Danielle Cloud, SVP, Enterprise Data Governance and Platforms at American Express, speaks with Nazar Labunets, Product Marketing Manager at Ataccama, in a video interview about measuring the success of data initiatives, tracking data quality, and her take on data modernization.
Cloud says that her approach to measuring success in data management combines quantitative metrics with qualitative indicators. Quantitatively, she collaborated with each business unit to establish a data roadmap. It identified specific data elements and mapped their system lineage. Deadlines were set for implementing data quality controls, cataloging metadata, and assigning ownership. Tracking the completion of these steps across different domains and business units provided a measurable picture of progress.
On the qualitative side, Cloud mentions fostering a data culture. This includes creating data steward and custodian roles, hosting annual data awareness days, and offering training programs customized for various levels. These initiatives have generated significant excitement for data work, and data management has even evolved into a recognized career path within the company, complete with opportunities for professional development. While these cultural shifts may have been less easily quantifiable in the past, Cloud recognizes them as a key factor in adding value and achieving success in data management.
Speaking of critical data elements and quality controls, Cloud says that different controls and rules have been put in place that help identify material issues and manage them through a quality issue tracking system. Overall, the organization utilizes a comprehensive set of quality metrics that are regularly reported.
Further, Cloud emphasizes that when collaborating with business units, it naturally includes discussions around the impact of data quality on business initiatives. For instance, highlighting how clean data is crucial for accurate financial reporting, effective modeling, or a smooth acquisition process. This focus on quality is deeply ingrained in the conversations. Both during discussions with individual business units and at the enterprise level with the advisory executive committee.
Cloud elaborates that the committee, with representatives from every business unit, vets these critical data elements. The forum fosters open communication, allowing business units to explain their strategies. For example, a unit might be tackling data governance in phases due to a system modernization journey, prioritizing quality efforts once the data resides in the new system. Ultimately, the committee fosters an interactive environment, challenging business units to prioritize data quality for the most critical information.
When asked how she views data modernization, Cloud states that it can be a lot of things looking at it from a platform, software, data, or product lens. It involves understanding the associated costs while also understanding and mitigating data risks. This includes data stewardship, lifecycle management (collection, usage, confidentiality, retention, deletion), and ensuring data quality.
Additionally, Cloud argues that modernization should be driven by business needs, not just for the sake of being new. Data fuels everything and so modernization must support core business priorities. She acknowledges the diverse needs of data users. To effectively serve a wide range of personas, she prioritizes investing in the right data platforms and management tools, while maintaining and iterating on them over time.
In a similar vein, Cloud mentions a CDO Magazine interview with Kavita Gupta, VP - Enterprise Data Platforms, Enterprise Digital and Data Solutions at American Express, about modernizing the organization’s information delivery network. She highlights the importance of continually assessing business needs and modernizing the available tools and solutions to drive our growth and customer value.
CDO Magazine appreciates Danielle Cloud for sharing her insights with our global community.