027 - Balancing Your Inner Data Science Nerd While Becoming a Trusted Business Advisor and Strategist with Angela Bassa of iRobot

Angela Bassa is the director of data science and head of data science and machine learning at iRobot, a technology company focused on robotics (you might have clean floors thanks to a Roomba). Prior to joining iRobot, Angela wore several different hats, including working as a financial analyst at Morgan Stanley, the senior manager of big data analytics and platform engineering at EnerNOC, and even a scuba instructor in the U.S. Virgin Islands. Join Angela and I as we discuss the role data science plays in robotics and explore: Why Angela doesn’t believe in a division between technical and non-technical skill Why Angela came to iRobot and her mission What data breadcrumbs are and what you should know about them The skill Angela believes matters most when turning data science into a producer of decision support Why the last mile of the UX is often way longer than one mile The critical role expectation management plays in data science, how Angela handles delivering surprise findings to the business, and the marketing skill she taps to help her build trust Resources and Links Twitter: @AngeBassa Angela’s Website iRobot Designing for Analytics Seminar Quotes from Today’s Episode “Because these tools that we use sometimes can be quite sophisticated, it’s really easy to use very complicated jargon to impart credibility onto results that perhaps aren’t merited. I like to call that math-washing the  result.” — Angela “Our mandate is to make sure that we are making the best decisions—that we are informing strategy rather than just believing certain bits of institutional knowledge or anecdotes or trends. We can actually sort of demonstrate and test those hypotheses with the data that is available to us. And so we can make much better informed decisions and, hopefully, less risky ones.” — Angela “Data alone isn’t the ground truth. Data isn’t the thing that we should be reacting to. Data are artifacts. They’re breadcrumbs that help us reconstruct what might have happened.” — Angela [When getting somebody to trust the data science work], I don’t think the trust comes from bringing someone along during the actual timeline. I think it has more to do with bringing someone along with the narrative.—Angela “It sounds like you’ve created a nice dependency for your data science team. You’re seen as a strategic partner as opposed to being off in the corner doing cryptic work that people can’t understand.” — Brian “When I talk to data scientists and leaders, they often talk about how technical skills are very easy to measure. You can see them on paper, you can get them in the interview. But there are these other skills that are required to do effective work and create value.” — Brian    

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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.