A 10-week online, instructor-led seminar teaching leaders the practical design, consulting & business skills needed to create indispensable data products & decision support applications.
Accelerate your innovation with human-centered design.
Registration Ends Oct 3, 2021
Next Session Starts October 4, 2021
Are you 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.
Are you sick of hearing customers say, “So what? What do I do with this data?” when they see your 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 technical work ends up never getting into production, perhaps due to model trust?
Do you 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 data products were “game changers?”
Imagine knowing what is going to get adopted by users before you start building the solution
Imagine hearing, “This is amazing! Can we start using it now?” when users see your data product
Imagine management doubling your budget because your solutions are delivering enormous value.
My design seminar is the answer…if you or your team are ready to change how you think.
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 product relies on humans to engage with it, 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 design framework will teach you or your team to:
- Uncover what users actually want and need using empathy
- Avoid building the wrong solutions that incur technical debt and cost
- Ensure stakeholders understand the value your data product will bring
- Identify the unspoken needs, desires, and whys in your customers' minds
- Turn vague “AI” requests into clear problems you can address
- Get everyone to agree on what to build before you build it
- Develop a "product" mindset to delivering decision support solutions
- Find out if customers will use your solution before you invest too much in 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
- Create better designs, not just how to do “design thinking”
“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”
“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.”
Who is this seminar for?
It's for data product leaders
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 directors of applied data science teams. Private team cohorts may include a VP/leader, their Directors, and their leads.
You may be a:
- 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 researchers focused on data products looking to move into design
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.
[Seminar Student] 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.”
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.
Curriculum: (8) Core Modules
Adults learn by doing, and so my modules are focused on how you can take action—today. There are no grades or certificates. You'll be learning skills you can apply immediately to begin uncovering latent customer needs and problems, when to apply analytical vs. creative thinking, and how to balance speed vs. quality. We'll also focus on when to prototype (make things) vs. research (further understand the customer) so your technology effort can move forward with more confidence and speed. 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:
Ready to join us?
100% Money-Back Guarantee
For individuals in public sessions: If you consume all of the assigned modules within the first two weeks, actively participate in those first four live video calls, and are still not happy for any reason after that, I'll refund your money in full, no questions asked.
Seminar Format, Class Size, and Free Bonus
- 100% online format via Slack, Google Docs, Vimeo, and Zoom featuring weekly lesson videos, hands-on activities (optional homework), and classroom discussion with the instructor. We use Slack for chat (no email!), Google Docs for text-based modules, Vimeo for module videos, and Zoom for live video calls.
- Maximum of (25*) students in public cohorts: you will also have full access to the other students in the class within Slack whether signing up as an individual or team. Learning with and from your peers is encouraged. Private team seminars can be larger.
- Includes: (8) video and text modules, plus special templates and cheat-sheets for creating project briefs, journey maps/service blueprints, UI cheatsheets, and usability studies
Duration and Time Commitment
- Duration: The total duration is spread over (10) calendar weeks, with the live calls taking 4 hours/week for 4 weeks, and dropping to 2 hours/week for the final 6 weeks—if you attend every live call. The seminar is intended to be applied to your real work so there is really no "additional homework." The total time will depend where you are in the lifecycle with data products you want to apply the seminar to, the type of projects/products you're working on, and how deeply you choose to apply the training to your work.
- Module Time: the seminar is primarily designed around "learning by doing;" skills you can apply to real projects. Module videos tend to be between 5-25 minutes each, and written module texts are 3-10 pages of reading typically.
- Application of Skill / Homework Time: This really varies widely and is difficult to estimate. Over time, you may not look at the seminar curriculum as "additional work," and rather just the "new way I/we do all of our work."
- Live Video Call Time: About 4hrs/week for the first four weeks, then it drops to 2hrs/week, however attendance is optional, calls can be recorded on request, and you may show up to just get your questions answered and then leave on busy days. Most people want to see/hear what other people are doing and hear the advice I give to them.
Dates & Schedule
- October 4, 2021 is the start of the final 2021 cohort. Private team training can start on a mutually-agreeable date. Get on the early-access notification list if you want to be notified about future seminar dates.
- Weeks 1-4: Learning Modules Released, 2 per week: each week, for the first 4 weeks, I will release (2) modules of curriculum inside the private Slack channel. You can access these pre-recorded videos and content on demand. I generally release the "assigned" modules on Thursday.
- Weeks 1–4: Live Video Calls on Mondays @ 12pm ET & Thursdays @ 12pm ET: Monday Zoom calls are primarily for students to ask questions about the modules that were previously released. Thursday Zoom calls are open office hours. Calls are not recorded by default unless a participant requests this in advance because of a planned absence. Calls end by 2pm ET.
- Weeks 5–10: Open Office Hours on Thursdays at 12pm ET: during these last 6 weeks, we only meet Thursdays (no Mondays). These sessions are primarily intended to address issues you encounter while applying what you learned in the modules.
- Private Slack Channel 24-7 Access Throughout All 10 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. Students are also encouraged to trade ideas and chat with other students 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.
- Private training comes with additional scheduling flexibilty to accommodate your team's time zone.
- Individuals registering for public sessions can register and pay online with a credit card (US/international) or ACH bank transfer (US only).
- For private sessions, teams, and complete payment details, see the last item in the FAQ.
For Individuals in Public Cohorts:
Tuition is $3,995/person, paid due up front (online checkout).
Private Team Training
Are you an executive or manager of a team who needs to develop better user-centered design skills in their data products? The format of my private seminars are essentially identical to the public cohorts except that they include additional benefits as follows:
- Get flexible scheduling in terms of the start date and the start time we set for the live office hour calls (particularly if you are outside the U.S.) Note that my available office hour times and days with your team may differ from the standard times listed under the Format section.
- During live session, we will go much more deeply into the specific challenges your team is facing with your users, stakeholders, or dept. colleagues. I will give frank, candid answers to your whole team, without any political bias or sugar coating—even if the questions aren't directly about the Seminar or its curriculum.
- Seminars may include a Pre-Seminar Assessment bundle, so I have context for your team and the work they do, before we begin the training.
- Seminars may also include a post-seminar Skill Retention Plan so the training has the best chance of "sticking," you have support from me when there are issues implementing the curriculum into your process, and you get a long-term ROI on the seminar.
"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."
Why Should You Study with Brian?
My name is Brian T. O'Neill, and I am the founder and principal of Designing for Analytics, a consulting firm that helps companies apply human-centered design to data science and analytics. 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.
In addition to hosting the Experiencing Data podcast and consulting, I also frequently give talks at conferences including O'Reilly Strata, Enterprise Data World, the International Institute for Analytics Symposium, and Predictive Analytics World. After these talks, attendees started asking me if I had a training offering, and I said no. Until now.
Want 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 students to work with.