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
What was wrong with this founder’s SAAS Analytics UI?
“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.
The Definition of Data Product
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.
10 reasons your customers/stakeholders don’t make time for your data science and analytics initiatives
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 … Read more
How Adopting a Product Mindset Can Improve the UX and ROI of Your Data Science and Analytics Work
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 … Read more
Why you need to stop saying yes when they ask, “can you build us a dashboard that shows this data?”
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 … Read more
My Top 10 Predictions for Data Product Leaders in 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 … Read more
Top 10 Experiencing Data Podcast Episodes for 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 … Read more
Data as Product: Links to Talks and Articles on Building Data Products
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 … Read more
MVPs: The Slow, Expensive Way to Build Data Products?
Is there a faster way than MVPs to create data products that actually get used, are simple, and are trustworthy?