Building a Skills-First Enterprise with Dr. Sandra Loughlin

[00:00:00] Vishnu: Hello, and welcome to Talent Draup, where we bring together minds shaping how talent, technology, and transformation are changing the future of work. I'm Vishnu Shankar from Draup and today's conversation, it's about something every people leader is grappling with right now. How do you build a truly skills first enterprise, not just as a talking point, but as something that actually changes how your staff develop and deliver.

My guest has been doing exactly that at EPAM Systems, a global software engineering firm of around 60- 65,000 people. Dr. Sandra Loughlin is EPAM's chief Learning Scientist, and she has a confession in her own LinkedIn bio. She calls herself a training hater coming from a chief learning scientist at this scale that's either very brave or very important.

I'm sure it's both. , Sandra, welcome to Talent Draup. It's a privilege to have you here. To start this off would be great to know a little bit more about the work you do at EPAM.

[00:01:03] Sandra: Absolutely. And thank you. That's, that's kind of a perfect introduction for me.

So, at EPAM, prior to coming to EPAM, I was a professor at the University of Maryland. In the business school and the education school, and I got to know EPAM — the reason that I came to EPAM was because of exactly what you said, which is the future of organizations and the future of talent is actually on skills and understanding the workforce and sensing what skills you need and what skills you have in the organization. Being able to develop those people, motivate them to learn, put them into the right positions that make sense and deploy them to create business value.

So I came to EPAM because it's the only company that I have ever seen to date that is able to do that and do it exceptionally well, although imperfectly at scale. My job at EPAM is kind of unusual. I try to make what we do internally better, and at the same time the other part of my job is helping clients start to get closer to that thing. So it relates to learning, to data around people, to building systems — organizational systems, operating models, data systems that allow all of that to happen.

[00:03:52] Sandra: Training is different versions of 'I'm gonna tell you something.' And that's what training is. But in reality, people can be exposed to content, they can actually engage with content, and it doesn't stick. We learn most things not from any sort of formal training program. We learn from reflection and practice and feedback and talking to people and screwing up and learning from it. That is just a broken model that has never been true.

[00:06:20] Sandra: The business owns skills governance. We ask the business — the cloud practice or the marketing team — what's happening? What are the skills that are critical for these super important jobs? We bring all the data and people together on a periodic basis and make a bet on what skills will be critical. Then the people organization creates learning programs, hires differently, puts new performance management metrics in place. It is a data-driven, human-owned governance process for the roles that matter.

[00:10:40] Sandra: We have two different things — a denominator and a numerator. The denominator is the expectation for the role. The numerator is the actual skills of the people in that job. You will always have people whose numerator exceeds the denominator. For those people, we want to put them on client projects where they have a skills fit that exceeds others in the same role. You need a really good data infrastructure to get an accurate numerator so that you can flex people where they actually fit best.

[00:13:25] Sandra: This whole skills thing for us started in 1993. EPAM's founders were high-end sophisticated software engineers who think in terms of denominator and numerator. They realized early on this is a data problem — not a technology problem. So they built all of these little platforms to run the business and made sure they all talked to each other, all fed into one data space. The first use case was staffing, then hiring, then learning. The system just evolved — built by software engineers who thought like software engineers about business problems.

[00:17:14] Sandra: The system itself is driving our learning culture — it's not just the people. I can be a manager who doesn't understand how learning works, and most of them don't, but the system corrects for that. The system is looking at a person's skill gaps and feeding them content, but also feeding them real learning opportunities — communities of practice, stretch assignments, conferences, reflection tools. The system itself reflects how learning really works, even though all the individuals in the system don't understand it.

[00:20:11] Sandra: There were two secrets. Secret one: driving a skills-based organization through skills-based performance management. Secret two: this is a data problem. The solution is a data mesh — all data from all systems of record and work, not just your ATS and LMS, but project management systems, staffing systems, systems of work like Jira and GitHub — all feeding into one place with no data silos. And that data architecture must be real-time, event-driven. At EPAM when we hire somebody, the skills profile goes to the LMS which pulls courses for missing skills, puts them into the onboarding program, alerts the manager, and blocks the staffing system from placing that person on projects where missing skills are critical. That's one example of thousands of what you can do when you have all the data in the right architecture.

[00:25:49] Sandra: You don't just ask 'what are the skills for this role?' You first ask 'what does this role do all day long? What are the tasks?' Then you ask what are the skills to do those tasks. That's how you arrive at the skills denominator. Context is also critical — project management in experience design is different from project management in construction or software engineering.

[00:29:58] Sandra: For skills, I think of four buckets: technical skills, professional skills (are you a good teammate, do you know how to manage up), self skills (are you resilient, reflective, empathetic, motivated), and organization-specific skills (do you know how to get things done in this company, our IP, our tools, our workflows). And beyond skills, there are qualities and characteristics — like who is a client whisperer, who do you call when something is on fire. We get characteristics data very differently than we get skills data.

[00:32:45] Sandra: Yes, or at least love learning and understand training. You don't have to hate it. Just don't love it so much.

[00:32:54] Vishnu: It was great having you here, Sandra. Wonderful session. Thank you so much for joining us today.

[00:33:02] Sandra: And thanks for all your awesome questions. It was a real pleasure to chat with you.