Driven by Data: The Podcast

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• Data Debrief: How to Translate your Work into Commercial Terms for an Interview 02.07.2026 39Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Diana Comsa, Global Director of Customer Data Products at Condé Nast, diving deeper into what it takes to reframe customer data as a growth engine rather than a marketing function, the value of professional friction in shaping better thinking, and the practical blueprint for translating technical output into commercial outcome.They cover:Why Diana's framing of customer data as a growth engine, rather than something that sits under a marketing initiative, struck such a chord, and what that reframing means for how data teams position their value across a businessDiana's account of learning to ask the right questions, shaped by mentors and managers who consistently challenged her, and why that kind of pushback, however uncomfortable in the moment, is often the biggest driver of professional growthThe distinction between challenge and conflict: why psychological safety isn't about agreement, but about creating an environment where pushback is understood as people wanting the best outcome, not personal frictionCatherine's take on choosing a boss over a company, why the person you report to, and the culture of professional friction they create, tends to shape a career more than a brand name ever willWhy relationship-building remains one of the most underrated skills in the data industry: fundamentally, the job is about changing what people think, do, and believe, and trust is what makes that possibleKyle's reflection on remote culture and professional friction, why strong company culture doesn't require co-location, but does require deliberate investment in getting to know people at a personal levelKyle's thought of the week: put on the spot by Catherine, Kyle lays out his blueprint for commercial articulation, the skill of anchoring data work to what a business actually cares about. He walks through the logic of tracing everything back to organisational goals and KPIs, then down through the decisions that influence them, before returning to his newspaper analogy: lead with the headline (the business outcome), not the small print (the technical how). Kyle unpacks the difference between an output (an improvement in data quality) and an outcome (what that improvement enabled for the business), and why board members and CFOs care almost exclusively about the latter. He also stresses that the narrative changes depending on the audience, a CIO, CFO, and CMO each need a different version of the same story. For anyone wanting to act on this today, his advice: ask your boss why you're doing what you're doing, build relationships with your CFO before you need them, and use tools like Claude to research a company's stated priorities from earnings calls and board updates.Plus, a few community shout-outs: registration is open for Driven by Data Live in October, the magazine is in production ahead of launch at the event, and the team is still on the hunt for book club nominations — reach out via community@orbitiongroup.co.uk.This episode explores why the technical work is only ever half the job — the ability to build trust, ask better questions, and translate output into outcome is what actually earns data leaders a seat at the table, and keeps them there.
• S7 | Ep 13 | Why Customer Data Is the Foundation of Business Growth with Diana Comsa, Global Director of Customer Data Products at Conde Nast 30.06.2026 52Min.

  In Episode 13 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Diana Comsa, Global Director of Customer Data Products at Conde Nast, where they discuss why customer data should be treated as a commercial growth engine rather than simply a marketing asset, and how solving the right customer problems unlocks long-term business value, which includes;Why the thread running through an unconventional career from strategy consulting to customer data has always been creating commercial value.Why understanding existing customers often creates more sustainable growth than simply acquiring new ones.How building a single customer view enables organisations to create deeper customer relationships and unlock new revenue opportunities.Why global organisations need consistency in customer identity, consent and architecture whilst empowering local teams to serve customers differently.Why defining business outcomes and success metrics before any work begins dramatically improves the chances of delivering value.Why customer data platforms should be designed around future business models rather than today's products and revenue streams.Why technology platforms and AI models are enablers, not the source of competitive advantage.Why AI strategy should always be an extension of business strategy and underpinned by strong data governance and quality.How AI is already helping organisations generate customer insight faster, improve reporting and increase engineering productivity.Why data monetisation isn't about selling data, but about increasing customer lifetime value through stronger customer relationships.Why the most successful customer data initiatives remain relentlessly focused on solving meaningful business problems rather than delivering technical outputs.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Debrief: Context, Culture & Clarkson's Farm 25.06.2026 48Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Justin Borgman, co-founder, CEO, and chairman of Starburst, diving deeper into why AI adoption keeps stalling at scale, the real cost of pointing powerful tools at the wrong problems, and what it means to build differentiated business capability rather than just better infrastructure.They cover:Why Justin's refreshingly candid starting premise — that messy, fragmented data is simply the reality most organisations are working in — cuts against the vendor instinct to promise a clean, unified solution, and why that honesty lands differently coming from a SaaS founderThe recurring pattern of businesses spending two to three years consolidating data into a single source of truth, only to arrive at the same "so what?" question — and why Starburst's founding premise of using data where it lives challenges the orthodoxy of centralisation as a prerequisite for valueThe context problem that no platform solves on its own: how the same number pulled from the same source can mean two completely different things depending on interpretation, and why that ambiguity at enterprise scale can quietly corrode trust in data across an entire organisationJustin's observation on where AI is delivering the clearest, most demonstrable value right now — coding — and what that signals for how skill sets in software development, data science, and adjacent technical roles are likely to evolve faster than most organisations are prepared forThe entry-level talent question neither businesses nor education systems have yet answered: as AI absorbs the work that once built foundational experience, where does the next generation of senior leaders come from, and who quality-assures the outputs of people who have never done the work themselvesCatherine's take on AI as fire: extraordinarily useful when understood and controlled, capable of running out of control very quickly when deployed at enterprise scale through FOMO rather than focus — and why a CFO's instinct to shut it all down is an entirely predictable response to cost spiralsKyle's reflection on the speed problem at the heart of this AI cycle: unlike previous technological revolutions, where the pace of change gave industries time to adapt and reskill, this one is moving fast enough that many organisations and individuals haven't yet worked out what adaptation even looks likeA moment from Catherine's farming background and the latest series of Clarkson's Farm that brings the AI transition into sharp relief — precision agricultural technology that looks futuristic to most farms but is closer than people think, and what the emotional weight of replacing a working horse with a tractor tells us about how humans really respond to transformationKyle's thought of the week: prompted by a pattern he's been tracking across executive search processes throughout 2026, Kyle reflects on a frustrating gap between capability and communication at the senior leadership level. The people not getting the roles aren't failing on technical grounds — they're losing out on energy and enthusiasm, inability to be concise, talking around questions rather than answering them, and failure to give specific examples. Kyle's concern is that these aren't just interview problems: they're signals of how someone will perform in front of a board or a CEO, and the skills that fix them can be self-taught and improved quickly. Catherine adds a practical tip for building confidence in high-pressure communication situations using AI tools like ChatGPT or Claude as a low-stakes rehearsal partner — and shares a striking example from a full studio broadcast that shows how dramatically even experienced communicators can disappear under pressure.This episode explores why the data and AI industry's biggest bottleneck isn't the models — it's the foundations, the focus, and the people trusted to lead the work and make the case for it.
• S7 | Ep 12 | The Real Bottlenecks Holding Back Enterprise AI with Justin Borgman, Co-Founder & CEO at Starburst 23.06.2026 50Min.

  In Episode 12 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Justin Borgman, Co-Founder and CEO of Starburst, where they discuss why the biggest barrier to AI success is no longer about models.The conversation explores why traditional approaches to data architecture are struggling in the AI era, how enterprises can overcome fragmented data estates, the importance of context and semantics, why many organisations remain stuck in pilot mode, rising AI costs, build versus buy decisions, agentic AI, and what the next three to five years of enterprise AI adoption are likely to look like, which includes;Why the vision of centralising all enterprise data into a single platform has never truly reflected reality.Why the AI industry's obsession with model selection is increasingly distracting organisations from the real challenges.How advances in foundation models are rapidly commoditising model performance and shifting attention elsewhere.What the true bottlenecks to AI adoption actually are.Where the clearest examples of AI delivering measurable value are today.Why many organisations remain trapped in POCs despite significant investment and executive attention.How the lack of context and semantic understanding continues to limit the effectiveness of AI in enterprise environments.Why trust, meaning and business context matter as much as access to data itself.Why AI success depends on; data foundations, analytics performance, enterprise context and trusted agentic interfaces.Why rising AI costs are becoming one of the biggest concerns for enterprise leaders and CFOs.Why data products are emerging as a practical solution for creating AI-ready context across the enterprise.Why separating context from physical data location creates more flexible and scalable architectures.Why executives are increasingly expecting answers rather than reports and dashboards.Why organisations should be building differentiated business capabilities rather than core platform infrastructure.How businesses that feel behind are often closer to the market than they realise.What the next three to five years could look like as AI becomes embedded into every major business function.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Debrief: Social Media Ban, Buses & CDO Future 18.06.2026 42Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with David Krauza, VP of Enterprise Data Strategy, Products & Governance at Comcast, diving deeper into the "arts and crafts" trap that derails data programmes, the discipline of building stakeholder trust before you need it, and what it really takes to drive the bus rather than ride it.They cover:Why David's mandated business school module ended up shaping his outlook on data leadership, and the recurring pattern of guests whose commercial thinking was forged outside a purely technical backgroundThe "arts and crafts project" analogy David's boss used to describe technically impressive work that never moves the needle, and why naming the difference between process-enjoyment and outcome-focus matters as much in data as it does in any creative pursuitWhy so much of the data and AI ecosystem gravitates toward exciting new models, tools, and techniques without tying the work back to specific goals, decisions, and KPIsDavid's framing that you have to help people before you need their help, and why the leaders who consistently land the biggest roles are the ones already putting into their networks and communities long before they need anything backCatherine's take on why this same principle defines external brand building, and why leaders who wait until they're job hunting to invest in relationships are always playing catch-up against those who started years earlierKyle's view that building relationships with future stakeholders is not a side project for a data leader, it is the job, every bit as much as overseeing platform delivery, governance, and architectureWhy David reframed the trust gap many data leaders face as a sequencing problem rather than a communication problem, and what that distinction means for how and when leaders should be reaching outThe "bus riders and bus drivers" analogy at the heart of the episode title, and why organisations hire a data leader precisely because they don't already know the answer, making it the leader's job to shape direction rather than simply execute instructionsWhy being a strong, detailed communicator changes the entire dynamic of a hiring conversation, and how that same skill plays out with stakeholders once someone is in the roleCatherine's practical tip for building interview and communication confidence using AI tools like ChatGPT or Claude as a low-stakes practice partner, and why consistent repetition beats waiting for natural talent to show upKyle's thought of the week: prompted by a message from a CDO at a crossroads in their career, Kyle reflects on why the CDO role isn't disappearing or resurging industry-wide so much as it's becoming entirely dependent on whether a business's leadership views data as a commercial value-creation function or a technology delivery capability. Where it's the latter, that responsibility increasingly sits with the CIO, and Kyle notes the early signs of broader transformation-style mandates emerging that fold CDO, CIO, and Chief AI Officer responsibilities into a single board-level role.This episode explores what it actually takes to drive value rather than just deliver outputs, the discipline of investing in relationships long before you need them, and why naming the gap between busywork and real impact is often the first step to closing it.
• S7 | Ep 11 | Bus Riders, Bus Drivers and the Strategy Problem Nobody Wants to Talk About with David Krauza, VP Enterprise Data Strategy, Products & Governance at Comcast 16.06.2026 51Min.

  In Episode 11 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by David Krauza, VP of Enterprise Data Strategy, Products & Governance at Comcast, where they discuss why strategic clarity and proactive stakeholder engagement are the keys to unlocking genuine business value from data and AI, which includes;Why the root cause of failed AI and data programmes is almost never the technology and almost always the absence of a clear business outcome.How to tell the difference between an organisation that has genuine strategic clarity and one that just has a compelling PowerPoint.Why a strategy without explicit trade-offs, knowing what you are not going to do, is no strategy at all.How "arts and crafts" projects quietly drain data programmes of focus, credibility, and commercial impact.Why retrofitting goals around work already underway creates a circular dependency that pulls organisations further from real value.Why the "bus riders and bus drivers" framework reframes what it means to be an effective data leader.Why waiting for perfect conditions before driving impact is one of the most common and costly habits of data leaders.How proactively building relationships with CFOs, COOs, and business unit heads before you need them is what separates influence from scrambling.Why the trust deficit most data leaders face is a sequencing problem, not a communication problem.How starting within your own team or with a single friendly stakeholder is the most practical way to begin building the bus driver muscle.Why most CDO mandates are structurally designed to deliver outputs rather than value and how that shapes the type of leader organisations end up hiring.How to navigate a broken mandate in practice and why challenging it in the interview room is riskier than it sounds.Why the incentive structures within data leadership roles have historically rewarded technical delivery over commercial impact.Why the data industry's technical origins created an archetype that is now working against the commercial value organisations actually need.How company size and culture determine whether data is treated as a strategic asset or an internal IT service and why that changes everything.Why organisations that started their data journey for the wrong reasons often find the perception too deeply embedded to shift from within.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Debrief: Juggling Plates, Commerical Value & Steven Bartlett Drinking Wine 11.06.2026 42Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Sarah Emerson, Group Director of Insight & Business Partnering at Howden, diving deeper into the growing importance of commercial thinking, business partnering, and the role relationships play in driving value from data.They cover:Why Sarah's background in finance and corporate strategy offers a unique perspective on data leadership, and how commercial acumen can become a powerful differentiator for leaders looking to influence organisational outcomesThe challenge of connecting data strategy to business strategy, why many organisations struggle to articulate strategic priorities clearly, and the practical ways data leaders can uncover them regardlessWhy curiosity about business value shouldn't be reserved for senior leaders, and how analysts at every level can develop a stronger understanding of commercial impactThe growing importance of business partnering as a dedicated capability, and how organisations can bridge the gap between technical teams and business stakeholders more effectivelyThe realities of operating model design, why federated approaches continue to gain traction, and the trade-offs organisations must consider when balancing proximity to the business with cost and complexitySarah's view that self-service analytics has largely failed to deliver on its original promise, and what that means for the future of data enablement and adoptionWhy understanding how business leaders are measured, incentivised, and rewarded can dramatically improve stakeholder engagement and increase adoption of data-led initiativesThe challenges of discussing performance, incentives, and accountability within organisations, and why trust and relationship-building remain critical leadership skillsThe evolving role of the Chief Data Officer, the increasing consolidation of data responsibilities back into CIO organisations, and what this shift could mean for the future of data leadershipHow AI has accelerated organisational debates around ownership, accountability, and transformation, with many businesses still determining where responsibility ultimately sitsThe emergence of broader transformation and innovation leadership roles that combine data, technology, AI, digital, and business transformation under a single mandateKyle's thought of the week: as more organisations place data leadership responsibilities back under the CIO, many of the lessons learned throughout the evolution of the CDO role risk being forgotten. The challenge now is ensuring that value creation, business engagement, and commercial impact remain at the centre of the agenda, regardless of where accountability sits.This episode explores the realities of commercial leadership in data, the importance of business partnering, and why understanding people, incentives, and organisational dynamics is often just as important as understanding data itself.
• S7 | Ep 10 | Commercial Thinking Meets Business Partnering: How to Make Data Actually Matter, with Sarah Emerson, Group Director of Insight & Business Partnering at Howden 09.06.2026 47Min.

  In Episode 10 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Sarah Emerson, Group Director of Insight & Business Partnering at Howden, where they discuss why commercial thinking and business partnering are the keys to uncovering business strategy and making data genuinely matter, which includes;Why having a non-technical background can give you a competitive edge as a data leader.How to infer business strategy when corporate goals are unclear or poorly defined.Why Sarah believes commercial KPIs should always take priority over internal data metrics.How finding out what a stakeholder is bonused on is the fastest route to their engagement.Why federated operating models consistently deliver more commercial value — and why they're expensive.Why self-serve analytics will never truly scale, particularly in relationship-driven industries like insurance.How conversational AI is poised to succeed where a decade of self-serve dashboards has failed.Why inconsistent data definitions across divisions remain the biggest hidden barrier to AI adoption.The importance of executive sponsorship in driving data culture — and what to do when you don't have it.How financially incentivising sales teams based on data adoption could become the industry's next big shift.Why embedded business partners bridge the gap between analytical output and real commercial impact.How to uncover business strategy when no one will give you the time or the meeting.Why defaulting to technical language is one of the fastest ways a data leader can lose the room.Why the business, not just the data team, needs to take accountability for driving data product adoption.How embedding analysts within business teams is what drives genuine commercial impact.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Debrief: Demystifying Data Leadership & Kyle makes a Bet on Topic Choice 04.06.2026 48Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Keith Moody, diving deeper into the realities of value creation, stakeholder management, and why the biggest barriers to success in data leadership are often human rather than technical.They cover:Why Keith's candid perspective stood out, and how some of the most honest conversations happen when leaders are able to speak without the constraints of corporate messaging and organisational politicsThe critical relationship between the CDO and CFO, why finance leaders remain the ultimate validators of value, and how a single nod of approval can determine whether an initiative succeeds or stallsWhy proving value still remains the defining challenge for data leaders, despite years of discussion around ROI, business outcomes, and commercial impactThe importance of stakeholder management, trust-building, and relationship development, and why no data leader succeeds without bringing others along on the journeyHow AI can be used as a practical leadership tool, from role-playing difficult stakeholder conversations to helping leaders navigate conflict, influence, and executive communication more effectivelyThe emerging ways data and AI leaders are using AI personally, including as a career coach, meeting assistant, productivity partner, and accessibility toolWhy change management isn't a phase of transformation programmes but the job itself, and how successful leaders recognise that adoption is an ongoing responsibility rather than a project milestoneThe reality that humans remain the most complex variable in any data strategy, and why technical excellence alone will never guarantee successHow previous experiences, organisational history, and leadership baggage influence every new data leader entering a role, whether they're inheriting success, failure, or scepticismWhy data leadership increasingly resembles sales, and how influencing decisions often requires changing perceptions, behaviours, and long-held beliefs rather than deploying new technologyThe growing importance of real-world communities, events, and human connection as AI-generated content becomes more prevalent and increasingly difficult to distinguish from human-created workWhy curiosity and imagination may become the defining skills that separate high-performing leaders in an era where access to technology becomes increasingly democratisedKyle's thought of the week: whilst many organisations claim they lack a clearly defined business strategy, the reality is that strategic priorities almost always exist somewhere. The responsibility for data leaders is to uncover them, build relationships with the people who own them, and connect their work to those outcomes rather than waiting for perfect documentation to appear.Catherine's thought of the week: we often have more control than we think. Whether it's improving stakeholder relationships, influencing difficult conversations, or navigating organisational complexity, the leaders who make progress are typically those willing to take ownership, seek support, and proactively shape their environment rather than waiting for conditions to improve.This episode is a practical discussion on the realities of leading change, proving value, and navigating organisational complexity, whilst exploring how human behaviour, relationships, and influence continue to matter just as much as technology in determining success.
• S7 | Ep 9 | The Mandate Gap: Why Data Teams Keep Failing to Deliver Commercial Impact with Keith Moody, VP of Analytics & AI 02.06.2026 53Min.

  In Episode 9 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Keith Moody, a renowned Data & AI Executive, where they discuss the relationship between the mandate of the CDAO and the results that data and analytics teams continue to deliver, which includes;How the absence of a clear value delivery mandate is the root cause of data being treated as a cost centre rather than a business asset.Why most CDO mandates are designed based on what organisations think the job is, not what it actually needs to be to generate commercial impact.How Keith built four analytics organisations across two companies and delivered over $500 million in incremental annual value.Why the data function's reporting line is rarely neutral, and how a once-thriving value-delivery team was reduced to an order-taking service desk.How convincing leadership that "no analytics could happen until data was perfect" brought an entire organisation to a standstill.Why CDOs who push for commercial accountability in interview processes face a catch-22.Why most interview processes focus on capability over delivery expectations leaving the value mandate undefined from day one.Why you should actively push for commercial targets.Why and how to routinely reframe the mandate once inside an organisation.Why the CFO should be the ultimate validator of any value numbers attributed to analytics.How reporting directly to the CEO removes prioritisation deadlock entirely.Why governance committees are a poor substitute for having a single accountable decision-maker at the top.How change management done at the end of a project is the single biggest reason analytics initiatives fail.Why blanket data literacy programmes are largely an admission of failure.How automating decision-making away from VPs was successfully sold internally.Why the AI investment cycle is repeating the exact same hype and collapse pattern seen with data science.How FOMO, shareholder pressure, and competitive optics drive organisations to invest in AI capabilities they haven't defined a use case for.How the first practical step for any CDO stuck in cost-centre mode is to audit their existing portfolio and how to do so.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Debrief: Navigating the Executive Journey with Confidence and Patience 28.05.2026 39Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where host Catherine Dowden-King and, this time, special guest Nirali Patel, unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Nirali reflect on the conversation with JoAnn Stonier, Lara Izlan and Abbi Agana, diving deeper into what it actually takes to step into a NED role, where your mindset needs to go, and how your patience may be your best asset.
• S7 | Ep 8 | How to become a NED? with JoAnn Stonier, EX-CDO Mastercard, Lara Izlan, Director of Data, ITV & Abbi Agana, CEO, Leathermarket JMB 26.05.2026 1Std. 2Min.

  This is a special episode of the Driven by Data Podcast, where we publish our recent NED webinar!Featuring JoAnn Stonier, Ex-CDO Mastercard, Lara Izlan, Director of Data, ITV and Abbi Agana, CEO, Leathermarket JMBOur speakers shared career trajectories into NED roles, emphasising diverse backgrounds (data, media, housing, finance, privacy) and recurring themes: continuous change, giving back, mentorship, and strategic coaching mindset.How to break into NED roles: build a board CV, clarify your 'why' and value proposition, leverage networks, observe boards, speak to chairs and current board members, and use targeted communities and programs.Differences between nonprofit and for-profit board experience: governance skills transfer but scale and profile matter; large/high-profile nonprofits can be gateways to commercial boards while small trustee roles mainly develop governance experience.What boards look for: subject-matter expertise gets you noticed, but financial literacy, generalist judgement, governance and fiduciary responsibility are baseline requirements; c-suite title is not strictly necessary.Practical expectations of NED work: time commitment varies (frequently ~20–25 hours/month for active boards), includes prep, board meetings, committee work, possible ad-hoc meetings and retreats, and requires doubling stated prep time as a rule of thumb.Common pitfalls and mindset shifts: NEDs must adopt 'noses in, hands out' approach, avoid being a hands-on operator, focus on strategic advisory and support rather than doing the work for exec teams.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Brief: Stop asking permission, and claim your lane (and the whole pool whilst you're at it) 21.05.2026 30Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Edward Chenard, diving deeper into what it actually takes to step outside your lane as a data leader, make yourself redundancy-proof, and shift the conversation from technical delivery to commercial impact.They cover:Why Edward's unattached, portfolio career status meant the episode landed differently, and why the growing constraints around PR and corporate communications are making truly candid guest conversations increasingly rare on podcastsHow the fractional and advisory model is reshaping what value creation looks like in data leadership, and why organisations often get more commercial clarity from a contracted external than a full-time hireWhy delivering exactly what the job spec asks of you is, in reality, a risky career strategy for any enterprise data leader or CDOThe mindset behind becoming redundancy-proof, and why Edward's firsthand experience of layoffs shaped his willingness to step outside his mandate rather than stay safely within itThe "ask forgiveness rather than permission" approach to data leadership, and why professional arrogance, done with nuance, is often what separates those who reshape mandates from those who get trapped by themWhy "talk numbers, not tech" should be on a post-it note in every data leader's office, and how reading the room determines whether your message lands or loses the room entirelyThe importance of knowing when to geek out with peers at industry events versus when to translate everything into conversion rates, revenue targets, and business outcomes at the board levelHow skill and will both play a role in whether data leaders break out of their comfort zones — and why going back to what feels familiar is the enemy of executive credibilityWhy sitting at "the children's table" is a mindset problem as much as a structural one, and what it actually takes to earn a seat in the room where the real decisions are madeThe growing challenge of getting guests to speak candidly on record as geopolitics and economic uncertainty push businesses toward risk aversion and comms-approved messagingKyle's thought of the week: why perfect conditions don't exist — and why waiting for the mandate to fix itself, the business to catch up, or the industry to finally get it right is a strategy that history has already proven doesn't work. The leaders who succeed are the ones who go and create the conditions themselves.Catherine's thought of the week: what happened when Orbition ran a NED webinar that LinkedIn declared a dead format — 67 senior leaders from across the UK, US, and Europe later, and the lesson is clear: don't let someone else's data point on what doesn't work override what your own experience and evidence tells you is worth trying.This episode is a practical, honest unpacking of what it means to go beyond the mandate, not by working harder or taking on more, but by having different conversations, building broader context, and being willing to step into rooms that weren't originally part of the brief.
• S7 | Ep 7 | From Cost Centre to Revenue Engine: How to Make Data Pay for Itself (and Then Some) with Edward Chenard, Fractional CDAO 19.05.2026 1Std. 2Min.

  In Episode 7, of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Edward Chenard, Fractional Chief Data and Analytics Officer, where they discuss how data leaders can break free from the cost centre trap and drive measurable, quantifiable business value, having personally delivered over $2.5 billion in revenue across Fortune 500s and start-ups alike, which includes;How a career in product management at GE laid the foundation for an outcome-first approach to data leadership.Why not having a seat at the table is not an excuse and why the biggest commercial wins came from several levels below the C-suite.How to read the type of organisation you are in and choose your influence strategy accordingly.Why the shift from AI-as-tool to AI-as-strategy matters for how data leaders position themselves now.Why data teams are correctly perceived as overheads.Building a personalisation platform at Best Buy that generated over $1 billion in revenue.Why identifying the metrics the C-suite actually obsess over is the only way to get and keep their attention.Why delivering what the job description says is the riskiest career move a data leader can make.How a predictive shipping tool built in four months turned a century-old logistics company into a recognised innovator.Why agreeing attribution with business stakeholders before the work starts is the only way to get the credit you deserve.Why the individual contributor mindset of doing what you are told actively works against data leaders when they step into leadership roles.Why data leaders need to think like intrapreneurs, owning a P&L and speaking the language of finance, VCs, and private equity rather than just tech.Why a background in international business and theology turned out to be better preparation for data leadership than a technical degree.Why philosophy and physics majors often outperform computer science graduates in data roles because thinking through problems without solid facts is the real differentiator.Why IT cultures that lead with process are structurally incapable of delivering transformation.Why training your team on AI regardless of what the C-suite thinks is a leadership obligation, not insubordination.How Edwards frameworks for moving data teams from dashboard builders to decision-makers are publicly available.Why it is human as the loop, not human in the loop, and why AI will quickly expose those who have been faking it.Thanks to our sponsor, Data & AI Literacy Academy.Data & AI 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 & AI literacy first.At Data & AI Literacy Academy, they don't just teach data skills. They empower individuals and teams to think critically, analyse effectively, and make decisions confidently based on data. They'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 & AI 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 they offer. They embed a deep data culture shift through a transformative change management programme.They 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.
• Data Debrief: Elephants, Driving & LinkedIn Debates 14.05.2026 43Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday’s episode, share what’s been on their minds, and explore the realities of leadership, culture, and capability across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Dru Patel from the FA, diving deeper into the human side of data leadership, from storytelling and self-awareness to the commercial realities of what it actually takes to succeed at the executive level.They cover:Why Dru Patel’s approach to storytelling and communication stood out as one of the most compelling conversations the podcast has hosted to dateHow technical capability alone has become “table stakes” in data leadership, and why the differentiator is now influence, communication, and the ability to shape perceptionWhy “soft skills” might be the most damaging phrase in the industry, and how cultural buy-in and human-centred leadership are often the real drivers of ROIThe uncomfortable reality that working hard and being technically brilliant doesn’t automatically lead to progression, and why self-awareness is becoming a critical leadership traitHow data leaders can shift conversations away from platforms, dashboards, and governance, and toward decisions, business outcomes, and commercial impactWhy organisations still struggle with the perception of data teams as back-office technical functions, and how that perception shapes hiring, mandates, and ultimately failureThe difference between data literacy and data culture, and why culture is what happens when nobody is watchingHow lived experience, industry context, and organisational history shape expectations around data quality, trust, and value creationWhy many CDO mandates continue to fail, not because the individuals lack capability, but because organisations hire for technical delivery while expecting commercial transformationThe growing disconnect between what data leaders are hired to do and what boards actually expect them to achieveThey also dig into the future of data leadership and organisational accountability:Why businesses are now entering their third, fourth, and even fifth iteration of the CDO role, and what those repeated resets reveal about the maturity of the marketHow hiring behaviour has unintentionally incentivised technical specialisation over commercial leadership for more than a decadeWhy asking questions around decisions, KPIs, revenue targets, and business performance during interviews can quickly reveal an organisation’s true perception of data leadershipKyle’s thought of the week: why the debate around failed CDO mandates is becoming too polarised between “it’s the organisation’s fault” and “it’s the individual’s fault,” and why the reality sits somewhere in the middleCatherine’s thought of the week: what happened after asking LinkedIn for web developer recommendations, and what the overwhelming response revealed about vendor outreach, personalisation, and the growing problem of AI-generated sales noiseThey also discuss:Why AI has enabled many organisations to operate “badly at scale, but faster”How senior leaders increasingly avoid broad vendor engagement unless there is an immediate needThe importance of building trusted communities where candid conversations can happen openly and safelyWhy Orbition Group’s private membership community continues to grow as leaders look for more meaningful peer-to-peer discussion away from the public spotlightThis episode is a candid exploration of the skills gap that rarely gets discussed in data and AI leadership, not the technical gap, but the commercial, cultural, and human capability gap that increasingly determines who succeeds, who gets overlooked, and why so many organisations still struggle to realise value from data.
• S7 | Ep 6 | Embracing Failure: The Human Side of Data Leadership with Dru Patel, Data Lead at The Football Association 12.05.2026 57Min.

  In Episode 6, of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Dru Patel, Data Lead at The Football Association, where they discuss how embracing failure fuels a human-centred approach to data leadership that unlocks adoption, trust, and real organisational change, which includes;How an unconventional background spanning Kenya, the Cabinet Office, and a life coaching qualification shaped a distinctly human approach to data leadership.Why hard work alone has a ceiling, and how the first ten years of Dru's career proved that technical output without soft skills will only take you so far.Why starting with the "why" is the most powerful tool a data leader has for driving engagement, adoption, and business buy-in.How asking "why" five times gets you to the real root of what a stakeholder actually needs, and why most data teams stop at the first answer.How the gap between data teams and the business is normal, and why failing to challenge it with the right questions is the real problem.Why data teams need to push back on the brief rather than just building what's requested.How a dashboard that stops being used isn't always a failure, and why it often signals that the business is ready to ask bigger questions of the data.Why data literacy and data culture are not the same thing, and what it actually takes to move from one to the other.How the six blind men and the elephant illustrates what happens when everyone is right in their own context and nobody is looking at the whole picture.Why treating data like the organisation's own money, rather than a technical function, is the mindset shift that drives real literacy.Why data leaders take failure far harder than anyone else in the room, and what a 1980 psychology study reveals about the stories we tell themselves.How building a PPE supplier system in six days during COVID taught Dru that perfection is the enemy of progress.Why owning failure openly builds more trust than silence, and how to reframe the conversation from blame to improvement.How imposter syndrome shows up in data leadership, why it never fully goes away, and what mentors and trusted voices can do to help reframe it.Why nerves and excitement are the same feeling, and how the most effective leaders choose which one to act on.Why listening, really listening, before jumping to solutions is the soft skill most data professionals underestimate.How a human-centred lens, not a technical one, is what ultimately bridges the gap between data teams and the decisions that matter.
• Data Debrief: Curiosity Is the New Python 07.05.2026 38Min.

  Welcome to another episode of the Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday's episode, share what's been on their minds, and explore what's really happening across the data and AI landscape.This week, Catherine and Kyle reflect on their conversation with Richard Masters, VP of Data & Analytics at Virgin Atlantic, diving deeper into the themes that matter most right now, from decision-led data strategies to the realities of building for reusability in an AI-driven world.They cover:Why Virgin Atlantic's surprisingly lean fleet of 44 planes is a masterclass in doing more with less, and what data teams can learn from itRichard's astrophysics background and how the principle of signal over noise shapes his entire approach to dataWhy the North Star of any data function should be decision support, and how working backwards from decisions changes everythingThe shift from "collect all the data" to "what decisions are we trying to impact" — and why that transition is still hard for most organisationsThe move from single-use data projects to reusable, scalable products, and why building for one use case is the old way of thinkingHow AI is democratising business capability, the rise of the "builders vs coders" mindset, and what that means for how data teams are structuredWhy fewer platforms, used well, will beat a sprawling vendor stack, and what that means for the vendor community going forwardThey also dig into the future of talent and skills in data:Why critical thinking, curiosity, and imagination are becoming more valuable than technical qualificationsHow the widening talent pool challenges universities and educators to stop being anti-AI and start teaching people how to use it responsiblyWhy neurodiversity and unconventional backgrounds will be a competitive advantage in an AI-augmented worldCatherine's thought of the week: why data professionals have a duty to educate those around them as AI misinformation spreads, from the boardroom to the toddler groupKyle's thought of the week: why the CDO role may be heading toward a fractional, advisory model, and what that split between strategy and execution means for the future of data leadership hiringThis episode is a candid look at where data is heading, where the real value is created, and why the leaders who thrive will be the ones who connect commercial strategy to the decisions that actually move the needle.
• S7 | Ep 5 | Signal Over Noise: The North Star of Decision Support with Richard Masters, VP Data & AI at Virgin Atlantic 05.05.2026 48Min.

  In Episode 5, of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Richard Masters, Vice President of Data & AI at Virgin Atlantic where they discuss how a "signal over noise” mindset helps cut through complexity, and enables better decision-making and real business impact, which includes;How an astrophysics background shaped a “signal over noise” mindset for data and decision-making.How reducing data noise and surfacing the right signal drives meaningful business action.Why decision support should be the North Star for every data team.How aligning data work to business strategy requires constant iteration, challenge, and course correction.Why iterative improvement wins the day.How data context and metadata are critical to trust, usability, and adoption.Why data lineage, governance and trust are foundational to scaling AI successfully.How prioritisation should be driven by impact vs feasibility, not technical curiosity.Why a product mindset enables reuse, scalability, and faster value realisation.How platforms act as the governed foundation for reusable data, AI and decision-making capabilities.Why simplifying to fewer platforms improves trust and speed of delivery.How observability and adoption tracking link data products to real decision-making and P&L impact.Why AI success depends on evaluation frameworks (“is it right?”) and human-in-the-loop validation.How AI is shifting roles from coders to builders using and diversifying D&A talent beyond traditional STEM backgrounds.
• Data Debrief: Push Back or Play Along? The Tough Truth About Data Leadership Today 30.04.2026 37Min.

  Welcome to another episode of Data Debrief, the companion show to Driven by Data: The Podcast, where hosts Catherine Dowden-King and Kyle Winterbottom unpack Tuesday’s episode, share what’s been on their minds, and explore what’s really happening across the data and AI landscape.This week, Catherine and Kyle reflect on the conversation with Peter Everill, diving deeper into the themes that matter most right now, from decision-led data strategies to the realities of operating in an AI-hyped market.They cover:Why the market is becoming saturated with “AI-everything” messaging, and how vendors are losing differentiationThe growing gap between activity and impact, and why many data teams are busy but not moving the needlePeter Everle’s decision-making framework, and why focusing on decisions that impact P&L is the only thing that really mattersThe cultural challenge of empowering teams to push back, and why most organisations still operate like a ticketing service deskThe tension data leaders face between challenging the business vs protecting their role, especially under board-level pressure to “do AI”Why this AI cycle feels different from previous hype cycles, and how pressure is now coming from every function, not just ITWhat separates leaders who deliver real commercial value from those who don’tThey also dive into the current hiring market:Why data leadership hiring has become overwhelmingly saturated, with thousands of candidates for a single roleHow CVs are becoming indistinguishable in the age of LLMsWhy job applications are no longer an effective strategy on their ownThe shift from traditional hiring to network-led, trust-based recruitmentAnd what candidates must do differently to stand out in a market that’s noisier than everThis episode is a candid look at the realities of data leadership today, where every path carries risk, AI pressure is unavoidable, and success comes down to judgement, influence, and the ability to focus on what truly drives value.
• S7 | Ep 4 | Why Data & AI Transformation Fails Without Decision Transformation with Peter Everill, Head of Data Product at IAG Loyalty 28.04.2026 53Min.

  In Episode 4, of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Peter Everill, Head of Data Product at IAG, where they discuss why most organisations still invest heavily in data, analytics and AI capabilities without ever connecting that work to the handful of decisions that truly move business performance. They break down why the future of data transformation is really decision transformation, sharing a practical five-layer framework that links performance visibility, root cause, budget trade-offs, automated decisioning and enterprise optimisation directly to P&L impact, which includes;Why the real purpose of data and AI is not building outputs, but improving the decisions that materially change business performance.How Peter’s career shifted from historical reporting into transforming decisions and workflows that directly influence operating models.Why the biggest capability gap in most organisations is linking technical capability to strategy, commercial priorities and P&L outcomes.How starting with business decisions instead of tools helps avoid the common trap of capability-first transformation.Why stakeholder requests that cannot be tied to action or performance change should rarely make the roadmap.How bottom-up demand creates sprawl, fragmented priorities and lots of activity that never ladders up to enterprise value.What the five decision layers are that connect data transformation directly to P&L impact.Why performance visibility is the first step to stop leadership teams debating numbers instead of making decisions.How root cause analysis becomes the turning point where prioritisation, ownership and commercial focus become clear.Why smarter budget trade-offs matter more than simply asking for more investment.How AI creates the most value when it improves decision quality before automating workflows at scale.Why automating workflows without improving the decision just helps organisations get to the wrong answer faster.How enterprise optimisation exposes where one team’s success is unintentionally creating cost or lost sales elsewhere.Why local optimisation inside siloed teams often damages enterprise performance without leaders realising it.How making performance problems visible requires executive sponsorship because transparency can create organisational tension.Why root cause is usually the point where leaders realise they still lack clarity on what really drives performance.How both business leaders and data leaders should start by focusing on one decision that matters most.