As a data leader, one of your most crucial decisions is how to structure your team. Should you centralize for consistency, embed for domain expertise, or find a middle ground?

In this episode of More than Numbers Live, Ollie Hughes sits down with Lydia Monnington, Data Science Lead at Google DeepMind, to explore this perennial challenge facing data organizations of all sizes.

With experience leading data teams at Meta, Ocado, Stuart, and now Google DeepMind, Lydia brings practical insights on what works (and what doesn't) when organizing data professionals. She breaks down the evolution of data team structures and provides actionable advice on making the most of your talent—regardless of your current setup.

In our conversation, Lydia shares:

• The natural evolution from centralized to embedded teams and the pitfalls to avoid in each model
• Why a matrix/hybrid model often delivers the best results and how to successfully implement it
• Practical approaches to managing specialized roles like data engineers, analysts and scientists
• The critical importance of establishing strong relationships between your data team and business stakeholders

Whether you're managing a small centralized team, leading embedded analysts, or navigating the complexities of a hybrid structure, this episode offers valuable frameworks to make your data organization more effective.

• [01:10] Lydia's journey from financial modeling at Citigroup to data science at Google DeepMind.
• [03:45] Inside DeepMind's data challenges: from fusion to forecasting typhoons.
• [05:29] How a 15-person central team supports DeepMind's data-intensive organization.
• [07:32] Common misconceptions about "perfect" data in big tech companies.
• [10:56] The evolution of data team structures: from centralized beginnings to embedded specialists.
• [12:08] Why centralized teams often become bureaucratic "data factories" as organizations scale.
• [15:00] The potential pitfalls of fully embedded teams: inconsistent tooling and duplicated work.
• [18:30] Matrix/hybrid structures: getting the best of both worlds with the right relationships.
• [22:20] Practical steps to move toward a hybrid model from either extreme.
• [25:40] How to approach structuring specialized roles like data engineers vs. analysts.
• [29:24] Lydia's career-defining advice: focus on outcomes and the "why" behind your analysis.

👋 Connect with Lydia on LinkedIn

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Is your business drowning in dashboards but still lacking clear insight? The solution might not be more reports, but a better way to organize what you already know.

In this episode of More than Numbers Live, Ollie Hughes sits down with Callum Ballard, Analytics Director at Omaze, to discuss how metric trees can transform business clarity and decision-making.

Omaze, the UK-based charity prize draw platform that offers multimillion-pound houses as prizes while raising millions for charity, has mastered operational clarity through a mathematical approach to metrics. Callum shares how his team built a comprehensive metric map that allows the entire organization to understand how different KPIs connect to drive top-line results.

In our conversation, Callum breaks down:

• Why traditional dashboard approaches often lead to metric overload and misplaced priorities
• How a mathematical breakdown of metrics creates a common language everyone can understand
• The process of building your first metric tree and proving its value to stakeholders

Discover how this powerful visualization technique can cut through the noise, reveal hidden opportunities, and ensure your team focuses on the metrics that truly matter.

• [00:01:38] Inside Omaze's mission to make dreams come true while raising millions for charity.
• [00:04:11] Omaze's modern data stack: Snowflake, Tran, dbt, Count, and ThoughtSpot in action.
• [00:05:41] How Count and ThoughtSpot complement each other for different analytical needs.
• [00:09:57] The pain of operational confusion: metrics without context create noise.
• [00:12:00] Convincing the business to embrace structured metrics through real examples.
• [00:15:12] Why teams get fixated on low-impact KPIs without proper context.
• [00:17:48] Translating improvements in any metric to top-line impact for better prioritization.
• [00:19:23] Starting small: how to apply the metric tree approach at different business levels.
• [00:21:23] First steps to create your own metric tree using metrics you already have.
• [00:24:01] How mathematical breakdowns can surface KPIs you never thought to track.
• [00:29:09] Using statistics as a foundation for navigating AI hype and delivering real value.
• [00:31:00] Leveraging metric trees for structured brainstorming and identifying high-impact ideas.

👋 Connect with Callum on LinkedIn

🔗 Learn more about Omaze

😍 See Count’s metric tree example

🔥 Build your own with a free Count account

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The best data teams don't just provide reports—they uncover insights that drive real business value. But how do you transition from being a dashboard factory to becoming a strategic problem-solving engine?

In this episode of More than Numbers Live, we dig into the answer. Ollie Hughes sits down with Jimmy Mogrip, Global Director of Insights and Analytics at Podimo, to discuss how his team focuses exclusively on generating actionable insights that move the business forward.

In our conversation, Jimmy breaks down:

• Why Podimo separated its data functions into three specialized teams: AI, Business Intelligence, and Insights & Analytics
• How his insights and analytics team is able to focus solely on solving high-value business problems
• The workflow for identifying opportunities and turning data explorations into actionable recommendations
• Why soft skills like problem translation and data storytelling are more valuable than technical abilities when hiring for insights roles

Want to learn how Jimmy’s team at Podimo have mastered the art and science of data-backed problem solving? Don't miss this episode!

What you'll learn

• [01:04] Jimmy's unexpected journey from behavioral science and communications into data analytics
• [05:01] Inside Podimo's Google-heavy data stack: BigQuery, Looker, dbt, Python and R
• [06:48] How Podimo structures its 20+ person data team across three specialized functions
• [09:11] The origin story of the dedicated Insights & Analytics team and its focus on recommendations
• [11:23] Finding the balance between exploratory analysis and delivering actionable insights
• [16:09] Building trust through embedded analysts and early stakeholder collaboration
• [19:26] Creating metric trees that connect squad-level work to company-wide business objectives
• [22:10] The critical soft skills Jimmy looks for when hiring analytical problem-solvers
• [24:18] Career advice: "A great data scientist never says 'Aha, I found it!' He always says 'Hmm, that's odd.'"

Downloads & links

🚀 Connect with Jimmy Mogrip

🔗 Learn more about Podimo

🚀 Connect with Ollie Hughes

🎙️ Subscribe to More than Numbers Live