096 - Why Chad Sanderson, Head of Product for Convoy’s Data Platform, is a Champion of Data UX

Today I chat with Chad Sanderson, Head of Product for Convoy’s data platform. I begin by having Chad explain why he calls himself a “data UX champion” and what inspired his interest in UX. Coming from a non-UX background, Chad explains how he came to develop a strategy for addressing the UX pain points at Convoy—a digital freight network. They “use technology to make freight more efficient, reducing costs for some of the nation’s largest brands, increasing earnings for carriers, and eliminating carbon emissions from our planet.” We also get into the metrics of success that Convoy uses to measure UX and why Chad is so heavily focused on user workflow when making the platform user-centered.   Later, Chad shares his definition of a data product, and how his experience with building software products has overlapped with data products. He also shares what he thinks is different about creating data products vs. traditional software products. Chad then explains Convoy’s approach to prototyping and the value of partnering with users in the design process. We wrap up by discussing how UX work gets accomplished on Chad’s team, given it doesn’t include any titled UX professionals.    Highlights: Chad explains how he became a data UX champion and what prompted him to care about UX (1:23) Chad talks about his strategy for beginning to address the UX issues at Convoy (4:42) How Convoy measures UX improvement (9:19) Chad talks about troubleshooting user workflows and it’s relevance to design (15:28) Chad explains what Convoy is and the makeup of his data platform team (21:00) What is a data product? Chad gives his definition and the similarities and differences between building software versus data products (23:21) Chad talks about using low fidelity work and prototypes to optimize solutions and resources in the long run (27:49) We talk about the value of partnering with users in the design process (30:37) Chad talks about the distribution of UX labor on his team (32:15)   Quotes from Today’s Episode   Re: user research: "The best content that you get from people is when they are really thinking about what to say next; you sort of get into a free-flowing exchange of ideas. So it’s important to find the topic where someone can just talk at length without really filtering themselves. And I find a good place to start with that is to just talk about their problems. What are the painful things that you’ve experienced in data in the last month or in the last week?" - Chad    Re: UX research: "I often recommend asking users to show you something they were working on recently, particularly when they were having a  problem accomplishing their goal. It’s a really good way to surface UX issues because the frustration is probably fresh." - Brian    Re: user feedback, “One of the really great pieces of advice that I got is, if you’re getting a lot of negative feedback, this is actually a sign that people care. And if people care about what you’ve built, then it’s better than overbuilding from the beginning.” - Chad   “What we found [in our research around workflow], though, sometimes counterintuitively, is that the steps that are the easiest and simplest for a customer to do that I think most people would look at and say, ‘Okay, it’s pretty low ROI to invest in some automated solution or a product in this space,’ are sometimes the most important things that you can [address in your data product] because of the impacts that it has downstream.” - Chad    Re: user feedback, “The amazing thing about building data products, and I guess any internal products is that 100% of your customers sit ten feet away from you. [...] When you can talk to 100% of [your users], you are truly going to understand [...] every single persona. And that is tremendously effective for creating compelling narratives about why we need to build a particular thing.” - Chad    “If we can get people to really believe that this data product is going to solve the problem, then

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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.