Nobody Wants Your ML/AI or Analytics!

Are you struggling to produce clear business or organizational value with your ML and analytics? Is user adoption of your dashboards, models, and apps lower than you'd hoped—despite giving the stakeholder what they asked for?

I believe that a "product orientation" is critical for any data and technology team seeking to turn data products into high value, usable, and useful solutions. What does that mean?

Get started with some of my resources below on data product management, data product UX design, and more.

New to Data Products? Start here:

My Definition of a Data Product (Start Here!)

All of my work is framed around this definition, so start here before reading anything else. Definitions about reusable containers, assets, data mesh, and the like are wrong in my opinion. Data products are more about how we work than the output. It's rooted in the idea that the job of a data product leader is to produce benefits not outputs.

Join my Insights Mailing List

This is home base for all of my thinking on data product UX design and product management. A portion of my weekly insights also get published on this website. Subscribers also get access to 1-page summaries of my podcast, early access to my newest offerings, and more.

15 Ways to Increase Adoption of Data Products

Available in both written and audio formats. One of my most popular resources for data product leaders struggling to increase the user adoption and business value of their ML and analytics solutions.

The Top (5) Reasons Enterprise ML/AI/Analytics SAAS Leaders Come to Me for UI/UX Design Help

Got that itch that maybe your product's data and tech isn't the reason customers aren't buying, demos aren't closing, churn is increasing, and the people who already paid aren't using the service? Here are the top (5) reasons founders, CxOs, and product leaders reach out to me for help—and the (20) key symptoms I see surface in the product itself.

Data Product Management Maturity Model

Do you lead a large enterprise data team? In 2024, I started to think about how orgs with large data teams might transition to a product-driven approach to building ML and analytics solutions—and what that maturity might look like. View the latest thinking

Data Product UX Design Resources

CED UX Framework for Advanced Analytics & ML Apps

A 3-part UX design framework for designing advanced decision support applications and tools specifically designed for data product leaders. Article and audio formats.

PiCAA Framework for Envisioning AI Use Cases

A 5-part method to generate ML/AI use cases from a UX perspective.

UX Design Considerations for LLM-Based GenAI Features in Enterprise Applications

Available in article and podcast format.

Download my Self-Assessment Guide for Analytics Apps

My free self-assessment guide covers 9 key topics to help you make your service indispensable. Each day, for 9 days, you will also get an email lesson that goes deeper into the topic and provides recommendations on how to start taking action.

Free Course Sample from Designing Human-Centered Data Products

My self-guided video course—Designing Human-Centered Data Products—can help you learn the creative problem solving skills that data-driven software leaders need to produce useful, usable applications and solutions. Download the first module's video and written supplement, free.

Podcast, Free Videos, Article Search and More:

🎧 Podcast

Free Webinars

Videos/Conference Talks

See my YouTube Channel and Speaking page.

🔍 Articles

I recommend searching my archive via Google or take your chance with WordPress' search below!

Join My Insights Mailing List

I only post select articles to the website. To get my latest thinking weekly in your inbox, plus summaries of my bi-weekly podcast, subscribe for free here.

Recent Articles by Brian

The Easiest Way to Simplify Your Product or Solution’s Design

By Brian T. O'Neill

Ok, you probably know this one, but let’s dig in a little farther. I recently started to explore using the TORBrowser when surfing on public wi-fi for more security (later finding out that using a VPN, and not TOR, is … Read more

(8) invisible design problems that are business problems

By Brian T. O'Neill

Today’s insight was originally inspired by a newsletter I read from Stephen Anderson on designing for comprehension, and I felt like this could be expanded on for analytics practitioners and people working on data products. One of the recurring themes … Read more

What internal analytics practitioners can learn from analytics “products” (like SAAS)

By Brian T. O'Neill

When I work on products that primarily exist to display analytics information, I find most of them fall into roughly four different levels of design maturity: The best analytics-driven products give actionable recommendations or predictions written in prose telling a user what … Read more

My reactions to the Chief Data Officer, Fall 2017 conference summary

By Brian T. O'Neill

I ran into a an article about the Chief Data & Analytics Officer, Fall conference that summarized some of the key takeaways at the previous year’s conference. One paragraph in the article stuck out to me: … The Great Dilemma – Product … Read more

How can you possibly design your service effectively without these?

By Brian T. O'Neill

I’m working with a large, household-name technology company right now on a large project, and they struggle with one of the same things so many of my clients struggle with. Today’s topic is articulating use cases and goals in an … Read more

Reader questions answered: “what are your top concerns designing for analytics?”

By Brian T. O'Neill

Today I want to respond to a reader who answered a previous email I sent you all about your top concerns designing for analytics. Here’s Évans’ email: +++++ In analytics, it’s not like a CRUD [Create-Read-Update-Delete] with a simple wizard-like workflow (Input … Read more

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.