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Earnings Insights Dashboard

UX + Data Visualization Project

Role: UX Strategist & Data Visualization Designer

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Duration: 3 months of data collection and observation

2 weeks of dashboard design and delivery.

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Tools & Methods: 

  • Excel for data modeling & dashboard design

  • Manual data collection and categorization

  • Custom tip-calculation formulas based on internal tip distribution structure

⚠️ All data in this project was collected independently and anonymized. No personal or company-specific financials are displayed.

Quick Summary

Objective: Analyze company revenue, compare role-based earnings, and identify busiest days and times of day

Data Period: 3 months of manual data collection across 6 pay periods

Roles Analyzed: Host, Expo, Bar

Key Metrics: Daily revenue, role-specific earnings, tip allocation, day/time performance

Tools Used: Excel (dashboard design), custom tip-calculation formulas

Major Findings: Dinner shifts earn ~21% more than lunch; Expo roles during dinner are top earners; Fridays and Saturdays are peak revenue days

Deliverables: Interactive Excel dashboard with filters, visual trends, and forecasting capability

Methodology

  • Data Capture

    • Collected daily earnings across all roles

    • Logged revenue totals and individual compensation per shift over multiple pay periods

  • Tip Formula Calibration

    • Developed tip-estimation formulas reflecting the company’s tip pooling and allocation mechanisms

    • Ensured consistency and comparability across roles and shifts

  • Time-Based Aggregation

    • Mapped earnings by

      • Day of week (e.g. Monday, Tuesday...)

      • Time of day (e.g. lunch, dinner, late-night)

  • Data Structuring & Visualization

    • Built a dashboard with filterable tables, trend charts, and comparative role metrics

    • Enabled interactive exploration across dimensions: role, day, time

Results

  • Data Scope

    • 6 pay periods captured

    • 75+ shifts logged across 3 roles (Host, Expo, Bar)

  • Earnings Comparisons

    • ~21% higher average earnings per shift during dinner compared to lunch

    • Dinner expo roles delivered the highest hourly income

  • Scheduling Insights

    • Detected inefficiencies—e.g. overlapping roles or under-staffed shifts

    • Identified peak revenue days (e.g. Fridays and Saturdays) and busiest hours (typically dinner service)

  • Forecasting Capability

    • Dashboard’s tip-estimation formulas enabled predictive income planning per role and shift type

Findings

  • Dinner Shifts Drive Earnings

    • Consistent ~21% uplift in average earnings during dinner vs lunch

    • Highest compensation yielded by expo roles during dinner

  • Days with Highest Demand

    • Weekends (especially Fridays and Saturdays) generate the most revenue

    • Weekday variability suggests opportunity for dynamic scheduling

  • Underutilization & Overlaps

    • Some shifts show role-overlaps or idle capacity—costly under current tip structure

    • Potential to rebalance scheduling for more efficient distribution

  • Predictive Insight Value

    • Tip-based formulas allow forecasters to anticipate income by role/day/time

    • Supports data-driven staffing and shift planning

Dashboard Deliverables

  • Fully functional Excel dashboard including:

    • Filterable shift-level data (role, day, time, earnings)

    • Visual charts: earnings distribution, trendlines by role/time

    • Interactive features for exploring patterns and forecasting

  • Documentation of tip-calculation logic for repeatability and transparency

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