Why Data Governance In Your Org is Broken (And How to Fix It)

Cara Dailey, VP and Head of Data Strategy at Early Warning (the parent company of Zelle), joins High Signal to discuss the evolution of high-stakes data leadership and governance. From her early work in online advertising at DoubleClick to shaping data strategy at Nike and holding Chief Data Officer roles at Bank of the West and T. Rowe Price, Cara has seen every iteration of the data leader’s role. Now, she’s navigating her 'product era'—shaping the data strategy for Early Warning's Decisions Intelligence business, where she leverages rich financial data and data science to drive fraud monitoring and modeling. In this episode, Cara shares her pragmatic 'progress over perfection' approach to governance, why she’s abandoning monolithic platforms in favor of incremental data products, and her 80/20 rule for balancing operational rigor with innovation. We also discuss why 'loving' data isn't enough—you have to actually 'take care' of it—and why AI is finally shining a spotlight on the often-neglected fundamentals of data stewardship and conversational BI.

Data Products Beat the Perfect Platform. 

Dailey argues that the quest for a single, unified data platform is a multi-year journey that fails to deliver short-term value. A more pragmatic "good enough" strategy focuses on shipping smaller, well-defined data products to deliver tangible wins for analytics and data science teams early and often.

Your Best Data Stewards Are on the Frontline. 

Instead of assigning stewardship as a side job to technical staff, Dailey recommends recruiting people from customer-facing roles. They intimately understand customer pain points, which directly connects the abstract work of data quality to concrete business impact and customer experience.

Governance Starts with a Simple Framework: Ownership, Quality, Knowledge. 

Dailey advises against launching complex, 18-point governance plans from day one. She advocates for a simple, three-pronged approach: clearly defining data ownership, identifying the most critical quality metrics, and building organizational knowledge through fluency programs.

The CDO Era Is Evolving into a Product Era. 

Dailey charts her own career trajectory from a traditional CDO focused on internal governance to a leader developing strategy for a data-based business. This reflects an industry shift where data leadership is increasingly measured by its ability to drive revenue and create external value through data products.

"Data Love" Isn't Enough; Ask About "Data Care." 

Dailey challenges the common sentiment of "I love data" by asking leaders and teams a more pointed question: "Do you take care of it?" This simple reframe shifts the focus from passive consumption to active stewardship, making it clear that data hygiene is everyone's responsibility.

AI Shines a Harsh Light on Governance Debt. 

The rise of AI makes strong data governance non-negotiable, putting immense pressure on previously underfunded governance teams. Dailey notes that AI's success is directly tied to fundamentals like a solid data foundation, a well-organized catalog, and reliable metadata—making governance a prerequisite for scalable AI, not an afterthought.

Innovation in Regulated Spaces Is an 80/20 Game. 

Dailey proposes a pragmatic 80/20 split for leaders in regulated industries: dedicate 80% of resources to operational rigor and 20% to focused innovation. Progress is achieved by picking small, safe use cases to prove value and build momentum, rather than attempting to overhaul core processes at once.

You can read the full transcript here.

00:00 The Future of BI: AI Takes Over

00:16 Introducing Cara Daily: A Data Leadership Journey

03:08 The Evolution of Data Leadership

05:06 Cara's Career Path: From Software to Financial Services

10:01 Data Strategy and Governance Insights

16:16 The Role of Data Stewardship

22:01 AI in Data Management: Starting Small and Safe

24:53 The Importance of Data Security and Governance

26:58 AI's Impact on Data Governance

29:38 The Rise of Agentic AI

31:56 AI in Financial Services

35:06 Future of AI and Data Governance

40:11 Balancing Innovation and Operational Rigor

45:27 Looking Ahead: Automation and AI

46:30 Conclusion and Wrap-Up