In this insightful conversation, Don Vu, SVP and Chief Data and Analytics Officer at New York Life, shares his journey from Major League Baseball to revolutionizing the insurance industry. He discusses how cutting-edge AI is used to tackle the 'last mile problem' in data operationalization, ensuring data strategies align with business needs. Don highlights the importance of data quality and readiness, and how innovative tools like the GuideMe app enhance advisor-client interactions. His unique blend of experiences showcases the transformative power of data and AI in legacy institutions.
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MLB's Data-Driven Baseball
Don Vu shared how Major League Baseball tracks every object in the stadium with radar and high-speed cameras.
The data is shared across all clubs to optimize player performance and strategy league-wide.
insights INSIGHT
The Last Mile Problem
The "last mile problem" is not building AI models, but operationalizing, adopting, and optimizing solutions.
Impact depends on change management and business process improvements, not just technology.
volunteer_activism ADVICE
Measure and Share Business Value
CDAs must relentlessly measure and communicate the business impact of their teams' work.
Collaborate closely with business partners to make impact a shared success.
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In 'Leading Change,' John P. Kotter presents an eight-stage model for effectively leading change in organizations. The stages include establishing a sense of urgency, creating a guiding coalition, developing a vision and strategy, communicating the change vision, empowering broad-based action, generating short-term wins, consolidating gains and producing more change, and anchoring new approaches in the culture. Kotter emphasizes the importance of clear communication, leadership over management, and addressing common pitfalls that hinder successful change initiatives. The book is filled with real-world examples and practical advice based on Kotter's extensive experience with numerous companies.
Step inside the world of data innovation as Don Vu, SVP and Chief Data and Analytics Officer at New York Life, reveals how a 180-year-old institution is embracing cutting-edge AI. Don, shares insights from his unique background, spanning Major League Baseball and retail startups, now applied to transforming the insurance industry. Hear how New York Life leverages AI to make experiences proactive and intelligent, addressing challenges like the "last mile problem" in data operationalization.
Key Moments:
MLB Data Insights (07:28): The conversation delves into how every baseball stadium is extensively instrumented with high-speed camera and radar technology, meticulously tracking every object on the field. This massive trove of data is then shared across all baseball clubs for in-depth analysis and the optimization of strategies.
The Last Mile Problem (09:38): A critical challenge in data and AI is identified as the "last mile problem," emphasizing that the primary hurdles often lie in the operationalization, change management, adoption, and acceptance of solutions, extending far beyond the mere building of models.
Data & AI in Business Strategy (13:08): The discussion highlights that data serves as the fundamental underpinning for seamless operations, while AI actively transforms experiences, making them proactive and intelligent. This deep integration of AI and data is central to New York Life's core business strategy.
Data Readiness & Quality (20:08): Persistent data readiness issues are addressed, underscoring that data quality, latency, governance, and stewardship—with business owners held accountable—are absolutely crucial for both structured and unstructured data environments.
AI Interoperability & Agent-Driven Future (22:43): The episode explores the importance of tracking emerging AI protocols such as MCP (Model Context Protocol) and agent-to-agent protocols. A compelling vision of the future is also shared, where AI agents act on behalf of consumers. Realizing this vision depends on interoperability across AI systems, enabling smooth, intelligent collaboration between diverse platforms.
GuideMe Application & AI (32:46): New York Life's innovative "GuideMe" tool, utilized by agents during client meetings, is described as possessing incredible potential for pervasive AI integration. This integration is set to significantly supercharge both the agent and client experience, streamlining financial planning.
Key Quotes:
“There is this phrase that data practitioners often cite. It's like this notion of garbage in, garbage out. And data quality matters. The latency of your data is significantly important. The notion of data governance and data stewardship, with a business owner being accountable for the quality of data, is really important." - Don Vu
“We think human-led protection-first holistic advice and guidance is really the key here, and we have amazing advisors, we have amazing agents throughout the country, and what we're really focused on is really enhancing them and trying to make their lives easier by having AI at their side.” - Don Vu
“Data is the underpinning foundation upon which that runs seamlessly and consistently. AI is the way by which it becomes proactive and intelligent across the entire set of experiences.” - Don Vu
Don Vu is the Senior Vice President and Chief Data and Analytics Officer at New York Life. In this role, Don leads the company's artificial intelligence (AI) and data team, overseeing AI, data, and insights initiatives and ensuring data architecture supports New York Life's business objectives. Prior to joining New York Life, Don served as chief data officer at Northwestern Mutual, where he spearheaded organizational transformation and enterprise data and AI strategy. His impressive career also includes leadership positions at WeWork as vice president of data and analytics and 13 years at Major League Baseball (MLB) as vice president of data and analytics. Don holds a B.S. in Information Systems and Commerce from the University of Virginia and actively contributes to the field as an advisory board member for McIntire's Business Analytics program.
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