Using Cafe's Consistency Report

This article will explain how to use the Consistency Report for your connected espresso machines.

• Why use Cafe's Consistency Report? 
  • Applying filters 
• Overview cards
  • Parameter Overview cards 
  • Calculating Outliers 
  • Box plot charts per parameter

Why use Cafe's Consistency Report? 

The Consistency Report provides valuable insights into the uniformity of brews produced by your connected espresso machines, allowing you to identify outliers and potential issues within your brewing process. 
📚 Learn more about what espresso machines are compatible with Cropster Cafe.

By following the steps below you can access Cafe's Consistency Report: 

1. Log in to the online platform C-sar.
   📚 Learn how to set the Cafe dashboard as your primarily dashboard. 
2. Navigate to Cafe on the main menu bar. You will be directed to the Telemetry Insights page. 
3. Select Consistency Report. 
   

Applying filters

By following the steps below you can apply filters on the Consistency Report: 

1. Select the following filters:
   
   
   • Date range
     💡 Click on the start date or end date fields to prompt a calendar to choose amongst predefined date ranges or enter a custom date.
   • Aggregate by
     • Day: Brews are aggregated per Equipment per day.
     • Day of week: Brews are aggregated per Equipment per day of the week (e.g. all mondays together, all tuesdays together, etc.).
     • Espresso machine
     • Brew type
       💡 You can also include test brews by clicking the respective checkbox.
   • Parameters
   • Espresso machines 
2. Click Apply filters. 

Overview cards 

The initial overview cards present essential metrics that reflect the consistency of your brews based on the filters you have applied:

1. Brews with these filters: The total number of brews with a recorded value for any of the selected parameters.
2. In range: Percentage of brews that fall within the acceptable range - this represents the proportion of brews that are consistent with the specified parameters and are not identified as outliers.
3. Outliers for Time
4. Outliers for Brew water pulse 

Parameter Overview cards

By utilizing the Parameter Overview cards, you can explore each parameter in detail, allowing you to gain a deeper understanding of the consistency associated with each individual metric.

Simply select the Parameter button for the parameter you want to focus on:
💡 The method to select a parameter changes between buttons/menu depending whether you are accessing the site on mobile or iPad/computer.

• Time
  • Brews with time
  • Outliers above 3rd quartile
  • Outliers below 1st quartile
  • Average
  • Standard deviation
• Brew water pulses 
  • Brews with brew water pulses
  • Outliers above 3rd quartile
  • Outliers below 1st quartile
  • Average
  • Standard deviation

Calculating Outliers 

The Consistency report uses a statistical calculation to identify outliers.

Any value below Q1-1.5xIQR and above Q3+1,5xIQR is considered an outlier, whereby:
💡 Any value that is not an outlier, is considered in range.

• Q1 (the first quartile): this value identifies the median of the lowest 50% of your brews
• Q3  (the third quartile): this value identifies the median of the highest 50% of your brews
• IQR (interquartile range): this value defines the difference between Q3 and Q1, which holds roughly 50% of your brews, ie. 25% above and 25% below your median.

Box plot chart per parameter

The Box plot chart enables you to analyze the consistency of brews based on the selected filters.

 

This tool facilitates comparisons across different days, specific weekdays, and various equipment, making it easier to identify potential issues in your brewing process.

In the chart, we utilize "box and whisker plots," commonly referred to as box plots. Each box plot visually represents the five-number summary of a set of brews based on the selected aggregation criteria.

A few visual easy-to-read cues to interpret these box plots; when the data is less spread out, thus it is more consistent, and...

• The more compact the actual box is (i.e. the roughly 50% of your brews around the median).
• The smaller the length of the whiskers is (i.e. the min and max values are also close to your 1st & 3rd quartile).
• The fewer outliers there are.

How to read a box plot?

The five-number summary is the minimum, first quartile, median, third quartile, and maximum.
💡The minimum and maximum values are the lowest and highest values in the dataset, excluding the outliers (calculated as per above).