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.
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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:
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Traced existing logic to understand what actually mattered operationally
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Rebuilt core calculations in a way that could handle changing data
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Automated data pipelines from source systems
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Reduced reporting lag from 12 hours to 30 minutes
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Created refresh-safe reports that didn't require manual fixes
The outcome
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Daily production reports became trusted and used site-wide
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Reporting time reduced by 80%
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Near-real-time tracking of production against targets
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Teams stopped debating numbers and started making decisions
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Management had visibility they'd never had before
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The operation could finally see what was happening while it was happening, not half a day later.