In this episode of our podcast, Talent Draup, Dr. Sandra Loughlin, Chief Learning Scientist at EPAM Systems and former professor at the University of Maryland, joins Vishnu Shankar, Chief Data Officer at Draup, to challenge one of the most persistent myths in the HR world, that training and learning are the same thing.
Sandra, who once described herself as a ”training hater” in her LinkedIn bio, brings a systems-thinking lens to workforce development. With EPAM's 60,000+ person engineering workforce as her canvas, she unpacks how skills-first thinking, powered by clean data and smart organizational design, can move beyond buzzword status to become the company's actual operating model. From the numerator-denominator framework for measuring skill fit to the data mesh architecture that enables real-time talent decisions, this conversation is a masterclass in what a truly skills-based organization looks like in practice.

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Quotes:

”Training is different versions of 'I'm gonna tell you something.' But that's not how learning works, it's never been true.” – Dr. Sandra Loughlin
”The system itself is driving our learning culture – it's not just the people.” – Dr. Sandra Loughlin
”You don't just ask 'what are the skills for this role?', you first ask 'what does this role do all day long?'” – Dr. Sandra Loughlin

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Moments You Can't Miss:
01:03 – Sandra's journey from professor to Chief Learning Scientist at EPAM
03:52 – Where training ends, and real learning begins
05:46 – Why AI skills demand a new approach to skill sensing
06:20 – EPAM's data-driven, business-owned skills governance model
10:40 – The numerator-denominator framework: baseline vs. actual skills
13:25 – How software engineers accidentally built the perfect skills-first org
17:14 – Why the operating model corrects for managers who don't understand learning
20:11 – The two secrets behind EPAM's skills-based model
25:49 – Why roles must be broken into tasks before defining skills
29:58 – The four buckets of skills and what lies beyond them

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Key Takeaways:

– Training ≠ Learning: Real learning happens through reflection, practice, feedback, and stretch experiences, not just courses or content exposure.
– Start with tasks, not skills: The skills required for a role can only be identified by first mapping what that role actually does all day.
– Skills is a data problem: Without a unified data architecture connecting hiring, learning, staffing, and performance systems, skills-based decisions remain siloed and incomplete.
– Systems drive culture: The right organizational infrastructure reinforces how learning works, even when individual managers don't fully understand it.

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More About EPAM:
EPAM Systems is a global software engineering and professional services firm of approximately 60,000–65,000 people. Known for its engineering-first culture, EPAM has built one of the most mature skills-based talent systems in the industry, connecting hiring, learning, staffing, and performance management through a unified data architecture. Its approach to workforce development is rooted in systems thinking, treating talent as a data problem long before it became an industry conversation.

More on Draup: 
Draup for Talent is a multidimensional labor and market data platform for HR teams that powers use cases across talent intelligence, skills architecture, and work redesign. It is trusted by more than 300 global enterprises, including 5 of the Fortune 10 and organizations such as Microsoft, Pep