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Does the value of your insights, analytics, or automated intelligence product sometimes feel invisible to buyers and users? Does your product have impressive analytics and AI technology, but user adoption and sales still are not where you want them to be?
While it has never been easier to build data-driven products, why does it still seem so hard to build indispensable data products that users can't live without—and will gladly pay for?
I’m Brian T. O’Neill, and on Experiencing Data — a Listen Notes top 2% global podcast — I help founders and B2B software product leaders close the Invisible Intelligence Gap through solo episodes and interviews with leaders at the intersection of product management, UX design, analytics, and AI.
If you’re building analytics, BI, or automated intelligence (AI) products, this non-technical show will help you better connect your product to outcomes, value, and the human factors that still matter — even in the age of AI.
Subscribe today on all major platforms or browse the episode archive.
Get 1-Page Episode Summaries:
https://designingforanalytics.com/experiencing-data-podcast/
About the Host, Brian T. O'Neill:
https://designingforanalytics.com/bio/
Does the value of your insights, analytics, or automated intelligence product sometimes feel invisible to buyers and users? Does your product have impressive analytics and AI technology, but user adoption and sales still are not where you want them to be?
While it has never been easier to build data-driven products, why does it still seem so hard to build indispensable data products that users can't live without—and will gladly pay for?
I’m Brian T. O’Neill, and on Experiencing Data — a Listen Notes top 2% global podcast — I help founders and B2B software product leaders close the Invisible Intelligence Gap through solo episodes and interviews with leaders at the intersection of product management, UX design, analytics, and AI.
If you’re building analytics, BI, or automated intelligence (AI) products, this non-technical show will help you better connect your product to outcomes, value, and the human factors that still matter — even in the age of AI.
Subscribe today on all major platforms or browse the episode archive.
Get 1-Page Episode Summaries:
https://designingforanalytics.com/experiencing-data-podcast/
About the Host, Brian T. O'Neill:
https://designingforanalytics.com/bio/
Episodes

Tuesday Dec 01, 2020
053 - Creating (and Debugging) Successful Data Product Teams with Jesse Anderson
Tuesday Dec 01, 2020
Tuesday Dec 01, 2020
In this episode of Experiencing Data, I speak with Jesse Anderson, who is Managing Director of the Big Data Institute and author of a new book
titled, Data Teams: A Unified Management Model for Successful Data-Focused Teams. Jesse opens up about why teams often run into trouble in their efforts to build data products, and what can be done to drive better outcomes.
In our chat, we covered:
- Jesse’s concept of debugging teams
- How Jesse defines a data product, how he distinguishes them from software products
- What users care about in useful data products
- Why your tech leads need to be involved with frontline customers, users, and business leaders
- Brian’s take on Jesse’s definition of a “data team” and the roles involved-especially around two particular disciplines
- The role that product owners tend to play in highly productive teams
- What conditions lead teams to building the wrong product
- How data teams are challenged to bring together parts of the company that never talk to each other – like business, analytics, and engineering teams
- The differences in how tech companies create software and data products, versus how non-digital natives often go about the process
Quotes from Today’s Episode
“I have a sneaking suspicion that leads and even individual contributors will want to read this book, but it’s more [to provide] suggestions for middle,upper management, and executive management.” – Jesse
“With data engineering, we can’t make v1 and v2 of data products. We actually have to make sure that our data products can be changed and evolve, otherwise we will be constantly shooting ourselves in the foot. And this is where the experience or the difference between a data engineer and software engineer comes into place.” – Jesse
“I think there’s high value in lots of interfacing between the tech leads and whoever the frontline customers are…” – Brian
“In my opinion-and this is what I talked about in some of the chapters-the business should be directly interacting with the data teams.” – Jesse
“[The reason] I advocate so strongly for having skilled product management in [a product design] group is because they need to be shielding teams that are doing implementation from the thrashing that may be going on upstairs.” – Brian
“One of the most difficult things of data teams is actually bringing together parts of the company that never talk to each other.” – Jesse
Links
- Big Data Institute
- Data Teams: A Unified Management Model for Successful Data-Focused Teams
- Follow Jesse on Twitter
- Connect with Jesse on LinkedIn

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