UK & Ireland CDAO Executive Summit

Please join the Summit’s Welcome Reception, an exclusive networking reception for all attendees to launch the Summit with an evening of drinks, gourmet food stations, and plenty of peer networking at The Orangery, Holland Park, London. A hidden gem located in one of London’s most beautiful settings, situated within the grounds of Holland Park.

The role of the CDAO is still relatively new and what an executive can do beyond this is even newer. How this role is evolving, the fight to remain relevant and grow in prestige and what the future holds beyond being a CDAO is uncertain. There is no set path for a CDAO to walk, but rather a plethora of opportunities. This session will ask key questions, like what is the CXO step beyond CDAO? Should they aim to be a COO or how many of you have non-executive director positions?

Join this panel to explore:

• Discussing key factors that can enhance the prestige and value of the CDAO
• The importance (or lack thereof) of having a clear roadmap for the CDAO
• The shifting responsibilities of the CDAO over the next five to ten years

Concerns around AI ethics are increasing as AI comes into the mainstream. There is a greater need for transparency, accountability, and auditability in AI models. Organisations need to work towards responsible AI adoption to build customer and stakeholder trust.

New regulations will hit the UK and EU as early as 2024. There are likely to be differences in how these rules will be governed and enforced across the EU member states, and with many other countries developing their own frameworks, what will this mean for the organisations’ operations and performance? Yet, self-policing ahead of regulation is necessary as organisations’ success and reputation depend on doing the right thing.

Join SAS to learn more about:

• Building fairness and equity into every AI model from the start
• Ethical frameworks in place incorporating privacy, respect, transparency and consent to allow enterprises to innovate quickly and responsibly whilst preparing for upcoming regulations
• The importance of data science practices to identify potential bias at a much earlier stage and therefore reduce operational, financial and emotional risk
• Best practices for leveraging AI technologies with a human-centric and ethics-lead approach

Data is the primary asset for organisations driving innovation. Converting data into actionable insights is a team effort and all employees must play a role to advance organisational objectives. Data and analytics leaders are tasked with creating a data literacy programme that streamlines and propels enterprise agility.

Join this roundtable discussion to discover how to:

• Identify skill gaps that prevent organisations from achieving critical business objectives and maximising technology investments
• Design scalable training programs that build organisation-wide data literacy and a data-driven culture through applied learning, without impacting your cost centre
• Increase team engagement and retention, alongside attracting a diverse talent pool that allows organisations to better represent and serve their customers

Multiple attempts to create value from data have been labelled “democratisation”: business intelligence in the 1990s, self-service analytics in the 2000s, and (citizen) data science in the 2010s. Yet progress on their common goal, putting more hands-on data outside central teams, has been wildly uneven. Cynical observers even note the same problem being “solved” over and over without understanding why earlier attempts failed. The current generative AI revolution has led, once again, to the same pronouncements, so what would make things different this time? Can AI help us escape the paradox of so-called structured data remaining impenetrable to domain experts? And how can data leaders avoid being left behind as business teams embrace AI faster than central teams can govern it?

You will leave this session, having discussed:

• What is different (if anything) about this moment vs prior waves of hype/progress
• Where your peers are realising value today from AI
• How to use current hype to accelerate value-driven adoption of AI

Neil Martin, renowned Formula One data scientist and former head of strategy at McLaren, Red Bull Racing and Ferrari will be sharing insights and experiences from his three-decade career of using pioneering data analytics, modelling and technology as key tools to drive results at the pinnacle of world motorsport.

In this keynote session, Neil will share:

• You will witness digital twins, simulation and predictive analytics in action that enable insights for various scenarios that would otherwise remain hidden; as some anti-intuitive outcomes are never discovered without these tools
• You will experience the sport’s data and analytics journey from its beginnings back in the early 1980’s up to the present day, explaining how risk is embraced, mitigated and exploited using various techniques for competitive advantage
• You will discover how Formula 1 techniques and tools have moved into the real world, as the techniques are used well beyond a race circuit and are in fact all around us in todays society

The role of the CDO is critical in maximising the value of data. The CDO's journey in transforming an organisation to become data-driven is a complex journey. 

This involves going through steps in the journey carefully balancing defence with offence. Defence is building capabilities for organisations to meet regulatory and control objectives, whilst offence is enabling organisations to leverage data & analytics to create growth and revenue opportunities.

To unlock the business impact of your data you need to develop and deploy more, new AI/ML applications faster. To do so, leaders need to overcome AI silos - not just data, but the data science tools, infrastructure and talent silos that exist in most organisations. In short, you need to implement a strategy to grow, unify, accelerate and empower your data science teams across the business.

Join this session, moderated by former industry analyst Dr. Kjell Carlsson, where we will discuss:

• Enabling data science: providing self-service access to the expanding ecosystem of data science tools and infrastructure
• Growing AI expertise: effective strategies for growing data science talent
• Unifying data science: driving consistent processes and best practices across teams
• Leveraging hybrid cloud: overcoming and taking advantage of on-prem and multi-cloud environments

As businesses strive to put data at the centre of decision-making and culture, it's critical for leaders to understand their core data and its quality, and remove data silos to activate trusted, timely data across the enterprise. Data and analytics leaders must have the proper people, processes and technology in place to manage their core data and effectively drive value from them.

Join this session as CDAOs discuss:

• Overcoming core data management challenges with faster time to value
• Instituting a system to uphold data quality
• Leveraging AI with real-time trusted data to harness valuable insights

Organisations' data teams operate differently in response to different business needs. Getting your structure right can be fundamental in determining the success of your data operation and thus its impact on the wider business. In this interactive session, CDAOs from different organisations will present short “board pitches” covering their team structures, reporting lines and the reasoning behind them, followed by an open discussion. You’ll leave this session, with a wide view of different team structures and business insights, you could implement to elevate your business unit.

In this interactive session, we will explore:

• Understanding the rationale behind each structure & discussing industry-specific nuances 
• Positioning your team as data advocates and driving business outcomes 
• Assessing how your business unit may evolve in line with new technological innovations 

ESG (Environmental, Social and Governance) offers a huge opportunity for CDAOs to be front of mind and lead the charge on improving their companies' impact on the world. They can play a key role in influencing strategic initiatives that drive ESG and the capital expenditure organisations develop in annual planning cycles. In this boardroom, we’ll consider how CDAOs can become catalysts for change and investments in companies.

Join this session to discuss:

• Assessing how CDAOs can act as changemakers, and lead the ESG charge
• Sharing strategic examples of CDAOs impacting ESG initiatives
• Implementing a value-led approach to your ESG strategy

In today's data-driven world, the Chief Data and Analytics Officer (CDAO) role is essential in driving innovation and growth. To succeed in this role, the CDAO must possess a unique skill set that includes technical and business acumen, effective communication skills, and the ability to build strong partnerships and retain top data talent. By doing so, the CDAO can become a key driver of data-driven strategies and ensure compliance with evolving regulations and ethical standards.

Join this roundtable discussion as CDAOs discuss:

• Strategic thinking to identify and prioritise opportunities for data-driven innovation
• Agility to adapt to changing business needs and emerging technologies
• Ethical and regulatory understanding to ensure data privacy and compliance

At Rolls-Royce Civil Aerospace, Stuart Hughes (CDIO) has been leveraging data and AI to empower the business, reduce waste and release value quickly and efficiently. As a result, they are answering questions faster than ever before. In this closing keynote session, Stuart will reflect on the journey to implementing a value-centric mindset across the enterprise, advancing Data-Driven innovation, and the challenges he faced along the way.

Stuart will address:

• Being a data disruptor — make it your mission to partner with the business and build a data-driven culture across your organisation
• Finding ways to accelerate time-to-value — defining successful outcomes with the business
• Using data lakehouse to increase simplicity, accelerate insights, and support the full ML lifecycle