The 38th episode of Datacast is my conversation with Brian O'Neill — a designer, advisor, and founder of Designing for Analytics, an independent consultancy that helps companies turn analytics into indispensable decision support applications. Give it a listen to hear about his advice on finding the minimum viable audience as a consultant; his thoughts to avoid building data products that are “technically right, effectively wrong”; his emphasis on the importance of human-centered design to measure meaningful engagements; his CED framework to build customer trust around advanced analytics; and much more.
Brian T. O'Neill is a designer, advisor, and founder of Designing for Analytics, an independent consultancy that helps companies turn analytics into indispensable decision support applications. For over 20 years, he has worked with companies including Dell EMC, Global Strategy Group, TripAdvisor, Fidelity, JP Morgan Chase, E-Trade, 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, where he reveals the strategies and activities that product, data science, and analytics leaders are using to deliver valuable experiences around data. In addition to consulting, Brian is also a professional percussionist and has performed at Carnegie Hall and The Kennedy Center.
Show Notes
(2:40) Brian discussed his career as a musician and his mission as a consultant to bring design principles into the analytics world.
(5:25) Brian talked about his career inception as a UX designer and his interest in human-centered design.
(9:48) Brian shared the backstory behind starting Designing for Analytics and his advice for anyone interested in becoming a consultant (hint: finding the minimum viable audience for your craft!).
(20:44) Brian shared the common problems that his clients ask him to solve - citing that many of the solutions in engineering-driven organizations are “Technically Right, Effectively Wrong” (listen to Brian’s podcast with David Stephenson).
(27:20) Brian explained why data product design goes well beyond user interfaces and helps define what is required to enable the desired user and business outcomes, referring to his post “Does your data product enable surgery or healing?”
(33:14) Brian revealed the tactical tips for designing an effective prototype for data products, as shared in his post “Designing MVPs for Data Products and Decision Support Tools.”
(40:31) Brian talked about the importance of using human-centered design to measure meaningful engagement in the context of data products, as shared in his post “Why Low Engagement May Not be the Problem with Your Data Product or Analytics Service” (Hint: Think about the last mile and use design to make deliberate choices to improve user engagement).
(47:46) Brian unpacked the design framework CED (which stands for Conclusion, Evidence, and Data), which helps build customer trust, engagement, and indispensability around advanced analytics.
(54:55) Brian shared his take on how to structure a quad team, including software engineers, UX designers, data scientists, and product managers to build machine learning-powered products.
(01:03:25) Brian emphasized the importance of trust in modern data products, after countless conversations with leaders in his podcast Experiencing Data.
(01:06:34) Brian unveiled his seminar called Designing Human-Centered Data Products for data scientists, technical product managers, and analytics practitioners.
(01:09:47) Closing segment.
His Contact Info
His Recommended Resources
Seth Godin’s podcast Akimbo
Scott Berkun (his book “How Design Makes The World”)
Amanda Cox (NYT’s The Upshot)
“Good Charts” (by Scott Berinato)
“Change By Design” (by Tim Brown)
“Infonomics” (by Douglas Laney)
“Competing In The Age of AI” (by Marco Iansiti and Karim Lakhani)