We’re kicking off Season 2 of the Leading Analytics Podcast with Bob Darin who holds both a chief analytics officer role and chief data officer role at CVS Health, which recently merged with the insurance giant Aetna. The combination of these two giant companies holds great promise in healthcare to bring together retail and pharmacy operations with health insurance services to produce a powerful end-to-end solution for patients and consumers. Bob shares a few selected approaches to how the data and analytics teams are organized, and specifically the expectations the organization has for the data and analytics capabilities. The bar is high for advanced technologies like AI at CVS/Aetna, and this episode walks you through the vision and tactics being employed step-by-step.
Describe your title and role.
I have two roles: Chief Analytics Officer for CVS Retail (supporting our 10,000 pharmacies across the country) and Chief Data Officer for all of CVS Health, which includes CVS Retail, Caremark, and Aetna. Prior to our integration with Aetna, I was the Chief Analytics Officer for CVS Health. When CVS Health and Aetna merged, we wanted to find a way to leverage the power of two powerful and capable teams. In our current structure, we have Chief Analytics Officers for CVS Retail, which is my role, and for Aetna and Caremark. We work together across the enterprise within our individual domains to drive solutions across CVS.
From day one of the CVS Health/Aetna integration, our senior leadership talked about data being one of the most critical enabling assets. That became the genesis of the Chief Data Officer team, which I lead for all of CVS Health.
Where does the analytics function sit in the organization, and report into?
Across CVS, analytics reports into our Chief Health Officer, Troy Brennan.
Is that the right place for the analytics function to report?
We are very well positioned where we report. Reporting into the Chief Health Officer and working with Troy across the entire company allows us to touch every part of our business and allows us to cut across all our health care processes, whether we're working with patients in our pharmacies, within our Aetna business unit, as we're managing pharmacy benefits through Caremark. And we've started developing an agenda that has us communicating with our board of directors in terms of how well we're leveraging the data and how we're creating value across the entire enterprise.
Describe the organizing model you have adopted for analytics.
We have a central data strategy team that I lead that works across the entire business, and understanding how we manage our data, how we connect it, how we manage the privacy and legal compliance…and how do we make it accessible and agile for businesses across the company. And we believe that that's best done as part of a central function to manage our data strategy.
But we also think there's a very specialized skill set on the top end of analytics around data science, machine learning, and artificial intelligence. And we’ve built centralized teams that serve the different businesses through our two analytics teams across retail and then Aetna and Caremark. We work with our businesses to identify opportunities to deploy advanced analytics, machine learning, advanced algorithms and optimization techniques that typically require a higher level of skill and sophistication and are more cutting edge.
In the middle of that are tens of thousands of data consumers who are not centralized. One of our strategies is to make their ability to access data and insights and self-service analytic tools as robust and easy as possible. Because we do believe if we put insights in the hands of the people can make business decisions day to day, that's a critical element of being a data-driven company.
What are four or five important qualities and behaviors of leaders of analytics?
- Innovation and creativity. We seek leaders who bring the ability to look at a problem from multiple dimensions. The ability to innovate and think in novel ways that haven't been tried before that leverage the combined assets across CVS, is one of the most critical elements when looking for an analytic leader.
- Execution mindset. At CVS we are no longer just finding insights. We are developing them, and automating them, and pushing them across the entire organization. The ability to push things across a very complex organization like CVS Health is critical.
- Collaboration. In our environment, analytics is a team sport. We must work with our IT partners, our marketing teams, legal, and our field force. There are literally sometimes dozens of constituencies and teams, internal and external, that we need to work with to solve problems that are very complicated about how individuals consume health care, the decisions they make, how they manage cost, access, and quality.
- Executive presence and vision. We are being asked to use analytics to drive strategies, analytics are at the forefront of how CVS Health is going to transform healthcare. We seek leaders who can come up with ideas, sell them within the organization at the most senior levels, and then help execute them across our company.
How do you measure performance and success when it comes to analytics?
When we think about success, we start with outcomes and work backwards. We're investing in analytics, so we can deliver better outcomes for our customers, whether they be CVS Retail customers, our members, or the businesses we support through our benefits plans. We ask, how can we deliver better health care quality? How do we improve access for populations, particularly underserved or at-risk populations? And how do we help our clients manage health care costs while getting access to great health care. Our analytics initiatives are aligned against how we can prove that we're making those results better. And we think about that as measurable. We develop KPIs when we set up programs that help us measure the improvement.
We also measure success on the value that analytics can drive to the business. If we can deliver a better consumer experience, that allows us to grow our products and services, to gain market share and invest in new businesses. Across all our businesses, we have value targets for analytics. We know that we deliver hundreds of millions of dollars of value across the company. And that number has been growing in the significant double digits every year. So, unlike a success metric about the number of reports we developed, or the models we built, we start with the outcomes we deliver to the business. And then we work back to understand how those needs get translated into specific granular goals. We do build models, we do build reports, particularly more advanced insight optimization reports, but they start with what the business objective we're trying to achieve.
For more insights from Bob, listen to the full podcast.