AWS Fintech Common Patterns Initiative
I led the Planning Pod program, a key initiative within AWS Finance, driving the evolution of Planning Central from a biannual OP planning hub for top-level executives to a cutting-edge Continuous Planning platform. This transformation involved the integration of advanced scenario modeling tools, empowering executives with more agile and data-driven decision-making capabilities.
As the manager of the Planning Pod Design team, I led a group of four skilled contractors to deliver this crucial AWS Finance planning hub in strategic phases. Our approach ensured a solid foundation and gradual expansion of capabilities, aligning with AWS's evolving financial planning needs. The team consisted of a senior developer, a UX/UI specialist, a data analyst, and a full-stack developer, each bringing specialized expertise to the project.
Throughout the project, our team focused on key delivery aspects including system integration, user experience optimization, robust data handling, and security compliance. The phased approach, coupled with the development of a user-centric homepage and guided by our North Star Vision, allowed us to create a stable, scalable, and strategically aligned platform. This comprehensive solution significantly enhanced adoption, efficiency, and cross-functional collaboration in AWS's financial planning processes.
To streamline AWS's complex, manual financial planning process (10+ systems, four-month cycle), hindering agility and timely decisions, I led the development of the Planning Central homepage. This centralized platform provides a "command central" for planning, improving visibility, efficiency, and collaboration. I spearheaded the design and development, integrating key features like a centralized dashboard, interactive process visualizations, a documentation hub, an initiative tracker, and real-time data integration (TM1, SCARF). An iterative, stakeholder-focused approach ensured usability. The result: a transformed planning process. Data gathering time decreased 30%, the planning cycle time 20%, and collaboration enhanced. User engagement surged: monthly users up 69% (13 to 22), unique users up 623% (13 to 94). Planning cycles supported increased 125% (4 to 9), and data intersections impacted up 242% (243 to 832).
To address AWS Finance's manual, inconsistent, and inefficient planning processes, which hindered the Automated Continuous Planning (ACP) vision, I led UX design for SWIFT (Scenario-based What-If Financial Tool). This centralized platform empowers AWS leaders to conduct scenario-based analyses, generate insights, compare trends, and publish guidance. My contributions included user research, information architecture design, and interaction design for the user interface. The SWIFT Minimum Lovable Product (MLP) for EC2 finance included scenario creation, automated baseline forecasting, configurable assumptions, version control, analysis tools, and collaboration features. As a result, SWIFT has improved efficiency by reducing manual work, enhanced decision-making through real-time visibility, increased consistency and transparency, and fostered collaboration. It also lays a crucial foundation for ACP, shaping AWS Fintech's planning tool strategy for years to come.
To streamline AWS financial planning and accelerate Automated Continuous Planning (ACP), I led UX for the Analytics and Insights module within Planning Central (PC), AWS's central financial planning hub. This module replaced a cumbersome nine-day manual process, reliant on Excel and cross-team coordination, with a streamlined, automated solution for custom reporting, reasonability checks, and key metric correlation analysis. My contributions included user research, information architecture design, and UI design for dashboards and reporting functionalities. Through a highly iterative process (5+ iterations, 50+ screens), incorporating eight user research sessions and close collaboration with SFP&A, AWS Fintech, and service finance teams, we delivered key features: custom report dashboards, configurable data validation rules, and customizable data refresh schedules. The successful launch has improved efficiency by automating manual processes, enhanced decision-making through real-time visibility, strengthened controllership with a single source of truth for reports, and garnered positive user feedback, including praise from Dylan Davis (SFP&A) for the significant time savings. This launch significantly enhances PC and lays the groundwork for future development, including SWIFT and enhanced guidance management.
