Free Insights on Turning ML, AI, and Analytics Into Indispensable Decision Support Applications and Products

Nobody wants another technically right, effectively wrong solution. As a software leader, your analytics/ML/AI technology is only good if you're delivering a positive outcome, not just an output

My resources below will help you learn how to begin applying human-centered design to produce indispensable data-driven software.

Are customers not getting the value out of your data product, analytics SAAS, or decision support application?

My free self-assessment guide covers 9 key topics to help you make your service indispensable. Each day, for 9 days, you will also get an email lesson that goes deeper into the topic and provides recommendations on how to start taking action.

Want to learn how to design engaging data products your customers and stakeholders will use and value?

My self-guided video course—Designing Human-Centered Data Products—can help you learn the creative problem solving skills that data-driven software leaders need to produce useful, usable applications and solutions. Download the first module's video and written supplement, free.

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Recent Articles by Brian

10 Sample Questions to Ask Users of Data Science Solutions to Solicit Needs and Get Problem Clarity

By Brian T. O'Neill

This is a two-part article focused on “what” to ask users of data science solutions and data products, and how to ask/conduct these types of research sessions. In part one, we will look at the “what,” and part two will … Read more 10 Sample Questions to Ask Users of Data Science Solutions to Solicit Needs and Get Problem Clarity

Think clean data is the blocker to your AI/Data Science initiative? Try people.

By Brian T. O'Neill

A few years ago when I started DFA, I wrote this article that aggregates many of the studies on failure rates for big data, analytics, and now AI projects. It serves as a reminder that you can keep throwing money … Read more Think clean data is the blocker to your AI/Data Science initiative? Try people.

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

By Brian T. O'Neill

Technology-driven projects that do not center around human needs continue to fail at a high rate. Here are the continued numbers to back it up.

Analytics Translators = Data Product Management + Service Design?

By Brian T. O'Neill

There’s a lot of buzz about analytics translators these days. In general, I find the name to be a really poor choice for what effectively is a product management role applied to internal data science or analytics services. But, I … Read more Analytics Translators = Data Product Management + Service Design?

A giant mess, peeps to follow, and an “anatomy of a decision”

By Brian T. O'Neill

This post is from Brian’s weekly mailing list. As I write this, I’m heading off to London for another edition of O’Reilly’s Strata conf. If you are headed there, you can catch my talk and mini-workshop on Wed, May. With … Read more A giant mess, peeps to follow, and an “anatomy of a decision”

The CED Design Framework for Integrating Advanced Analytics into Decision Support Software

By Brian T. O'Neill

A UX and UI framework for designing effective decision support software applications that leverage data science and analytics.

How do you make data products and services engaging without AI and advanced analytics?

By Brian T. O'Neill

Low engagement; it’s a common challenge for many of my clients and the people I talk to in the analytics world. In fact, it’s the subject of my talk this year at the IIA Symposium next week. One of the … Read more How do you make data products and services engaging without AI and advanced analytics?

Is an engineering or data-driven culture driving your current data product or analytics initiative toward risk?

By Brian T. O'Neill

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 … Read more Is an engineering or data-driven culture driving your current data product or analytics initiative toward risk?

Why Low Engagement May Not be the Problem With Your Data Product or Analytics Service

By Brian T. O'Neill

If you’re concerned about low engagement with your enterprise data product, analytics service, or decision support tool, then you might be focusing on the wrong problem. What you need to do is design an engaging experience, instead of focusing on … Read more Why Low Engagement May Not be the Problem With Your Data Product or Analytics Service