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Are you responsible for creating business impact with data products, SAAS analytics solutions, dashboards or generative AI/ML applications? Do you believe one of the biggest challenges with monetizing data products is navigating the humans in the loop—from stakeholders to users? Do you believe that a product-driven approach coupled with solid UX design is critical to ensuring that analytics and ML solutions even get used? My name is Brian T. O’Neill, and on Experiencing Data, I offer you a designer’s perspective on why simply developing ML models, dashboards, and apps—outputs—aren’t enough to drive meaningful user and business outcomes with data. Through solo episodes and interviews with data product management leaders, CDAOs, VCs, and designers, I explore how teams are integrating product-oriented methodologies and UX design to ensure that data products get used in the last mile. After all, you can’t create business value if the humans in the loop won’t use your “solution.” Whether you work in product at a B2B / SAAS analytics company, or you build internal data products for a traditional enterprise, join me as I dig into what’s working—and what isn’t. Hashtag: #ExperiencingData. PODCAST HOMEPAGE: For 1-page summaries and full text transcripts, join my Insights mailing list on the podcast homepage: https://designingforanalytics.com/ed ABOUT THE HOST, BRIAN T. O’NEILL: https://designingforanalytics.com/bio/
Episodes
Tuesday May 18, 2021
Tuesday May 18, 2021
I once saw a discussion on LinkedIn about a fraud detection model that had been built but never used. The model worked — it was expensive — but it just simply didn’t get used because the humans in the loop were not incentivized to use it.
It was on this very thread that I first met Salesforce Director of Product Management Pavan Tuvu, who chimed in on the thread about a similar experience he went through. When I heard about his experience, I asked him if he would share it with you and he agreed. So, today on the Experiencing Data podcast, I’m excited to have Pavan on to talk about some lessons he learned while designing ad-spend software that utilized advanced analytics — and the role of the humans in the loop. We discussed:
- Pavan's role as Director of Product Management at Salesforce and how he works to make data easier to use for teams. (0:40)
- Pavan's work protecting large-dollar advertising accounts from bad actors by designing a ML system that predicts and caps ad spending. (6:10)
- 'Human override of the machine': How Pavan addressed concerns that its advertising security system would incorrectly police legitimate large-dollar ad spends. (12:22)
- How the advertising security model Pavan worked on learned from human feedback. (24:49)
- How leading with "why" when designing data products will lead to a better understanding of what customers need to solve. (29:05)
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