059 - How Design Thinking Helps Organizations and Data Science Teams Create Economic Value with Machine Learning and Analytics feat. Bill Schmarzo

With a 30+ year career in data warehousing, BI and advanced analytics under his belt, Bill has become a leader in the field of big data and data science – and, not to mention, a popular social media influencer. Having previously worked in senior leadership at DellEMC and Yahoo!, Bill is now an executive fellow and professor at the University of San Francisco School of Management as well as an honorary professor at the National University of Ireland-Galway. I’m so excited to welcome Bill as my guest on this week’s episode of Experiencing Data. When I first began specializing my consulting in the area of data products, Bill was one of the first leaders that I specifically noticed was leveraging design thinking on a regular basis in his work. In this long overdue episode, we dug into some examples of how he’s using it with teams today. Bill sees design as a process of empowering humans to collaborate with one another, and he also shares insights from his new book, “The? Economics of Data, Analytics and Digital Transformation.” In total, we covered: Why it’s crucial to understand a customer’s needs when building a data product and how design helps uncover this. (2:04) How running an “envisioning workshop” with a customer before starting a project can help uncover important information that might otherwise be overlooked. (5:09) How to approach the human/machine interaction when using machine learning and AI to guide customers in making decisions – and why it’s necessary at times to allow a human to override the software. (11:15) How teams that embrace design-thinking can create “organizational improvisation” and drive greater value. (14:49) Bill take on how to properly prioritize use cases (17:40) How toidentify a data product’s problems ahead of time. (21:36) The trait that Bill sees in the best data scientists and design thinkers (25:41) How Bill helps transition the practice of data science from being a focus on analytic outputs to operational and business outcomes. (28:40) Bill’s new book, “The Economics of Data, Analytics, and Digital Transformation.” (31:34) Brian and Bill’s take on the need for organizations to create a technological and cultural environment of continuous learning and adapting if they seek to innovate. (38:22) Quotes from Today’s Episode There’s certainly a UI aspect of design, which is to build products that are more conducive for the user to interact with – products that are more natural, more intuitive … But I also think about design from an empowerment perspective. When I consider design-thinking techniques, I think about how I can empower the wide variety of stakeholders that I need to service with my data science. I’m looking to identify and uncover those variables and metrics that might be better predictors of performance. To me, at the very beginning of the design process, it’s about empowering everybody to have ideas. – Bill (2:25) Envisioning workshops are designed to let people realize that there are people all across the organization who bring very different perspectives to a problem. When you combine those perspectives, you have an illuminating thing. Now let’s be honest: many large organizations don’t do this well at all. And the reason why is not because they’re not smart, it’s because in many cases, senior executives aren’t willing to let go. Design thinking isn’t empowering the senior executives. In many cases, it’s about empowering those frontline employees … If you have a culture where the senior executives have to be the smartest people in the room, design is doomed. – Bill (10:15) Organizational charts are the great destroyer of creativity because you put people in boxes. We talk about data silos, but we create these human silos where people can’t go out … Screw boxes. We want to create swirls – we want to create empowered teams. In fact, the most powerful teams are the ones who can embrace design thinking to create what I call organizational improvisation. Meaning, you have

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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.