What does it take to lead analytics at a truly global scale? In this episode, Amir sits down with Anant Veeravalli, Global Chief Data and Analytics Officer at Media Brands (part of IPG), to unpack how he built and scaled a Center of Excellence (COE) that spans regions, brands, and disciplines. Anant shares the real-world challenges of aligning thousands of data professionals under one strategic vision—and why analytics is far more than just reporting.

If you're leading data, analytics, or transformation work inside a large enterprise, this one is packed with battle-tested insight on structure, talent, AI adoption, and the real work of enabling data to drive business value.

Key Takeaways

A COE must be built around client outcomes, organizational excellence, and scalable innovation—not just reporting structure

True analytics value comes from harmonizing data, tools, and talent while making insights accessible and actionable

A skills-first approach helps align talent to opportunity, enabling flexibility and specialization at scale

AI isn’t just a buzzword—it’s already reshaping content, audience segmentation, modeling, and competitive intelligence

Communication during change is everything. Transparency, context, and repetition are essential to alignment and trust

Timestamped Highlights

03:00 — Why Media Brands needed a global Center of Excellence for analytics

05:30 — How they approached organizational change and stakeholder education

08:50 — Mapping the COE into four key capabilities: growth, audience analytics, data science, and data engineering

11:50 — Delivering flexible analytics support across diverse clients and geographies

15:45 — How AI is driving faster insights, better segmentation, and creative automation

21:30 — The #1 thing Anant would do differently if starting over: communicate the why more consistently and directly

Quote of the Episode

“We overly underestimate the value of transparent communication. If people don’t understand why the change matters to them, they’ll never be aligned.”

Pro Tips

Invest early in an internal asset library to avoid duplicated effort and unlock speed

When hiring, prioritize specialization over generalization—then connect specialists across a shared framework

Don’t just train on AI tools. Raise the entire organization’s AI literacy

Call to Action

Enjoyed this episode? Follow The Tech Trek for more conversations with leaders building the future of tech, data, and innovation. Share this episode with someone navigating data transformation—or connect with Anant Veeravalli on LinkedIn to keep the conversation going.