110 - CDO Spotlight: The Value and Journey of Implementing a Data Product Mindset with Sebastian Klapdor of Vista

Today I’m chatting with Dr. Sebastian Klapdor, Chief Data Officer for Vista. Sebastian has developed and grown a successful Data Product Management team at Vista, and it all began with selling his vision to the rest of the executive leadership. In this episode, Sebastian explains what that process was like and what he learned. Sebastian shares valuable insights on how he implemented a data product orientation at Vista, what makes a good data product manager, and why technology usage isn’t the only metric that matters when measuring success. He also shares what he would do differently if he had to do it all over again.   Highlights/ Skip to: How Sebastian defines a data product (01:48) Brian asks Sebastian about the change management process in leadership when implementing a data product approach (07:40) The three dimensions that Sebastian and his team measure to determine adoption success (10:22) Sebastian shares the financial results of Vista adopting a data product approach (12:56) The size and scale of the data team at Vista, and how their different roles ensure success (14:30) Sebastian explains how Vista created and grew a team of 35 data product managers (16:47) The skills Sebastian feels data product managers need to be successful at Vista (22:02) Sebastian describes what he would do differently if he had to implement a data product approach at a company again (29:46) Quotes from Today’s Episode “You need to establish a culture, and that’s often the hardest part that takes the longest -  to treat data as an asset, and not to treat it as a byproduct, but to treat it as a product and treat it as a valuable thing.” – Sebastian Klapdor (07:56) “One source of data product managers is taking data professionals. So, you take data engineers, data scientists, or former analysts, and develop them into the role by coaching them [through] the product management skills from the software industry.” – Sebastian Klapdor (17:39)   “We went out there and we were hiring people in the market who were experienced [Product Managers]. But we also see internal people, actually grooming and growing into all of these roles, both from these 80 folks who have been around before, but also from other areas of Vista.” – Sebastian Klapdor (20:28)   “[Being a good Product Manager] comes back to the good old classics of collaborating, of being empathetic to where other people are at, their priorities, and understanding where [our] priorities fit into their bigger piece, and jointly aligning on what is valuable for Vista.” – Sebastian Klapdor (22:27)   “I think there’s nothing more detrimental than saying, ‘Yeah, sure, we can deliver things, and with data, it can do everything.’ And then you disappoint people and you don’t stick to your promises. … If you don’t stick to your promise, it will hurt you.” – Sebastian Klapdor (23:04) “You don’t do the typical waterfall approach of solving business problems with data. You don’t do the approach that a data scientist tries to get some data, builds a model, and hands it over to data engineer who should productionize that. And then the data engineer gets back and says certain features can’t be productionized because it’s very complex to get the data on a daily basis, or in real time. By doing [this work] in a data product team, you can work actually in Agile and you’re super fast building what we call a minimum lovable product.” – Sebastian Klapdor (26:15) “That was the biggest learning … whom do we staff as data product managers? And what do we expect of a good data product manager? How does a career path look like? That took us a really long time to figure out.” – Sebastian Klapdor (30:18) “We have a big, big, big commitment that we want to start stuffing UX designers onto our [data] product teams.” - Sebastian Klapdor (21:12) Links Vista: https://vista.io LinkedIn: https://www.linkedin.com/in/sebastianklapdor/ Vista Blog: https://vista.io/blog

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Are you an enterprise data or product leader seeking to increase the user adoption and business value of your ML/AI and analytical data products? While it is easier than ever to create ML and analytics from a technology perspective, do you find that getting users to use, buyers to buy, and stakeholders to make informed decisions with data remains challenging? If you lead an enterprise data team, have you heard that a ”data product” approach can help—but you’re not sure what that means, or whether software product management and UX design principles can really change consumption of ML and analytics? My name is Brian T. O’Neill, and on Experiencing Data—one of the top 2% of podcasts in the world—I offer you a consulting product designer’s perspective on why simply creating ML models and analytics dashboards aren’t sufficient to routinely produce outcomes for your users, customers, and stakeholders. My goal is to help you design more useful, usable, and delightful data products by better understanding your users, customers, and business sponsor’s needs. After all, you can’t produce business value with data if the humans in the loop can’t or won’t use your solutions. Every 2 weeks, I release solo episodes and interviews with chief data officers, data product management leaders, and top UX design and research professionals working at the intersection of ML/AI, analytics, design and product—and now, I’m inviting you to join the #ExperiencingData listenership. Transcripts, 1-page summaries and quotes available at: https://designingforanalytics.com/ed ABOUT THE HOST Brian T. O’Neill is the Founder and Principal of Designing for Analytics, an independent consultancy helping technology leaders turn their data into valuable data products. He is also the founder of The Data Product Leadership Community. For over 25 years, he has worked with companies including DellEMC, Tripadvisor, Fidelity, NetApp, Roche, Abbvie, and several SAAS startups. He has spoken internationally, giving talks at O’Reilly Strata, Enterprise Data World, the International Institute for Analytics Symposium, Predictive Analytics World, and Boston College. Brian also hosts the highly-rated podcast Experiencing Data, advises students in MIT’s Sandbox Innovation Fund and has been published by O’Reilly Media. He is also a professional percussionist who has backed up artists like The Who and Donna Summer, and he’s graced the stages of Carnegie Hall and The Kennedy Center. Subscribe to Brian’s Insights mailing list at https://designingforanalytics.com/list.