101 - Insights on Framing IOT Solutions as Data Products and Lessons Learned from Katy Pusch

Today I’m chatting with Katy Pusch, Senior Director of Product and Integration for Cox2M. Katy describes the lessons she’s learned around making sure that the “juice is always worth the squeeze” for new users to adopt data solutions into their workflow. She also explains the methodologies she’d recommend to data & analytics professionals to ensure their IOT and data products are widely adopted. Listen in to find out why this former analyst turned data product leader feels it’s crucial to focus on more than just delivering data or AI solutions, and how spending more time upfront performing qualitative research on users can wind up being more efficient in the long run than jumping straight into development.   Highlights/ Skip to: What Katy does at Cox2M, and why the data product manager role is so hard to define (01:07) Defining the value of the data in workflows and how that’s approached at Cox2M (03:13) Who buys from Cox2M and the customer problems that Katy’s product solves (05:57) How Katy approaches the zero-to-one process of taking IOT sensor data and turning it into a customer experience that provides a valuable solution (08:00) What Katy feels best motivates the adoption of a new solution for users (13:21) Katy describes how she spends more time upfront before development to ensure she’s solving the right problems for users (16:13) Katy’s views on the importance of data science & analytics pros being able to communicate in the language of their audience (20:47) The differences Katy sees between designing data products for sophisticated data users vs a broader audience (24:13) The methods Katy uses to effectively perform qualitative research and her triangulation method to surface the real needs of end users (27:29) Katy’s views on the most valuable skills for future data product managers (35:24)   Quotes from Today’s Episode “I’ve had the opportunity to get a little bit closer to our customers than I was in the beginning parts of my tenure here at Cox2M. And it’s just like a SaaS product in the sense that the quality of your data is still dependent on your customers’ workflows and their ability to engage in workflows that supply accurate data. And it’s been a little bit enlightening to realize that the same is true for IoT.” – Katy Pusch (02:11)   “Providing insights to executives that are [simply] interesting is not really very impactful. You want to provide things that are actionable and that drive the business forward.” – Katy Pusch (4:43)   “So, there’s one side of it, which is [the] happy path: figure out a way to embed your product in the customer’s existing workflow. That’s where the most success happens. But in the situation we find ourselves in right now with [this IoT solution], we do have to ask them to change their workflow.”-- Katy Pusch (12:46)   “And the way to communicate [the insight to other stakeholders] is not with being more precise with your numbers [or adding] statistics. It’s just to communicate the output of your analysis more clearly to the person who needs to be able to make a decision.” -- Katy Pusch (23:15)   “You have to define ‘What decision is my user making on a repeated basis that is worth building something that it does automatically?’ And so, you say, ‘What are the questions that my user needs answers to on a repeated basis?’ … At its essence, you’re answering three or four questions for that user [that] have to be the most important [...] questions for your user to add value. And that can be a difficult thing to derive with confidence.” – Katy Pusch (25:55)   “The piece of workflow [on the IOT side] that’s really impactful there is we’re asking for an even higher degree of change management in that case because we’re asking them to attach this device to their vehicle, and then detach it at a different point in time and there’s a procedure in the solution to allow for that, but someone at the dealership has to engage in that process. So, there’s a change management in the w

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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.