pl-cost-analysis

P&L cost analysis automates monthly profit-and-loss review by computing COGS, cost percentages, and manager bonuses from NET SALES and inventory data. This Skill extracts data from PDFs or CSVs, applies tiered bonus logic, and outputs structured results for multi-location comparison and period-over-period variance tracking.

Yes. This Skill accepts dual-PDF workflows with Food Usage Reports and Gross Sales breakdowns, extracting NET SALES and inventory data to compute actual COGS using Beginning Inventory + Purchases − Ending Inventory, then calculating tiered bonuses and Top Line eligibility.

The Skill works with dual PDFs (foodUsageReport and Gross_Sales) for detailed workflows or a single P&L CSV for legacy inputs, enabling flexibility across different restaurant reporting systems and data sources.

After processing NET SALES and COGS data, the Skill supports multi-location benchmarking by structuring results for cross-location comparisons, enabling finance teams to identify performance variances and benchmark insights across Cantina, OAK, WB, and other locations.

You need Python 3, the dependencies pdfplumber, pandas, and numpy, plus either two PDFs (Food Usage Report + Gross Sales) or a single P&L CSV, and a location identifier to launch the analysis.

Yes. The Skill outputs structured P&L and bonus results suitable for embedding in RAG systems, enabling downstream decision automation, financial reporting pipelines, and bonus approval workflows.