Chief Data and Analytics Officer, Americas Data & AI
Risk & Finance Data Quality & Metadata
Bank of America
VP of Data Enterprise Management
Head of Data Validation
Industrial and Commercial Bank of China
The adage that “knowledge is power” has been accepted for hundreds of years, but as with every legacy entity, it could use some modernization: “data is power.” Business leaders have come to recognize this over the past few years, and this increased focus on data puts Chief Data and Analytics Officers (CDAOs) on a pedestal to drive insight and value for the organization.
With immense volumes of data, ever evolving business needs, and pressure to increase data availability across the enterprise, CDAOs continue to name data governance as a mission critical priority to achieve their goals. Recently, CDAOs in the New York CDO Community gathered for a Town Hall to discuss how they can streamline their approach to data governance and successfully unify data across the enterprise.
The program was moderated by Erik Zwiefel, Chief Data and Analytics Officer, Americas Data & AI at Microsoft Corporation with New York CDO Governing Body Members as discussion leaders: Michael Finnen, Risk & Finance Data Quality & Metadata at Bank of America; Ashok Kumar, VP of Data Enterprise Management at Voya Financial; and Sid Narayan, Head of Data Validation, at Industrial and Commercial Bank of China.
During this engaging conversation, data and analytics leaders shared ways they are modernizing their company’s data estate, optimizing data for advanced analytics and AI, and implementing best practices and market trends.
Responsibility: The Core of Data Governance
Zwiefel opened the Town Hall by sharing Microsoft’s definition for data governance as “the people, processes and tools to responsibly manage data as a corporate asset.” He specifically stressed the terms “responsibly” and “corporate asset” in his address.
Zwiefel stated how responsibility is at the core of data governance and how the cost can be great if CDAOs fail to responsibly manage their data. He shared that bad data cost the GDP over $3 trillion dollars in 2016 from issues such as missing data, incorrect decision making from mistakes in analytics, rework and more. CDAOs are responsible for providing “consistent, reliable, trustworthy, accessible, and safe data” across the organization, and a proper data governance framework is essential to ensuring data quality.
When it comes to how data is recognized across the business, Zwiefel emphasized that it must be seen as a corporate asset, and it cannot be dismissed as just a team-specific asset. This is a cultural shift, and he shared that CDAOs can drive a data-driven culture from both key stakeholders and the wider organization by putting the “right level” of data governance in place to match the pace of the business.
Key Takeaways from the Discussion
Participants then split into small groups to further discuss their data governance challenges and strategies. These are the key takeaways:
- Identify and control the source of truth for the business.
CDAOs in attendance cited how it can be difficult to get the business to agree on a source of truth. One data and analytics leader stated, “Analytics should be the neutral party. We don’t care what the metrics say, we just care that it's the truth and reflects reality.” Another CDAO mentioned how this can sometimes stem from problems with data clarity. He shared, “People don’t trust the data, because they don’t have clarity on it."
Many CDAOs are also struggling to get their organization to use the same nomenclature around data, especially regarding metrics. The data and analytics leaders were in agreement that they need to take control of this moving forward.
- Align data governance with business outcomes to create tangible value.
The group discussed how business alignment is important for getting both buy-in and funding from key stakeholders. One CDAO shared an example about how to frame initiatives, saying that instead of telling business leaders they need a business glossary, find their business problem and provide how a glossary can be a solution. Another shared the importance of starting with small wins to build credibility. They said, “Prioritize one or a few challenges and go solve them to prove worth and gain momentum.” They continued by sharing that building solutions around both use cases and foundational capabilities can quickly show value.
- Advocacy is critical for executing and scaling a governance strategy.
One data leader shared, “You want to get the business to speak for you and say these are things that data governance needs to help us with.” Another CDAO explained how every interaction with the business is an opportunity to achieve these goals, and this is especially pertinent when data teams work with business functions to adapt frameworks for their needs.
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