Pizza Delivery Dashboard

Context

I wanted one dashboard to track earnings, compare delivery zones, and forecast tips.

Role

• Built the dataset and Tableau dashboard (data shaping, KPIs, and forecasting).

Approach

• Reshaped ~12,000 rows for Tableau and built maps, histograms, and a 12-month forecast with date/zone filters.
• Set it up so I can compare zones quickly during a shift.

Impact

• Used it to compare zones and plan shifts based on tips and delivery time.
• Improved tip revenue per delivery by more than 10%.

Data Shaping for Tableau

I built a Tableau-ready dataset so the dashboard stays fast and the filters work cleanly.

• Reshaped ~12,000 rows into a tidy table with consistent dates, zones/cities, and housing types.
• Defined KPIs (tip $, tip %, delivery time) that work across filters and aggregations.
• Kept the layout simple enough to use mid-shift.

Dashboard UX

• Maps to compare zones by average tip, tip %, and delivery time.
• Histograms to understand distributions, not just averages.
• Breakdowns by housing type and city to explain why zones differ.

Forecasting

• Added a 12-month tip forecast to see seasonal changes.
• Used date/zone filters so forecasts and comparisons stay consistent.
• Made it easy to compare 'tip per delivery' vs. 'tip per hour'.

What I'd Improve

• Add distance/drive-time estimates to better model tips per hour in real conditions.
• Track acceptance rates and deadhead time to capture full earnings efficiency.
• Publish a mobile-first layout for on-shift use.

Links

Interactive Dashboard