As a data scientist, there’s nothing worse than devoting months of your time to building a data product that appears to meet your stakeholders’ every need, only to find it never gets used. It’s depressing, demotivating and can be devastating for your career.
But as the old saying goes, “You can lead a horse to water, but you can’t make it drink”. Or can you?
In this episode, Brian T O’Neill joins Dr Genevieve Hayes to discuss how you can apply the best techniques from software product management and UI/UX design to create ML and AI products your stakeholders will love.
Guest Bio
Brian T O’Neill is the Founder and Principal of Designing for Analytics, an independent data product UI/UX design consultancy that helps data leaders turn ML & analytics into usable, valuable data products. He also advises on product and UI/UX design for startup founders in MIT’s Sandbox Innovation Fund; hosts the podcast Experiencing Data; founded The Data Product Leadership Community and maintains a career as a professional percussionist performing in Boston and internationally.
Highlights
- Introducing Brian T. O’Neill (00:19)
- Brian’s journey from music to data product design (02:16)
- Understanding the real needs of stakeholders (06:45)
- The importance of user-centered design in data products (09:33)
- Gaining insights through direct user interaction (12:16)
- Focusing on business and user experience outcomes (17:48)
- Debunking the myths of self-serve analytics and dashboarding (22:46)
- Data platforms vs. data products (27:26)
- Defining a data product: the value exchange principle (29:08)
- Designing human-centered data products (32:56)
- The CED framework: conclusions, evidence, data (36:01)
- Final advice for data scientists (45:06)
Links
- Connect with Genevieve on LinkedIn
- Be among the first to hear about the release of each new podcast episode by signing up HERE
