Industry Focus: Restaurants

Leading Restaurants have turned to AcuITy For their Business Intelligence, Planning, Scorecarding And Dashboard projects.

Here's Why:

Acuity has successfully implemented solutions that address your specific industry areas such as:

  • Labor Management
  • Food Trend Analysis
  • Store Profitability Analysis
  • Food Supply Planning
  • Scenario Planning For New Franchises
  • Financial Budgeting & Reporting

Additionally, Acuity has delivered solutions for:

  • Improved Reporting:
  • Comp vs. Non-Comp Analysis
  • Menu Mix Analysis
  • Weather affected Restaurant Performance Reports
  • Store/Regional Level Scorecarding

Improved Budgeting:

    • Streamline Budgeting for the entire operation
      (down to the individual store/location)
    • Enhance Store Level budget-to-actual Reporting & Store Variance Reporting
    • Budgeting and "what-if" analysis for covers/time of
      day/manpower/store profitability

Some Examples:

Improved Reporting - Store Level P&L with Roll up

 


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A “basic” P&L Report in excel. However, this excel report is really a template that leverages an OLAP database behind the scenes.

You create 1 template and leverage it across all of your restaurants, districts, regions, or any other rollup that you want.

Additionally, it is dynamic in that as accounts are added, business structure changes, or data changes, those changes are automatically updated in this report.

 
Improved Reporting - Menu Mix Analysis

 


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In this report we have created a “dynamic” top 20 menu items that changes as the Data changes.

As you can see we automatically filter the 2269 menu items down to just the 20 most popular items as well as the dollars spent on them.

Additionally, we can “drill into” this report as we are currently looking at Corporate Total, but we can get down to individual restaurant counts with the click of a button.

 
Improved Reporting - Comp vs. Non-Comp Analysis

 


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In this report we have created a “Comp” store report.

By leveraging attributes to determine if a store is considered Comp or NonComp we can slice and dice the total data and return just the values that you are looking for. In this case we pulled all of the Comp Restaurants for FY2004 (which we can drill all the way down to the day) and returned values for Dine In Sales: Beverage/Alcohol/Food and then subcategories for Food. We can then analyze these stores on the same basis without the variations from Non-Comp stores skewing the data.

 

 

  
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