In the race to align data strategies with business strategies, organizations often overlook a crucial reality — many departments, such as finance and actuarial, aren’t asking for help. They’re comfortable using tools like Excel or outdated software, even if those tools fall short of modern organizational standards.

The result? IT teams and data offices build technically sound solutions aligned with business objectives — but these solutions fail to resonate with the actual users.

To create a truly effective data strategy, we need to focus not only on business functionality but also on matching the technology functionality departments are already using. This approach isn’t about forcing change for modernization’s sake but designing solutions that seamlessly integrate with or enhance the tools and workflows departments already rely on.

At its core, this means adopting a democratized approach to data architecture, one that empowers users without compromising governance or security.

The problem — The gap between strategy and reality

When IT or data teams align strategies solely to business objectives, they often aim for “best-in-class” solutions. These solutions might be technically robust, but they fail to resonate with the people they’re intended to serve. Business units stick to tools like Excel because they value the flexibility and simplicity it offers — even if it’s inefficient or error-prone in the long term.

This gap creates friction. IT views these tools as unsuitable, while business teams see new solutions as over-engineered or disruptive.

The solution: Build a strategy that fits the tools people use

Leverage democratized data architecture

A democratized data architecture is about giving business users direct access to the data and tools they need, in a way that aligns with their workflows and technical expertise. It empowers teams to solve their problems while maintaining a shared framework for governance and scalability.

1. Empower through access, not complexity:

• Solution: Instead of creating rigid, fully centralized systems, build an architecture that allows users to interact directly with the data in a way that makes sense for them while centralizing group results.

• Example: Provide self-service tools that let finance teams access pre-approved datasets directly from and to managed platforms, into familiar platforms, like Excel or Power BI.

• Outcome: Users gain autonomy without needing to learn new, complex tools or workflows.

2. Create guardrails, not bottlenecks:

• Solution: Enable departments to work independently while ensuring data quality, security, and compliance through automated governance.

• Example: Use automated data cataloging and lineage tracking to ensure that all datasets accessed by business teams are accurate and traceable.

• Outcome: Business users can innovate without creating risks or silos.

3. Distribute ownership:

• Solution: Assign ownership of specific datasets to the teams that use them most, allowing them to curate and manage their data within the broader architecture.

• Example: Actuarial teams manage historical claims datasets, ensuring they are updated and validated, while IT provides the infrastructure, support, and central group modeling and consolidation.

• Outcome: Teams feel ownership over their data, which fosters trust and accountability.

The cultural component — Winning hearts and minds

Democratization in Action

A democratized data architecture isn’t just about technology—it’s about changing the way teams interact with data. Instead of relying on IT to provide every answer, business users gain the tools and confidence to find answers themselves.

1. Showcase tangible benefits:

• Solution: Demonstrate how this new approach saves time and reduces frustration.

• Example: A finance analyst no longer has to submit a ticket to IT to access data but can pull it directly from a governed self-service operational platform.

• Outcome: Users see immediate value and become advocates for the new system.

2. Focus on collaboration:

• Solution: Position IT as a partner, not a gatekeeper, in delivering data solutions.

• Example: Co-create dashboards or reports with teams, blending technical expertise with business insight.

• Outcome: Users feel heard and empowered, which reduces resistance to change.

Conclusion — Building for people, not just processes

A successful data strategy isn’t just about aligning with business objectives or implementing the latest technology. It’s about empowering people to do their jobs more effectively by giving them tools and data that work the way they work.

By embracing a democratized data strategy, organizations can strike a balance between control and flexibility, ensuring that business teams can access and use data without compromising governance. This approach isn’t about forcing change; it’s about meeting departments where they are, enhancing their workflows, and gradually guiding them toward a more efficient and scalable future.

When we combine practical tools with cultural empathy, we create a data strategy that drives not just adoption but transformation — one solution, one team, and one win at a time.

About the Author

At the helm of Enstar Group’s data strategy, David Tuppen’s role as Chief Data Officer encompasses spearheading data platform modernization and guiding enterprise-wide transformation initiatives. Championing enterprise data management and client solutions, he drives the realization of data’s full potential to underpin decision-making and operational excellence.

Tuppen’s previous leadership roles include organisations such GFT Technologies, Wipro, and Athene, particularly in Data & AI and the Insurance sector, which has enriched his approach to customer centric data solutions. His team’s commitment to delivering transformative data solutions aligns with his goal of propelling organizations to the forefront of data-driven innovation.