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.
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Recent Articles by Brian
(8) reasons why data visualization training for your BI team may not increase analytics adoption
Customers want simple, well-designed decision support tools and UX’s that are actionable. Businesses want to see value from data and adoption of data-driven decision making. However, the UX that is afforded to is often simply a byproduct of the analytics team’s engineering, or, at best, “data viz” efforts—and it’s not working. A decade later, success rates for data projects remain unchanged, despite vendor/BI tooling improvements. What are BI/analytics teams still missing? Design.
Humans – The Weak Link in your ML / AI Strategy?
In many cases, machine learning needs to be deployed to augment human decision making, not automate it. What are you doing to account for this dependency on the success of your data product?
My Too-White Data Podcast Looks ~Like This: 🧑🦲🧑🦲🧑🦲🧑🦲🧑🦲🧑🦲🧑🦲🧑🦲👩🦰👨🏾
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
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?
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
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?
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
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
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…