Trust and accountability sit at the heart of every successful global data function. For Yorck F. Einhaus, Global Chief Data Officer at Liberty Mutual Insurance, these two foundational elements must also be anchored in three interconnected pillars: strong governance, genuine transparency, and a people-first culture that blends accountability with innovation.
With an illustrious career leading data stewardship across major insurance organizations like Farmers Insurance Group and Allianz Group, Einhaus has spent more than two decades shaping enterprise data, technology and AI functions, always guided by a conviction that trust is the real catalyst for scale and impact. “Both are non-negotiable when building and scaling data functions globally,” he says.
It’s a perspective that reflects not only years of hands-on transformation work, but also a fundamental belief that people and process must evolve in tandem. For him, the key is to build a single source of truth, strengthen a team‑of‑teams operating model, embed governance, and ensure accountability that connects directly to business value, creating a clearer throughline for the enterprise.
Governance as the Backbone of Trust
The foundation of trust begins with ownership. Governance must be a structure that clarifies responsibility and empowers teams to take meaningful action. In prior roles, he partnered closely with business leaders to ensure governance translated into practical outcomes, giving each data domain clear ownership, measurable KPIs, and streamlined processes that eliminated ambiguity.
This structure only works when it is lived. It requires leaders to model accountability and teams who understand not just what the rules are, but why they matter. “Accountability is not a one off,” he says. “It is part of the DNA of how we work.”
Transparency as a Catalyst for Shared Responsibility
Contrary to common belief, transparency is more than visibility. It is a mechanism that turns governance principles into actionable insights. This is where well-designed dashboards and analytics become powerful, giving teams a clear view of how data moves through the enterprise and where value or risk emerges. “If teams cannot see how data is being used or misused, they cannot act responsibly,” he says.
For example, by providing metrics on usage patterns, data quality scores and lineage pathways, transparency brings business and technology partners into the fold. They can detect issues earlier, understand dependencies and make better decisions. This shared clarity reduces the risk of siloed thinking and fuels a culture where improving data value becomes a collective effort. When people understand the true lifecycle of the information they rely on, trust becomes a natural outcome.
Creating a Culture That Balances Accountability and Innovation
Leading teams spread across the US, Europe and Asia has given him a front‑row view into what truly drives performance. “No matter the region or remit, it always comes down to people,” he says. From guiding enterprise platforms at Allianz Group in Austria to modernizing core systems at Farmers Insurance Group in Los Angeles, he’s seen that teams thrive when they are trusted to experiment, challenge assumptions and take thoughtful risks. “People do their best work when they feel both empowered and supported,” he says, noting that psychological safety is essential for learning from missteps rather than hiding them.
This, he notes, is the hallmark of a high‑performing data organization. Data ethics is central to this. He expects teams to consider the downstream impact of their work, particularly in AI and ML development. “Accountability is not about blame,” he says. “It is about responsibility and growth.” This approach enables teams to innovate while maintaining the safeguards essential for responsible data stewardship.
A Model for Global Impact
To build global data functions that people trust, leaders must anchor them in governance, transparency and culture. When these elements work together, teams become aligned and empowered to deliver meaningful business value.
“When organizations understand their data and trust the people working with it, you can feel the shift in how quickly value emerges,” he says. “That alignment is the engine behind sustainable transformation.”
Follow Yorck F. Einhaus’ work on his LinkedIn.
