Nobody Wants ML, AI, and Analytics.

Customers and users want a UX that provides indispensable decision support, useful insights, and actionable intelligence—their way. 

Before business value can emerge from your data product, there must be adoption, trust, usabilty and utility. 

This is the domain of human-centered design.

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

One of the only email subscriptions I read

Your [list] is one of only a few email subscriptions I read. Super bright and always thoughtful.

Nancy Duarte Nancy Duarte
Principal @ Duarte
Author & TED Speaker

Additional Resources

Are customers not getting the value out of your data product, analytics SAAS, or decision support application?

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.

Want to learn how to design engaging data products your customers and stakeholders will use and value?

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 Webinars

See my Speaking page for samples.

🔍 Article Search

Browse by Topic

📖  Reading

Browse my reading list.

Videos

Subscribe to my YouTube Channel to see conference talks, sample UI/UX audits, and more.

Watch Conference Talks

Recent Articles by Brian

My Too-White Data Podcast Looks ~Like This: 🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲🧑‍🦲👩‍🦰👨🏾

By Brian T. O'Neill

Self-reflecting on #BLM, the makeup of my podcast guests to date, racism, and the responsibilities of consultants with platforms and audiences in fighting injustice.

A UI Design Audit of MITRE’s Covid-19 Decision Support Dashboard

By Brian T. O'Neill

I performed a rapid UI/UX and data visualization audit on the MITRE Covid-19 Healthcare Coalition Decision Support Dashboard. Watch it here, and see my recommended design changes the team should make.

$1M spent on a predictive model/data science w/ $0 value and no user engagement?

By Brian T. O'Neill

How to avoid spending 6-8 months on a technically right, effectively wrong model. Are you successful with ML if nobody uses your solution, model, or application?

(6) Ways to Sanitize Your Data Product, Dashboard Visuals or Analytics due to Covid-19

By Brian T. O'Neill

Covid-19 presents a major disruption to our lives and businesses. However, sanitizing your hands isn’t the only thing you data leaders need to be considering. Your data product, dashboards, or UI may also need to be cleaned up. No hard-to-find Clorox wipes needed; just some good design thinking centered around your customers.

UX Designers & Data Scientists: United in Job Misery?

By Brian T. O'Neill

My conversations and research suggest that individual contributor UX designers and data scientists share one thing in common: it’s often a challenge to “get to do the job I was hired for.” People, process, and political roadblocks at every turn—so what can you do about it if this is you? And if you’re managing these people, what are you doing to ensure these people don’t leave?

Empathy & Human-Centered Design in a World with the Coronavirus

By Brian T. O'Neill

It takes more than math and technical skills to develop simple, useful, and usable decision support solutions. It starts with problem clarity, customer empathy and…

Technically Right, Effectively Wrong: Why 85% Data Science Projects Fail

By Brian T. O'Neill

It takes more than math and technical skills to develop simple, useful, and usable decision support solutions. It starts with problem clarity, customer empathy and…

10 human reasons your data product or solution may fail

By Brian T. O'Neill

It takes more than math and technical skills to develop simple, useful, and usable decision support solutions. It starts with problem clarity, customer empathy and…

Should a vision for a new AI or data product be inspired by existing data…or not?

By Brian T. O'Neill

How should we be innovating in AI? Work backwards from in-shape data? Or start with a vision for how we’ll create value for the customer or organization?