Jared Spool is arguably the most well-known name in the field of design and user experience. For more than a decade, he has beena witty, powerful voice for why UX is critical to value creation within businesses. Formerly an engineer, Jared started working in UX in 1978, founded UIE (User Interface Engineering) in 1988, and has helped establish the field over the last 30 years. In addition, he advised the US Digital Service / Executive Office of President Obama and in 2016, Jared co-founded the Center Centre, the user experience design school that’s creating a new generation of industry-ready UX designers.
Today however, we turned to the topic of UX in the context of analytics, ML and AI—and what teams–especially those without trained designers on staff–need to know about creating successful data products.
In our chat, we covered:
“Center Centre is a school in Chattanooga for creating UX designers, and it's also the name of the professional development business that we've created around it that helps organizations create and exude excellence in terms of making UX design and product services…” - Jared
“The reality is this: on the other side of all that data, there are people. There's the direct people who are interacting with the data directly, interacting with the intelligence interacting with the various elements of what's going on, but at the same time, there's indirect folks. If someone is making decisions based on that intelligence, those decisions affect somebody else's life.” - Jared
“I think something that's missing frequently here is the inability to think beyond the immediate customer who requests a solution.” Brian
“The fact that there are user experience teams anywhere is sort of a new and novel thing. A decade ago, that was very unlikely that you'd go into a business and there’d be a user experience team of any note that had any sort of influence across the business.” - Jared
[At Netflix], we'd probably put the people who work in the basement on [server and network] performance at the opposite side of the chart from the people who work on the user interface or what we consider the user experience of Netflix […] Except at that one moment where someone's watching their favorite film, and that little spinny thing comes up, and the film pauses, and the experience is completely interrupted. And it's interrupted because the latency, and the throughput, and the resilience of the network are coming through to the user interface. And suddenly, that group of people in the basement are the most important UX designers at Netflix. - Jared
My feeling is, with the exception of perhaps the FANG companies, the idea of designers being required, or part of the equation when we're developing probabilistic solutions that use machine learning etc., well, it's not even part of the conversation with most user experience leaders that I talk to. - Brian
Links142 - Live Webinar Recording: My UI/UX Design Audit of a New Podcast Analytics Service w/ Chris Hill (CEO, Humblepod)
141 - How They’re Adopting a Producty Approach to Data Products at RBC with Duncan Milne
140 - Why Data Visualization Alone Doesn’t Fix UI/UX Design Problems in Analytical Data Products with T from Data Rocks NZ
139 - Monetizing SAAS Analytics and The Challenges of Designing a Successful Embedded BI Product (Promoted Episode)
138 - VC Spotlight: The Impact of AI on SAAS and Data/Developer Products in 2024 w/ Ellen Chisa of BoldStart Ventures
137 - Immature Data, Immature Clients: When Are Data Products the Right Approach? feat. Data Product Architect, Karen Meppen
136 - Navigating the Politics of UX Research and Data Product Design with Caroline Zimmerman
135 - “No Time for That:” Enabling Effective Data Product UX Research in Product-Immature Organizations
134 - What Sanjeev Mohan Learned Co-Authoring “Data Products for Dummies”
133 - New Experiencing Data Interviews Coming in January 2024
132 - Leveraging Behavioral Science to Increase Data Product Adoption with Klara Lindner
131 - 15 Ways to Increase User Adoption of Data Products (Without Handcuffs, Threats and Mandates) with Brian T. O’Neill
130 - Nick Zervoudis on Data Product Management, UX Design Training and Overcoming Imposter Syndrome
129 - Why We Stopped, Deleted 18 Months of ML Work, and Shifted to a Data Product Mindset at Coolblue
128 - Data Products for Dummies and The Importance of Data Product Management with Vishal Singh of Starburst
127 - On the Road to Adopting a “Producty” Approach to Data Products at the UK’s Care Quality Commission with Jonathan Cairns-Terry
126 - Designing a Product for Making Better Data Products with Anthony Deighton
125 - Human-Centered XAI: Moving from Algorithms to Explainable ML UX with Microsoft Researcher Vera Liao
124 - The PiCAA Framework: My Method to Generate ML/AI Use Cases from a UX Perspective
123 - Learnings From the CDOIQ Symposium and How Data Product Definitions are Evolving with Brian T. O’Neill
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