This week, Product School hosted Andreea Bodnari, Former AI Product Leader at Google for a special #AskMeAnything session. Andreea is deeply knowledgable about AI and its applications to improving healthcare outcomes. She touches on the AI space and gives tips on skills needed to be successful at Product Management.
Andreea is the Chief Product Officer at DataOrb and former Google executive where she built the Healthcare AI product department from 0 to scale. The technology built by Google during her tenure outperformed the likes of Microsoft and AWS. Andreea founded and exited several AI-enabled companies. In addition to her work in the industry, Andreea is also faculty at NYU Computer Science, where she teaches machine learning. Andreea is a well-published AI scientist and holds a Ph.D. in machine learning from MIT.
What is the best 0 to 1 process you have seen/used for consistently creating ideas that make it to scale?
I lead with customer demand + strong pulse on industry trends. If you want to build a sustainable business you need a strong differentiator that will enable you to capture large % of the market ahead of competition. So as a PM it’s critical to stay on top of market trends and be in touch with thought leaders in addition to surveying customers – both directly and through customer survey platforms like GLG.
I am an aspiring technical Product Manager with a Data Engineering background. Do you have any advice?
You’re a coveted PM for any tech organization. I’d start with background reading on consumer psychology, negotiation skills, and sales models. Practice makes perfect, so the more you’ll practice your negotiation skills the more compelling a PM you’ll become.
But you can develop skills like business models and pricing models by taking existing businesses (both successes and failures), mapping out their business models and articulating how their approach landed in the market. If a business model failed, what was missed from the end user psychology, etc. I’ve always operated as a PM entrepreneur/intrapreneur, so for me the PM role enabled me to be the CEO of a specific line of business – elegant way to drive innovation and solve real-world business problems.
What framework do you use to conduct competitive research?
I generally follow the flow of user action workflows, problem, solution, offering, channels, revenue. When doing competitor research, I identify which user workflows are underserved and prioritize based on speed of execution, revenue potential, and differentiation potential. Hope this helps!
What is the major blocker for adoption of health care technology with respect to chronic ailments and how do you envision it being solved in the future?
Good question. There’s a lot going on in the US healthcare system as there are many stakeholders that influence the market dynamics. Chronic ailments have some of the most advanced technology across the spectrum of disorders. The new trend in chronic ailments are closed loop systems (see dexcom for continuous monitoring) that allow for e2e disease management.
Any advice on building one’s knowledge stack in AI domain?
It’s great to hear that you’re interested in AI. I’d recommend taking some online courses (Coursera, MIT OCW) in this space and even going into coursework that asks you to write small coding assignments. Nothing compares to getting hands on experience with AI.
What’s the best way to get into AI Product Management?
It would really help to understand the tech stack so you’re aware of technical state of the art and limitations. Then you want to be cognizant of ethical implications and always study design developments around HITL. It’s a fun journey and you’ll get to build super innovative tech, best of luck!
How do you approach prioritization?
As you know, prioritization is a science and an art. You want to have your long-term strategic plan + short term objectives that meet critical customer requirements. Short term objectives are a mix of revenue and customer impact, long-term objectives are more strategic – and look at differentiation and business plan diversification.
What should I focus on when transitioning from marketing to Product?
Great to hear about your interest to transition to PM. It’s good to start work at an organization that has a strong PM culture – Google, Meta, Dropbox. These companies will equip you with the playbooks for getting the job done and then you can move to smaller companies where you get more creative freedom, can experiment and discover your style. It’s a great and rewarding journey!
What’s your perspective on choosing and right-sizing your outcomes with regards to AI/ML? What is your process for choosing an outcome, and how are you balancing audacious with achievable when setting goals and applying key results?
I always attach AI outcomes to existing user/action workflows. The workflow needs to be frequent, critical, and involve substantial #employees. Expectation management is super important when building AI/ML because we’re running the risk of burning bridges with overpromising. So identify a workflow that is frequent and expensive to run, automate/augment an atomic part of that workflow, prove success, and then expand.
Any final tips?
I really enjoyed sharing from my experience as a PM and getting your questions here on Slack. Being a PM is like a playground for the creative mind. So my advice is to never stop learning, always ask the hard questions, and listen more than you talk. Happy to keep in touch over LinkedIn if anyone wants to continue the conversation.
Written by Adrianna Berring. Adrianna is a Mexican-American, Madrid-based Content Associate at Product School. She knows a little about a lot, and especially likes learning about communication and business-driven social change.
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