Chief Data Analytics Officer emphasizes the criticality of centralized, co-located data & analytics teams.
By centralizing data and analytics, companies can achieve economies of scale, and also help create career paths for data analytics and data science professionals, according to Ryan Swann, Chief Data Analytics Officer at Vanguard.
“You get to do things that allow you to be more efficient, and at scale, than you would otherwise. That would not happen if the data and analytics teams are siloed,” he told Traders Magazine.
By having centralized data and analytics, organizations can use their scale to drive down cost, Swann said, adding that the centralization of the CDAO helped Vanguard save more than $100 million in 2022.
“We continue to lower our cost of operating a business so that our advisors can have more information at their fingertips, which allows them to give our clients the best information at the right time with the right message based on everything that’s going on in the world,” he said.
“In order to do that at scale, you got to have a foundation that ultimately allows you to provide those capabilities,” he added.
Vanguard, a global financial services firm based in Malvern, Pennsylvania, formed its Chief Data & Analytics Office (CDAO) two years ago.
Swann said that he witnessed several improvements as a result of the centralization of their data analytics teams.
He said that centralizing data and analytics functions helps build synergies between teams and enables increased collaboration.
In addition, co-locating teams allows leaders to keep closer ties to those they support, creating a better career path for data and analytics professionals.
Finally, by ingraining data and analytics best practices, organizations can transform data into a strategic asset that enables personalized client experiences, scales advice, optimizes investment and business operations, and reduces risk, he said.
Swann said that the data analysts and data scientists have to be close to business stakeholders and leaders.
“Many of our data analytics teams still sit within the business and are very much aligned to the various business-line goals, but they’re able to leverage our center of excellence from a scalability and technical perspective,” Swann said.
According to Swann, his team has identified behaviors that were prohibitive for investors maximizing their investments, such as leaving money in settlement funds and defaulting to the company match levels for 401k contributions.
One tool that is available out on the Vanguard website, according to Swann, is a multi-goal solver that allows clients to go in and put in multiple goals.
“We also provide tools, behavioral nudges that allow us to communicate in a way that the client understands,” he said.
CDAO uses AI and ML in a number of ways to help bring tools and capability to the client and to help their portfolio managers, according to Swann.
He said that Vanguard’s CDAO is “really focused” on continuing to unlock the value of data at scale, and also continues to modernize its infrastructure by “moving more things to the Cloud”.
“That’s continuing to allow us to unlock the value of data,” he said.
“We’ve had great progress in really articulating the value that we create with data analytics and showing how the organization and the clients are benefitting by leveraging data analytics.”
