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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#skillsbasedorganization #futureofwork #hrleaders #learninganddevelopment #talentintelligence #workforceplanning #skillsdevelopment #hrstrategy #hrinnovation #chieflearningofficer #learningculture #datadriven #hrtech #talentmanagement #draup #hrpodcast #epam #learningatwork #skillsgap #organizationaldesign

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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

In this episode, Vijay Swami sits down with Leonardo’s people strategy leader Vincenzo and digital transformation leader Davide to break down what it takes to retain talent, modernize HR workflows, and scale skills in an AI-accelerated world.

Leonardo shares how employee experience (EX) and self-employability sit at the heart of retention—enabled by hybrid work, flexibility, and lifelong learning. The conversation then shifts to the operating model behind transformation: a fully integrated talent management architecture that connects performance, learning, skills visibility, and continuous feedback across the employee lifecycle.

The leaders also unpack the reality of adoption: why an AI recruiting tool can underdeliver without change management, and why immersive learning (like AR simulations for behavioral skills) can outperform expectations when it helps people become better at their jobs fast.

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Quotes

“Innovation and transformation are not a straight line. Sometimes you have to rethink and reimagine. Learn. Try again.”
“Rather than separate systems, we embed performance, learning, and succession into one talent architecture.”
“In AI recruiting, the constraint wasn’t technology, it was adoption.”

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Moments you can’t miss!

01:01 – AI reshaping early-career learning and apprenticeships
05:34 – Learning in the flow of work (microlearning + champions)
08:50 – Measuring learning impact beyond completion (KPIs + 360 + managers)
11:04 – “Cold feedback” 6–8 months later to validate real impact
12:28 – Compliance vs personalized learning paths and why you need both
15:51 – Accelerating early-career onboarding with checkpoint-based journeys
19:25 – Upskilling across generations using simulations, digital twins, and partners

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Key Takeaways

Retention is built on autonomy + growth
Hybrid work, flexibility, and lifelong learning enable employees to perform and stay.

Integrated talent architecture beats disconnected programs
Unifying performance, learning, skills, and succession improves visibility, engagement, and execution.

Adoption is the real bottleneck in AI HR tools
AI recruiting requires training data, strong inputs (like job descriptions), and change management to succeed.

Immersive learning drives faster behavior change
AR-based simulations can accelerate leadership and feedback skills when the value is immediate and obvious.

Future-ready skills are both technical and human
Leonardo highlights quantum computing and programming, paired with critical thinking and human-machine collaboration.

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#talentintelligence #strategicworkforceplanning #recruiting #skillsstrategy #hranalytics #workforceplanning #employerbranding #futureofwork #aiinhr #aerospaceanddefense

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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, PepsiCo, PayPal, and Moderna.

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More on Leonardo:
Leonardo is a global aerospace, defense, and security company focused on advancing innovation through cutting-edge technologies and transformation initiatives. With a strong presence across Europe and worldwide, Leonardo invests in future-ready skills and talent strategies to stay ahead in an increasingly competitive market.

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Social media:
Vincenzo Cozzolino: https://www.linkedin.com/in/vincenzo-cozzolino-a0887830/
Davide Ambaile: https://www.linkedin.com/in/davideamabile/
Leonardo: https://www.leonardo.com/en/
Vijay Swaminathan: https://www.linkedin.com/in/vijay-swaminathan-a44101/
Draup: https://draup.com/

In this episode, Vijay Swaminathan sits down with Leonardo’s learning and skills transformation leaders Assunta (Suzy) Galasso and Alessandro Venturi to unpack what it takes to modernize early-career development—and enterprise learning overall—in an AI-shaped labor market. Leonardo shares how they’re revamping their professional system to map roles, skills, and evolving competencies, then using AI-enabled analysis to spot emerging capabilities and tailor development programs.

A recurring theme emerges on how learning can’t be extra work. Instead, it must be embedded into day-to-day operations through micro-learning, digital platforms, and on-the-job knowledge sharing—while still maintaining governance and business alignment.

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Quotes

“Rather than considering learning as something separate from work, we focus on integrating learning into the flow of operations.”
“We implemented… ‘cold feedback’… delayed post-training… after six, eight months… to evaluate the real impact.
“Both have their place… standardized compliance-driven training [and] personalized learning are essential for engagement… and developing future capabilities."

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Moments you can’t miss!

01:01 – Using AI to map roles and emerging skills
05:34 – Embedding learning into daily work
08:50 – Tracking learning impact with multi-input metrics
11:05 – “Cold feedback” 6–8 months later to confirm impact
12:28 – Balancing compliance training with personalized paths
15:34 – Strengthening early-career growth with structured checkpoints
19:25 – Upskilling across generations with hands-on learning + partners

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Key Takeaways

Make learning part of the job
Embed upskilling into operations using micro-learning, digital access, and team-level knowledge sharing.

Use AI to keep role/skill maps current
A structured professional system, paired with AI analysis, helps identify existing vs. emerging skills—and tailor development accordingly.

Measure impact beyond completion
Combine KPIs with skill assessments, 360-degree feedback, manager evaluations, and progression tracking—then validate with delayed cold feedback.

Balance consistency with personalization
Keep compliance training standardized where needed, but layer in personalized learning paths shaped by skills, performance feedback, and career goals.

Soft skills are back in the spotlight
Leonardo explicitly ties performance to both what (outcomes) and how (soft skills), evolving leadership expectations as AI changes work.

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#learningstrategy #skillstransformation #corporatelearninganddevelopment #ldstrategy #skillsbasedorganization #workforceskillsmapping #aiinlearninganddevelopment #aiinhr #talentdevelopmentstrategy #earlycareerdevelopment #graduateprogramstrategy #onboardingandtraining #learningintheflowofwork #microlearning #learningexperienceplatform #employeeupskilling #reskillingstrategy #futureofworkskills #learninganalytics #measuringtrainingeffectiveness #performanceandpotential #softskillstraining #leadershipdevelopment #digitallearningtransformation #hrtransformation

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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, PepsiCo, PayPal, and Moderna.

More on Leonardo:
Leonardo is a global aerospace, defense, and security company focused on advancing innovation through cutting-edge technologies and transformation initiatives. With a strong presence across Europe and worldwide, Leonardo invests in future-ready skills and talent strategies to stay ahead in an increasingly competitive market.

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Social media: