What is The Frugal Analyst?
The Frugal Analyst is an automated daily financial analysis blog that examines public companies through the lens of labor economics. Each day, we analyze corporate financials to uncover how companies generate value relative to their workforce, how headcount changes correlate with financial performance, and what workforce metrics reveal about a company's operational efficiency.
Our analysis goes beyond traditional financial metrics to explore questions like: How much revenue does each employee generate? Is the company becoming more or less efficient as it grows? What do hiring and layoff patterns tell us about a company's strategic direction?
Methodology
Each analysis begins with the latest available financial data from SEC filings, combined with macroeconomic indicators from government sources. We calculate labor-adjusted financial metrics including revenue per employee, profit per employee, compensation ratios, and workforce productivity trends.
Our models compare these metrics against sector benchmarks and historical performance to identify notable trends, outliers, and inflection points. All analyses are generated programmatically and reviewed for accuracy before publication.
Data Sources
We draw from a range of public, authoritative data sources:
- SEC EDGAR -- 10-K and 10-Q filings for corporate financial data
- Financial Modeling Prep API -- standardized financial statements and ratios
- Bureau of Labor Statistics (BLS) -- employment, wages, and labor market data
- Federal Reserve Economic Data (FRED) -- macroeconomic indicators and sector benchmarks
About
The Frugal Analyst is built on the principle that the most valuable financial insights come from systematic, transparent analysis rather than speculation. By automating the collection and processing of financial data, we can provide consistent, bias-reduced analysis at a pace that manual research cannot match.
This project combines financial engineering, data science, and labor economics to offer a unique perspective on corporate performance. All content is generated by AI, reviewed by humans, and published as a free public resource.