For our milestone 200th Data Futurology podcast, we have the immense fortune of being able to host Gina Papush, the 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 being 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 innovations. “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 Read the full podcast episode summary here.

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