Designing Human-Centered Data Products (Seminar)

In just 4 core weeks, learn to increase the user adoption and business value of your ML and analytics applications via data product management and UX design.

Prange cut in half, painted blue on the outside, on a matching blue background, showing the inside unpainted portion.

Is your team tired of building data solutions that don't get used or are undervalued?

Is low user engagement preventing your data initiatives from generating their full potential business value?

~85% of AI, data, and analytics projects fail to deliver value or make it into production. Your company or team can contribute to that, or you can join the 15% who are creating useful, usable solutions that customers need.

Is the team sick of hearing customers say, “So what? What do I do with this data?” when they see their solutions?

Are you afraid your budget or team might be facing cuts because your solutions are having little impact?

Is it frustrating when all of your team's technical work ends up never getting into production, perhaps due to model trust?

Does your team frequently get inflated requests to "use AI" or "ML" because the project sponsor doesn't understand what's possible with data?

Wouldn't it be amazing if users felt your team's data products were “game changers?”

Imagine knowing what is going to get adopted by users before your team starts building the solution

Imagine hearing, “This is amazing! Can we start using it now?” when users see better data products emerging

Imagine management doubling your budget because your solutions are delivering enormous value they can actually quantify or feel

"Technically right, effectively wrong" data products aren't good for you, your users, or your stakeholders. My seminar will give you the non-technical skills to make your team's solutions indispensable.

Whether you're leading a commercial software data product (i.e. SAAS/cloud decision support, market intelligence, IOT analytics) or you oversee an internal BI team or AI/ML initiative where simplicity, user engagement, and successful operationalization are critical to value creation, you're in the right place.

If your data products rely on human engagement, then success boils down to the UX you deliver in the last mile. Doing this requires more than technical or business skills. Design is the glue that connects the stats, analytics, AI, ML, and engineering work with the value and outcomes the business and customers seek. In short, users don't want data; they want clear answers and actionable decision support.

My training seminar will teach your team to:

  • Understand what users and stakeholders actually need
  • Avoid building the wrong solutions through better problem definition
  • Ensure stakeholders understand the value a proposed data product will bring
  • Identify the unspoken needs, desires, and whys in your customers' minds
  • Turn vague “AI” requests from stakeholders into clear data science / tech work
  • Getting alignment on what to build before you build it
  • Develop a "product" mindset to delivering decision support solutions
  • Find out if users will adopt your solution before you invest too much in developing it
  • Navigate the organizational obstacles that might keep your solution from getting incorporated into production
  • Lead a cross-department design jams (ideation sessions) to generate solution ideas
  • Learn to rapidly sketch evaluate, and revise a prototype/design/idea
  • Design vs. just doing design thinking!

Before the seminar ended, I had already seen direct results. It's totally worth the price.

“I remember the moment stopping dead in my tracks while on a run. I was listening to episode 49 of Brian’s podcast, Experiencing Data, and it suddenly clicked: THIS is what my data team had been missing. I knew data science and design needed to be integrated in order for us to build better data products for our customers, and this seminar helps you do just that. Before the seminar ended, I had already seen direct results: several of our clients commented on how they’d noticed a change in how our team engages them and that they really felt heard. Having your data teams incorporate a design mindset, and a general embrace of UX, is totally worth the price of Brian’s seminar. In fact, I’ve already set aside budget to enroll another person on my data team to a future cohort”

Bill BaezDr. William Baez
Data Scientist & VP of Strategy
Ascend Innovations
[Seminar Participant]

Switching my mindset from outputs to outcomes was a total game changer for me.

“Brian's more practical, targeted approach in this seminar has been very beneficial as it was focused specifically on designing data products with UX in mind. It’s not every time you can meet someone, ask questions and get useful responses, and I was able to do that in Brian’s seminar. In addition to realizing some of the common mistakes I had been making, I also had a big aha moment: understanding outcomes versus outputs. This is more valuable than some of the tactical things because you shift your frame of mind and it’s a total game changer. The way you interact with your users and develop and deliver a solution completely changes. That’s the power of that wisdom. I’ll be referring back to the content and videos from the seminar now and again, and I’d definitely recommend this seminar to other technical product managers.

Meenakshi SharmaMeenakshi Sharma
Technical Product Manager, AI/ML
[Seminar Participant]

Who is this seminar for?

It's for current and aspiring data product leaders and data product managers.

It's for people who know that it takes more than technology, engineering, modeling and data to produce value when humans are in the loop...but they don't have a set of recipes and the support to begin making the change.

If you're leading the creation of a data product—commercial or otherwise—and you have responsibility to ensure the solution is useful, usable, and valuable to your customers, this seminar can help.

Past participants have included BI/AI teams at pharma companies, AI/ML product managers at tech companies, managing directors and principals at AI/ML/analytics consulting firms, and VP/directors of applied data science teams. Private team cohorts can vary in their mix from ICs to upper management, but I recommend the key stakeholders and management participate in the first cohort to help understand if their ICs and leads are a good fit for future training.

You may be a:

  • VP/Director/Manager of a BI, analytics, data science, or engineering team looking to understand "what skills are my team missing to get people to use our solutions?" Managers sometimes take the Seminar so they are up to date with the changes that may be required in their organization to enable their team to be successful with the curriculum.
  • Lead data scientists, analytics/BI consultants, translators, and informatics leaders
  • Data product managers (AI/ML, IOT, SAAS intelligence services, decision support solutions, or  technical tools)
  • Consultant/service firm leader providing data science, analytics, or digital services
  • Data/AI/ML startup founders
  • UX designers/researchers focused on data products

If you're good at the technical parts—data science, analytics, or engineering—but find it hard to turn your outputs into indispensable outcomes, you probably are a good fit.

Who is this seminar NOT for?

You likely will not find this training useful if:

  • You're primarily doing execution oriented work or want to focus mostly on heads-down technical implementation
  • You're more interested in getting a grade or certificate than applying the training to your work
  • You're not ready to make changes to how you currently design or build data products
  • You plan to just "observe" silently
  • You were assigned to take the training as part of a private cohort, but don't have more than a passing curiosity about it
  • You're not ready or interested in being a leader, or evangelizing the ideas in the seminar so they can begin to spread (hint: design is a team sport that begins with individuals)

I would recommend this seminar. Brian gives really clear feedback and understands what we [as data scientists] deal with when trying to design effective data products.

“I would recommend this seminar. You clearly pinpointed us to specific things around keeping the actual needs of a specific user in mind. We also very much appreciated your input, which was really clear and would make us ask, ‘does this bring value to the user? What is the actual value?’ It's also good to have more than one person [in the seminar] if you're working as a team as it helps to do some sparring and to collect questions to bring back into the Seminar. Finally, I just really liked how you led through it and were able to jump between topics or send us some links afterwards for further study. I think you're pretty capable of putting yourself into the positions of others and have an understanding of what we are dealing with.”

Matthias BöckMatthias Böck
Data Scientist
[Seminar Participant]
Cover Image - Designing Human-Centered Data Products by Brian T. O'Neill (cover image for the curriculum book)

Curriculum: (8) Core Modules

A very solid framework to get started on design for data solutions

It's a quick and accessible snapshot of how to think about user design for data solutions products. You can go deep in UX design, you can talk about data solutions, but how do you combine the two in a very digestible way? I think it’s a very solid framework to get started. I would definitely recommend the seminar.

Wendy RobertsWendy Roberts
Manifold (AI Engineering Consultancy)
[Seminar Participant]

My curriculum is a mix of UX design, product management, consulting and other applicable skills from domains as far away as FBI hostage negotiation—but always focused on skills you can put into practice immediately. There are no grades or certificates. Most modules also include a section on "Key Considerations for AI," which explain the special design considerations for machine-learning applications that may differ from traditional (descriptive) analytics applications.

The modules are:

Brian's process was holistic and internally consistent

"I never had fully appreciated the level of integration and the number of different disciplines required to arrive at a thoughtful piece of analysis that properly communicates the evidentiary support for my argument…What I like about Brian's seven step process is that it is holistic and internally consistent. Each piece builds off of the previous pieces…and Brian presents it as a repeatable process…There are a lot of things about designing UI things I just never would have thought of. I think the people who will probably get the most benefit out of Brian's seminar will be people who are more senior level people. Junior people are just not being asked to deal with the entire lifecycle, which is what the seminar is about."

Brian ClancyBrian Clancy
Managing Director
Logistics Capital & Strategy
[Seminar Participant]

Is your team ready?

Let's talk!

Schedule a free 30-min discovery call here:

Get your questions answered—and get my advice if your team is ready.

Space in my calendar to teach this seminar is limited.

Totally worth the investment. I would recommend Brian’s seminar if your team is looking for a solid structure to design better data products.

"Before Brian’s seminar, we had a very unstructured way of designing analytics tools for our internal stakeholders. We were just fulfilling as fast as possible, but weren’t developing the relationships with our stakeholders that we wanted. We needed a structure and playbook to design better user experiences for our analytics tools, and that’s what we got out of this. It forced me to think about the design of the deliverables instead of just delivering. I liked how our team got to discuss actual projects and got Brian’s outside, cross-industry perspective. I thought we had a lot of really great conversations. I would recommend Brian’s seminar if you’re looking for a solid structure for designing better data products."

Erin ReynoldsErin Reynolds
Sr. Manager, Clinical Analytics
[Private Team Seminar Client]

100% Money-Back Guarantee

If your team has read and watched all of the first 2 modules of curriculum, attended the first week of calls, and actively contributed on these calls, and you are still not happy for any reason after that, I'll refund your money in full, no questions asked.

Format and Group Size

    • 100% online format via Slack, Google Docs, Vimeo, and Zoom featuring weekly lesson videos, practice activities, design reviews, and group Q/A discussion with the instructor.  We use Slack for chat (no email!), Vimeo for module videos, and Zoom for live video calls. The text supplements that go with the videos are in a 74-pg. PDF e-book. Any practice exercises will be explained in shared Google Docs / Sheets.
    • No boring lectures: there are (8) modules in the curriculum, plus special templates and cheat-sheets you can use on your real projects. Each module has a video and some reading, which you can consume at your own pace outside of our live calls. I will drop (2) modules of curriculum each week inside our private Slack channel, but you'll have access to all (8) modules immediately if you want to move faster.
    • Weekly, Live nteractive Zoom Calls: Get your questions answered, share wins, collaborate on challenges, and to do practice exercises (as time permits). Priority is given to answering the group's questions and learning from other's experiences. See the Dates & Schedule section. You can request a call be recorded, but they will only be available for download for 24 hours.
    • Maximum of (25) participants however, I generally recommend teams begin with up to 10 people in the first cohort.
    • Available year round starting on a mutually agreeable start date.

Duration and Time Commitment

  • Total Duration: The total duration is spread over 8 calendar weeks, however the time commitment is small each week. The first 4 weeks are the core of the seminar, and the final 4 weeks is the "application period" where students have access to me for office hours and questions as they apply their learning. The seminar is intended to be applied to your team's real work so there is really no "homework." You will get the most out of this seminar by practicing doing design against real projects and data products.  There will be some practice exercises during our live calls when time permits. Plan to spend at least ~3-4 hours/week between the following (not including your actual "work" where you're applying what you're learning):
    • Video and Reading Time:  Each module of the curriculum has a video that is ~5-25 minutes long, and a text supplement that's ~8-10 pages long.
    • Live Call Durations:  up to 2 hours, often less.

Schedule for Live Calls

  • The days of week can change based on your team, but in general, I recommend:
    Week 1Weeks 2—4 (Core Training Period)Weeks 5—8 (Application Period)
    • Monday 12-2pm ET (Kickoff Call)
    • Thursday 12-2pm ET (Regular Call)
    • Thursdays 12-2pm ET (Regular Calls)*
    • Mondays at 12pm ET (going no later than 2pm) is an optional "overflow" day if we don't get to everything the prior Thursday. Participants seeking Monday overflow help  just need to request this in person by the end of the prior Thursday call.  
    • Thursday 12-2pm ET (Office Hours Support as needed)
  • Curriculum Videos and Reading: this happens on your own time although I will recommend you go at the pace of 2 modules/week . See Format section above.
  • Private Slack Channel 24-7 Access for 8 Weeks: Between our Zoom calls, I will be monitoring the Slack conversations during the week to comment or respond as questions arise, or to give follow up instruction/clarity. Participants are also encouraged to trade ideas and chat with other participants taking the Seminar.
  • With regard to Time Zones & Holidays:
    • Be aware that the 12pm ET start time for live calls may result in a scheduling "shift" for you if we change to/from daylight savings time during the seminar.
    • If a call is scheduled on  a US National Holidays (e.g. Thanksgiving), we will not meet, however a rescheduled date will be announced during the seminar.


I offer 3 different packages of this seminar, with more advisory help, accountability, and level of engagement within your business being the main differences. Pricing is also based on the 3 cohort sizes: 1-10 people, 11-15 people, and 16-24 people. While not individually priced, private training starts ~$4k USD per team member for the basic seminar package.

Once we have scheduled a call, I can provide you with pricing based on your budget, goals, and team size.

The seminar was absolutely worth the price.

“When we were looking for analytics product design training, we saw lot of really good keywords on Brian’s seminar page, and that actually kind of tipped the scales for us, but we were a little worried that maybe it was just going to be a bunch of buzzwords. In the end, I told my boss that I think the seminar was absolutely worth the price. I have worked with a lot of people that just build something and say, 'let's just see if it works.' Hearing that we should talk to users first—and learning how exactly to do that—was really good confirmation of my suspicions about how to do things correctly. This seminar was really helpful for me to get out of the Tableau headspace, and to think much more broadly about good approaches to building tool agnostic, digital products that humans will use.”

Keith DykstraKeith Dykstra
Analytics Lead
[Seminar Participant]
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I would absolutely highly recommend Brian's seminar. Without a doubt.

I hadn’t heard of Brian before, but I had been enjoying his podcast and way of thinking, and on a leap of faith, I decided to bring him in to train my data science and analytics managers and leads. And after completing our first training, I can safely say there is no risk associated with this seminar. One of my goals was to change my team’s mindset about putting users at the center of our work, and I am already starting to see a positive change, though a long journey ahead of us. You get some tangible, real-world tools that are practical and applicable, so it’s not just “theoretical.” My head of data science also now sees UX and design as a must-have in his team’s advanced analytics projects, not a nice-to-have. I would absolutely highly recommend the seminar without a doubt, and plan to have more of my team take the seminar in the future

Omar KhawajaOmar Khawaja
Head of BI & Analytics
Roche Diagnostics
[Private Team Seminar Client]


Why Should You Study with Brian?

Brian O'NeillMy name is Brian T. O'Neill, and I help data product leaders increase adoption of ML and analytics solutions using design. I have worked with companies including DellEMC, Tripadvisor, Fidelity, JP Morgan Chase, ETrade and numerous SAAS startups so my perspective working in business, product, and UX design spans multiple industries and everything from tech companies to banks. I also run the Data Product Leadership Community, host the Experiencing Data podcast, consult and give keynotes on data product design and management.

Prefer to learn on your own?

My seminar is also offered as a self-directed video course for people who don't need an instructor, live Q/A video calls, or a cohort of other participants to work with.


Just email me at

Note: Pricing and other details in this seminar are subject to change without notice.

Photo by davisco on Unsplash