Project / operations and data
Turn staffing schedules into decisions about operational coverage.
A full-stack and data project combining schedule conversion, coverage rules, dashboards and automation around store operations.
From schedule to decision
The problem was not simply displaying shifts. The useful question was whether planned staffing covered the operational demand by interval, role and location, with inconsistencies visible before they became a floor-level issue.
What was built
The solution connects schedule ingestion, transformation rules, operational views and analytical outputs. The architecture keeps source assumptions and calculation rules explicit so a dashboard does not hide data-quality problems.
Where the evidence stops
The portfolio can show product flows, code and testable calculation behavior. Commercial impact, adoption across every store and production uptime require business and operational evidence outside the public repository.
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