How data teams become trusted business partners with Nick Zervoudis

Nick Zervoudis, data product manager, trainer, and consultant at Value from Data & AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! In this conversation, we cover how a service desk model breaks down when a request can’t be described in a few words, why dashboards get opened once and then forgotten, and how product thinking differs from project management in data work. We also discuss how to start doing discovery without a full transformation, and what AI does and doesn’t change about that work.See omnystudio.com/listener for privacy information.

This is the takeaway episode with Nick Zervoudis, data product manager, trainer, and consultant at Value from Data & AI, joins Juan and Time to talk about why many data teams end up working like a service desk and what to do about it. The answer is: DO DISCOVERY! See omnystudio.com/listener for privacy information.

Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo, recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems.  In this episode, Mohammed lays out a framework for talent in the AI era. Automation is already taking over the known, repeatable work. What remains is the unknown, and that takes people who keep learning and who take initiative. The framework plots people on two dimensions, learning and drive. You have Doers, Philosophers, Commanders, Hackers, Strategist, Innovators, Game changers and more. Topics discussed Automation and the innovation engine The known versus the unknown Two dimensions of talent The talent quadrants The multiplier effect Commanders and scaling Environments that don’t build initiative Rarity of high-potential people Investing in human potential The human mind as the limit Critical thinking through discomfort See omnystudio.com/listener for privacy information.

This is the takeaway episode with Mohammed Aaser, former chief data officer at McKinsey and former chief data strategy officer at Domo. He recently visited Juan and shared his framework on talent in the AI era. It was incredibly insightful and we asked if he could come back to the podcast (after 5 years!) His argument is that the potential of AI will be unlocked by humans because humans understand the problems, and are driven/motivated to solve the problems. See omnystudio.com/listener for privacy information.

How do leaders preserve executive trust and credibility? Dora Boussias, executive advisor and former data executive returns to the podcast to unpack this question. Her answer: protect your judgement.  In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Dora’s point is that the equation still holds, but each part now means something different. Nobody will out-know AI, so expertise is less about what you know and more about asking the right questions and challenging assumptions. A track record is harder to read when you can’t tell whether a good result came from you or from the model. Judgment carries the most weight now, and it’s the part leaders are most likely to hand off without noticing. Topics discussed:  Trust equation under AI Expertise is changing Track record is harder to read Judgment carries the most weight Decision fog Speed isn’t everything Ford’s rehiring of experienced engineers Business fundamentals matter more Alignment and accountability are cross-functional Real value is “so what” See omnystudio.com/listener for privacy information.

This is the takeaway episode with Dora Boussias, executive advisor and former data executive. We unpack the question "How do leaders preserve executive trust and credibility?" Her answer: protect your judgement. In this episode, Dora presents the trust equation that most leaders grew up with: expertise + track record + judgment. Don't miss it!See omnystudio.com/listener for privacy information.

Agents will build data infrastructure at every layer and become its primary consumers. Tristan Handy, President and Co-founder of Fivetran / dbt Labs joins Juan and Tim where we unpack the big shift that is happening: teams need to move from working in the process (picking up individual tickets) to working on the process (building the factories that handle those tickets). In this episode, we break down what this means for data roles, why open components matter more than vendor stacks, and the socio-political problem nobody's talking about, deciding what counts as truth so your agents (and humans) ask the right questions in the first place. Topics discussed: Agents as builders and consumers  Data roles are collapsing From working IN to working ON  Loop building as the competitive advantage Business understanding beats technical specs  From humans in the loop to humans out of the loop  Open components over vendor stacks Defining truth is a political problem Data observability becomes business observability Real-time becomes necessary   Humans delegate outcomes, set goals, sit in control See omnystudio.com/listener for privacy information.

This is the takeaway episode with Tristan Handy, President and Co-founder of Fivetran / dbt Labs where he joins Juan and Tim to discuss how agents will build data infrastructure at every layer and become its primary consumers. We unpack the big shift that is happening: teams need to move from working in the process to working on the process, what this means for data roles, why open components matter more than vendor stacks, and the socio-political problem nobody's talking about, deciding what counts as truth so your agents (and humans) ask the right questions in the first place. See omnystudio.com/listener for privacy information.

#Localization #Globalization #ServiceNow #AI A translation can be word-for-word accurate and still be completely wrong. In this episode, Bobby Brill sits down with Sam Smyth, Product Manager on the globalization side at ServiceNow, to get into what happens after you decide to go multilingual — the tools, the governance, and the quiet work nobody sees until it breaks. Sam spent fifteen years in localization operations and management before joining ServiceNow, and he's blunt about what actually goes wrong: it's rarely the translator. It's the content you sent them. We get into Localization Workspace, the new globalization agent that builds a glossary from your knowledge articles in minutes, why every customer still insists on a human in the loop, and the one mistake that will break your product UI in six languages at once. Past Localization episodes: https://youtu.be/4ka4qLk8Uj0 https://youtu.be/cGXCnABXKow Guest: Sam Smyth, Product Manager - ServiceNow Chapters 00:00 "People don't see localization until it goes wrong" 00:22 Translation vs. localization — a quick recap 00:56 Meet Sam Smyth: fifteen years in localization 01:37 When a perfect translation is still wrong 03:34 Why customers don't want to leave the platform 04:07 Localization Workspace: no more spreadsheets and email chains 05:13 The surprise: everybody still wants a human in the loop 05:38 Speed, cost, quality — picking all three 06:55 Inside the globalization agent 08:50 Who approves the terms? (And which shade of green?) 09:55 Language governance and the invisible costs 11:49 AI, volume, and doing the work upstream 13:02 Where to actually start with a glossary 16:28 A day in the life of a localization program manager 18:56 Shifting left: from firefighting to strategy 20:35 The one mistake: never hardcode your UI 22:10 Wrap-up ServiceNow Training and Certification: https://www.servicenow.com/services/training-and-certification.html ServiceNow Insights podcast playlist: https://www.youtube.com/playlist?list=PLCOmiTb5WX3qvGq7Cp3o2KkCiplJyqQOK Servicenow.com: https://www.servicenow.comSee omnystudio.com/listener for privacy information.

AI doesn't create your problems. It inherits the business choices you never made and the results nobody owns. David Krauza, VP of Data Strategy and Governance at Comcast, joins Juan and Tim to make the case that most "data problems" aren't data problems at all. They are accountability problems, definition problems, assumption problems, and what-are-we-even-measuring problems. The fix isn't better tooling. Data teams are so focused on delivery that they never stop to ask what the business is actually trying to do. It's going to the C-suite, asking about the top three goals, and following the definitions until the cracks show up. Topics discussed: AI inherits your unmade decisions The output trap Definitions are the real foundation Talk to the business Data as a cost center vs. a value driver Single source of data, multiple versions of the truth Think like a product owner The revenge of the liberal arts majors See omnystudio.com/listener for privacy information.