The Data Chief

• How Lloyds Banking Uses Data Escape Rooms to Build a Data Culture

  Tune in for a masterclass in data leadership. Josh Cunningham, Group Head of Data and AI Culture at Lloyds Banking Group, unveils how this distinguished institution is boldly innovating with cutting-edge AI. Josh provides a riveting look into his unique role, which is dedicated to accelerating talent, building capabilities, and articulating data and AI's profound impact across the organization. Learn how Lloyds is rapidly expanding its data and AI graduate scheme and learn more about their ambitious quest to be the "most data literate bank". Hear how their innovative five-persona literacy framework, and engaging initiatives like the "Data and AI Summer School" and a physical "Data Escape Room," are driving their business forward on data and AI.Key Moments: The "People Side" of Data and AI (12:33): Reflecting on his career, Josh highlights his passion for the "people side" of data and AI, focusing on building teams and fostering career development. This addresses a critical industry gap where technology readiness often outpaces human capability.Scaling Data and AI Talent (17:23): Lloyds Banking Group significantly scaled its data and AI graduate scheme from approximately 10 to 100 graduates annually over three years, while demonstrating a proactive approach to balancing between AI training and tool adoption for their increasing talent pool.Data and AI Literacy Framework (22:52): Lloyds developed a data and AI literacy framework with five personas, from "data beginner" to "citizen," representing an evolving maturity lifecycle. This framework helps map and track colleagues' literacy levels over time.The Data and AI Summer School (29:06): Josh highlights this major, two-month, virtual program that offers over 200 live sessions hosted by internal and external experts. It covers diverse data and AI topics for all colleagues, from beginners to practitioners, and has attracted over 42,000 sign-ups in the previous year.The Physical Data Escape Room (32:18): Lloyds innovated with a physical data escape room that tours the UK, designed to engage colleagues (even those disengaged with data). Its puzzles, anchored to the entire data value chain, enable "learning by stealth" with phenomenal feedback. Key Quotes:"It's trying your best to meet people where they are and make it real for them. So... finding a way to anchor the learning to something that's relevant to their their day to day role, is always gonna make it land better." - Josh Cunningham"I think every organization needs to find a really well-structured balance in terms of training versus adoption." - Josh Cunningham"If I was to think about our data and AI literacy framework, we've developed a framework that consists of five personas. We've tried to break it down in terms of where people might be on their data or AI literacy journey. You can go from data beginner through to data enthusiast, through to data and AI explorer, through to storyteller, through to citizen. - Josh CunninghamMentionsLloyds Banking Group - Escape RoomLloyds Banking Group's partnership with Women in Data Lloyds Banking Group's partnership with Code First Girls The AI Daily Brief PodcastGuest Bio:Josh Cunningham is the Group Head of Data and AI Culture at Lloyds Banking Group, where he leads the Data Culture Pillar—one of five strategic pillars in the Group’s data strategy. He is focused on embedding data-driven mindsets across the organization and empowering teams to unlock the full value of data.Josh spearheads a range of initiatives, including enterprise-wide data literacy programs, innovative talent attraction efforts, and collaboration events that foster a culture of experimentation and learning. With a background in data and a deep commitment to talent development, he is passionate about transforming how large organizations cultivate data careers, scale innovation, and use insights to shape the future of banking. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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• How a CDAO goes from baseball to insurance with Don Vu - New York Life

  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 VuMentionsHow New York Life’s “Guide Me” is Leading the Way in Digital TransformationRockaway Beach: New York’s Best Kept SecretLeading Change: By John P. KotterDiner: South Williamsburg, Brooklyn RestaurantGuest Bio 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. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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• How the Met Police Uses AI to Prevent Crime and Protect Communities

  Step into the future of policing where data is a mission-critical asset. Cindi Howson talks with Aimee Smith, Director of Data at the Metropolitan Police, about the Met’s bold data transformation—from digitizing records dating back to 1829 to using AI and cloud tech for smarter, faster decisions. Hear how initiatives like the V100 program and real-time analytics help improve city safety. Key Moments: Genesis of the Met’s Data Strategy (03:35) - The Met's data strategy's origin is traced to former Commissioner Cressida Dick's leadership, who envisioned leveraging data to transform policing, leading to a program building data capabilities and broadening analytics use beyond traditional intelligence and performance applications.  Mission with Data and AI (13:34): The Met's overarching mission to use data and AI for precise decision-making is articulated, acknowledging the complexity of policing's multiple goals: crime prevention, incident response, organized crime intervention, victim service, and custody safety.  Infrastructure Evolution (15:18): The transformation of the Met's data infrastructure over 5 years, from 8 separate operational systems to an integrated one with cloud technology adoption, is described, enhancing analytics and data science capabilities.  V100 Initiative (19:58): The V100 initiative, a data and analytics effort to reduce violence against women and girls by prioritizing individuals with a history of harm, is explained.  Concert Security Powered by Analytics (27:50): The use of ThoughtSpot by frontline officers is illustrated with a sergeant's innovative application for analyzing crime data around events like the Taylor Swift Eras tour to improve policing plans.  AI Agent Development (36:37): An innovative project to build an AI agent that assists frontline officers at crime scenes by providing real-time guidance is outlined, aiming to improve public protection and investigative outcomes.  Key Quotes:“So if an officer wants to start being able to do their own searches, creating their own sort of planners, thinking about doing their own trend analysis essentially, of crime data, which is great, isn't it? I mean, that's just exactly how you want ThoughtSpot to be used. Every officer has access to that.” - Aimee Smith"I like to think of it as a utility belt—you know how cops wear their utility belt? Well, hanging on there is this ThoughtSpot tool. A sergeant invented a way to use it for planning major events, concerts, to make sure our presence is right. And now that's replicable by other people who want to do the same thing." - Aimee Smith"One of the 5 principles of our business strategy for London to keep it safe is to be more precise in the use of data for decision making. So it's a high-level principle of our strategy. That makes data and analytics much harder, because there aren't enough data specialists and too many data parts to point at all those missions in one go.” - Aimee SmithMentionsMet Police’s V100 InitiativeMet Police Develops an Open Data Strategy with the Open Data InstituteMet Police’s Concert Preparation for Taylor Swift’s Eras Tour Cressida Dick Reflects on Public Trust in the Digital Age The Data Protection ActGuest Bio Aimee Smith's distinguished career in the Metropolitan Police Service (MPS) spans almost a quarter-century, truly a testament to her profound dedication to integrating robust data into the very core of police decision-making. She embarked on her journey in 2001 as an Intelligence Analyst, steadily rising through the ranks. By 2014, her leadership capabilities led her to head UK Policing’s largest Confidential Intelligence Unit. A pivotal "light-bulb moment" crystallized for her the critical importance of effective data management in driving operational outcomes, inspiring her to passionately spearhead the comprehensive MPS data transformation program. In a landmark achievement, Aimee was appointed as the first Director of Data for the MPS, where in 2019, she successfully established the inaugural Data Office within law enforcement, fundamentally reshaping how the service leverages its information. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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• Why Hyatt is Investing in AI and Self-Service to Transform the Future of Hospitality

  Embark on an insightful exploration of the hospitality sector, powered by data-driven analysis. Cindi Howson and Hyatt's data trailblazer, Ray Boyle (Vice President, Data and Analytics), are charting a course through Hyatt's data innovation. Witness how Hyatt's four-pillar data strategy is revolutionizing everything from employee empowerment to guest personalization and operational efficiency. Discover how Hyatt is democratizing data with self-service tools and pioneering an AI-powered frontier to redefine the very essence of hospitality!Key Moments: Data as an Asset (08:26): Ray emphasizes the importance of shifting the organizational mindset to view data not as a cost center, but as a critical asset. He discusses how data should be cared for, invested in, and stored like any other valuable asset, with the expectation of generating value for the business.  Hyatt's Data Strategy Pillars (13:00): Ray outlines the four key pillars that form the foundation of Hyatt's data strategy. These pillars include cultivating people and building a data-driven culture, personalizing the guest and customer experience in a high-trust environment, operating with excellence by ensuring operational efficiency and information consistency, and growing with intent by integrating new businesses and data flows.  Key Milestones in Hyatt's Data Transformation (16:42): Ray details the significant milestones in Hyatt's data transformation journey. These include clarifying the data strategy, establishing the data and AI operating model, building data governance capabilities, modernizing the data platform and infrastructure, expanding data assets, and releasing new services like personalization and forecasting.  Data Democratization and Data Fluency (23:00): Ray explains Hyatt's strong emphasis on self-service analytics to empower users across the organization. He discusses the importance of data accessibility, trustworthiness, and usability, as well as the potential of generative AI to further democratize data access and insights.  This includes building a data community to facilitate knowledge sharing and learning, as well as providing tooling and guidance to business organizations to effectively roll out analytics within their domains.  AI's Impact and Collaboration (31:35): Ray explores the transformative impact of AI on businesses and its role in fostering tighter collaboration between business and technology teams. He discusses how AI is driving the need for reimagined workflows and how it's changing the way data is used and delivered across the organization.Key Quotes:“ThoughtSpot has been a key partner of ours on that journey. We just roll the data into the cloud, and we're working to publish our assets, sales, finance, loyalty, revenue, search, and marketing into that infrastructure so that there's just a growing base of information that everybody can use in the self-service context.” - Raymond Boyle"Velocity is something you build over time. It's how I think about the operating model around data, ensuring everyone plays their role and develops the necessary skills. To me, velocity increases as you establish the operating model and you have the business, technology, and data organizations, along with governance and security, all participating effectively. - Raymond Boyle"When you think about the business outcomes and how people are beginning to consider AI's potential in that transformation, I believe AI is becoming a more significant factor every quarter." - Raymond BoyleMentionsThe Four V’s of Big Data, Including VelocityDalva, By Jim HarrisonMinnesota Timberwolves’ SuccessGuest Bio Ray Boyle (current Vice President, Data and Analytics at Hyatt) has enjoyed a distinguished career spanning several industries and roles across consulting, software, analytics, and data leadership. His notable roles include leading strategic planning, research, and analytics for Walmart’s Sam’s Club division; serving as Vice President of Walmart Global Customer Insights and Analytics; Vice President of Walmart’s Global Data and Analytics Platform; Vice President leading FICO’s global retail and CPG practice; and Executive Vice President heading IRI’s Global Shopper Analytics and Services team.Since 2019, Ray has served as Vice President, Data and Analytics at Hyatt. Aligned with Hyatt’s purpose — to care for people so they can be their best — his ambition is to elevate and scale that care through data-driven decisions and automation that benefit guests, customers, owners, and colleagues.Guest Bio Ray Boyle (current Vice President, Data and Analytics at Hyatt) has enjoyed a distinguished career spanning several industries and roles across consulting, software, analytics, and data leadership. His notable roles include leading strategic planning, research, and analytics for Walmart’s Sam’s Club division; serving as Vice President of Walmart Global Customer Insights and Analytics; Vice President of Walmart’s Global Data and Analytics Platform; Vice President leading FICO’s global retail and CPG practice; and Executive Vice President heading IRI’s Global Shopper Analytics and Services team.Since 2019, Ray has served as Vice President, Data and Analytics at Hyatt. Aligned with Hyatt’s purpose — to care for people so they can be their best — his ambition is to elevate and scale that care through data-driven decisions and automation that benefit guests, customers, owners, and colleagues. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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• How Macquarie Bank Uses AI and Data to Enhance Customer Experience

  Prepare to see banking in a new light! Cindi Howson and Macquarie Bank's data trailblazer, Ashwin Sinha (Chief Data Officer), go deep into the AI revolution transforming financial services. Discover how one of Australia's most dynamic financial institutions, Macquarie Bank, is wielding the disruptive force of generative AI, not just for efficiency, but to combat high-stakes threats like fraud. Plus, discover the remarkable evolution of the data analyst from report-generator to AI-powered strategic powerhouse!Key Moments: Drivers of Digital Transformation (04:36): Ashwin outlines the key factors driving a digital transformation and early cloud adoption, emphasizing customer obsession, improving turnaround times, and ensuring technology reliability.  Leveraging Dual Cloud Providers (12:25): Ashwin discusses Macquarie Bank's use of AWS for infrastructure and core applications and Google Cloud (GCP) for its digital and data stack, including AI capabilities.  The Power of Gen AI in Analytics (14:16): Ashwin explores the role of generative AI in enhancing productivity for data analysts, particularly through prompt engineering and tools like ThoughtSpot.  Empowering Analysts Through Evolution (16:56): Ashwin details Macquarie Bank's successful strategy for evolving the data analyst role by proactively introducing self-service analytics, emphasizing upskilling, and enabling analysts to concentrate on higher-impact activitiesCombating Data Risk and Fraud Prevention (26:04): Ashwin discusses the increasing threat of scams and fraud and details Macquarie's two-pronged approach: educating customers and employing AI and machine learning to detect and prevent fraudulent activities.  Importance of Prompt Engineering (32:57): Ashwin stresses the significance of prompt engineering as a general-purpose technology that can drive productivity across various business functions, not just within technical roles.  Key Quotes:"There is always a big backlog in most organizations, which you cannot get done just because you do not have enough capacity. You cannot prioritize them. You cannot execute fast enough. And so, what prompt engineering and GenAI broadly does is take away the low-value tasks that you could just use AI and machine learning to do for you." - Ashwin Sinha"Prompt engineering—even though it has 'engineering' in it— I see that as a general-purpose technology. It's a bit like we've just got access to a super powerful search with a lot more analytical and reasoning capability. That's how I think of the usage of any of the foundational or large language models for, you know, the general population who are not in engineering or technical roles. Whether they're in business roles, sales and distribution, finance, marketing, or any of those functions, the use of prompt engineering just enables the next level of productivity for them. - Ashwin SinhaMentionsPrompt Engineering in the Age of AIAI Agent GovernanceThoughtSpot Spotter: Your AI AnalystScuba Diving and the History of the Liberty Shipwreck in BaliThe Importance of Child Education in IndiaGuest Bio Ashwin Sinha is the Chief Data Officer and Executive Director at Macquarie Bank, where he oversees the strategy and execution of Data and AI. Before joining Macquarie in 2019, Ashwin was a Partner at KPMG, leading the Data business. He has also held various global software engineering, start-up, and consulting roles over the past 22 years, focusing on data and digital transformations. Outside work, Ashwin is passionate about child education and macroeconomics Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

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