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What is Above Store Reporting?

Posted by Dave

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The Evolution of Restaurant Performance Management: A three part series detailing Above Store Reporting (ASR), Enterprise Data Warehousing (EDW), the differences between the two and the future of Restaurant Performance Management.

In the restaurant industry, measuring restaurant profit margin preceded computers, both inside the restaurant and up the chain of command. Forms and slips of paper were used to record important financial and operational data and were snail-mailed to headquarters before the days of fax and Internet. With computers, the paper forms were replaced with screens to capture the data, or it was taken directly from the Point of Sale (POS) or back of house (BOH) system and sent to headquarters.

Today, the phrase ‘above store reporting’ means different things to different people, but I am going to take a shot at explaining generally what it is. There are other models for measuring performance within restaurant operations other than this one. For example, a company could decide that all of the decision-making should occur at the restaurant, eliminating the need for centralizing all of the data. Another alternative is an Enterprise Data Warehouse, which we will discuss in Part 2 of this blog.

From an operational perspective, there are five daily activities in an ASR solution:

  1. Collect the raw data from the POS or BOH systems at each location
  2. Consolidate the data into a centralized storage system
  3. Calculate summaries of the data (Year-to-date, District totals, etc.)
  4. Update the worksheets, files, and databases with the details and summaries
  5. Distribute the data using standardized worksheets, or printing paper reports


There are three characteristics of an ASR system that define this model of performance measurement.

Characteristic 1

ASR systems typically collect data only from store-level systems, such as POS and BOH. Many do not even capture all of the in-store data such as kitchen video, or speed of service data.  Adding new types of data, such as mystery shopper, or loyalty data, is often very expensive, if possible at all, in many above store reporting systems.

Characteristic 2

ASR systems typically collect summarized data, not the detail. For example, collecting Product Mix summaries but not the underlying transaction level details (TLD) of every customer receipt. Summarized data is always less valuable compared to detailed data because it limits your ability to analyze or understand where opportunities or issues reside.

Characteristic 3

ASR systems typically ‘harden’ the shape of the data.  For example, if it includes labor as a percent of sales for the entire day, there is no way of breaking that down to Lunch and Dinner. In this model, change is expensive both in terms of time and money.


In short, the job of an ‘above store reporting system’ is to answer the question of “What happened?” across a multi-unit restaurant company.

In my follow up blog, I will describe the operational activities and characteristics of an enterprise data warehouse.


What Are Your Thoughts?

Do you currently use an above store reporting solution?  How well does it meet your information needs? Please share your stories, comments, and any other tips that may be helpful!

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About Mirus:

Mirus provides decision makers across operations, finance and marketing with actionable intelligence. Our analytic software consolidates transactional information and a host of other data sources to measure and improve restaurant performance. Headquartered in Houston, Texas, Mirus is a recognized leader in restaurant business intelligence.

For more information, please visit www.mirus.com


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