Agricultural operations reporting

At a large-scale farming operation, I automated daily production reporting that had been manually rebuilt each period for years. Reporting lag dropped from 12 hours to 30 minutes, accuracy improved 4-5%, and teams stopped arguing about numbers and started making decisions with them.

The problem

At a large-scale farming operation, daily production reporting was fragile and time-consuming. The reports existed, but they were rebuilt manually each period using spreadsheet logic that had evolved over years. When staff changed or processes shifted, the reports broke.

Nobody fully trusted the numbers. Teams spent more time arguing about whether the data was right than using it to make decisions. Management wanted real-time operational visibility, but the reporting lag was 12+ hours and required constant manual intervention.

What I built

I migrated the reporting infrastructure into a centralized, automated system:

Traced existing logic to understand what actually mattered operationally
Rebuilt core calculations in a way that could handle changing data
Automated data pipelines from source systems
Reduced reporting lag from 12 hours to 30 minutes
Created refresh-safe reports that didn't require manual fixes

The outcome

Daily production reports became trusted and used site-wide
Reporting time reduced by 80%
Near-real-time tracking of production against targets
Teams stopped debating numbers and started making decisions
Management had visibility they'd never had before

The operation could finally see what was happening while it was happening, not half a day later.