116 - 10 Reasons Your Customers Don’t Make Time for Your Data Product Initiatives + A Big Update on the Data Product Leadership Community (DPLC)
Do you ever find it hard to get the requirements, problems, or needs out of your customers, stakeholders, or users when creating a data product? This week I’m coming to you solo to share reasons your stakeholders, users, or customers may not be making time for your discovery efforts. I’ve outlined 10 reasons, and delve into those in the first part of this episode.
In part two, I am going to share a big update about the Data Product Leadership Community (DPLC) I’m hoping to launch in June 2023. I have created a Google Doc outlining how v1 of the community will work as well as 6 specific benefits that I hope you’ll be able to achieve in the first year of participating. However, I need your feedback to know if this is shaping up into the community you want to join. As such, at the end of this episode, I’ll ask you to head over to the Google Doc and leave a comment. To get the document link, just add your email address to the DPLC announcement list at http://designingforanalytics.com/community and you’ll get a confirmation email back with the link.
Links
Join the Data Product Leadership Community at designingforanalytics.com/thecommunity
My definition of “data product” is outlined on Experiencing Data Episode 105
Product vs. Feature Teams by Marty Cagan
Email Brian at brian@designingforanalytics.com.
Om Podcasten
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.
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