Where Finance Operators Read First
Analysis built for CFOs, FP&A leads, and transformation teams — operational specificity on Excel automation, AI in finance, and reporting infrastructure.
When AI Improves a Forecast — and When It Doesn't
A workflow-level breakdown of which forecasting steps respond to AI augmentation and which still require a finance operator's judgment. Evidence from three FP&A teams.
12 min read
Four Disciplines. One Platform.
Navigate directly to your active problem area — each discipline is its own body of analysis, not a tag.
FP&A Execution
AI for Finance Teams
Excel Automation
Reporting Transformation
Budgeting cycles, rolling forecasts, variance analysis, and the model architecture that makes planning defensible.
From manual pack assembly to automated board reporting — the infrastructure decisions that change what finance can deliver.
Which AI workflows compound over time, which are hype, and how to evaluate both without vendor-led framing.
Power Query, dynamic arrays, VBA to Python migration, and building models that run themselves without breaking.
Rigorous Work. No Filler.
Dynamic Arrays Are Changing Model Architecture
Rebuilding the Monthly Close for Automated Output
Rolling Forecasts That Finance Leaders Actually Trust
SPILL-range logic eliminates dozens of helper columns. Here's how to restructure a mature financial model without breaking its audit trail.
A step-by-step account of how one FP&A team cut pack assembly from four days to six hours using Power Query and structured templates.
The structural decisions — driver-based logic, locked actuals, scenario branching — that make a rolling forecast defensible under board scrutiny.
8 min read
10 min read
9 min read