(8) invisible design problems that are business problems

Today’s insight was originally inspired by a newsletter I read from Stephen Anderson on designing for comprehension, and I felt like this could be expanded on for analytics practitioners and people working on data products. One of the recurring themes I hear from my clients is around the topic of general engagement (or lack thereof) … Read more(8) invisible design problems that are business problems

What internal analytics practitioners can learn from analytics “products” (like SAAS)

When I work on products that primarily exist to display analytics information, I find most of them fall into roughly four different levels of design maturity: The best analytics-driven products give actionable recommendations or predictions written in prose telling a user what to do based on data.  They are careful about the quantity and design of the … Read moreWhat internal analytics practitioners can learn from analytics “products” (like SAAS)

Failure rates for analytics, BI, and big data projects = 85% – yikes!

Not to be the bearer of bad news, but I recently found out just how many analytics, IOT, big data, and BI projects fail. And the numbers are staggering. Here’s a list of articles and primary sources. What’s interesting to me about many of these is the common issue around “technology solutions in search of … Read moreFailure rates for analytics, BI, and big data projects = 85% – yikes!

My reactions to the Chief Data Officer, Fall 2017 conference summary

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

Getting confidence in the value of your data

(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

UI Review: Next Big Sound (Music Analytics) – Part 1

Today I got an interesting anomaly email from a service I use called Next Big Sound. Actually, I don’t use the service too much, but it crosses two of my interests: music and analytics. Next Big Sound aggregates music playback data from various music providers (Spotify, Pandora, etc) and also, apparently, tries to correlate changes … Read moreUI Review: Next Big Sound (Music Analytics) – Part 1

Tips to help focus your analytics design/engineering efforts on results

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

“Post-truth,” data analytics, and omissions–are these design considerations?

Post-truth. The 2016 word of the year. Yikes for some of us. This got me thinking about UX around data, analytics, and information, and what it means when we present conclusions or advice based on quantitative data. Are those “facts”? If your product generates actionable information for customers, then during your design phase, your team … Read more“Post-truth,” data analytics, and omissions–are these design considerations?

Think it’s hard building an analytics product or service? Try cutting features out.

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.

A Venture Capitalist’s Take on Designing Useful Big Data Products

I loved this quote: ”Identify 2-3 need-to-know insights, and make that the focus of the product. Rather than thinking about competing products, think about competing processes. The goal of the product is to be consistently used by all users, not just power users, and the only way to accomplish this is to make it as simple as possible to discover the … Read moreA Venture Capitalist’s Take on Designing Useful Big Data Products