Driven by Data: The Podcast

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  S7 | Ep 20 | Your Data & AI Investment Portfolio: How to Decide What Gets Funded with Nick Zervoudis, Founder at Value from Data & AI 18.08.2026 58мин

  In Episode 20 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Nick Zervoudis, Founder at Value from Data & AI, where they discuss why so many data and AI teams struggle to demonstrate measurable business value — and why the real failure almost always happens upstream, long before anyone tries to articulate it.Nick makes the case that "we can't prove our value" is usually a symptom, not the disease: teams solve the wrong problem, skip the value case, or hand off value realisation to no one. Along the way they get into his five-point diagnostic framework, how to build a credible back-of-the-envelope ROI estimate before a line of code is written, how to prioritise a portfolio of opportunities, and where AI productivity savings are real versus imaginary.They also discuss:Why the inability to demonstrate value is usually an upstream failure, not a communication problem.What Nick's five-point framework reveals: wrong problem, wrong solution, poor execution, no measurement, weak communication.Why data teams keep solving the wrong problem by starting from technology instead of the problem itself.How to separate the "problem space" from the "solution space" before reaching for a tool.Why 70–80% of data teams operate as order takers rather than true collaborators.Why being ROI-positive is only the entry ticket, not a reason to do a project.What criteria actually decide prioritisation: return, payback speed, implementation readiness, and strategic relevance.Why nothing a data team builds has inherent value without an owner on the business side to realise it.How to build a credible back-of-the-envelope value case before anything gets built.Why estimating value is far easier to learn than the technical craft most data people already have.How to get stakeholders to correct a rough estimate rather than hand them a blank sheet.Why "how will we measure success?" is the most useful question you can ask when scoping work.What the bystander effect has to do with data teams quietly failing to create value.How framing work around outcomes turns engineers from code-writers into problem-solvers.Why hours saved rarely become money on the balance sheet.What the five-to-six buckets of productivity value are, and why you must never double-count them.Why some AI investment should deliberately have no business case at all.How Monday.com turned a five-week experimentation window into a $100M ARR product.Why blanket self-serve analytics or company-wide AI licences often set you up for failure.What first steps a CDO should take to re-prioritise a roadmap around measurable value.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/driven
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  Data Debrief: Wildfires, New things at Orbition, and teases of things to come! 13.08.2026 33мин

  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 Marion Shaw, Senior Director of Data, Analytics and Data Management at Cencora, and her new book on data culture, before digging into why the "data culture" debate keeps circling the same questions, and why the answer almost always comes back to people rather than technology.They cover:The wildfires spreading across South Wales and Europe, and how AI and drones are being deployed in France to spot smoke earlier, distinguish dust from smoke, and cut down the false positives that waste emergency resourceThe bigger climate paradox facing the industry, from record-wet winters followed by hosepipe bans and water mismanagement, to the uncomfortable reality that the data centres powering AI advances are themselves enormous consumers of waterWhy absolutism helps no one, and how the healthiest position on AI, sustainability, and change sits somewhere in the messy middle rather than all-in or all-outHow incentives quietly shape behaviour, illustrated by the fact that three flights across Europe can cost less than a single train from Manchester to London, and why people ultimately do what they're incentivised to doCatherine's latest build for the Orbition community: a NED Opportunity Finder, a live, daily-updating table of listed non-executive director roles showing remuneration, location, and whether the board is public or private, free to access for registered community members, and why she's so keen to see more data leaders move into board positionsWhy Marion's candour hit home, especially the reminder that you simply cannot force people to be interested in or care about data, and why that truth is uncomfortable but essentialHow technology becomes a distraction, the "shiny thing syndrome" that pulls focus away from the outcomes that actually matter, and why that's the real answer to "why now"The endlessly debated question of whether "data culture" even exists, why the industry loves arguing over semantics no one outside it cares about, and why every organisation already has a data culture, somewhere on the spectrum from barely-there to full tiltWhy culture and outcomes feed each other rather than being an either/or, and how influencing behaviours and showing results almost always happen in tandemWhy every business claims to be "data-driven," how the reality usually differs, and why a new CDO's first 90 to 100 days is really about working out where the organisation actually sits versus where leadership thinks it doesThe "slippery shoulders" problem, and why nothing improves or gets maintained unless someone genuinely owns itWhy you can't see your own culture from the inside, and how stepping out to network, attend events, and compare notes with peers is often the only way to know whether you're ahead, behind, or better off than you thoughtA look ahead to the Orbition magazine landing in October, featuring a data leader who hasn't spoken publicly in over two years, alongside mentor and mentee stories and perspectives from beyond the CDO communityThe Director of Police AI role at the College of Policing, and how its rigid entry criteria expose the same old problem seen across data leadership: job descriptions that bear little resemblance to what organisations actually want from the roleKyle's thought of the week: most job descriptions are disconnected from what the business actually needs. Organisations have learned to use the right language, asking for leaders who'll work with the board and use data to drive commercial performance, then listing purely technical requirements underneath. Until that gap closes, the mismatch between what's advertised and what's wanted will keep repeating itself. Fundamentally, every organisation already has a data culture; it simply sits somewhere on a spectrum, and the job is to understand where before trying to move it.Catherine's thought of the week: you rarely recognise your own culture until you step outside it. Whether it's trust versus micromanagement, or how your data leaders are really perceived, the comparison only becomes clear when you go out, meet people, and see how others operate. And the honesty applies inward too, because no organisation describes itself as not caring about data, so the real work is uncovering where it genuinely stands.This episode is a candid, wide-ranging conversation on data culture, ownership, and incentives, and a reminder that the hardest problems in data and AI leadership remain stubbornly human, no matter how much the technology moves on.Housekeeping: The podcast is now broadcasting on LinkedIn Live. To watch along in real time, head to the Driven by Data Productions page on LinkedIn and follow it. We go live with each episode every Tuesday at 1pm BST, and our guest often joins the comments to answer your questions. Keep an eye out for upcoming events towards the end of the year, including Driven by Data Live, where Catherine will be handing out physical copies of the new magazine.
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  S7 | Ep 19 | Technology Is Easy, People Are Hard with Marion Shaw, Senior Director, Data Analytics and Data Management at Cencora 11.08.2026 50мин

  In Episode 19 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is rejoined by Marion Shaw, Senior Director, Data Analytics and Data Management at Cencora, where they discuss why building a genuine data culture is a people and process problem rather than a technology one, and what it actually takes to embed trust, curiosity and business value into how an organisation works with data.The conversation centres on Marion's new book, Why Data Culture Matters, and digs into why trust is the single attribute with the biggest ripple effect on a data culture, plus the "AI paradox" — why people distrust their own data yet blindly trust the same data when an AI hands it back to them.They also discuss:Why so many organisations pour money into technology yet still fail to see the returns.What Why Data Culture Matters covers, and who Marion wrote it for.How data culture should reflect and be built around a company's existing business culture.Why there is no universal blueprint for data culture — every organisation's version looks different.How giving people access to data without teaching them to interpret it undermines self-serve initiatives.How trust is built through recognisability, explainability, transparency and repeatability.Why CDOs should never promise something they can't actually deliver.What the "AI paradox" means for organisations rolling out generative AI tools.How younger generations risk losing critical thinking skills by taking AI output at face value.Why healthy scepticism should be a core attribute of every data culture, regardless of industry.How to measure progress in building a data culture beyond simple adoption metrics.Why dashboard adoption is a flawed proxy for a genuinely data-driven culture.Why data teams need to shift from being "order takers" to acting as business partners.What the biggest mistakes are that organisations make when trying to mandate a data culture from the top down.Why flexibility, not rigid planning, is the mindset shift data leaders need most.Why influence and communication skills are essential to embedding a data culture successfully.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/driven
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  Data Debrief: The AI Rollback & Regrets 06.08.2026 39мин

  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 Kyle's conversation with Laura Fiacco, Founder of Adaptive Assets, exploring why communication, influence and commerciality remain some of the most overlooked skills in data leadership. Alongside the episode discussion, they dive into LinkedIn's apparent AI U-turn, the growing challenge of AI-generated content, and why the future of data leadership may be less about technology and more about transformation.They cover:Why LinkedIn, Snapchat and Substack are all taking steps to tackle AI-generated content, and what it says about organisations pushing AI adoption before understanding its long-term consequencesWhether we're heading towards a world where overusing AI becomes just as much of a performance concern as not using it at allThe ethical grey areas surrounding AI-generated communication, from political statements to funeral tributes, and why context matters far more than blanket rulesLaura's perspective on communication as a skill that compounds over time, and why nobody starts by presenting to a thousand peopleWhy communication isn't synonymous with public speaking, but instead about translating technical concepts into language that business leaders understand and care aboutThe importance of influencing without authority, building relationships, and developing the commercial mindset needed to turn technical work into business valueHow organisations continue to undervalue communication, relationship building and commerciality because they're harder to measure than technical capabilityPractical ways data professionals can develop these skills themselves, including writing, voice conversations with AI, and using large language models as personalised coaching toolsWhy curiosity, listening and asking better questions are just as important as being able to communicate confidentlyKyle's reflections on why transformation is becoming the next major destination for senior data leaders as technology becomes less of the challenge and organisational change becomes the real differentiatorCatherine's comparison between today's AI leadership roles and the "e-business" and "Chief Internet Officer" titles of the dot-com era, and why AI leadership may ultimately become absorbed into every business function as the technology maturesProgramming note: If you've been following Catherine's recent LinkedIn series on the evolution of executive technology roles, this episode expands on that conversation, exploring why today's AI job titles may eventually follow the same path as digital and internet leadership before them.This episode is a reminder that while AI continues to dominate headlines, long-term success still depends on the fundamentals: communicating clearly, influencing effectively, building relationships, and helping organisations change, not just implement new technology.
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  S7 | Ep 18 | Influence without Authority by Communicating like an Executive with Laura Fiacco, Founder at Adaptive Assets 04.08.2026 51мин

  In Episode 18 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Laura Fiacco, Founder of Adaptive Assets, where they discuss why communication, influence and commercial thinking have become the competitive advantage for modern data professionals, and how learning to communicate like an executive is now just as important as technical expertise.They also discuss:Why influence without authority is the defining skill for modern data leaders.The 4 quadrant brain framework for tailoring communication to different thinking styles.Why successful influence starts by understanding other people's goals before presenting your own ideas.Why relationship building happens outside the meeting room, not inside it.How to communicate technical work in a way executives immediately care about.Why every presentation should start with the business outcome, not the analysis.Why data professionals often answer questions that were never asked.What data leaders can learn from sales discovery.The questions every data professional should ask before proposing a solution.Why understanding failed attempts and hidden assumptions leads to better stakeholder conversations.How to influence when different executives have conflicting priorities.Why peer success stories influence behaviour more effectively than data alone.Why communication, influence and leadership should become measurable career progression criteria.Practical habits that help build influence, trust and credibility every day.Why AI will make communication, influence and judgement more valuable than technical expertise.Why every person needs to understand their specific role in delivering the wider business objective.Why every business strategy is built on assumptions that data should validate or challenge.How to align stakeholders when everyone interprets the same strategy differently.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.
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  Data Debrief: Patios, Politics & the Perils of Meta Glasses 30.07.2026 48мин

  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 returns from a two-week break to catch up with Kyle on the conversation with Joanne Riseborough, Group Data Management and Culture Director at Lloyd's Banking Group, alongside a wide-ranging catch-up covering AI ethics, the future of education, and why context is everything when it comes to new technology.They cover:Why Joanne's willingness to repeat the same simple truth throughout her episode, rather than apologise for it, was itself the standout takeaway, and why data management has long been the least glamorous but most under-resourced part of the data value chainHow the AI boom has quietly made data management one of its biggest beneficiaries, as businesses scramble to build the foundations needed to use their new tools effectivelyWhy a job title that puts "management" and "culture" side by side gets to the heart of why the two are inseparable, and can't succeed without one anotherCatching up on two episodes missed while on holiday: Priya's candid take on the CIO-CDO relationship, and the idea that failing to draw clear lines of accountability creates "competition for relevance" between the two roles, not collaborationA conversation with Vin on turning AI into revenue, the value of concrete company examples over abstract theory, and how his "information flywheel" concept has moved from a future prediction to something organisations are now actively chasingA detour into Meta's AI glasses, why the debate over them (cool or creepy?) is really about context and nuance, and why platforms like LinkedIn struggle to hold space for anything in betweenA tie-back to Catherine's own past research using facial recognition technology, and how the same tool can be a public safety asset in one context and deeply troubling in anotherWhether AI ethics has a genuine seat at the boardroom table, or whether "activity as the barometer of perception" makes leaders reluctant to be the one applying the brakesAndy Burnham's call for parity between university and vocational routes, what it might mean for how people enter data careers, and the idea (borrowed from a recent Taylor Culver conversation) that data is a skill rather than a career path in its own rightWhy the debate over LLMs in university coursework mirrors the harm-reduction argument in sex education: teaching safe, responsible use beats an outright banProgramming note and community shout-out: Catherine's back from a two-week camping-and-patio-laying hiatus (send help, or bricklaying tips), and registration for Driven by Data LIVE is officially open, with a growing list of bespoke, invite-only events also on the horizon. Make sure you're on the events list to hear about them first.This episode is a reminder that the unglamorous, unsexy fundamentals, data management, clear accountability, honest conversations about ethics, are usually what make the shinier stuff actually work.
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  S7 | Ep 17 | Data Management: The AI Boom's Biggest Winner with Joanne Riseborough, Group Data Management and Culture Director at Lloyds Banking Group 28.07.2026 41мин

  In Episode 17 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Joanne Riseborough, Group Data Management and Culture Director at Lloyds Banking Group, where they discuss why the AI boom has quietly made data management one of the most strategically important disciplines in the boardroom.They explore why AI is shining a spotlight on data quality, governance and culture, how large enterprises balance modernisation with legacy technology, and why organisations that invest in strong data foundations will be best positioned to realise meaningful value from AI.They also discuss:Why AI has made data management more important than ever.Why data quality has moved back onto the boardroom agenda.How organisations should define what "good enough" actually means.What data quality should actually be measured against.How large enterprises balance modernisation whilst continuing to operate critical legacy platforms.The unique data management challenges created by hybrid cloud and on-premise environments.How data culture influences the success or failure of AI adoption.Why data and AI literacy is becoming a strategic capability rather than a technical nice-to-have.How Lloyds Banking Group is building capability through education, practitioner communities and leadership development.Why executive sponsorship remains one of the strongest predictors of successful AI transformation.How organisations should balance fixing today's problems whilst investing in tomorrow's capabilities.Why continuous monitoring and data observability will become fundamental components of modern data management.How reusable data products can accelerate both governance and AI adoption.Why organisations should think about both data for AI and AI for data.Why responsible AI starts with trusted data, lineage and governance rather than model oversight alone.How central strategy and standards can successfully coexist with federated ownership and delivery.Why organisations should assess their data maturity before accelerating AI ambitions.Why the strongest AI strategies are built on strong data foundations rather than stronger AI models.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.
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  S7 | Ep 16 | The CIO vs CDO: Where the Tension Really Comes From with Priya Enefer, Chief Information Officer at Hakluyt & Company 21.07.2026 55мин

  In Episode 16 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Priya Enefer, Chief Information Officer at Hakluyt & Company, where they discuss why the tension between CIOs and CDOs isn't a people problem, but an organisational design problem.They explore how operating models, accountability, product thinking and executive alignment determine whether technology, data and AI become genuine competitive advantages or simply create duplication, politics and confusion.They also discuss:Why the tension between CIOs and CDOs is usually created by organisational design rather than the people themselves.Why every CIO role looks different and how organisational context should define the mandate.Why organisations should define accountabilities before they hire executives or choose job titles.Whether every organisation actually needs a Chief Data Officer.Why technology, data and product leadership must operate as one team if transformation is going to succeed.The lessons learned moving from Chief Product Officer to CIO and why she still thinks like a product leader.How separate technology, product and data strategies create duplication, confusion and competing priorities.Why product operating models fundamentally outperform traditional project delivery.Who should own AI and why there is no universal answer.Why many organisations are measuring AI activity instead of AI value and repeating mistakes made during previous technology waves.How AI risks becoming another executive land grab unless organisations are crystal clear on ownership and accountability.Why centralised data teams can become ivory towers.What the private sector can learn from government about delivering successful transformation.Why dashboards and insights in isolation is not leadership.Whether technology, product and data leadership roles will ultimately converge or simply become much more interconnected.Why organisational design, incentives and culture will ultimately matter far more than whichever AI model an organisation chooses.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.
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  S7 | Ep 15 | What the Organisations Turning AI Into Revenue Do That Others Don't with Vin Vashista, CEO/Founder of VSquared 14.07.2026 58мин

  In Episode 15 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined for the third time by Vin Vashishta, CEO and Founder of V-Squared, where they discuss why the organisations getting the most value from AI are focused less on models and use cases, and more on outcomes, information architecture and business transformation, which includes;Why AI strategy has become a revenue growth strategy rather than a technology strategy.Why AI is an information product that depends on context, information architecture and data.Why information flywheels will become the defining capability that separates AI leaders from everyone else.Why organisations are moving from buying AI products to forming outcome-based partnerships with technology and consulting providers.Why CEOs and CFOs are now demanding clear links between AI investment, business outcomes and shareholder value.Why meaningful AI ROI requires organisations to transform operating models rather than simply automate existing processes.Why the fastest-growing organisations are extracting the greatest value from AI by creating entirely new forms of value.Why organisations such as JPMorgan Chase and Eli Lilly are turning AI into sustainable competitive advantage.How organisations can begin building information flywheels.Why technical strategy is becoming a core capability for both executive leaders and technical practitioners as traditional management layers disappear.Why ownership of commercial outcomes matters far more than whether AI sits with the CIO, CDO or a Chief AI Officer.Why robotics, autonomous systems and edge AI could soon eclipse today's generative AI conversation.Why LLMs will become just one small component within far more sophisticated agentic systems.Why we'll see LLMs diminish in importance.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.
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  Data Debrief: It's coming home! Solving Problems & Career Journeys 09.07.2026 37мин

  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 Peter Crouch, Group Innovation Director at Lloyd's Banking Group, digging into what it really takes to build an innovation function that earns its keep, why "solving the right problem" beats "solving the problem right," and the discipline required to stay pragmatic about AI when the pressure to look busy is everywhere.They cover:Why Peter's insistence that his team isn't a consultancy or a bolt-on, but something fully embedded in the business, matters for how any new function establishes its identity and avoids becoming just another side-of-desk activityThe distinction Peter drew between solving the right problem and solving a problem right, and why so much technical effort gets poured into questions that were never worth asking in the first placeCatherine's tie-in to a Rory Sutherland case study on managing customer perception, and why reframing expectations can matter more than actually speeding up a processThe Porsche brakes analogy: why confidence and trust in the underlying systems, not raw speed or new tech, are what actually give people the courage to move fastPeter's candour about AI decisions ageing quickly given the pace of change, and why the psychological safety to kill a six-month project that isn't working is more valuable than seeing it through for the sake of appearancesThe idea of building repeatable, scalable capability for turning ideas into outcomes, rather than chasing the next isolated "big idea"Kyle's thought of the week: prompted by Catherine, Kyle unpacks a pattern he's seeing across senior searches, talented specialists (using data governance as the example) who've risen to the very top of their track, out-earning some CDOs, only to find themselves boxed in with nowhere left to go. He explains why deep expertise in one domain rarely translates into credibility for a central, cross-value-chain leadership role, and why the people who make that jump early, often before they feel ready, tend to end up better positioned long-term. His advice: get genuinely clear on where you want to end up, be honest about whether your current track can get you there, and be willing to take a sideways or even backward step now if it sets up the bigger move later.Catherine's thought of the week: inspired by Harry Kane losing his voice mid-interview, Catherine reflects on her own voice-loss moment hosting last year's Driven by Data Live, and makes the case for giving everything to your work when it counts, leaving it all out on the pitch without apology, while still knowing that pace isn't sustainable every single day.Plus, a programming note and a community shout-out: Catherine is off for a short camping-holiday hiatus, so the show will pause for a couple of weeks, and the mentorship scheme's winter cohort is now open, get in touch to be paired with someone outside your usual industry and hear how genuinely non-linear most people's career paths really are.This episode explores why real innovation isn't about chasing shiny new ideas, but about building the capability, confidence, and psychological safety to work on the right problems, know when to walk away from the wrong ones, and be intentional about where your own career is actually headed.
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  S7 | Ep 14 | Why Innovation Is Built on Capability, Not Ideas with Pete Crouch, Group Innovation Director at Lloyds Banking Group 07.07.2026 47мин

  In Episode 14 of Season 7 of Driven by Data: The Podcast, Kyle Winterbottom was joined by Peter Crouch, Group Innovation Director at Lloyds Banking Group, where they discuss why the organisations that thrive in the AI era won't necessarily be those with the best ideas, but those that build the strongest innovation capability, and how large enterprises can adopt startup thinking without compromising governance, risk or customer trust, which includes:• Why innovation capability matters more than individual ideas.• How solving the right problem is more important than solving the problem right.• Why large organisations should adopt startup principles to innovate faster and reduce risk.• How staged funding and rapid experimentation prevent costly investment in the wrong ideas.• Why innovation requires a completely different operating model from traditional delivery.• How regulated organisations can create space for experimentation without compromising governance or customer trust.• Why embedding innovation into the business creates greater impact than isolated innovation teams.• How portfolio thinking stops organisations falling in love with ideas too early.• Why modern engineering platforms are essential for accelerating innovation.• Why AI should always be driven by business outcomes rather than technology hype.• How agentic AI is more likely to augment high-value work than replace skilled professionals.• Why the biggest opportunity for AI in software engineering is removing friction rather than writing code.• How replacing certainty with a learning-first mindset transforms innovation culture.• Why treating failure as learning is essential to building innovative organisations.• How creating intrapreneurs unlocks innovation at enterprise scale.• Why proving value early is the key to scaling innovation successfully.• How embedded, personalised financial services could redefine the future of banking.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.
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  Data Debrief: How to Translate your Work into Commercial Terms for an Interview 02.07.2026 39мин

  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.
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  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 52мин

  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.
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  Data Debrief: Context, Culture & Clarkson's Farm 25.06.2026 48мин

  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.
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  S7 | Ep 12 | The Real Bottlenecks Holding Back Enterprise AI with Justin Borgman, Co-Founder & CEO at Starburst 23.06.2026 50мин

  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.
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  Data Debrief: Social Media Ban, Buses & CDO Future 18.06.2026 42мин

  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.
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  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 51мин

  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.
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  Data Debrief: Juggling Plates, Commerical Value & Steven Bartlett Drinking Wine 11.06.2026 42мин

  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.
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  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 47мин

  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.
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  Data Debrief: Demystifying Data Leadership & Kyle makes a Bet on Topic Choice 04.06.2026 48мин

  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.