Dashboard Overview Guide

Key Metrics Explained

Monthly Projection

The monthly projection provides an estimate of total sales for the current month based on performance to date.

Monthly Projection = (Average Daily Sales) × (Days in Month)

This projection helps managers anticipate cash flow, inventory needs, and labor requirements for the remainder of the month.

Staffing Efficiency

Measures how effectively your staff is serving guests, calculated as covers per labor hour.

Staffing Efficiency = Total Guests Served ÷ Total Labor Hours

Higher numbers indicate more efficient staffing. Industry benchmarks vary by service style:

  • Fine dining: 1.5-2.5 covers/labor hour
  • Casual dining: 2.5-3.5 covers/labor hour
  • Quick service: 4.0+ covers/labor hour

Prime Cost

The sum of food/beverage costs and labor costs as a percentage of total sales.

Prime Cost = (Food Cost + Beverage Cost + Labor Cost) ÷ Total Revenue × 100

This is the most important metric for restaurant profitability. Ideal targets:

  • Full service: 60-65%
  • Quick service: 50-55%

How These Metrics Relate

These three metrics form the foundation of restaurant financial health:

  1. Monthly Projection predicts revenue potential
  2. Staffing Efficiency measures labor productivity
  3. Prime Cost combines food and labor costs to show overall profitability

Improving one metric often affects the others. For example, increasing staffing efficiency typically improves prime cost by reducing labor percentage.

Dashboard Charts

Sales Trend Chart

Visualizes weekly sales patterns to identify:

  • Seasonal trends
  • Growth patterns
  • Impact of marketing initiatives
  • Day-of-week patterns
Best Practice: Compare current year to previous year (YoY) to account for seasonality when analyzing trends.

Staff Allocation Chart

Shows the standard distribution of staff roles in your restaurant:

  • Helps visualize team structure
  • Identifies potential over/under staffing in certain positions
  • Provides baseline for scheduling
Note: Ideal allocation varies by service style, menu complexity, and restaurant layout.

Sales Forecasting Guide

Record Daily Sales

Purpose

Accurate daily sales recording is the foundation of all forecasting. This data helps:

  • Identify sales patterns
  • Measure impact of promotions
  • Track seasonality
  • Calculate key metrics like average check

Key Fields Explained

  • Date: Essential for trend analysis
  • Revenue: Total sales including tax
  • Guest Count: Used to calculate average check and staffing needs
  • Weather: External factor affecting sales
  • Special Notes: Record events, promotions, or unusual circumstances
Average Check = Total Revenue ÷ Guest Count

Best Practices for Data Collection

  1. Record data at the same time each day (e.g., after closing)
  2. Include all revenue streams (food, beverage, merchandise)
  3. Be consistent with weather descriptions
  4. Note special events that might affect future forecasts

Sales Averages

Types of Averages

Fixed Average: Calculated using all available data points

Fixed Average = Sum of All Values ÷ Number of Values

Rolling Average: Calculated using only the most recent data points

7-Day Rolling Average = Sum of Last 7 Days ÷ 7

When to Use Each

Fixed Averages are best for:

  • Long-term planning
  • Annual comparisons
  • Identifying overall trends

Rolling Averages are best for:

  • Short-term adjustments
  • Accounting for seasonality
  • Recent trend analysis

Connection to Other Tools

Sales averages feed directly into:

  1. Sales Forecasting: Provides the base average
  2. MTD Forecasting: Helps project month-end totals
  3. Staff Forecasting: Informs expected covers

Sales Variance Analysis

Purpose

Measures the difference between actual and forecasted sales to:

  • Evaluate forecasting accuracy
  • Identify unexpected performance changes
  • Adjust future forecasts
Variance = Actual Sales – Forecasted Sales
Variance % = (Variance ÷ Forecasted Sales) × 100

Interpreting Variance

  • ±5%: Normal fluctuation
  • ±5-10%: Investigate causes
  • ±10%+: Significant – requires action
Note: Positive variance (actual > forecast) isn’t always good – it may indicate understaffing or missed sales opportunities.

Variance Analysis Process

  1. Calculate variance daily
  2. Investigate significant variances immediately
  3. Document causes (weather, events, etc.)
  4. Adjust future forecasts based on findings

Day Factor Calculator

What is a Day Factor?

A multiplier that shows how a particular day’s sales compare to your average day.

Day Factor = Typical Day Sales ÷ Overall Average Daily Sales

Example: If Fridays average £4,000 and your overall daily average is £3,000, Friday’s factor is 1.33.

Using Day Factors

Day factors help:

  • Account for weekly patterns in forecasting
  • Identify your strongest/weakest days
  • Plan staffing and inventory
Tip: Calculate day factors using at least 3 months of data for accuracy.

Connection to Sales Forecasting

Day factors are multiplied by your base average in the sales forecast formula:

Forecast = Base Average × Day Factor × Season Factor × Event Factor

This adjusts your forecast up or down based on the day of week.

Sales Forecast Generator

Forecasting Formula

Forecast = Base Average × Day Factor × Season Factor × Event Factor

Base Average: Your typical daily sales (from Sales Averages tool)

Day Factor: Adjustment for day of week (from Day Factor tool)

Season Factor: Adjustment for time of year (e.g., 1.1 for holiday season)

Event Factor: Adjustment for special events (e.g., 1.2 for local festival)

Determining Factors

Season Factors: Calculate from historical data showing monthly patterns

Event Factors: Estimate based on:

  • Past similar events
  • Expected attendance
  • Marketing efforts
Note: Factors are multipliers where 1.0 = no change, 1.1 = 10% increase, 0.9 = 10% decrease.

Forecasting Best Practices

  1. Start with at least 3 months of historical data
  2. Update factors quarterly based on new data
  3. Document assumptions for each forecast
  4. Review accuracy weekly and adjust methods

MTD Forecasting Guide

MTD Forecasting Explained

What is MTD Forecasting?

Month-To-Date (MTD) forecasting projects your full month’s performance based on the first 7 days’ results.

Monthly Projection = (Average Daily Sales MTD) × (Days in Month)

This early warning system helps managers:

  • Adjust labor and inventory before problems arise
  • Identify potential budget variances early
  • Make strategic decisions to hit monthly targets

Why 7 Days?

The first week provides:

  • At least one of each day of week (Monday-Sunday)
  • Enough data to smooth out daily fluctuations
  • Time to make meaningful adjustments
Note: After day 7, update the forecast weekly or after any major event.

MTD Best Practices

  1. Calculate after day 7, then weekly
  2. Compare to both budget and previous year
  3. Factor in known upcoming events
  4. Share projections with department heads

Prime Cost Analysis

What is Prime Cost?

The sum of your largest controllable expenses:

Prime Cost = Food Cost + Beverage Cost + Labor Cost

Expressed as a percentage of total revenue:

Prime Cost % = (Prime Cost ÷ Total Revenue) × 100

Prime Cost Targets

Ideal prime cost percentages vary by restaurant type:

  • Fine dining: 60-65%
  • Casual dining: 55-60%
  • Quick service: 50-55%

Within prime cost, typical breakdowns:

  • Food cost: 28-35%
  • Beverage cost: 20-25%
  • Labor cost: 25-30%

Connecting Prime Cost to MTD

MTD forecasting helps manage prime cost by:

  1. Projecting total revenue for the month
  2. Allowing adjustment of labor schedules
  3. Informing purchasing decisions
  4. Identifying potential cost overruns early

Staff Forecasting Guide

Staffing Calculator

Staffing Formula

Staff Needed = (Covers ÷ Covers per Staff) × Service Level × Experience Factor

Covers: Expected number of guests (from sales forecast)

Covers per Staff: Your standard productivity measure per role

Service Level: Complexity adjustment (1.0=standard, 1.2=premium)

Experience Factor: Team skill adjustment (1.1=junior, 0.9=senior)

Standard Covers per Staff

Typical benchmarks per service role:

  • Head Waiter: 20-30 covers
  • Chef de Rang: 15-20 covers
  • Food Runner: 35-45 covers
  • Busser: 25-35 covers
  • Sommelier: 40-60 covers
Note: These vary based on menu complexity, table turnover, and restaurant layout.

Staffing Best Practices

  1. Calculate needs by meal period (lunch vs. dinner)
  2. Round up for key positions (never have 0.5 of a host)
  3. Schedule 10-15% extra for training and breaks
  4. Adjust based on reservation patterns

Labor Cost Calculator

Labor Cost Formula

Labor Cost = Total Service Hours × Average Hourly Wage
Labor % = (Labor Cost ÷ Forecasted Revenue) × 100

Labor Cost Targets

Ideal labor cost percentages:

  • Fine dining: 25-30%
  • Casual dining: 20-25%
  • Quick service: 15-20%

Within labor cost:

  • Front-of-house: 10-15%
  • Back-of-house: 10-15%

    • Connecting Staffing to Sales

    The staffing process flows from sales forecasting:

    1. Sales forecast predicts covers
    2. Covers determine staffing needs
    3. Staffing plan determines labor hours
    4. Labor hours × wages = labor cost
    5. Labor cost compared to revenue = labor %

    Staff Deployment

    Service Phases

    Effective deployment assigns staff to specific roles during each service phase:

    1. Preparation: Setup before service
    2. Greeting: Initial guest contact
    3. Ordering: Taking food/drink orders
    4. Service: Delivering food and drinks
    5. Turnover: Resetting for next guests

    Role Responsibilities

    Standard front-of-house roles and primary duties:

    • Head Waiter: Oversees section, greets VIPs
    • Chef de Rang: Takes orders, serves courses
    • Food Runner: Delivers food from kitchen
    • Busser: Clears tables, resets
    • Sommelier: Wine service, recommendations

    Deployment Best Practices

    1. Cross-train staff for multiple roles
    2. Schedule overlaps for shift changes
    3. Assign sections based on strengths
    4. Rotate difficult sections fairly

    Data Management Guide

    Importing Data

    CSV Import Requirements

    For successful imports, your CSV file must include:

    • Date: In YYYY-MM-DD format
    • Revenue: Total sales amount
    • Guests: Total covers served

    Optional but helpful columns:

    • Day (Monday-Sunday)
    • Avg Check
    • Weather
    • Notes

    Import Best Practices

    1. Export data from your POS in consistent format
    2. Keep backup copies of original files
    3. Verify data after import
    4. Import weekly to maintain current data

    Exporting Data

    Export Formats

    CSV: Best for spreadsheets and basic analysis

    • Can be opened in Excel, Google Sheets
    • Lightweight file size
    • Limited to tabular data

    JSON: Best for transferring to other systems

    • Preserves data structure
    • Can include nested information
    • Better for programmers

    Export Best Practices

    1. Export before major system updates
    2. Use descriptive filenames with dates
    3. Store exports in secure location
    4. Export before clearing old data

    Backup & Recovery

    Backup System

    The application maintains:

    • Primary Data: Current working data
    • Backup Data: Most recent manual backup
    Important: Backups are stored in your browser’s local storage. Clearing browser data will delete backups.

    Backup Strategy

    1. Backup weekly or before major changes
    2. Download exports as additional backup
    3. Note backup dates in your calendar
    4. Test restore process periodically

    Data Reset Warning

    Resetting data will:

    • Permanently delete all sales, staffing, and forecast records
    • Reset all settings to defaults
    • Cannot be undone

    Always export data before resetting!

    Reports Guide

    Report Types

    Daily Sales Report

    Includes:

    • Daily revenue totals
    • Comparison to forecast
    • Key metrics (average check, covers)
    • Notes on variances

    Best for: Shift managers, daily operations

    Weekly Performance Report

    Includes:

    • Weekly sales totals
    • Comparison to previous weeks
    • Labor cost analysis
    • Prime cost update

    Best for: Management team meetings

    Monthly Forecast Report

    Includes:

    • MTD projections
    • Budget comparisons
    • Staffing plans
    • Inventory needs

    Best for: Owner/GM strategic planning

    Report Components

    Executive Summary

    The high-level overview should:

    • Highlight key findings first
    • Use clear, concise language
    • Focus on actionable insights
    • Include visual callouts for important metrics

    Performance Metrics

    Effective metric presentation:

    • Groups related metrics together
    • Shows current period vs. comparison period
    • Highlights variances with color coding
    • Includes brief explanations for anomalies

    Report Design Tips

    1. Put most important information first
    2. Use consistent formatting
    3. Include charts for key trends
    4. Keep appendix data available but not prominent