Enterprise strategy · Capital One
How service-design research made a complex ecosystem visible—and gave leaders the evidence to invest in a 0-to-1 dashboard.
This page is structured around what senior hiring leaders look for: the scale of the challenge, your mandate, how you created alignment, the choices you made, and the evidence that your work changed an outcome.
Data and Engineering teams supporting the credit-card business relied on a sprawling ecosystem of tools, applications, and services to understand data health. That fragmentation created operational risk and could result in millions of dollars in fines when data incidents occurred. Without a single source of truth, leaders lacked the visibility to identify issues early and act proactively.
I owned foundational strategic research and product discovery across the ecosystem, partnering with Product, Technology, and senior leadership to connect user needs with platform strategy and shape the investment decision.
I began by quantitatively benchmarking the impact of data health and visibility. I then used qualitative research to define the needs for a centralized leadership platform that would connect with the tools engineers and data scientists use every day. Finally, I tested proofs of concept to ensure the designs would meet those needs.
The findings helped secure funding for the dashboard and revealed significant gaps between the proposed solution and other enterprise tools. Most importantly, the research showed that a leadership dashboard would not succeed unless it also served the engineers and data scientists responsible for day-to-day data work. That insight aligned seven teams around a broader product strategy.
More effective data monitoring is projected to deliver $5–15M in annual savings when incidents are avoided. The team also expects faster onboarding for new data and shorter resolution times when data falls below key health criteria. In concept testing, average satisfaction reached 4.5 out of 5, compared with a 3.4 baseline, and Product prioritized approximately 97% of the research recommendations.
Starting with measurement made the investment case more credible. When baseline data is not readily available, a research leader must build alignment around slowing down long enough to establish it. That creates a clear way to express both the current experience and the improvement a new product is expected to deliver.