CDAO UK schedule

During this 10-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

• How can organizations design a data governance framework that balances regulatory compliance, data security, and business agility? 

• What are the most effective approaches for integrating AI and machine learning capabilities within a data organization to drive innovation and maintain competitive advantage? 

• In the context of scaling data operations, what role do advanced data architectures and technologies (such as data lakes, data warehouses, and cloud platforms) play in enhancing organizational efficiency and data-driven decision-making? 

• How can senior data leaders foster a culture of data literacy and continuous improvement across the organization, ensuring that all employees are equipped to leverage data effectively?  

An informal, interactive session where attendees ask questions directly to an AI ethics and data privacy expert. The expert will answer questions on the fly, providing practical insights and advice on navigating regulations and building trustworthy AI systems. 

Kimberley Miles, Data Protection Officer- DUAL 

Focus Areas: AI ethics, data privacy, regulatory challenges.  

As Channel 4 embarks on its new Fast Forward strategy, we will explore how we’re supporting the business through the development of a new centralised Analytics function. Will it be happy ever after? Or will the business stand us up at the altar? 

• Things we’ll cover: 

• How we changed our operating model to overcome siloed data and insights teams. 

• How we plan to overcome functional silos between Analytics, BI and Research to deliver a source of truth to the business. 

• How the structure has enabled us to deliver holistic insights about our audiences. 

• The early wins we’ve had and lessons learned as we’ve gone through this transformation.  

Adam Sangster, Senior Insight Manager, Social & Product – CHANNEL 4 

Parves Khan, Lead Business Transition Partner – CHANNEL 4 

• As AI systems become more complex, how can organizations ensure that ethical principles are maintained across various industries? 

• Discussion on the evolving regulations around AI and data use, focusing on new legal frameworks like the EU AI Act, and how organizations can stay compliant globally. 

• Exploring best practices for identifying, addressing, and mitigating bias in machine learning models. This will cover fairness frameworks and transparent AI to avoid reputational and financial risks. 

• How can data strategy be better aligned with overarching business goals? 

• What are the most effective ways to measure the business value generated by data investments? 

• How do you ensure that data-driven decisions lead to operational improvements? 

• What are the common challenges in translating data into actionable outcomes, and how can they be overcome

• With the exponential growth of data sources, leaders often face cognitive overload that makes it harder to discern valuable insights from noise. How can decision-makers prevent data overload from clouding strategic insights? 

• Having more data doesn’t always equate to better decisions. What mechanisms can organizations put in place to prioritize quality over quantity in data use? 

• The allure of new tools and metrics can lead to decision-makers getting distracted by trends rather than focusing on data that drives real value. How can executives balance the use of cutting-edge data analytics with the risk of chasing trends that don’t align with business objectives? 

• As leaders increasingly rely on data, they can lose sight of the importance of intuition. What role should human intuition play in decision-making when data-driven insights seem overwhelming or contradictory?  

Pankaj Manek, Data Manager - CAMBRIDGE & COUNTIES BANK 

• How can organizations cultivate a leadership approach that values data as a strategic resource? 

• What are the persistent barriers that prevent organizations from fully embracing data confidence? 

• Why is it crucial to shift the perception of data to make it accessible to all employees, not just analysts? 

• How does the integration of data literacy and leadership contribute to fostering innovation and accelerating business growth? 

• • What to expect: A solution-oriented think tank where senior leaders can discuss challenges with real-time data infrastructure. The session will guide participants through a collaborative problem-solving approach focused on scaling real-time analytics. 
  • Participation: Come ready to engage in a dialogue about current challenges and opportunities in real-time data processing. Even if you don’t have a specific plan, you’ll contribute by brainstorming with other senior leaders on practical solutions. 

   

  Rajan Srivastwa, Head of Engineering - Personalised Products - NATWEST MARKETS 

   

  Mohit Joshi, Director of Data and ML Platforms – COLLINSON

• What to expect: A practical discussion on how organizations are dealing with increasing regulations while maintaining data-driven innovation. Participants will work through governance frameworks that protect data while allowing for business insights. 

Participation: No preparation is necessary—just bring your experience with data privacy challenges and collaborate with others to develop workable solutions for navigating regulatory landscapes. 

• How does effective data management serve as a catalyst for digital transformation within organizations? 

• Real-world examples where data management has significantly accelerated digital transformation 

• How important is cross-functional collaboration in implementing successful data management strategies for digital transformation? 

• What roles do technologies like AI, machine learning, and analytics play in transforming raw data into actionable insights that drive innovation and decision-making? 

Mohit Joshi, Director of Data and ML Platforms – COLLINSON

During this 5-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

• What foundational AI concepts, such as machine learning and algorithm design, are crucial for establishing a robust groundwork for AI readiness? 

• How can organizations assess their AI readiness by evaluating infrastructure, data quality, and team skills to identify and address any critical gaps? 

• What strategies can be used to leverage AI tools for enhancing collective intelligence and improving team collaboration and decision-making? 

• How can organizations ensure their AI initiatives align with strategic goals and measure their success using key performance indicators (KPIs) to deliver real value?  

Panel Discussion: Turning Insights into Action: Does Data-Driven Change Deliver? 

• How can we identify and prioritize which data to bring under governance when dealing with vast amounts of data? 

• What are the challenges of regulatory compliance when applying data governance, and how can we navigate them? 

• How can we enable versatile governance strategies to serve as a vehicle for tailored data accessibility? 

• What strategies can be employed to break up data silos across business units and accelerate data-led decision-making? 

• How can we achieve strong data governance by aligning stakeholder engagement with business culture and maturity?  

Jean Ortiz Perez, Director of Data & Analytics – VALUEDYNAMX 

Kassim Hussein, Head of Data and Analytics (Director Grade) - CLEVELAND CLINIC LONDON 

Mike Leverington, Director of Data Capability – ITV 

Brendan Ellis, Head of Data & Business Intelligence – PANTHEON VENTURES 

James Davies, CDAO - BY ROTATION 

Sudesh Yog, Vice President, Data & Analytics – APETITO UK 

• How do organizations navigate ethical complexities in advanced analytics and machine learning? 

• What proactive strategies can businesses use to address emerging privacy risks in the evolving landscape of big data and AI? 

• Beyond compliance, how can organizations innovate to integrate ethical principles into their core data strategies? 

• In the age of encryption and decentralization, how do businesses balance data privacy with the need for accessibility 

• What tools and approaches enable organizations to transparently communicate and address ethical considerations in complex data models within the era of explainable AI? 

Andi McAleer, Head of Data & AI Governance - FINANCIAL TIMES 

• How are businesses across industries using real-time data to adapt to customer needs in a fast-paced digital environment? 

• What role does AI play in anticipating customer behaviors and personalizing digital experiences at scale? 

• How can data leaders ensure the integration of data-driven solutions without compromising on customer privacy and trust? 

• What are the key strategies for balancing automation with the human touch to meet evolving customer expectations? 

• How can organizations balance the need for data-driven insights with increasingly stringent privacy regulations like GDPR and CCPA in the age of big data? 

• What strategies can companies implement to ensure compliance with data privacy laws while still leveraging personal data for business growth and innovation? 

• How do emerging technologies such as AI and machine learning complicate privacy concerns, and what legal safeguards should be in place to mitigate risks? 

• In an era where data breaches are becoming more common, how can businesses protect consumer trust while maintaining transparency about their data practices and legal obligations? 

What You’ll Learn: 

• Data as a Strategic Asset: How businesses can generate revenue from their data, such as through data-sharing partnerships or insights-based products. 

• Overcoming Challenges in Data Monetization: Legal, ethical, and practical challenges and strategies for overcoming them. 

• Measuring ROI on Data Investments: How to evaluate the financial returns on your data initiatives. 

Workshop Outline: 

• Introduction: An overview of data monetization and its significance in today’s world. 

• Data as a Strategic Asset: Learn about different revenue streams generated from data and share your own ideas. 

• Challenges & Solutions: Discuss legal, ethical, and practical challenges, with real-world examples of overcoming them. 

• ROI on Data Investments: Discover simple frameworks to measure the success of your data initiatives. 

How You Can Participate:  

• No preparation is needed! 

• Share how your organization uses data or could monetize it. 

• Participate in discussions and ask questions. 

• If you don't have direct experience, think about potential opportunities for your industry. 

Brendan Ellis, Head of Data & Business Intelligence – PANTHEON VENTURES 

Format: Interactive Leadership Roundtable 

This session brings together data leaders to discuss how they are cultivating the next generation of data talent. What leadership skills are needed in future CDAO roles? How can senior leaders' mentor and upskill their teams to meet the demands of a rapidly evolving data landscape? Participants will share their mentorship approaches and discuss strategies for closing the talent gap. 

• Focus Areas: Leadership development, talent strategy, future skills. 

• Preparation: Minimal — 1 facilitator guides the discussion with key questions. 

• Objective: Encourages reflection on talent development and sharing of leadership strategies to help organizations grow their data capabilities from within  

Kevin Bould, Associate Director of Digital Data and Technology – TEENAGE CANCER TRUST 

James Davies, CDAO - BY ROTATION 

• How can organizations create ethical guidelines that protect data privacy while still enabling innovation and data-driven insights? 

• What practices ensure transparency, accountability, and fairness in data governance to meet both ethical standards and stakeholder expectations? 

• How can businesses mitigate bias in AI models and integrate ethical principles to prevent discrimination in data use? 

• What steps must companies take to ensure their data practices remain ethical and compliant with evolving regulations like GDPR and CCPA across regions? 

AI-Powered Analytics: The Next Frontier 

• What to expect: A fluid discussion on how AI is being integrated into data strategies across industries. Participants will share their insights on balancing innovation and governance when deploying AI in their organisations. 

Participation: No preparation needed—just join in and share any high-level experiences with AI, even if it’s a work-in-progress. The goal is to exchange thoughts on AI’s potential and discuss common obstacles like data privacy or ROI. 

• What to expect: A conversational session where leaders discuss how they’re enabling non-technical teams to access and use data, while maintaining security and quality standards. Focus is on balancing accessibility with governance. 

• Participation: Simply join and share your organization's experience with democratizing data—whether it’s just getting started or fully implemented. No need for slides or formal input, just ideas and insights. 

Kassim Hussein, Head of Data and Analytics (Director Grade) - CLEVELAND CLINIC LONDON 

Rajan Srivastwa, Head of Engineering - Personalised Products - NATWEST MARKETS 

• How are companies leveraging AI and big data to deliver hyper-personalized customer interactions across digital platforms? 

• What role does predictive analytics play in anticipating customer needs and shaping more proactive service models? 

• How can businesses ensure data privacy and compliance while still using vast customer data to enhance experiences? 

• Are there limits to automation in customer experiences, and how do companies balance human touch with data-driven efficiency? 

• How can we detect and reduce bias in AI models that are trained on historically skewed data? 

• What roles do diverse data sets and inclusive teams play in ensuring fairness across AI systems? 

• How do regulatory bodies address the ethical implications of biased AI in sectors like healthcare and finance? 

• Is there a trade-off between AI accuracy and fairness, or can both be achieved simultaneously through advanced techniques? 

• How can data teams effectively collaborate with business units, legal, and IT for meaningful impact? 

• What best practices can foster a culture where data is a shared resource rather than a siloed asset? 

• How have cross-functional teams unlocked new insights and innovations through collaboration?