Data-driven decision-making is a guiding principle in financial services institution Pacific Life Insurance Company’s ongoing digital transformation. John Damalas, Vice President and Chief Technology Officer at Pacific Life, joined us on the latest episode of Rise of the Data Cloud to discuss those topics and share his take on what’s next in data and analytics trends.
For 153 years, Pacific Life has helped millions of individuals and families with their insurance and financial needs through a broad portfolio of life insurance products, annuities, and mutual funds. The company offers a variety of investment products and services to individuals, businesses, and pension plans, counting more than 100 of the largest U.S. companies among its clients. Although Pacific Life is a Fortune 500 company, its headcount of around 4,000 employees results in what Damalas describes as a really tight-knit community family feel.
His job combines traditional CTO enterprise architecture and technology strategy responsibilities with his office’s role as the “connective tissue” to coordinate Pacific Life’s digital transformation journey across workstreams to increase the entire organization’s digital maturity. Damalas leads Pacific Life’s enterprise data program, which includes developing the company’s data governance operating model.
Pacific Life’s retirement solutions business started working with Snowflake a couple of years ago. The division’s data science and advanced analytics teams were spending a lot of time wrangling data siloed in different parts of the organization. The team was wrestling with performance issues related to some of the queries and models with which they were working. Moving to the Data Cloud sped up one extremely complex query, which had previously taken as much as 90 minutes to execute, to run in a matter of seconds.
Other divisions then adopted the Data Cloud, including life insurance. Pacific Life is in the process of implementing an enterprise shared service framework to manage the Snowflake platform centrally, removing much of the administrative work from divisional resources. “We can put some consistency around how tasks like object and user provisioning and environment and jobs monitoring are being done,” Damalas said. Having a centralized infrastructure enables much more seamless sharing of data sets across different divisions.
“With the Snowflake platform, you land the data once and then you can create myriad logical views,” Damalas said. “We can give our users the capability they need without a lot of that administrative overhead that you would have in a traditional data warehouse platform.”
Another key benefit of Snowflake is the ability to source and manage third-party data sets from partners such as Experian and DiscoverOrg centrally. Pacific Life has started to leverage the Data Marketplace to publish third-party data sets and then make them discoverable to its business users.
Damalas is excited about some of the Snowpark functionality that will allow for Python execution within the environment (currently in private preview). Pacific Life wants to give its data scientists some flexibility in the programming language that they use for modeling during controlled data experimentation.
Over the next few years, Damalas sees embedding the impact or the results of analytics directly in an enterprise user’s workflow becoming crucial in further enabling data-driven decision-making. Data catalogs and access will help analysts and business users discover which data is available to them and is relevant to their role as well as whether they should have access to those data sets.
Looking further into the future, Damalas expects technical solutions to play a larger role in helping to manage the appropriate and ethical use of data for specific use cases. “It will be about how we tag data sets and analytic use cases to help us be a lot more consistent in how those uses are applied,” he said.
Damalas also predicts that individuals will become much more aware of the value of their own personal data as a quantifiable asset. “They will make explicit cost-benefit decisions when they go to exchange that data with someone else and make sure that they are getting something of value in return for their data,” he said.
Rise of the Data Cloud is a podcast hosted by award-winning author and journalist Steve Hamm. For each episode, Hamm speaks with a data leader to learn how they leverage the cloud to manage, share, and analyze data to drive business growth, fuel innovation, and disrupt their industries. You can listen to more episodes here.