Driven by Data: The Podcast

In Episode 29, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Evie Dineva, Group Head of Data Engineering & Data Science at Gymshark, where they discuss how to balance delivering commercial value through data, analytics and AI products responsibly and ethically, which includes;Being driven by the purpose of improving business performanceArticulating the commercial value of what Data & Analytics teams doThe importance of supporting people to be better at what they doWorking for a brand as big and prominent as GymsharkThe importance of being in an environment where company values are visibleCommon pitfalls as to why organisations fail to deliver commercial value with data Focusing on the why and not the how The importance of understanding your vision Why success is largely down to building strong relationshipsWhat good business partnering looks likeThe differences between tactical versus commercial business partnering Being advocated for and championed without having to be in the roomWhy the strategic initiatives often hold the bigger commercial gainsDefining the measure of success before you define the solutionThe rise of Data & AI products and the difference it’s created Balancing the pursuit of commercial value with building responsible and ethical data & AI productsThe risks of neglecting ethical considerations Where accountability lies with humans and artificial intelligenceThe importance of humans in the loopThe relationship between risk and literacy The relationship between authentic leadership and ethics Thanks to our sponsor, Data Literacy Academy.Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

Pete Youngs, Managing Partner at Ortecha, dives into the intricacies of data operating models. He emphasizes their importance over data strategies, citing chaos in organizations lacking a model. Youngs discusses the difference between operating models and team structures and highlights why people are the most crucial element. He also explores trends like centralized versus decentralized models and the need for adaptability in the face of generative AI. Key insights include measuring success through clear metrics and fostering an organizational data culture for effective implementation.

In Episode 27, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Tom Betts, Group Data Director at Kingfisher Plc , where they discuss the complexities, challenges and opportunities of building a centralised data function at a group level to support multiple operating brands, which includes;His journey from DJ to Travel Agent to CDO Studying Artificial Intelligence in the early 2000sOrganising a centralised data domain to serve a multi-brand business Being the first data leader at group level The benefits and challenges of starting from a blank canvasThe challenge of attracting talent as a group company that people haven't heard ofBuilding a data-led customer experience as a pillar of a corporate strategyDeciding which capabilities sit within the operating companies versus what is centralised at the group level  Working out where the biggest opportunities lie across multiple brands Adopting different ways of working within different teams The importance of meeting each operating company where they are and not having a group approach to everything Dealing with different; cultures, literacy, adoption and maturity across the different brands The core use cases that are scalable and reusable across different operating companies  Building an orchestration framework for Generative AI tools Using gamification as a tool for education and upskilling The benefits of building working prototypes to drive buy-in and adoption Building a customer-facing generative AI solution Understanding and mitigating the risks of a customer-facing GenAi solution Considering the risks of inaction Why you’ll always learn more from just doingWhy the role of Chief AI Officer is not needed in isolation Why it’s important to have teams that are delivering DS/AI solutions to go as end-to-end as possible in a cross-functional way Why it’s faster to build things than it is to leverage what has been built Thanks to our sponsor, Data Literacy Academy.Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

In Episode 26, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Michelle Gansle, Chief Data, Analytics & AI Officer at McDonald's, where they discuss why, as one of the world's biggest brands, they still have a commitment to change and innovation and how Data & Analytics fuels that, which includes;3 fun facts that people don’t know about McDonald's The data and analytics goals of McDonald's The size and scale of the D&A capability at McDonalds Defining the right operating model for such a large enterprise Key D&A use cases in the fast food industry Why prioritisation should be the easiest part of the job Why even the biggest companies need to optimise and innovate to be successful Why one of the world's biggest brands has a commitment to change The tangible impact that certain innovations like drive-thru’s and delivery apps have had on their business What the landscape looked like before and after the pandemic Building a foresight team to predict what may happen in the future The three-legged stool concept Why the McDonalds culture has always been tied to innovationHow innovation is in service of the organisation's core business Why they view their size and scale as an incomparable advantageThe double-edged sword of being a large business Why relentless curiosity will make you successful Understanding the difference between what you could do versus what you should do The benefit of having a seat at the table Why it’s imperative to understand what “the end” is, and why Data & Analytics is not itWho really are the competitorsWhy they’re rarely first to market but are often fast followers The role that GenAI will play at McDonald's The 3 horizons of Generative AI How D&A was mentioned 42 times at investor meetings Thanks to our sponsor, Data Literacy Academy.Data Literacy Academy is leading the way in transforming enterprise workforces with data literacy across the organisation, through a combination of change management and education. In today's data-centric world, being data literate is no longer a luxury, it's a necessity.If you want successful data product adoption, and to keep driving innovation within your business, you need to start with data literacy first.At Data Literacy Academy, we don't just teach data skills. We empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. We're bridging the gap between business and data teams, so they can all work towards aligned outcomes.From those taking their first steps in data literacy to seasoned experts looking to fine-tune their skills, our data experts provide tailored classes for every stage. But it's not just learning tracks that we offer. We embed a deep data culture shift through a transformative change management programme.We take a people-first approach, working closely with your executive team to win the hearts and minds. We know this will drive the company-wide impact that data teams want to achieve.Get in touch and find out how you can unlock the full potential of data in your organisation. Learn more at www.dl-academy.com.

Irina Mihai, Director of Data at Adidas, shares insights on creating visibility for D&A teams, authentic leadership, decision-making, team building, and fostering psychological safety. Key topics include prioritizing projects, communication skills, organizational culture, and stakeholder engagement.

In Episode 24, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Chris Bannocks, Group Chief Data Officer at QBE Insurance, where they discuss how they are productionising GenAI use cases from scratch within 8 weeks, which includes; Being a CDAO/Group CDAO in multiple organisations/sectors The importance of international experience Being allergic to the term ‘data strategy’The impact that Gen AI will have on businessWhy GenAI/AI isn’t the solution to every problem Harnessing the value that GenAI can bring The top and bottom line opportunities of GenAI Why GenAI raises the stakes further for D&A teamsThe requirements of the semantic understanding of your data organization Going fast and hard on one opportunity to prove it could be doneUsing different mediums to gather 300 potential use cases Building things to be reusable and scalable Measuring the addressable opportunity Why they didn’t have to quantify the value before they got started Standing up a technical spike within 6 days to show what could possibly be done Having a 12 week deadline to get it done from a standing start with no capability How that capability has now reduced time to production to 8 weeks The collaboration needed with each leader from different business units The importance of creating a working product in productionWhy they avoided focusing on efficiency and focused on increasing revenue instead Avoiding enthusiastic experimentation Why tight deadlines helped to make decisions quickly and focus on scope/MVPWhy you should never start a piece of work without input from business stakeholders The challenge of ethical and bias considerations How they tackled GenAI education across the organisation The importance of having a human in the loopBuilding a team that can deliver Top pieces of advice for anyone about to embark on this journey

Caroline Zimmerman, Director of Data Product & Strategy at Profusion, talks about how private equity firms leverage data & AI for growth. They discuss the unique definition of value in PE, the role of data in value creation, and the challenges faced in the D&A community. The podcast explores the differences between PE-backed firms and others, the power of growth modeling, and the career opportunities for Data Leaders in PE.

Simon Ferriter, CEO at Anmut, discusses the valuation of data assets, the importance of understanding key data for decision-making, and the challenges organizations face in managing data effectively. He explores the financial methods for valuing data, the social impacts of data, and how putting a financial figure on data assets can drive improved decision-making and board involvement. The conversation highlights the under-investment in data management capability and the universal problem statements across industries.

Ranil Boteju, Group Chief Data & Analytics Officer at Lloyds Banking Group, discusses the power of purpose, evolving views of value creation, future analytics skills, potential of Generative AI, fostering a data culture, building unique teams, and the existence of the CDAO role in 5 years.

In this episode, Anthony Cosgrove, Co-Founder at Harbr, discusses building a data platform, challenges of data sharing, importance of scalability, empathy in data assets, and the value of diversity and flexibility in data management.