Today, I’m sharing my impressions of one of Spotify’s analytics touchpoints—a monthly email I receive with a boatload of design choices I mostly hope you will not copy, especially if you’re working in an enterprise capacity. Most of you by now probably know I have another career as a professional musician, and that includes having three recordings I … Read more
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.
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?
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.
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.
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…
You got the data. Your model rocks. Your analytics are impressive. But, do customers see indispensable decision support….or a metrics toilet?
Today I want to tell you why your ugly, clunky, hard-to-use data/AI product or analytics solution should scare you. But first, you, your boss, your customer, your stakeholder—somebody—has to pass that judgement on it. They probably have, but don’t expect it to necessarily come out in the words you may expect. Just as most designers (in … Read more
AI and Machine Learning Are Not a Panacea for Underused Analytics Services Ears, Eyes and Empathy Guide the Best MVPs Since AI, predictive, and prescriptive analytics are big right now, there is a tendency for companies to “want” to use this technology and throw it into their marketing jargon as well. Boards and executives are … Read more
Author’s Note: This article was originally published to my mailing list, hence the reference to previous emails and published podcast episodes. Before I jump into this week’s article on MVPs for custom data products, just wanted to address one listener’s response to the new podcast in case others had the same experience. Re: the audio … Read more