Automated Operations Productivity Report

Developed a comprehensive OB regulatory dashboard to track and standardize +50 KPIs across several institutions. This dashboard allowed for multi-level analysis and provided real-time data insights, leading to more consistent care delivery and improved performance tracking. The new system replaced siloed, spreadsheet-based reporting and established a benchmark for quality improvement.

I developed an automated weekly operations report using Python and SQL, pulling data from a large data warehouse. This report tracks key operational metrics over time, such as customer arrival, door-to-entry, and door-to-leaving averages, providing a comprehensive view of throughput efficiency. Delivered via email, this self-service report allows stakeholders to monitor performance trends without manual intervention, enabling timely adjustments that optimize processes and improve customer experience.

I trained hospital staff, including physicians, nurses, and leadership, on a self-service dashboard, despite initial reluctance. Over time, with mandated reporting training, staff grew more confident in using the tool, leading to positive feedback across teams. This increased their willingness to explore new tools as they’re introduced, fostering greater employee buy-in and engagement with new technologies.

The non-profit faced significant reporting inefficiencies and struggled to meet compliance deadlines due to reliance on manual spreadsheet processes. To address these challenges, I automated data entry and integrated various data systems, resulting in a remarkable KPI improvement of over 60%. Additionally, I implemented a notification system to capture data entry errors, ensuring consistent and reliable reporting. These data workflows not only minimized manual labor but also enhanced data accuracy, enabling the organization to meet regulatory guidelines effectively.

Integrated GIS data, including zip codes, political boundaries, past voting patterns, and community demographics, to conduct a geospatial analysis that identified key 'swing' assembly districts. By overlaying these diverse data sources, I pinpointed regions where legislative support could be gained. This analysis helped refine the proposal, ultimately contributing to the successful passage of the legislation. This project highlights how data integration and geospatial analysis can provide strategic insights that drive policy success, particularly in environmental advocacy.