Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I have spent 25 years working in Pharma, FMCG, and IT, focusing on talent management, culture transformation, and succession planning. As Assistant General Manager at Viatris, I lead organizational effectiveness initiatives, using Hogan assessments and Belbin team dynamics to build strong leadership pipelines.

I use the ADKAR framework to drive change management, which has increased engagement by 40%. I also apply Generative AI and Power Apps in HR to make coaching more accessible and cut content creation time in half.

 

Q2. In which industries is human capital beginning to show up as a driver of valuation rather than an operating expense, and how is that value becoming measurable?

Industries where human capital is increasingly treated as a core asset—not a cost—include technology (especially AI and SaaS), biotech/pharmaceuticals, professional services, and high-end creative sectors (e.g., gaming, design, advertising). In these fields, innovation, speed-to-market, and proprietary knowledge are directly tied to talent quality.

Organizations are measuring the value of human capital in several ways:

Human Capital Analytics: Linking team composition, leadership quality, and retention metrics to product cycle time, R&D success rates, or customer NPS.

Investor frameworks: Intangible asset reporting (e.g., ISO 30414 HR metrics), ESG disclosures that include workforce stability and upskilling, and inclusion in valuation models like Market-to-Book ratios where >70% of value stems from intangibles.

Patent-to-employee ratios in pharma/biotech, or code contribution velocity in software firms—both proxy talent density.

 

Q3. Where does AI in HR genuinely compound productivity—and where is it still cosmetic automation with limited economic impact?

Genuine productivity compounding occurs in:

Talent intelligence platforms: AI that maps internal skills to project needs (e.g., at Unilever or Accenture), cutting external hiring by 30%+.

Personalized learning at scale: Adaptive L&D engines (e.g., Degreed + AI) that reduce time-to-proficiency by 40% in complex roles like clinical research or cloud architecture.

Predictive attrition + intervention: Systems that not only flag flight risk but prescribe manager actions (e.g., “offer stretch assignment X”)—proven to reduce regrettable attrition by 20–25% (McKinsey, 2024).

Cosmetic automation persists in:

Chatbot-based HR helpdesks that deflect <15% of tier-1 queries.

Resume-screening AI that merely digitizes bias without improving the quality of hire.

“AI-powered” engagement surveys that repackage sentiment data without linking to operational levers.

 

Q4. Across Pharma, FMCG, and IT, where has leadership capability most directly influenced market share retention during periods of disruption?

In the pharmaceutical industry, when pricing and access became especially difficult, Novo Nordisk remained ahead in GLP-1 therapies by empowering leaders across different functions to truly collaborate. Instead of working in isolated teams, people from medical, regulatory, and commercial backgrounds came together, shared knowledge, and problem-solved as one group. This teamwork meant patients in emerging markets could get access to treatments up to nine months sooner than they would have otherwise, putting Novo Nordisk well ahead of its competitors.

In FMCG, Nestlé maintained market share during inflation by giving local leaders the authority to reformulate products with regional inputs, supported by a decentralized decision structure built over many years.

In IT, Infosys and TCS managed the recent cloud transition by quickly reskilling over 50,000 engineers for AI-augmented roles. Leadership aligned learning, delivery, and sales to prevent client losses during this period.

 

Q5. Where have you seen data-driven HR interventions materially reduce costs without eroding future capability?

Pfizer’s internal talent marketplace: Reduced agency spend by $180M/year (2022–24) by redeploying 4,200 critical-role employees from legacy pipelines to mRNA and oncology projects—without increasing attrition, because mobility was tied to career pathing.

Hindustan Unilever’s predictive workforce planning: Used attrition + performance + market data to freeze external hiring in 3 support functions, instead rotating high-potentials through “capability tours”—cut FTE costs by 12% while increasing readiness for digital roles by 35% (internal audit, 2023).

Microsoft’s skills-based org redesign: Replaced 30% of redundant roles via AI-augmented role carving, but mandated 80-hour upskilling for affected staff—leading to 92% internal redeployment and zero loss in innovation pipeline velocity.

 

Q6. Which HR-led transformations meaningfully increase a firm’s ability to absorb AI-driven disruption without talent flight?

Successful HR-led transformations have three key traits:

First, companies like Siemens have built dynamic skill maps that show employees how their current skills align with new AI-driven roles. This transparency helps reduce anxiety.

Second, at Adobe, HR and engineering teams worked together to redesign creative roles with AI copilots, involving frontline employees in the process. This approach ensured that work remained meaningful.

Third, Ericsson’s Talent Shift program gives employees affected by AI changes the first opportunity to move into reskilled roles, supported by a six-month upskilling stipend. As a result, voluntary attrition fell by 40% after the AI rollout.

 

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

I would ask senior management to explain how their people strategy not only supports the business model but also strengthens competitive advantage in a rapidly changing environment. With code easily copied, patents expiring, and pricing power shifting, the real differentiator is how talent adapts and applies knowledge faster than others. I would look for data that links internal mobility rates to product innovation speed, or shows how leadership pipeline depth predicts client retention during technology shifts. If there is no clear connection between HR metrics and business resilience, then the talent strategy is just a cost center.