All Articles by Date

User Adoption: The Wrong Way to Measure the Value of Data Products

By Brian T. O'Neill | June 4, 2024

The sooner you stop believing this, the better off you will be-if you really want to increase the organizational, economic and human value of your data products. Stop measuring your product’s user adoption by counting things like viewing sessions, time on page, and other analytics. In fact, simply measuring “adoption” is wrong-with or without analytics. … Read more

Data Product Management Maturity Model (v. 0.5)

By Brian T. O'Neill | May 1, 2024

I’ve developed a 4-level maturity model for data product management in enterprises, ranging from unaware order-takers to mature, cross-functional teams delivering strategic, high-value data products. Though imperfect, this emerging model aims to provide insights for assessing and advancing organizational maturity in this space.

The (5) Top Reasons AI/ML and Analytics SAAS Product Leaders Come to Me For UI/UX Design Help

By Brian T. O'Neill | March 26, 2024

Plus, a list of (20) symptoms that your enterprise data product, ML app, or SAAS analytics solution has a design problem.

colorful chopped veggies on cutting board

What is a data product?

By Brian T. O'Neill | January 1, 2024

Most definitions of data product focus on trying to firmly define the boundaries of the technology output. My definition focuses on the benefits to the user and the innate requirement of value to be present.

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15 Ways to Increase User Adoption of Data Products (Without Handcuffs, Threats and Mandates) 

By Brian T. O'Neill | November 2, 2023

You probably rock at building enterprise ML and analytics applications, software products, and dashboards-but if buyers, stakeholders, and users just aren’t seeing the value, your problem isn’t your tech. Similarly, the solution is not in your code, pipeline, model, or GitHub. However, there are tactics and strategies from UX design, product management, psychology, marketing and other fields that you can apply so your technical work has impact, creates delight, and generates value.

White brick wall with black lines and orange dots

What was wrong with this founder’s SAAS Analytics UI?

By Brian T. O'Neill | August 29, 2023

“Can you take a look at my UI and provide feedback?” It’s a common question I get. How do we judge a UI/UX design of an SAAS analytics tool? By understanding what the customer is trying to do and what a meaningful outcome looks like. What are the signs we’re on track? Learn more in this story from my time advising MIT Sandbox Venture Fund founders.

10 reasons your customers/stakeholders don’t make time for your data science and analytics initiatives

By Brian T. O'Neill | April 5, 2023

If you’re running an internal enterprise data science or analytics team, and you can’t get the time of your stakeholders and business partners “to help you help them,” there’s probably a reason – or two – or three. These are some of the cold hard facts that maybe they won’t tell you–but maybe they are … Read more

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How Adopting a Product Mindset Can Improve the UX and ROI of Your Data Science and Analytics Work

By Brian T. O'Neill | March 9, 2022

The work of enterprise data science and analytics teams is often experienced in software-whether it be via custom apps, dashboards, or BI tools. As such, data teams are software teams-but many of them do not build solutions the way the best software product teams do. What can data leaders learn-and steal-from software teams who put … Read more

Yes We Can written in scrabble pieces.

Why you need to stop saying yes when they ask, “can you build us a dashboard that shows this data?”

By Brian T. O'Neill | February 14, 2022

If there’s one thing I see a lot of in my work, it’s dashboards.  I don’t talk about dashboards a ton because a dashboard alone is neither a data product nor an experience. It is an output and artifact that is part of a user or stakeholder’s overall experience, typically in our case, in some decision making context. … Read more

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My Top 10 Predictions for Data Product Leaders in 2022

By Brian T. O'Neill | January 3, 2022

Below are ten 2022 predictions for data product leaders and organizations trying to leverage ML and analytics in their software, tools, apps, and services. From the lens of a consulting product designer. Yea, you head that one right. If that PhD in physics, statistics, math or engineering in you is already making you cringe, you may depart this … Read more

Top 10 Experiencing Data Podcast Episodes for 2021

By Brian T. O'Neill | December 14, 2021

Everybody loves a Top 10 list at the end of the year! How about one with pretty lousy data to back it up? 😉 Analytics on analytics here ladies and gentlemen! Since I know this audience will probably be asking what the data is behind the ranking, it’s pretty simple: it’s the number of downloads … Read more

Data as Product: Links to Talks and Articles on Building Data Products

By Brian T. O'Neill | November 22, 2021

A link list of articles and resources on building data products, and particularly the mind shift involved in approaching data products as just that: products, not projects. Is something missing here? Shoot me an email and let me know. From Data to Product (Newsletter, Eric Weber) Run Your Data Team as a Product Team (YouTube) feat. … Read more

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MVPs: The Slow, Expensive Way to Build Data Products?

By Brian T. O'Neill | July 20, 2021

Is there a faster way than MVPs to create data products that actually get used, are simple, and are trustworthy?

10 challenges internal data leaders will face creating a revenue-generating data product

By Brian T. O'Neill | July 6, 2021

Satisfying internal vs. external customers is not the same. What do data science, analytics, and engineering leaders need to know about the messy world of birthing a new commercial data-driven product?

Why software teams need to look beyond “user-centered” when referring to ML or AI-driven data products

By Brian T. O'Neill | June 24, 2021

As a designer, I used to say “user-centered”-a lot. It’s terminology we now hear from non-designers now, people like many of you. That’s a good thing. But, I want you and your teams to think bigger. For me, that “user-centered” descriptor is missing something about design, and particularly so if you are working on ML/AI systems. … Read more

Heads vs. Hands

By Brian T. O'Neill | March 17, 2021

If you’re struggling to solve human problems with data, the mindset of your analytics org may be the problem.

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Intergalactic data infrastructures != customer value

By Brian T. O'Neill | February 1, 2021

Ok, let’s dive into another reader question. This time from Loris via LinkedIn originally: Cheers, Loris My take? Just buy Snowflake – it will fix everything. Just kidding. Actually, one thing I think I’m hearing more from leaders (which is GREAT) is that it’s not the technology that’s the problem. “The technology part is easy.” … Read more

Collection of tools and hammer on a wooden board.

“No more dashboards!”

By Brian T. O'Neill | January 11, 2021

Is it time to stop using dashboards in analytics solutions and data product design?

Bison blocking a country road. by Yann Allegre

How to get 1 x 1 research access to users of enterprise data products—when your own company is in the way

By Brian T. O'Neill | December 21, 2020

Are you a leader in charge of creating innovative ML and analytics solutions within a very large enterprise organization? Getting the “makers” of the solutions talking to real end-users can be extremely difficult. Here’s how to navigate the gatekeepers and bureaucracy so that the data products you spend so much time and money building actually are useful, usable, and valuable.


AI / Product Management / UX Design Predictions for 2021

By Brian T. O'Neill | December 17, 2020

I’m not putting out a long list of 2021 predictions, but I have a couple that I will mention to you that are on my radar. First, AI/Data Product Management Seems to be Picking Up There seem to be more jobs appearing in product management in the AI/ML space, in particular. I am not sure why we don’t … Read more