Why your ugly, clunky, hard-to-use data product or solution should scare you

frustrated worker at computer with hands over his eyes

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 moreWhy your ugly, clunky, hard-to-use data product or solution should scare you

Keeping Analytics Solutions in Check with Customer Needs

Toy men assembling something with frustration

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 moreKeeping Analytics Solutions in Check with Customer Needs

Designing MVPs for Data Products and Decision Support Tools

Rough prototype of a miniature car powered by a AA battery

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 moreDesigning MVPs for Data Products and Decision Support Tools

Video Sample: 2018 O’Reilly Strata Conference (NYC)

This is recording of my presentation at the O’Reilly Strata Data Conference in New York City in 2018. Gartner says 85%+ of big data projects will fail, despite the fact your company may have invested millions on engineering implementation. Why are customers and employees not engaging with these products and services? Brian O’Neill explains why a … Read moreVideo Sample: 2018 O’Reilly Strata Conference (NYC)

Why the difference between design and Design may make or break your data product.

Commuters in a Terminal

Good Design–what I sometimes call—”Capital D Design”—has the power to make your data sing, delight customers/users, bring new/better ROI to your organization, provide inspiration to teams, reduce complexity, reduce engineering cost, save time for users, and expose new value in your existing service. However, the big gains usually don’t come from focusing on the surface level alone. Better data visualization cannot fix every data product and analytics problem.

Dashboard Design: Is Maximum Simplicity the Goal?

Should maximum simplicity dictate success? We all love usability these days right? “User experience is important.” Of course it is! But, it doesn’t mean that every user you show the design to is going to, or should immediately be able to, understand fully what you’re showing them. Why? Most valuable things in life take a … Read moreDashboard Design: Is Maximum Simplicity the Goal?

How can you possibly design your service effectively without these?

I’m working with a large, household-name technology company right now on a large project, and they struggle with one of the same things so many of my clients struggle with. Today’s topic is articulating use cases and goals in an effective manner that allows your design and development to proceed with clarity and accountability. If … Read moreHow can you possibly design your service effectively without these?

Reader questions answered: “what are your top concerns designing for analytics?”

Today I want to respond to a reader who answered a previous email I sent you all about your top concerns designing for analytics. Here’s Évans’ email: +++++ In analytics, it’s not like a CRUD [Create-Read-Update-Delete] with a simple wizard-like workflow (Input – Validate – Save). It’s kinda hard to keep the user focused when there are … Read moreReader questions answered: “what are your top concerns designing for analytics?”

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