Data Analyst | SQL · Power BI · Excel · R
I am a senior at the University of South Florida with a quantitative background in chemistry and economics, focused on applying data analysis to operational and business decision-making.
- LinkedIn: https://www.linkedin.com/in/anthonyfdesimone/
- GitHub: https://github.com/afdesimone
This portfolio highlights analytics projects centered on evaluating business assumptions, interpreting results, and supporting data-driven decisions.
Key Insight
Analysis showed minimal variation in driver-level KPIs and limited impact on revenue, indicating that individual driver performance is not a primary operational driving force. Results suggest that system-level factors such as routing, demand patterns, and load characteristics are more likely to drive revenue and efficiency.
Business Problem
Operations teams often assume that individual driver performance materially affects revenue and efficiency. This project evaluates whether driver-level KPIs meaningfully explain revenue outcomes or whether performance is driven by system-level factors.
Supporting Evidence
- Driver-level performance metrics showed minimal variation across individuals
- Individual driver KPIs exhibited limited explanatory power with respect to revenue
- Performance patterns were consistent across time periods and drivers
Business Implications
- Individual driver performance is unlikely to be a high-impact management lever
- Analytical and operational focus should be directed toward system-level drivers rather than driver-level interventions
Analytical Approach & Deliverables
- Designed a relational data model and created SQL views consumed by Power BI to ensure consistent KPI reporting, with CTEs used for exploratory and ad-hoc analysis
- Analyzed driver and fleet-level performance trends using SQL
- Developed interactive Power BI dashboards to support fleet-level monitoring and decision-making
View GitHub Repository: https://github.com/afdesimone/logistics-operations-analytics
- SQL (CTEs, views, schema design)
- Power BI (dashboards, reporting, basic DAX)
- Microsoft Excel (pivot tables, formulas, Power Query)
- R (regression analysis, data visualization)