Closing the data management and analytics divide in Financial Services

At this year’s Datanova conference, two outstanding Bank of America leaders, Amy Avery, SVP of Analytics and Research Insights, and Michelle Boston, Managing Director of Data Management Technology, shared their perspectives on the data transformation at this iconic bank. Amy and Michelle are playing an integral role in Bank of America’s journey to effectively leverage data in order to change every aspect of their businesses — without losing sight of the underlying data privacy, data governance, and security obligations they have to their 67 million customers. 

Amy and Michelle shared three core facets of Bank of America’s data strategy. In this recap, we’ll explore how the bank is closing the divide between sound, customer-centric data management practices and democratizing business analytics across team lines to enhance customer experiences and fuel growth. 

It’s all about trust 

It’s very easy to tell the health of a relationship when observing how executives from different parts of the business engage. Too often, fiefdoms and turf wars are in play, driven by underlying corporate political agendas and fear. So naturally, these types of environments exude mistrust. Meanwhile, the exchange between Amy and Michelle showed a deep trust and focus on everyone rowing in the same direction. Michelle explained how this has been a company priority at all levels, from the top down to the bottoms-up for years.

“[The] commitment starts from the top, and it takes years and years and years to take hold, and I think what you see at Bank of America is the realization of that intention.”

Michelle Boston

In less tightly aligned organizations, the data function and analytics function are at odds with each other — one is typically perceived by the other as being innovative but risk-taking in their use of data, and the other is seen as too controlling and limiting business impact. Ideally, data and analytics teams should work as one team focused on delivering value for their joint customers through sound data practices. You see this come to life where the technologists don’t just own technology roadmaps, but the business unit has an active voice. 

As Amy Avery put it, “Michelle’s roadmap and my roadmap are intertwined. And if we don’t start at the beginning and say, what is the end state we want for our customers and for our business, we’re going to be broken from the beginning.” 

This is further reinforced by the understanding that Michelle and her team have that “technology has evolved past the point where you can say only technical people do technology work and business people do business work, because data science is so intrinsically technical and data analytics are so intrinsically technical now.”

Answer the WHY

As trust matures in the organization, you begin to see a shift in the next focus area: obsessing over answering the WHY we are doing what we are doing and less on the how — which typically ends up being a technology conversation on specs, feeds, and speeds. By fixating on answering why we are doing this, why customers demand x, y, or z, and why this matters to the health of the business, it becomes natural for cross-functional teams to join forces to answer those fundamental questions. It’s taking a page from the Amazon playbook of being customer obsessed and working backward from the first principles. 

“[At Bank of America, it] starts with delivering great experiences for our customers and clients so that we can help them seamlessly deliver whatever they want to do in their homes. Whether it’s a mortgage or a car, saving for retirement, we provide the connections, the great experiences, and the world-class services to deliver that. Technology is an enabler of that. So we always start in the technology space with a business partner telling us what our customers and clients need of us.”

Michelle Boston

Answering the WHY also requires having clearly defined roles and responsibilities with solid business data ownership, which allows business leaders to plan and strategize for their organizations effectively. As a part of this, business teams must also constantly put themselves in their customers’ shoes. 

As Amy puts it, “if I think of myself as a customer, I am, too, thinking about what I want shared, what I would be worried about being protected, what would be helpful for me to receive personalized information on, and I think it makes for a very easy roadmap.” 

Strong business ownership of the data helps intertwine the IT and data management teams. The IT team can effectively deliver the modern data stack. Data management can provide strong data management practices to ensure data privacy, protection, and governance are all factored into whatever use case is enabled to achieve the strategy’s objectives. 

Measure success on aligned business outcomes

Ensuring the data and analytics teams align to a common goal and measuring progress toward those goals further ensures collaboration. First-generation CDOs were only measured on defensive responsibilities: storing and protecting the data. They were not thinking about leveraging data for value. And even the latest research suggests that the shift to value isn’t as mainstream as one would think, with only 41% of CDOs being measured on value creation. This philosophy resonates within Bank of America.

“I think what makes a lot of our work possible is that constant step forward with that end vision of, we’re here to help make financial heads better, and we’re all rowing towards that thing, and that common goal makes it easy to collaborate because we don’t want different things, we’re not measured differently, we’re all measured on that, so it makes it very easy to succeed together.”

Amy Avery

Technology should be an enabler to this new world order, not a detractor

For years, Starburst and ThoughSpot have been collaborating to help organizations close the divide between sound data management practices and data analytics to deliver measurable business value. By leveraging the two, organizations empower every data team to create, consume, and operationalize data-driven insights. Creating a single point of access across multiple sources, without needing to move the data, helps enforce sound data management practices.  

This single source of truth empowers data teams to run AI-powered, natural language search on their live data for real-time analytics. And, it allows product teams to quickly embed analytics within their data apps to operationalize business intelligence in finance, and speed up insight to action across the organization. These modern data experiences help businesses like Bank of America focus on achieving aligned business value outcomes. 

You can watch the complete discussion on demand and ungated. Then, learn more about how Starburst and ThoughtSpot are helping financial institutions better use their distributed data and effectively democratize analytics to the edge.