Experiencing Data w/ Brian T. O’Neill - Data Products, Product Management, & UX Design  By  cover art

Experiencing Data w/ Brian T. O’Neill - Data Products, Product Management, & UX Design

By: Brian T. O’Neill from Designing for Analytics
  • Summary

  • If you’re a leader tasked with generating business and org. value through ML/AI and analytics, you’ve probably struggled with low user adoption. Making the tech gets easier, but getting users to use, and buyers to buy, remains difficult—but you’ve heard a ”data product” approach can help. Can it? 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 designer’s perspective on why creating ML and analytics outputs isn’t enough to create business and UX outcomes. How can UX design and product management help you create innovative ML/AI and analytical data products? What exactly are data products—and how can data product management help you increase user adoption of ML/analytics—so that stakeholders can finally see the business value of your data? Every 2 weeks, I answer these questions via solo episodes and interviews with innovative chief data officers, data product management leaders, and top UX professionals. Hashtag: #ExperiencingData. PODCAST HOMEPAGE: Get 1-page summaries, text transcripts, and join my Insights mailing list: https://designingforanalytics.com/ed ABOUT THE HOST, BRIAN T. O’NEILL: https://designingforanalytics.com/bio/
    © 2019 Designing for Analytics, LLC
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Episodes
  • 142 - Live Webinar Recording: My UI/UX Design Audit of a New Podcast Analytics Service w/ Chris Hill (CEO, Humblepod)
    Apr 30 2024

    Welcome to a special edition of Experiencing Data. This episode is the audio capture from a live Crowdcast video webinar I gave on April 26th, 2024 where I conducted a mini UI/UX design audit of a new podcast analytics service that Chris Hill, CEO of Humblepod, is working on to help podcast hosts grow their show. Humblepod is also the team-behind-the-scenes of Experiencing Data, and Chris had asked me to take a look at his new “Listener Lifecycle” tool to see if we could find ways to improve the UX and visualizations in the tool, how we might productize this MVP in the future, and how improving the tool’s design might help Chris help his prospective podcast clients learn how their listener data could help them grow their listenership and “true fans.” On a personal note, it was fun to talk to Chris on the show given we speak every week: Humblepod has been my trusted resource for audio mixing, transcription, and show note summarizing for probably over 100 of the most recent episodes of Experiencing Data. It was also fun to do a “live recording” with an audience—and we did answer questions in the full video version. (If you missed the invite, join my Insights mailing list to get notified of future free webinars).

    To watch the full audio and video recording on Crowdcast, free, head over to: https://www.crowdcast.io/c/podcast-analytics-ui-ux-design

    Additional show notes, full transcription, and quotes for this episode are coming soon.

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    51 mins
  • 141 - How They’re Adopting a Producty Approach to Data Products at RBC with Duncan Milne
    Apr 16 2024

    In this week's episode of Experiencing Data, I'm joined by Duncan Milne, a Director, Data Investment & Product Management at the Royal Bank of Canada (RBC). Today, Duncan (who is also a member of the DPLC) gives a preview of his upcoming webinar on April 24, 2024 entitled, “Is that Data Product Worth Building? Estimating Economic Value…Before You Build It!” Duncan shares his experience of implementing a product mindset within RBC's Chief Data Office, and he explains some of the challenges, successes, and insights gained along the way. He emphasizes the critical role of understanding user needs and evaluating the economic impact of data products—before they are built. Duncan was gracious to let us peek inside and see a transformation that is currently in progress and I’m excited to check out his webinar this month!

    Highlights/ Skip to:

    • I introduce Duncan Milne from RBC (00:00)
    • Duncan outlines the Chief Data Office's function at RBC (01:01)
    • We discuss data products and how they are used to improve business process (04:05)
    • The genesis behind RBC's move towards a product-centric approach in handling data, highlighting initial challenges and strategies for fostering a product mindset (07:26)
    • Duncan discusses developing a framework to guide the lifecycle of data products at RBC (09:29)
    • Duncan addresses initial resistance and adaptation strategies for engaging teams in a new product-centric methodology (12:04)
    • The scaling challenges of applying a product mindset across a large organization like RBC (22:02)
    • Insights into the framework for evaluating and prioritizing data product ideas based on their desirability, usability, feasibility, and viability. (26:30)
    • Measuring success and value in data product management (30:45)
    • Duncan explores process mapping challenges in banking (34:13)
    • Duncan shares creating specialized training for data product management at RBC (36:39)
    • Duncan offers advice and closing thoughts on data product management (41:38)
    Quotes from Today’s Episode
    • “We think about data products as anything that solves a problem using data... it's helping someone do something they already do or want to do faster and better using data." - Duncan Milne (04:29)
    • “The transition to data product management involves overcoming initial resistance by demonstrating the tangible value of this approach." - Duncan Milne (08:38)
    • "You have to want to show up and do this kind of work [adopting a product mindset in data product management]…even if you do a product the right way, it doesn’t always work, right? The thing you make may not be desirable, it may not be as usable as it needs to be. It can be technically right and still fail. It’s not a guarantee, it’s just a better way of working.” - Brian T. O’Neill (15:03)
    • “[Product management]... it's like baking versus cooking. Baking is a science... cooking is much more flexible. It’s about... did we produce a benefit for users? Did we produce an economic benefit? ...It’s a multivariate problem... a lot of it is experimentation and figuring out what works." - Brian T. O'Neill (23:03)
    • "The easy thing to measure [in product management] is did you follow the process or not? That is not the point of product management at all. It's about delivering benefits to the stakeholders and to the customer." - Brian O'Neill (25:16)
    • “Data product is not something that is set in stone... You can leverage learnings from a more traditional product approach, but don’t be afraid to improvise." - Duncan Milne (41:38)
    • “Data products are fundamentally different from digital products, so even the traditional approach to product management in that space doesn’t necessarily work within the data products construct.” - Duncan Milne (41:55)
    • “There is no textbook for data product management; the field is still being developed…don’t be afraid to create your own answer if what exists out there doesn’t necessarily work within your context.”- Duncan Milne (42:17)
    Links
    • Duncan’s Linkedin: https://www.linkedin.com/in/duncanwmilne/?originalSubdomain=ca
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    44 mins
  • 140 - Why Data Visualization Alone Doesn’t Fix UI/UX Design Problems in Analytical Data Products with T from Data Rocks NZ
    Apr 2 2024
    This week on Experiencing Data, I chat with a new kindred spirit! Recently, I connected with Thabata Romanowski—better known as "T from Data Rocks NZ"—to discuss her experience applying UX design principles to modern analytical data products and dashboards. T walks us through her experience working as a data analyst in the mining sector, sharing the journey of how these experiences laid the foundation for her transition to data visualization. Now, she specializes in transforming complex, industry-specific data sets into intuitive, user-friendly visual representations, and addresses the challenges faced by the analytics teams she supports through her design business. T and I tackle common misconceptions about design in the analytics field, discuss how we communicate and educate non-designers on applying UX design principles to their dashboard and application design work, and address the problem with "pretty charts." We also explore some of the core ideas in T's Design Manifesto, including principles like being purposeful, context-sensitive, collaborative, and humanistic—all aimed at increasing user adoption and business value by improving UX. Highlights/ Skip to: I welcome T from Data Rocks NZ onto the show (00:00)T's transition from mining to leading an information design and data visualization consultancy. (01:43)T discusses the critical role of clear communication in data design solutions. (03:39)We address the misconceptions around the role of design in data analytics. (06:54) T explains the importance of journey mapping in understanding users' needs. (15:25)We discuss the challenges of accurately capturing end-user needs. (19:00) T and I discuss the importance of talking directly to end-users when developing data products. (25:56) T shares her 'I like, I wish, I wonder' method for eliciting genuine user feedback. (33:03)T discusses her Data Design Manifesto for creating purposeful, context-aware, collaborative, and human-centered design principles in data. (36:37)We wrap up the conversation and share ways to connect with T. (40:49) Quotes from Today’s Episode "It's not so much that people…don't know what design is, it's more that they understand it differently from what it can actually do..." - T from Data Rocks NZ (06:59)"I think [misconception about design in technology] is rooted mainly in the fact that data has been very tied to IT teams, to technology teams, and they’re not always up to what design actually does.” - T from Data Rocks NZ (07:42) “If you strip design of function, it becomes art. So, it’s not art… it’s about being functional and being useful in helping people.” - T from Data Rocks NZ (09:06) "It’s not that people don’t know, really, that the word design exists, or that design applies to analytics and whatnot; it’s more that they have this misunderstanding that it’s about making things look a certain way, when in fact... It’s about function. It’s about helping people do stuff better." - T from Data Rocks NZ (09:19)“Journey Mapping means that you have to talk to people... Data is an inherently human thing. It is something that we create ourselves. So, it’s biased from the start. You can’t fully remove the human from the data" - T from Data Rocks NZ (15:36) “The biggest part of your data product success…happens outside of your technology and outside of your actual analysis. It’s defining who your audience is, what the context of this audience is, and to which purpose do they need that product. - T from Data Rocks NZ (19:08)“[In UX research], a tight, empowered product team needs regular exposure to end customers; there’s nothing that can replace that." - Brian O'Neill (25:58) “You have two sides [end-users and data team] that are frustrated with the same thing. The side who asked wasn’t really sure what to ask. And then the data team gets frustrated because the users don’t know what they want…Nobody really understood what the problem is. There’s a lot of assumptions happening there. And this is one of the hardest things to let go.” - T from Data Rocks NZ (29:38)“No piece of data product exists in isolation, so understanding what people do with it… is really important.” - T from Data Rocks NZ (38:51) Links Design Matters Newsletter: https://buttondown.email/datarocksnz Website: https://www.datarocks.co.nz/LinkedIn: https://www.linkedin.com/company/datarocksnz/BlueSky: https://bsky.app/profile/datarocksnz.bsky.socialMastodon: https://me.dm/@datarocksnz
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    43 mins

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