surprising insights or lessons you've learned from having this skills-based approach?
[0:31:54] Sandra Loughlin: The biggest thing is how lacking it is in so many organisations. Again, when you think about all the data that organisations have, they have tons of data on their customers, they have tons of data on their products, because they recognise the value of data to make valuable decisions about those things. What's been remarkable to me is appreciating the not complete lack of data, but we have so much less data around people, even though people are, in most organisations, the biggest cost, and certainly a huge reason or the mechanism by which you can achieve your business strategy. And so, I think that one of the biggest things that I have learned being in this space is that the people that tend to care about people are less comfortable with, aware of, and driven toward making data a core part of understanding and decision-making in their space. And so, I guess I would say it's been the most eye-opening thing, is appreciating that my orientation toward data is not normal, and seeing how hungry organisations are to understand how to do that better. And also, seeing the super-cool emergence of tools to help in this space. It's been eye-opening and I'm also very excited that I think in the next couple of years, we're going to get a lot better a lot faster, because of renewed interest and support for data-driven decisions in the people space.
[0:33:36] David Green: And of course, a lot of the time we do have this data, we just don't use it or we can't access it, or sometimes the quality leaves a little bit to be desired. But yeah, a lot of the times we do have the data, sometimes we don't know where to find it, and that's the other thing. And I guess the challenge with skills is you're potentially having to integrate data from lots of different sources, both under the auspices of the HR function and obviously out in the business as well, and probably external to the organisation as well, which actually sets us up quite nicely for the question of the series.
So, this is the question we're asking everyone in this series of the Digital HR Leaders podcast, and it hopefully is quite an easy one for you actually, Sandra. How can organisations leverage skills intelligence to make more informed decisions?
[0:34:25] Sandra Loughlin: Well, collect good data! Collect good data and then understand and build an operating model where it is expected that those data are going to be analysed and used to inform decision-making. Again, this can be done with tools, it will definitely have to have some governance involved. But I think that the number one walking-away point is, there's a need for skills intelligence. The sources do exist. They're not going to be perfect, but they're good enough. Marry that with intelligence on tasks, and then just think about operating as a business in a world where you have excellent access to data and can use that access to understand the problem space, weigh options, and then apply and then see how well your interventions have worked.
[0:35:18] David Green: And actually sort of a follow-up question, Sandra, because I haven't really talked about it yet, about external data to support skills strategy. What would be your guidance around that and what external skills data, for example, do you bring into the mix at EPAM to help you?
[0:33:37] Sandra Loughlin: So, we do, of course, a lot of workforce and analysis, so we have data just like many other data sources looking at what are the job postings, what are the skills that are required, what are trends in the space from a skills perspective, compensation-related, you know, all the workforce-related stuff. We're also looking at external data even on our existing people. What are they doing? What are their public appearances? What are they writing about on LinkedIn? Those are external data sources that we pull in a lot. And we are also pulling in data sources that I guess are external, I don't know, where we have clients who are requesting stuff from us. So, that's another source that we're pulling in to understand what is all the nature of the work to be done. And very importantly, we have data sources where we're crowdsourcing projections, like forecasting, what are the trends, what are the skills, what are the things that we think are coming down the pipe.
Bringing all of those data sources together, along with a ton of stuff coming from inside the organisation, is a massive effort, but it is the best way for us to have the closest thing to a crystal ball to be able to look into the future, assess our current state against that and make decisions.
[0:36:59] David Green: Great, thank you for sharing your knowledge and expertise and guidance really for listeners around skills. I mean, it really is truly impressive what you've done, what EPAM's done over the last 30 years, I think. And I suspect we'll be hearing a lot more from you at conferences and the like coming up. I definitely recommend people follow you on LinkedIn. But are there any other ways that people can stay in touch you, Sandra, or learn more about the work that you're doing at EPAM?
[0:37:28] Sandra Loughlin: Yeah, just reach out. I feel like I spend half my life talking about this because it's a passion area of mine, so I do talk about it on LinkedIn a lot. You can always reach out to me. And yeah, I'm starting to go to conferences. So, come check, come look, come find me and we can chat. But I'm always happy to talk more about this.
[0:37:47] David Green: Well, I look forward to seeing you at a conference in the not too distant future, Sandra. So, take care and thank you very much for being a guest on the show.
[0:37:55] Sandra Loughlin: Thanks for having me, this was super-awesome.
[0:37:58] David Green: What an inspirational conversation into the workings of the mature skills-based organisation. Thank you again, Sandra, for joining me today and sharing EPAM's journey for others. Your insights into EPAM's 30-year evolution as a skills-based organisation were truly eye-opening. If you enjoyed this episode, please subscribe and leave us a five-star review on your favourite podcast platform. And if you would like to stay connected with us at Insight222, you can follow us on LinkedIn, visit our website at insight222.com, and sign up for our weekly newsletter at myHRfuture.com. That's all for now. Thank you for tuning in and we'll be back next week with another episode of the Digital HR Leaders podcast. Until then, take care and stay well.