156-The Challenges of Bringing UX Design and Data Science Together to Make Successful Pharma Data Products with Jeremy Forman

Jeremy Forman joins us to open up about the hurdles– and successes that come with building data products for pharmaceutical companies. Although he’s new to Pfizer, Jeremy has years of experience leading data teams at organizations like Seagen and the Bill and Melinda Gates Foundation. He currently serves in a more specialized role in Pfizer’s R&D department, building AI and analytical data products for scientists and researchers. .     Jeremy gave us a good luck at his team makeup, and in particular, how his data product analysts and UX designers work with pharmaceutical scientists and domain experts to build data-driven solutions..  We talked a good deal about how and when UX design plays a role in Pfizer’s data products, including a GenAI-based application they recently launched internally.       Highlights/ Skip to: (1:26) Jeremy's background in analytics and transition into working for Pfizer (2:42) Building an effective AI analytics and data team for pharma R&D (5:20) How Pfizer finds data products managers (8:03) Jeremy's philosophy behind building data products and how he adapts it to Pfizer (12:32) The moment Jeremy heard a Pfizer end-user use product management research language and why it mattered (13:55) How Jeremy's technical team members work with UX designers (18:00) The challenges that come with producing data products in the medical field (23:02) How to justify spending the budget on UX design for data products (24:59) The results we've seen having UX design work on AI / GenAI products (25:53) What Jeremy learned at the  Bill & Melinda Gates Foundation with regards to UX and its impact on him now (28:22) Managing the "rough dance" between data science and UX (33:22) Breaking down Jeremy's GenAI application demo from CDIOQ (36:02) What would Jeremy prioritize right now if his team got additional funding (38:48) Advice Jeremy would have given himself 10 years ago (40:46) Where you can find more from Jeremy     Quotes from Today’s Episode “We have stream-aligned squads focused on specific areas such as regulatory, safety and quality, or oncology research. That’s so we can create functional career pathing and limit context switching and fragmentation. They can become experts in their particular area and build a culture within that small team. It’s difficult to build good [pharma] data products. You need to understand the domain you’re supporting. You can’t take somebody with a financial background and put them in an Omics situation. It just doesn’t work. And we have a lot of the scars, and the failures to prove that.” - Jeremy Forman (4:12) “You have to have the product mindset to deliver the value and the promise of AI data analytics. I think small, independent, autonomous, empowered squads with a product leader is the only way that you can iterate fast enough with [pharma data products].” - Jeremy Forman (8:46) “The biggest challenge is when we say data products. It means a lot of different things to a lot of different people, and it’s difficult to articulate what a data product is. Is it a view in a database? Is it a table? Is it a query? We’re all talking about it in different terms, and nobody’s actually delivering data products.” - Jeremy Forman (10:53) “I think when we’re talking about [data products] there’s some type of data asset that has value to an end-user, versus a report or an algorithm. I think it’s even hard for UX people to really understand how to think about an actual data product. I think it’s hard for people to conceptualize, how do we do design around that? It’s one of the areas I think I’ve seen the biggest challenges, and I think some of the areas we’ve learned the most. If you build a data product, it’s not accurate, and people are getting results that are incomplete… people will abandon it quickly.” - Jeremy Forman (15:56) “ I think that UX design and AI development or data science work is a magical partnership, but they often don’t know how to work with each ot

Om Podcasten

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.