(Note: this article is updated from time to time as I encounter similar studies and news on this theme.) Not to be the bearer of bad news, but I recently found out just how many data science, analytics, IOT, big data, and BI projects fail. And the numbers are staggering. Here’s a list of articles … Read moreFailure rates for analytics, AI, and big data projects = 85% – yikes!
A three-part UX framework for designing your ML / predictive / prescriptive analytics UI around trust, engagement, and indispensability. As you continue to design interfaces and experiences into your analytics tools that rely more and more on machine-based analysis and prediction, the challenge within the design starts to change. Whereas before, we might be dealing … Read moreC-E-D: A Design (UX) Framework for Integrating Advanced Analytics into Decision Support Software
Here are (25) design faults that should trigger the check-engine light I really don’t know much about cars. Furthermore, with all the computers on them now, I probably never will. However, I do care when the “CEL” goes on. The CEL, or check-engine light, is that often cryptic, blood-pressure-raising notification that mostly just makes you … Read moreIs an engineering or data-driven culture driving your current data product or analytics initiative toward risk?
Good design happens at the intersection of discovering real user needs/wants and business goals that are ACTIONABLE (by design and engineering). Yes, there’s a little magic/instinct that creeps into good design too, but you can get far without a lot of this magic. It’s really more about nailing the problem set, and having really clear … Read moreReasons your next sprint, product, or project might fail
Readers of DFA know that I’m big on not immediately giving customers what they asked for, and instead asking the question “why” to learn what the real latent customer needs are. And for you internal analytics folks, remember your employees, vendors, etc. are your “customers” whether you think of them that way or not! Anyhow, … Read moreHow to solicit *real* needs from users via UX research interviews
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 what will enable safer surfing). However, in the process of downloading and trying the TORBrowser … Read moreThe Easiest Way to Simplify Your Product or Solution’s Design
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 vs Project vs Capability Analytics Approaches Although not one of these approaches will provide a … Read moreMy reactions to the Chief Data Officer, Fall 2017 conference summary
(As shown to customers in your UI) I’m talking to a prospective SAAS client right now, and they’re trying to expose some analytics on their customers’ data so that the customers can derive ROI from the SAAS on their own. The intent is that the data can also be useful to the SAAS sales team, … Read moreGetting confidence in the value of your data
If you are starting out on a new feature design, or analytics effort, can you clearly state what the value will be in quantifiable terms at the end of the sprint? Are you building an “exploratory” UI, or one that is supposed to drive home conclusions for the customer? When clients come to me about … Read moreTips to help focus your analytics design/engineering efforts on results
Try cutting features out of it. Apparently, that whole quote from Michaelangelo about “I just carve away the part of the statue that doesn’t look like David” is a myth. But, it’s a good myth for design thinkers. It helps me remember that you can add customer value by removing materials from a design. We talk a … Read moreThink it’s hard building an analytics product or service? Try cutting features out.