From Control to Confidence: The New Era of Investment Data Strategy

In August, industry leaders gathered at The Fullerton Sydney for the 10th Investment Data and Tech Summit – a milestone event marking a decade of evolving conversations around data, technology, and strategy in investment management.

Having attended many of these summits over the years, I’ve seen firsthand how the dialogue has matured— moving beyond the basics of data management toward a future where governance, agility, and transparency define success.

This year’s summit was no exception. It brought together a rich mix of perspectives, practical insights, and forward-looking strategies that reflect just how far the industry has come, and where it’s heading next.

Agility Without Anarchy: The Rise of Federated Models

One of the strongest undercurrents at the summit was the tension between speed and control. Investment firms want to empower teams to innovate, but without creating chaos in their data landscape. This is where federated analytics comes in – a model that combines the stability of centralized governance with the flexibility of decentralized innovation.

In practice, it allows different teams to work with a governed core data set while extending and enriching it in their own environments. Think of it as a hub-and-spoke model. The hub is a governed, read-only core data set—the single source of truth that ensures consistency and compliance. The spokes are the business teams, who can extend and enrich this data in their own environments, using tools like Databricks or Snowflake. This approach allows experimentation and advanced analytics without destabilising the core.

The real value of this model is cultural as much as technical. It signals a shift from rigid centralisation to controlled flexibility. Teams get the freedom to innovate, but within a framework that protects data integrity. Done well, federated analytics accelerates insight generation while maintaining trust—a balance that’s becoming essential in today’s fast-moving markets. In our work with clients, we see this model come to life through our partner ecosystem for portfolio analytics, where a well-governed central hub of investment data – covering transactions, positions, security reference, and pricing – is shared with specialist tools such as FactSet, MSCI, and Opturo. This allows each team to use the tools best suited to their needs, while maintaining confidence in the consistency and integrity of the underlying data.

But agility alone isn’t enough. Without visibility, even the most flexible models can fail. That’s where observability comes in.

This is where federated analytics comes in – a model that combines the stability of centralized governance with the flexibility of decentralized innovation.

Why Observability Matters

If federated analytics is about freedom with guardrails, then data observability is about visibility with confidence. Too often, data pipelines operate like black boxes—opaque until something goes wrong. Observability flips that paradigm by embedding transparency into the entire data lifecycle.

This means real-time monitoring of pipeline health, the ability to trace data lineage from source to output, and integration with incident management systems to analyse any issues arising. In short, observability answers the questions every investment team cares about: Where did this data come from? How was it transformed? Can I trust it?

Why does this matter? Because trust is the foundation of data-driven decision-making. Without visibility, even the most sophisticated analytics can falter under the weight of uncertainty. Observability doesn’t just reduce operational risk, it builds confidence and enables firms to scale their data strategies.

Observability answers the questions every investment team cares about: Where did this data come from? How was it transformed? Can I trust it?

The Cultural Shift: From Projects to Products

Both federated analytics and observability point to a deeper truth: data is no longer a back-or-middle-office function – it’s a product. This requires a fundamental change in how organisations think and operate. If your architecture isn’t designed to produce data as a product, microservices¹ offer a way to create modular, right-sized components that align with your operating model.

Instead of treating data initiatives as isolated projects, they are now foundational to almost every business transformation. This requires cross-functional collaboration between data, technology, and investment teams. It involves embedding governance directly into workflows rather than applying it retrospectively. It also means fostering purposeful experimentation—where pilots are time-boxed, learnings are captured, and successful ideas are industrialised.

Several panelists and attendees brought this to life when discussing their unique journeys toward a Total Portfolio Approach. Many shared how they’re rethinking the role of data—not as an “IT project,” but as a product that underpins strategic decision-making. This shift was echoed across multiple sessions, with strong views that subsets of data should be treated as products in their own right, tailored to specific business needs and embedded into operational workflows.

Many shared how they’re rethinking the role of data—not as an “IT project,” but as a product that underpins strategic decision-making.

Building Confidence at Scale

The conversations at this year’s summit made one thing clear: the future of investment data strategy is not about choosing between governance and agility – it’s about achieving both. Federated models provide the flexibility to innovate, observability ensures transparency and trust, and cultural change makes these capabilities sustainable.

The firms that succeed will be those that treat data not as a cost centre, but as a strategic asset – governed, trusted, and ready to power the next decade of innovation.

If you’re exploring how to evolve your data strategy, I’d welcome the opportunity to connect and share ideas.

[1] This ‘micro-servicing the future’ article offers a useful perspective on how investment firms are rethinking their technology stacks to balance adaptability and control.