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Chernoff’s Faces Generator
How to create a simplistic yet powerful data
visualization engine that generates complex data i...
Purpose of this Document
This document is a series of studies, whitepapers,
presentations, instagrams, and other forms of ...
What is Chernoff’s faces (wikipedia)
Chernoff faces, invented by Herman Chernoff, display
multivariate data in the shape o...
Example of Chernoff’s Faces
Getting started
The ideology behind the simplistic Chernoff’s
Faces Engine (CFE) is quite straight forward.
Each of the ‘f...
Facial indicators (Variables)
Eyes = Sales increase /decrease in %
Gaze = EBITDA increase /decrease in %
Eye-brows = Custo...
Variable Values = Eyes
Eyes = Sales increase /decrease in %Sales	
  
	
  	
   	
  	
   	
  	
   	
  	
   	
  	
   	
  	
  ...
Variable Values = Gaze
Gaze = EBITDA increase /decrease in %
Excellent	
  
Good	
  
Sa/sfactory	
  
Poor	
  
Bad	
  
	
  	...
Variable Values = Eye-brows
Eye-brows = Customer Retention %
Excellent	
  
Good	
  
Sa/sfactory	
  
Poor	
  
Bad	
  
	
  	...
Variable Values = Nose
Nose = Market Share %
Excellent	
  
Good	
  
Sa/sfactory	
  
Poor	
  
Bad	
  
	
  	
   	
  	
   	
 ...
Variable Values = Ears
Ears = CAC (Customer Acquisition Cost)
Excellent	
  
Good	
  
Sa/sfactory	
  
Poor	
  
Bad	
  
	
  ...
Variable Values = Mouth
Mouth = Brand Awareness increase
Excellent	
  
Good	
  
Sa/sfactory	
  
Poor	
  
Bad	
  
	
  	
   ...
Variable Values = Head
Head = Employees
Excellent	
  
Good	
  
Sa/sfactory	
  
Poor	
  
Bad	
  
	
  	
  
	
  	
   	
  	
  ...
Sample Chernoff-KPI
The sample Chernoff-
KPI on the right is
based on the 5-level
threshold-driven
character engine. Each
...
Super Analytics CFE
applied into realistic perspective.
We will create a simplistic comparison of Apple Inc and Nokia
Corp...
Competitor Analysis
(Apple vs. Nokia 2006)
Growth
Market Share
HI
LO HI
HI
Nokia	
  =	
  $41bn	
  
Apple	
  =	
  $19bn	
  
Competitor Analysis
(Apple vs. Nokia 2012-2013)
Growth
Market Share
HI
LO HI
HI
Apple	
  =	
  $156bn	
  
Nokia	
  =	
  $39...
What else could be done
with the Super Analytics CFE?
Customer
Experience
Measurement
Marketing
Campaign
Happiness
Custome...
Marketing Channel Analysis
(Bought vs. Earned Media)
ReturnonInvestment
Cost Per Acquisition
HI
LO HI
HI
Earned	
  media	
...
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Reporting KPI's with Chernoff Faces by Super Analytics

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This document is a series of studies, whitepapers, presentations, instagrams, and other forms of publications in which the Super Analytics team seeks to find new / old smart and even crazy as yet innovative ways to report performance or to visualize data.

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Reporting KPI's with Chernoff Faces by Super Analytics

  1. 1. Chernoff’s Faces Generator How to create a simplistic yet powerful data visualization engine that generates complex data in Chernoff’s Faces style.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        
  2. 2. Purpose of this Document This document is a series of studies, whitepapers, presentations, instagrams, and other forms of publications in which the Super Analytics team seeks to find new / old smart and even crazy as yet innovative ways to report performance or to visualize data. Prior to making this document we wrote a blog post at www.superanalytics.fi/blog about the Chernoff’s faces We hope you’ll enjoy! J Best, Kalle Heinonen Super CEO @super_analytics
  3. 3. What is Chernoff’s faces (wikipedia) Chernoff faces, invented by Herman Chernoff, display multivariate data in the shape of a human face. The individual parts, such as eyes, ears, mouth and nose represent values of the variables by their shape, size, placement and orientation. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff faces handle each variable differently. Because the features of the faces vary in perceived importance, the way in which variables are mapped to the features should be carefully chosen (e.g. eye size and eyebrow-slant have been found to carry significant weight)
  4. 4. Example of Chernoff’s Faces
  5. 5. Getting started The ideology behind the simplistic Chernoff’s Faces Engine (CFE) is quite straight forward. Each of the ‘facial indicators’ are generated by their predefined min-max locations on x-y graph. At first we will need to define the variables or the facial indicators.
  6. 6. Facial indicators (Variables) Eyes = Sales increase /decrease in % Gaze = EBITDA increase /decrease in % Eye-brows = Customer Retention % Ears = Customer Acquisition Cost Nose = Market Share Mouth = Brand Awareness increase /decrease Head = Employees
  7. 7. Variable Values = Eyes Eyes = Sales increase /decrease in %Sales                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           Excellent   Good   Sa/sfactory   Poor   Bad   2   1   0   -­‐1   -­‐2  
  8. 8. Variable Values = Gaze Gaze = EBITDA increase /decrease in % Excellent   Good   Sa/sfactory   Poor   Bad                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   2   1   0   -­‐1   -­‐2  
  9. 9. Variable Values = Eye-brows Eye-brows = Customer Retention % Excellent   Good   Sa/sfactory   Poor   Bad                                                                                                   2   1   0   -­‐1   -­‐2  
  10. 10. Variable Values = Nose Nose = Market Share % Excellent   Good   Sa/sfactory   Poor   Bad                                                                                                                                                                                       2   1   0   -­‐1   -­‐2  
  11. 11. Variable Values = Ears Ears = CAC (Customer Acquisition Cost) Excellent   Good   Sa/sfactory   Poor   Bad                                                                                                                                                                                                                                                                                                                                                   2   1   0   -­‐1   -­‐2  
  12. 12. Variable Values = Mouth Mouth = Brand Awareness increase Excellent   Good   Sa/sfactory   Poor   Bad                                                                                                                                                                                                                               2   1   0   -­‐1   -­‐2  
  13. 13. Variable Values = Head Head = Employees Excellent   Good   Sa/sfactory   Poor   Bad                                                                                                                                                                                                                                                                                                                                                                                           2   1   0   -­‐1   -­‐2  
  14. 14. Sample Chernoff-KPI The sample Chernoff- KPI on the right is based on the 5-level threshold-driven character engine. Each set of 5 characters is defined for each KPI individually. As a combination these form holistic performance report, with a grin.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         Pretty much everything is down. The market share and amount of employees remains high, yet all other fronts are performing poor. Sales & EBITDA is going down.
  15. 15. Super Analytics CFE applied into realistic perspective. We will create a simplistic comparison of Apple Inc and Nokia Corporation to form an Analysis of their Competitive Positioning via Market Share, Growth and Turnover in FY2006 and FY2012. NOKIA CORPORATIONAPPLE INC.
  16. 16. Competitor Analysis (Apple vs. Nokia 2006) Growth Market Share HI LO HI HI Nokia  =  $41bn   Apple  =  $19bn  
  17. 17. Competitor Analysis (Apple vs. Nokia 2012-2013) Growth Market Share HI LO HI HI Apple  =  $156bn   Nokia  =  $39bn  
  18. 18. What else could be done with the Super Analytics CFE? Customer Experience Measurement Marketing Campaign Happiness Customer Satisfaction Analysis Employee Satisfaction Analysis Marketing Channel Analysis Production Quality Analysis
  19. 19. Marketing Channel Analysis (Bought vs. Earned Media) ReturnonInvestment Cost Per Acquisition HI LO HI HI Earned  media   Bought  media  
  • ansik

    Mar. 17, 2015

This document is a series of studies, whitepapers, presentations, instagrams, and other forms of publications in which the Super Analytics team seeks to find new / old smart and even crazy as yet innovative ways to report performance or to visualize data.

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