AI and Analytics for Business
AI and Analytics for Business Senior Fellow
Victoria Lewis-Bogatyrenko, WG’94
Victoria (Tory) Lewis-Bogatyrenk0, WG’94, is the Senior Vice President of UnitedHealth Networks at UnitedHealthcare. In addition to being a Wharton graduate, Tory also serves as Senior Fellow with AI and Analytics for Business (AIAB), and, most recently, as a mentor to a student team from the Fall 2021 Analytics Accelerator. We recently caught up with her to discuss her experience with that team, her career journey, and why she felt compelled to speak at this year’s WiDS Philadelphia @ Penn Conference.
How did you get involved with the Analytics Accelerator? What was your role?
I am what they call a Senior Fellow. I serve in the role as a mentor for the Analytics Accelerator project, mentoring a project team. I’m an alum from Wharton and I have an interest in giving back to that community. When I was spending time getting to know (AIAB Executive Director) Mary [Purk] and understanding what the opportunities were, what really appealed to me was having a chance to engage directly with students. That, to me, was invigorating, it was exciting to actually connect and give back not just to Wharton, but to the people who were there.
What stood out to you about this semester’s group of students?
Besides super smart? I mean incredibly smart! They were not afraid of the challenge. They did not shy away. They had a challenging data set and some very interesting questions to answer through their analytics, and what was impressive to me was their persistence in going at that data in a number of different ways, applying different models, rethinking their approach, in order to ultimately get to a conclusion that would be useful to Zillow, and would answer the questions that Zillow was looking to answer. In the process, as they came back to us through their interim presentations, they were very good about simplifying the statistical models they were utilizing to help everybody understand, because there was a wide range of knowledge. I just found the students to be accomplished, persistent, very mature in their approach, very curious in making sure they were getting feedback. The depth of analytical skill was unbelievable.
Having served as a mentor, what value do you see in the Analytics Accelerator, both from the perspective of students and organizations?
Let me take the student one first. If you’re in an MBA program or even an undergrad business program – everyone’s doing group projects. So you have an opportunity during the normal course of your education to partner with others and learn to manage through all of the group dynamics and collectively arrive at your work product. What is different here is that the students had a real-world client. So not only were they managing their own internal team-building but they were managing the expectations of that client and the challenges that come with real world data that has flaws in it. This is not and was not an academic exercise. This was real. The opportunity that this team had was maybe less about the academics and the group piece of it, but more about “how do I take all of those challenges in stride while I manage the expectations of my client and build a credible relationship?”
From a customer’s perspective – what an opportunity for any of us in corporate America today to get a fresh set of perspectives from young people who have tons of energy, lots of curiosity, and no pre-defined ideas of what the conclusion ought to be. I think any client who has the opportunity to engage [with these students] is very lucky to do that, frankly. I just think it’s a great opportunity for us.
In what ways has being a woman in data science impacted your journey?
There is an expression that I often use and that i have found to be really helpful, and that is “let’s have a fact-based conversation.” You can always rely on that data to drive your perspective and help you argue your position. I think, sometimes, women more-so don’t argue their perceptions or beliefs, they argue by grounding [their perspective] in data. I have found that to be extremely helpful. Using data to have an informed conversation helps to shift the perspective of others. I have found that being facile with data has helped me advance my career. When I left Wharton, I moved right into industry and started working at Oxford Health Plans. I’ve always been analytical. I’ve always liked data, and I think being comfortable using data has allowed me to do things like transition from a provider-facing role into leading a team of actuaries. I am not an actuary, but I know enough about data that I can follow along with the language and bring along the business expertise to help those individuals. I could pivot from a role that was provider-facing, building relationships with hospitals and doctors, to a product development role, because all of them are grounded in data. Being facile with data and being comfortable in that world opens up so many doors. That to me has been incredibly helpful.
Right, there seems to be some egalitarian qualities to the data. It doesn’t care who you are. The numbers are the numbers.
That’s right, and being able to translate the mathematical model into something that people understand, and utilize it to help you to have the fact-based conversation to make your argument, is always useful. In my opinion, it always wins the day.
What advice would you give to someone – regardless of their gender – who is interested in starting their career in data analytics?
Don’t be afraid of data. You don’t have to be an expert. You don’t have to be a statistics geek. You don’t have to be an econometrics geek. Don’t be afraid of data, stay curious about data. Take classes and be open to the challenges that come along with those classes. There are so many people who say “I’m not a math person. I’m afraid of math,” and I would say the same is true of the use of the word “data.” Don’t let it scare you away. Be curious. Everybody has limits as to how their mind works with data. That’s okay. You should just go after it. It leads to so many different opportunities.
In your own words – #WhyWiDS?
In this era of information and technology – the velocity at which information is coming at us, and the velocity at which technology is truly advancing the ways in which we work – [WiDS 2022 Philadelphia @ Penn] is an amazing opportunity to stay curious, to absorb what’s going on in the world and in industries, and to learn from other people. When it comes to diversity of thought, we need to be intentional and make sure genders, perspectives, global views, cultures, and so on are all represented, because it makes the conversation richer. WiDS is an opportunity to do that in the space of data and technology. What a wonderful learning opportunity. Why would you not want to be there?