#200 The Constant Evolution And Future Opportunity Of Data – with Gina Papush, Former Global Chief Data & Analytics Officer at Cigna

For our milestone 200th Data Futurology podcast, we have the immense fortune of being able to host Gina Papush, the former Global Chief Data & Analytics Officer of wellness and insurance company, Cigna.

Papush has a long history in data science, having been involved in modelling and coding from before the time where “data scientist” was a defined role. In the years since, she has observed that enterprises have become siloed across computer science, data science, and other roles, and that the next stage of data science evolution now is to now break those silos down and find ways to bring cohesion across the organisation.

She has also seen the role of the CDO and their remit evolve, from one that focused on governance and controls, to being a value creator within the organisation. Being an effective agent for change has been important to that evolution, she says on the podcast, and data executives need to look to the “blind spots” that they might have. Many have the technical skills to excel in analytics, but building skills in influence and thought leadership, and to be a partner to the other stakeholders of the organisation, is the next critical step for the CDO.

Finally, Papush also shares her insights on how value is extracted from data. A “one size fits all” approach cannot work, she says, and organisations need to build their strategies based on the maturity of their own data practice, rather than the hype in the market.

Once the maturity is there, she says, data scientists can start looking at real life-changing innovation. “It’s (data) a huge part of how we move healthcare to be more preventive and more interactive,” she said. “Health is currently very event driven. But analytics and AI could make it much more seamless and unlock real-time care.”

Tune in to the full podcast for more of Papush’s thoughts on the history and future of data science.

Thank you to you our sponsor, Talent Insights Group!

Join us for one of our upcoming events: https://www.datafuturology.com/events

Join our Slack Community: https://hubs.li/Q01gKNBn0

“I find that there’s almost a gap that we have in developing our people to allow them to be very effective once they become a leader. And I think that one of the blind spots for a lot of people in their professional development is the manner of collaboration and communication and change management.”

— Gina Papush, Former Global Chief Data & Analytics Officer at Cigna

WHAT WE DISCUSSED

0:00 Introduction
04:43 How have you seen those (AI) come together in organizations?
09:28 How is it that you have both breadth and depth?
11:14 What would be some of the stages that you see in your career? And how did you go from one stage to the next? How do you develop yourself professionally?
14:47 You're really good at focusing on who is the person that we're making a difference in their life. Where did that come from for you and how has that helped you in your career?
19:21 Organization and the culture: What do you think about that? How have you seen it evolve? What are your thoughts on this space?
23:21 How do you find the responsibility of the CEO and analytics leaders of having to influence and work across the organization?
26:37 Strategic data assets: What are your thoughts on this space? In terms of how much focus and maybe what type of approaches you've seen work?
29:15 What do you think are some of the next stages of evolution in our field and in this space?
34:34 How do you think that a broader or maybe bigger digital play will start to affect this?
37:34 Could you tell us a little bit about some of the work that you're doing in that in that space?

EPISODE HIGHLIGHTS

• I think that's a huge part of how we move healthcare to be more preventive and more interactive. today. It's very event-driven, right? And it's very discrete. But this technology and these capabilities from an analytics and AI standpoint could make it much more seamless and continuous.

• You kind of got two choices, you can either rely on others to be the experts, or you can learn from them. And I just love to learn.

• But as a modeller, I was always looking to understand, what are we solving. Who is this going to help? What is the business process around it? What is the customer experience that results from things we do? You have a real human approach to analytics and to business so that in your approach, you always think about the individual that is getting the service or the benefit at the end of this long and complicated chain.

• We have to view ourselves as change agents, we're not there just to build and maintain, we're there to constantly evolve.

• Being able to bring that thought leadership to the table in a partnership setting, being able to turn that idea into something that actually drives actions and collaboration.

• What I think we all recognize, data by itself doesn't generate value. It's putting the data into some sort of an intelligent form where it drives decisions, drives actions and drives outcomes that ultimately enable value creation.

• And so I think in healthcare, we've got this whole frontier of data exchange and interoperability and being able to bring data together in a timely fashion from all the different touch points the patient has, and put that in the hands of people who are delivering care.

• Folks with chronic conditions, and the monitoring that can happen, the preventive nature of what could be done if that data is streaming, right in real-time, and we've got the AI systems that can actually monitor that pick up any kind of abnormality, notify the doctor in a timely manner, notify anyone else who needs to do something, you know, that is huge.

• I was fortunate to grow up in a family where I've had the women of older generations, my grandmothers, my aunts, and my mother, who are all in various types of technical roles, as scientists, finance professionals, and engineers. I had that exposure at a young age. And I was encouraged to do that.

• I tried to contribute in various ways, to women in STEM and participate in different types of events, or do whatever I can to encourage women to come and do this work.

• The support of man in all sorts of roles is critically important. Critically important. I've had wonderful mentors who are men and women. I think all of us can contribute there.

---

At Data Futurology, we are always working to bring you use cases, new approaches and everything related to the most relevant topics in data science to help you get the most value out of these technologies! Check out our upcoming events for more amazing content.