Dinesafe Knowledge Base
  • Welcome
  • Return to DineSafe.com
  • Real-Time Norovirus Surveillance
    • Introduction
  • Methodology
  • Data Collection & Processing
  • Metrics & Indicators
  • Implementation Guidelines
  • FAQs
  • Benchmarking
    • Introduction
      • The Importance of Food Safety
      • Introduction to Our Benchmarking System and Its Purpose
      • Why Food Safety Benchmarking Matters: A Stakeholder Overview
    • Methodology & Systems
      • The Metrics We Use
        • Reports per 100 Stores
        • Reports per $1M Revenue
        • Persons Reported Sick per 100k Customers Served
      • Data Sources & Methodology
        • How We Gather Data
        • Estimating Data When Exact Figures Aren't Available
        • Ensuring Accuracy and Transparency
      • Our Benchmark Indexing System
        • Why We Use Indexing
        • Index Composition
        • Index Calculation Process
        • Understanding Index Comparisons
    • Case Study
      • Case Study - Chipotle Mexican Grill
    • Applications
      • Global Applicability of Our Benchmarking System
      • Product-Specific Benchmarking for Food Producers
    • Service Information
      • Why Subscribe to Our Benchmarking Service
      • Limitations & Considerations
      • Conclusion
      • FAQ
        • Q1: How often are the benchmarks updated?
        • Q2: Are the food poisoning reports reviewed before being included in the benchmarks?
        • Q3: How do you account for differences in restaurant size when comparing benchmarks?
        • Q4: Can restaurants submit their own data to improve the accuracy of the benchmarks?
        • Q5: How do your benchmarks relate to official health inspections and ratings?
        • Q6: How can businesses improve their benchmark scores?
  • Data Dictionary
    • Introduction
    • Primary Fields
    • Specialized Fields
    • Delivery Methods
    • Glossary
    • Further Questions
  • IWP Reporting Widget
    • Introduction
    • Why Our Widget? Key Features & Benefits
    • Embedding the Widget
      • How to Embed the Code
      • When to Use Simple Embedding Code vs Advanced Embedding Code
        • Benefits of the Advanced Embedding Code
        • Considerations When Using the Advanced Embedding Code
      • Test the Code
      • Standalone URL Option
      • Customization Options
      • Language Support
      • Mobile-Friendly Link
    • Data Management and Access
    • Compliance with FDA’s Voluntary National Retail Food Regulatory Program Standards
    • Examples of Embedded Widgets
    • FAQ
      • Q1: Who can use the Iwaspoisoned.com reporting widget and what is it?
      • Q2: How do I embed the widget on my website?
      • Q3: Is the widget customizable?
      • Q4: How do I access the reports?
      • Q5: How does the widget support FDA compliance?
  • Email Notifications
    • Introduction
    • Widget Email Alerts
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  • How We Calculate It
  • Why This Metric Matters

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  1. Benchmarking
  2. Methodology & Systems
  3. The Metrics We Use

Reports per $1M Revenue

Our "Reports per $1M Revenue" metric provides a standardized way to compare food safety incidents across restaurants of different sizes and revenue scales. This metric allows us to account for the volume of business a restaurant does, offering a more nuanced view than raw incident numbers or store-based metrics alone.

How We Calculate It

  1. Calculate Total US Revenue

    • We focus on the total revenue generated from all US stores, including both company-owned and franchised locations (for those brands that franchise).

    • Importantly, we exclude franchising fees, royalties, and other non-food-sales revenue to ensure we're measuring based on actual food service activity.

    • For public companies, we typically source this data from their annual SEC 10-K reports.

    • For private companies or when 10-K data is incomplete, we use one of two methods: a) We calculate an imputed revenue by multiplying the average sales per location by the number of US stores. Typically, the 10-K provides the average sales per location metric. However, for private companies or situations where this information is unavailable, we find this number through research.

      b) We conduct thorough research to find reliable US revenue estimates from industry reports or other credible sources.

      Example: Chili’s Grill & Bar's parent company, Dine Brands, does not provide total U.S. revenue for both company-owned and franchised store locations in their 10-K report. Therefore, for example in year 2023, we estimated the revenue by using the 10-K provided Average Sales per Store ($5.1 million) and multiplying it by the U.S. store count of 1,231 (The 10-K report provides separate counts for U.S. company-owned and franchised stores, which we combined: 1,130 company-owned locations plus 101 franchised locations = 1,231 U.S. store count), resulting in an estimated U.S. revenue of $6,278.1 million for both company-owned and franchised locations.

  2. Calculate the Metric The formula looks like this:

    Reports per $1M Revenue = 
    (Number of Reports / Total US Revenue in millions) × 1,000,000
    • We take the total number of food poisoning reports associated with the brand for the year.

    • We divide this number by the total US revenue (in millions of dollars).

    • Finally, we multiply the result by 1 million to get our "Reports per $1M Revenue" figure.

Why This Metric Matters

This metric is crucial for several reasons:

  1. Revenue-Based Comparison: It allows for a fair comparison between high-volume and low-volume restaurants, as well as between budget and premium dining establishments.

  2. Business Activity Reflection: By basing the metric on revenue, we get a sense of how many incidents occur relative to the amount of food being served.

  3. Scalability: This metric scales well, making it possible to compare small local chains with national brands.

By combining this metric with “Reports per 100 Stores” and “Persons Reported Sick per 100k Customers Served,” we provide a comprehensive, multi-dimensional analysis of a restaurant's food safety performance across various operational aspects.

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Last updated 9 months ago

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